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Sample records for computational multiscale model

  1. Distributed multiscale computing

    NARCIS (Netherlands)

    Borgdorff, J.

    2014-01-01

    Multiscale models combine knowledge, data, and hypotheses from different scales. Simulating a multiscale model often requires extensive computation. This thesis evaluates distributing these computations, an approach termed distributed multiscale computing (DMC). First, the process of multiscale

  2. A distributed multiscale computation of a tightly coupled model using the Multiscale Modeling Language

    NARCIS (Netherlands)

    Borgdorff, J.; Bona-Casas, C.; Mamonski, M.; Kurowski, K.; Piontek, T.; Bosak, B.; Rycerz, K.; Ciepiela, E.; Gubala, T.; Harezlak, D.; Bubak, M.; Lorenz, E.; Hoekstra, A.G.

    2012-01-01

    Nature is observed at all scales; with multiscale modeling, scientists bring together several scales for a holistic analysis of a phenomenon. The models on these different scales may require significant but also heterogeneous computational resources, creating the need for distributed multiscale

  3. Towards distributed multiscale computing for the VPH

    NARCIS (Netherlands)

    Hoekstra, A.G.; Coveney, P.

    2010-01-01

    Multiscale modeling is fundamental to the Virtual Physiological Human (VPH) initiative. Most detailed three-dimensional multiscale models lead to prohibitive computational demands. As a possible solution we present MAPPER, a computational science infrastructure for Distributed Multiscale Computing

  4. Multiscale Computing with the Multiscale Modeling Library and Runtime Environment

    NARCIS (Netherlands)

    Borgdorff, J.; Mamonski, M.; Bosak, B.; Groen, D.; Ben Belgacem, M.; Kurowski, K.; Hoekstra, A.G.

    2013-01-01

    We introduce a software tool to simulate multiscale models: the Multiscale Coupling Library and Environment 2 (MUSCLE 2). MUSCLE 2 is a component-based modeling tool inspired by the multiscale modeling and simulation framework, with an easy-to-use API which supports Java, C++, C, and Fortran. We

  5. Computer-Aided Multiscale Modelling for Chemical Process Engineering

    DEFF Research Database (Denmark)

    Morales Rodriguez, Ricardo; Gani, Rafiqul

    2007-01-01

    Chemical processes are generally modeled through monoscale approaches, which, while not adequate, satisfy a useful role in product-process design. In this case, use of a multi-dimensional and multi-scale model-based approach has importance in product-process development. A computer-aided framework...

  6. Community effort endorsing multiscale modelling, multiscale data science and multiscale computing for systems medicine.

    Science.gov (United States)

    Zanin, Massimiliano; Chorbev, Ivan; Stres, Blaz; Stalidzans, Egils; Vera, Julio; Tieri, Paolo; Castiglione, Filippo; Groen, Derek; Zheng, Huiru; Baumbach, Jan; Schmid, Johannes A; Basilio, José; Klimek, Peter; Debeljak, Nataša; Rozman, Damjana; Schmidt, Harald H H W

    2017-12-05

    Systems medicine holds many promises, but has so far provided only a limited number of proofs of principle. To address this road block, possible barriers and challenges of translating systems medicine into clinical practice need to be identified and addressed. The members of the European Cooperation in Science and Technology (COST) Action CA15120 Open Multiscale Systems Medicine (OpenMultiMed) wish to engage the scientific community of systems medicine and multiscale modelling, data science and computing, to provide their feedback in a structured manner. This will result in follow-up white papers and open access resources to accelerate the clinical translation of systems medicine. © The Author 2017. Published by Oxford University Press.

  7. Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models.

    Science.gov (United States)

    Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J

    2014-01-01

    The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. © 2014 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc.

  8. Multiscale modeling of complex materials phenomenological, theoretical and computational aspects

    CERN Document Server

    Trovalusci, Patrizia

    2014-01-01

    The papers in this volume deal with materials science, theoretical mechanics and experimental and computational techniques at multiple scales, providing a sound base and a framework for many applications which are hitherto treated in a phenomenological sense. The basic principles are formulated of multiscale modeling strategies towards modern complex multiphase materials subjected to various types of mechanical, thermal loadings and environmental effects. The focus is on problems where mechanics is highly coupled with other concurrent physical phenomena. Attention is also focused on the historical origins of multiscale modeling and foundations of continuum mechanics currently adopted to model non-classical continua with substructure, for which internal length scales play a crucial role.

  9. Multiscale computing in the exascale era

    NARCIS (Netherlands)

    Alowayyed, S.; Groen, D.; Coveney, P.V.; Hoekstra, A.G.

    We expect that multiscale simulations will be one of the main high performance computing workloads in the exascale era. We propose multiscale computing patterns as a generic vehicle to realise load balanced, fault tolerant and energy aware high performance multiscale computing. Multiscale computing

  10. Multiscale computer modeling in biomechanics and biomedical engineering

    CERN Document Server

    2013-01-01

    This book reviews the state-of-the-art in multiscale computer modeling, in terms of both accomplishments and challenges. The information in the book is particularly useful for biomedical engineers, medical physicists and researchers in systems biology, mathematical biology, micro-biomechanics and biomaterials who are interested in how to bridge between traditional biomedical engineering work at the organ and tissue scales, and the newer arenas of cellular and molecular bioengineering.

  11. Advanced computational workflow for the multi-scale modeling of the bone metabolic processes.

    Science.gov (United States)

    Dao, Tien Tuan

    2017-06-01

    Multi-scale modeling of the musculoskeletal system plays an essential role in the deep understanding of complex mechanisms underlying the biological phenomena and processes such as bone metabolic processes. Current multi-scale models suffer from the isolation of sub-models at each anatomical scale. The objective of this present work was to develop a new fully integrated computational workflow for simulating bone metabolic processes at multi-scale levels. Organ-level model employs multi-body dynamics to estimate body boundary and loading conditions from body kinematics. Tissue-level model uses finite element method to estimate the tissue deformation and mechanical loading under body loading conditions. Finally, cell-level model includes bone remodeling mechanism through an agent-based simulation under tissue loading. A case study on the bone remodeling process located on the human jaw was performed and presented. The developed multi-scale model of the human jaw was validated using the literature-based data at each anatomical level. Simulation outcomes fall within the literature-based ranges of values for estimated muscle force, tissue loading and cell dynamics during bone remodeling process. This study opens perspectives for accurately simulating bone metabolic processes using a fully integrated computational workflow leading to a better understanding of the musculoskeletal system function from multiple length scales as well as to provide new informative data for clinical decision support and industrial applications.

  12. Multiscale Cancer Modeling

    Science.gov (United States)

    Macklin, Paul; Cristini, Vittorio

    2013-01-01

    Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate predictions. A growing number of examples illustrate the value of this approach in providing quantitative insight on the initiation, progression, and treatment of cancer. In this review, we introduce the most recent and important multiscale cancer modeling works that have successfully established a mechanistic link between different biological scales. Biophysical, biochemical, and biomechanical factors are considered in these models. We also discuss innovative, cutting-edge modeling methods that are moving predictive multiscale cancer modeling toward clinical application. Furthermore, because the development of multiscale cancer models requires a new level of collaboration among scientists from a variety of fields such as biology, medicine, physics, mathematics, engineering, and computer science, an innovative Web-based infrastructure is needed to support this growing community. PMID:21529163

  13. Multiscale methods in computational fluid and solid mechanics

    NARCIS (Netherlands)

    Borst, de R.; Hulshoff, S.J.; Lenz, S.; Munts, E.A.; Brummelen, van E.H.; Wall, W.; Wesseling, P.; Onate, E.; Periaux, J.

    2006-01-01

    First, an attempt is made towards gaining a more systematic understanding of recent progress in multiscale modelling in computational solid and fluid mechanics. Sub- sequently, the discussion is focused on variational multiscale methods for the compressible and incompressible Navier-Stokes

  14. Numerical Analysis of Multiscale Computations

    CERN Document Server

    Engquist, Björn; Tsai, Yen-Hsi R

    2012-01-01

    This book is a snapshot of current research in multiscale modeling, computations and applications. It covers fundamental mathematical theory, numerical algorithms as well as practical computational advice for analysing single and multiphysics models containing a variety of scales in time and space. Complex fluids, porous media flow and oscillatory dynamical systems are treated in some extra depth, as well as tools like analytical and numerical homogenization, and fast multipole method.

  15. Multiscale modeling in biomechanics and mechanobiology

    CERN Document Server

    Hwang, Wonmuk; Kuhl, Ellen

    2015-01-01

    Presenting a state-of-the-art overview of theoretical and computational models that link characteristic biomechanical phenomena, this book provides guidelines and examples for creating multiscale models in representative systems and organisms. It develops the reader's understanding of and intuition for multiscale phenomena in biomechanics and mechanobiology, and introduces a mathematical framework and computational techniques paramount to creating predictive multiscale models.   Biomechanics involves the study of the interactions of physical forces with biological systems at all scales – including molecular, cellular, tissue and organ scales. The emerging field of mechanobiology focuses on the way that cells produce and respond to mechanical forces – bridging the science of mechanics with the disciplines of genetics and molecular biology. Linking disparate spatial and temporal scales using computational techniques is emerging as a key concept in investigating some of the complex problems underlying these...

  16. Implementation of Grid-computing Framework for Simulation in Multi-scale Structural Analysis

    Directory of Open Access Journals (Sweden)

    Data Iranata

    2010-05-01

    Full Text Available A new grid-computing framework for simulation in multi-scale structural analysis is presented. Two levels of parallel processing will be involved in this framework: multiple local distributed computing environments connected by local network to form a grid-based cluster-to-cluster distributed computing environment. To successfully perform the simulation, a large-scale structural system task is decomposed into the simulations of a simplified global model and several detailed component models using various scales. These correlated multi-scale structural system tasks are distributed among clusters and connected together in a multi-level hierarchy and then coordinated over the internet. The software framework for supporting the multi-scale structural simulation approach is also presented. The program architecture design allows the integration of several multi-scale models as clients and servers under a single platform. To check its feasibility, a prototype software system has been designed and implemented to perform the proposed concept. The simulation results show that the software framework can increase the speedup performance of the structural analysis. Based on this result, the proposed grid-computing framework is suitable to perform the simulation of the multi-scale structural analysis.

  17. Development of a Sampling-Based Global Sensitivity Analysis Workflow for Multiscale Computational Cancer Models

    Science.gov (United States)

    Wang, Zhihui; Deisboeck, Thomas S.; Cristini, Vittorio

    2014-01-01

    There are two challenges that researchers face when performing global sensitivity analysis (GSA) on multiscale in silico cancer models. The first is increased computational intensity, since a multiscale cancer model generally takes longer to run than does a scale-specific model. The second problem is the lack of a best GSA method that fits all types of models, which implies that multiple methods and their sequence need to be taken into account. In this article, we therefore propose a sampling-based GSA workflow consisting of three phases – pre-analysis, analysis, and post-analysis – by integrating Monte Carlo and resampling methods with the repeated use of analysis of variance (ANOVA); we then exemplify this workflow using a two-dimensional multiscale lung cancer model. By accounting for all parameter rankings produced by multiple GSA methods, a summarized ranking is created at the end of the workflow based on the weighted mean of the rankings for each input parameter. For the cancer model investigated here, this analysis reveals that ERK, a downstream molecule of the EGFR signaling pathway, has the most important impact on regulating both the tumor volume and expansion rate in the algorithm used. PMID:25257020

  18. Multiscale methods in turbulent combustion: strategies and computational challenges

    International Nuclear Information System (INIS)

    Echekki, Tarek

    2009-01-01

    A principal challenge in modeling turbulent combustion flows is associated with their complex, multiscale nature. Traditional paradigms in the modeling of these flows have attempted to address this nature through different strategies, including exploiting the separation of turbulence and combustion scales and a reduced description of the composition space. The resulting moment-based methods often yield reasonable predictions of flow and reactive scalars' statistics under certain conditions. However, these methods must constantly evolve to address combustion at different regimes, modes or with dominant chemistries. In recent years, alternative multiscale strategies have emerged, which although in part inspired by the traditional approaches, also draw upon basic tools from computational science, applied mathematics and the increasing availability of powerful computational resources. This review presents a general overview of different strategies adopted for multiscale solutions of turbulent combustion flows. Within these strategies, some specific models are discussed or outlined to illustrate their capabilities and underlying assumptions. These strategies may be classified under four different classes, including (i) closure models for atomistic processes, (ii) multigrid and multiresolution strategies, (iii) flame-embedding strategies and (iv) hybrid large-eddy simulation-low-dimensional strategies. A combination of these strategies and models can potentially represent a robust alternative strategy to moment-based models; but a significant challenge remains in the development of computational frameworks for these approaches as well as their underlying theories. (topical review)

  19. Multiscale modeling of mucosal immune responses

    Science.gov (United States)

    2015-01-01

    Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM. Background Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Implementation Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. Conclusion We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut

  20. Multiscale modeling of mucosal immune responses.

    Science.gov (United States)

    Mei, Yongguo; Abedi, Vida; Carbo, Adria; Zhang, Xiaoying; Lu, Pinyi; Philipson, Casandra; Hontecillas, Raquel; Hoops, Stefan; Liles, Nathan; Bassaganya-Riera, Josep

    2015-01-01

    Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation.Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T

  1. Predictive multiscale computational model of shoe-floor coefficient of friction.

    Science.gov (United States)

    Moghaddam, Seyed Reza M; Acharya, Arjun; Redfern, Mark S; Beschorner, Kurt E

    2018-01-03

    Understanding the frictional interactions between the shoe and floor during walking is critical to prevention of slips and falls, particularly when contaminants are present. A multiscale finite element model of shoe-floor-contaminant friction was developed that takes into account the surface and material characteristics of the shoe and flooring in microscopic and macroscopic scales. The model calculates shoe-floor coefficient of friction (COF) in boundary lubrication regime where effects of adhesion friction and hydrodynamic pressures are negligible. The validity of model outputs was assessed by comparing model predictions to the experimental results from mechanical COF testing. The multiscale model estimates were linearly related to the experimental results (p < 0.0001). The model predicted 73% of variability in experimentally-measured shoe-floor-contaminant COF. The results demonstrate the potential of multiscale finite element modeling in aiding slip-resistant shoe and flooring design and reducing slip and fall injuries. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  2. Distributed multiscale computing with MUSCLE 2, the Multiscale Coupling Library and Environment

    NARCIS (Netherlands)

    Borgdorff, J.; Mamonski, M.; Bosak, B.; Kurowski, K.; Ben Belgacem, M.; Chopard, B.; Groen, D.; Coveney, P.V.; Hoekstra, A.G.

    2014-01-01

    We present the Multiscale Coupling Library and Environment: MUSCLE 2. This multiscale component-based execution environment has a simple to use Java, C++, C, Python and Fortran API, compatible with MPI, OpenMP and threading codes. We demonstrate its local and distributed computing capabilities and

  3. Multiscale Computational Fluid Dynamics: Methodology and Application to PECVD of Thin Film Solar Cells

    Directory of Open Access Journals (Sweden)

    Marquis Crose

    2017-02-01

    Full Text Available This work focuses on the development of a multiscale computational fluid dynamics (CFD simulation framework with application to plasma-enhanced chemical vapor deposition of thin film solar cells. A macroscopic, CFD model is proposed which is capable of accurately reproducing plasma chemistry and transport phenomena within a 2D axisymmetric reactor geometry. Additionally, the complex interactions that take place on the surface of a-Si:H thin films are coupled with the CFD simulation using a novel kinetic Monte Carlo scheme which describes the thin film growth, leading to a multiscale CFD model. Due to the significant computational challenges imposed by this multiscale CFD model, a parallel computation strategy is presented which allows for reduced processing time via the discretization of both the gas-phase mesh and microscopic thin film growth processes. Finally, the multiscale CFD model has been applied to the PECVD process at industrially relevant operating conditions revealing non-uniformities greater than 20% in the growth rate of amorphous silicon films across the radius of the wafer.

  4. A high-order multiscale finite-element method for time-domain acoustic-wave modeling

    Science.gov (United States)

    Gao, Kai; Fu, Shubin; Chung, Eric T.

    2018-05-01

    Accurate and efficient wave equation modeling is vital for many applications in such as acoustics, electromagnetics, and seismology. However, solving the wave equation in large-scale and highly heterogeneous models is usually computationally expensive because the computational cost is directly proportional to the number of grids in the model. We develop a novel high-order multiscale finite-element method to reduce the computational cost of time-domain acoustic-wave equation numerical modeling by solving the wave equation on a coarse mesh based on the multiscale finite-element theory. In contrast to existing multiscale finite-element methods that use only first-order multiscale basis functions, our new method constructs high-order multiscale basis functions from local elliptic problems which are closely related to the Gauss-Lobatto-Legendre quadrature points in a coarse element. Essentially, these basis functions are not only determined by the order of Legendre polynomials, but also by local medium properties, and therefore can effectively convey the fine-scale information to the coarse-scale solution with high-order accuracy. Numerical tests show that our method can significantly reduce the computation time while maintain high accuracy for wave equation modeling in highly heterogeneous media by solving the corresponding discrete system only on the coarse mesh with the new high-order multiscale basis functions.

  5. Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.

    Directory of Open Access Journals (Sweden)

    Matthew B Biggs

    Full Text Available Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool.

  6. Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.

    Science.gov (United States)

    Biggs, Matthew B; Papin, Jason A

    2013-01-01

    Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool.

  7. Multifunctional multiscale composites: Processing, modeling and characterization

    Science.gov (United States)

    Qiu, Jingjing

    Carbon nanotubes (CNTs) demonstrate extraordinary properties and show great promise in enhancing out-of-plane properties of traditional polymer/fiber composites and enabling functionality. However, current manufacturing challenges hinder the realization of their potential. In the dissertation research, both experimental and computational efforts have been conducted to investigate effective manufacturing techniques of CNT integrated multiscale composites. The fabricated composites demonstrated significant improvements in physical properties, such as tensile strength, tensile modulus, inter-laminar shear strength, thermal dimension stability and electrical conductivity. Such multiscale composites were truly multifunctional with the addition of CNTs. Furthermore, a novel hierarchical multiscale modeling method was developed in this research. Molecular dynamic (MD) simulation offered reasonable explanation of CNTs dispersion and their motion in polymer solution. Bi-mode finite-extensible-nonlinear-elastic (FENE) dumbbell simulation was used to analyze the influence of CNT length distribution on the stress tensor and shear-rate-dependent viscosity. Based on the simulated viscosity profile and empirical equations from experiments, a macroscale flow simulation model on the finite element method (FEM) method was developed and validated to predict resin flow behavior in the processing of CNT-enhanced multiscale composites. The proposed multiscale modeling method provided a comprehensive understanding of micro/nano flow in both atomistic details and mesoscale. The simulation model can be used to optimize process design and control of the mold-filling process in multiscale composite manufacturing. This research provided systematic investigations into the CNT-based multiscale composites. The results from this study may be used to leverage the benefits of CNTs and open up new application opportunities for high-performance multifunctional multiscale composites. Keywords. Carbon

  8. Integrated multiscale modeling of molecular computing devices

    International Nuclear Information System (INIS)

    Cummings, Peter T; Leng Yongsheng

    2005-01-01

    Molecular electronics, in which single organic molecules are designed to perform the functions of transistors, diodes, switches and other circuit elements used in current siliconbased microelecronics, is drawing wide interest as a potential replacement technology for conventional silicon-based lithographically etched microelectronic devices. In addition to their nanoscopic scale, the additional advantage of molecular electronics devices compared to silicon-based lithographically etched devices is the promise of being able to produce them cheaply on an industrial scale using wet chemistry methods (i.e., self-assembly from solution). The design of molecular electronics devices, and the processes to make them on an industrial scale, will require a thorough theoretical understanding of the molecular and higher level processes involved. Hence, the development of modeling techniques for molecular electronics devices is a high priority from both a basic science point of view (to understand the experimental studies in this field) and from an applied nanotechnology (manufacturing) point of view. Modeling molecular electronics devices requires computational methods at all length scales - electronic structure methods for calculating electron transport through organic molecules bonded to inorganic surfaces, molecular simulation methods for determining the structure of self-assembled films of organic molecules on inorganic surfaces, mesoscale methods to understand and predict the formation of mesoscale patterns on surfaces (including interconnect architecture), and macroscopic scale methods (including finite element methods) for simulating the behavior of molecular electronic circuit elements in a larger integrated device. Here we describe a large Department of Energy project involving six universities and one national laboratory aimed at developing integrated multiscale methods for modeling molecular electronics devices. The project is funded equally by the Office of Basic

  9. Multiscale Space-Time Computational Methods for Fluid-Structure Interactions

    Science.gov (United States)

    2015-09-13

    thermo-fluid analysis of a ground vehicle and its tires ST-SI Computational Analysis of a Vertical - Axis Wind Turbine We have successfully...of a vertical - axis wind turbine . Multiscale Compressible-Flow Computation with Particle Tracking We have successfully tested the multiscale...Tezduyar, Spenser McIntyre, Nikolay Kostov, Ryan Kolesar, Casey Habluetzel. Space–time VMS computation of wind - turbine rotor and tower aerodynamics

  10. REVIEW OF THE GOVERNING EQUATIONS, COMPUTATIONAL ALGORITHMS, AND OTHER COMPONENTS OF THE MODELS-3 COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODELING SYSTEM

    Science.gov (United States)

    This article describes the governing equations, computational algorithms, and other components entering into the Community Multiscale Air Quality (CMAQ) modeling system. This system has been designed to approach air quality as a whole by including state-of-the-science capabiliti...

  11. Front-end vision and multi-scale image analysis multi-scale computer vision theory and applications, written in Mathematica

    CERN Document Server

    Romeny, Bart M Haar

    2008-01-01

    Front-End Vision and Multi-Scale Image Analysis is a tutorial in multi-scale methods for computer vision and image processing. It builds on the cross fertilization between human visual perception and multi-scale computer vision (`scale-space') theory and applications. The multi-scale strategies recognized in the first stages of the human visual system are carefully examined, and taken as inspiration for the many geometric methods discussed. All chapters are written in Mathematica, a spectacular high-level language for symbolic and numerical manipulations. The book presents a new and effective

  12. Integrated multiscale biomaterials experiment and modelling: a perspective

    Science.gov (United States)

    Buehler, Markus J.; Genin, Guy M.

    2016-01-01

    Advances in multiscale models and computational power have enabled a broad toolset to predict how molecules, cells, tissues and organs behave and develop. A key theme in biological systems is the emergence of macroscale behaviour from collective behaviours across a range of length and timescales, and a key element of these models is therefore hierarchical simulation. However, this predictive capacity has far outstripped our ability to validate predictions experimentally, particularly when multiple hierarchical levels are involved. The state of the art represents careful integration of multiscale experiment and modelling, and yields not only validation, but also insights into deformation and relaxation mechanisms across scales. We present here a sampling of key results that highlight both challenges and opportunities for integrated multiscale experiment and modelling in biological systems. PMID:28981126

  13. Efficient Computation of Multiscale Entropy over Short Biomedical Time Series Based on Linear State-Space Models

    Directory of Open Access Journals (Sweden)

    Luca Faes

    2017-01-01

    Full Text Available The most common approach to assess the dynamical complexity of a time series across multiple temporal scales makes use of the multiscale entropy (MSE and refined MSE (RMSE measures. In spite of their popularity, MSE and RMSE lack an analytical framework allowing their calculation for known dynamic processes and cannot be reliably computed over short time series. To overcome these limitations, we propose a method to assess RMSE for autoregressive (AR stochastic processes. The method makes use of linear state-space (SS models to provide the multiscale parametric representation of an AR process observed at different time scales and exploits the SS parameters to quantify analytically the complexity of the process. The resulting linear MSE (LMSE measure is first tested in simulations, both theoretically to relate the multiscale complexity of AR processes to their dynamical properties and over short process realizations to assess its computational reliability in comparison with RMSE. Then, it is applied to the time series of heart period, arterial pressure, and respiration measured for healthy subjects monitored in resting conditions and during physiological stress. This application to short-term cardiovascular variability documents that LMSE can describe better than RMSE the activity of physiological mechanisms producing biological oscillations at different temporal scales.

  14. Hierarchical multiscale modeling for flows in fractured media using generalized multiscale finite element method

    KAUST Repository

    Efendiev, Yalchin R.

    2015-06-05

    In this paper, we develop a multiscale finite element method for solving flows in fractured media. Our approach is based on generalized multiscale finite element method (GMsFEM), where we represent the fracture effects on a coarse grid via multiscale basis functions. These multiscale basis functions are constructed in the offline stage via local spectral problems following GMsFEM. To represent the fractures on the fine grid, we consider two approaches (1) discrete fracture model (DFM) (2) embedded fracture model (EFM) and their combination. In DFM, the fractures are resolved via the fine grid, while in EFM the fracture and the fine grid block interaction is represented as a source term. In the proposed multiscale method, additional multiscale basis functions are used to represent the long fractures, while short-size fractures are collectively represented by a single basis functions. The procedure is automatically done via local spectral problems. In this regard, our approach shares common concepts with several approaches proposed in the literature as we discuss. We would like to emphasize that our goal is not to compare DFM with EFM, but rather to develop GMsFEM framework which uses these (DFM or EFM) fine-grid discretization techniques. Numerical results are presented, where we demonstrate how one can adaptively add basis functions in the regions of interest based on error indicators. We also discuss the use of randomized snapshots (Calo et al. Randomized oversampling for generalized multiscale finite element methods, 2014), which reduces the offline computational cost.

  15. Fast Multiscale Reservoir Simulations using POD-DEIM Model Reduction

    KAUST Repository

    Ghasemi, Mohammadreza; Yang, Yanfang; Gildin, Eduardo; Efendiev, Yalchin R.; Calo, Victor M.

    2015-01-01

    snapshots are inexpensively computed using local model reduction techniques based on Generalized Multiscale Finite Element Method (GMsFEM) which provides (1) a hierarchical approximation of snapshot vectors (2) adaptive computations by using coarse grids (3

  16. A posteriori error analysis of multiscale operator decomposition methods for multiphysics models

    International Nuclear Information System (INIS)

    Estep, D; Carey, V; Tavener, S; Ginting, V; Wildey, T

    2008-01-01

    Multiphysics, multiscale models present significant challenges in computing accurate solutions and for estimating the error in information computed from numerical solutions. In this paper, we describe recent advances in extending the techniques of a posteriori error analysis to multiscale operator decomposition solution methods. While the particulars of the analysis vary considerably with the problem, several key ideas underlie a general approach being developed to treat operator decomposition multiscale methods. We explain these ideas in the context of three specific examples

  17. Multiscale Modeling in the Clinic: Drug Design and Development

    Energy Technology Data Exchange (ETDEWEB)

    Clancy, Colleen E.; An, Gary; Cannon, William R.; Liu, Yaling; May, Elebeoba E.; Ortoleva, Peter; Popel, Aleksander S.; Sluka, James P.; Su, Jing; Vicini, Paolo; Zhou, Xiaobo; Eckmann, David M.

    2016-02-17

    A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multi-scale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multi-scale approaches present in silico opportunities to advance laboratory research to bedside clinical applications in pharmaceuticals research. This is achievable through the capability of modeling to reveal phenomena occurring across multiple spatial and temporal scales, which are not otherwise readily accessible to experimentation. The resultant models, when validated, are capable of making testable predictions to guide drug design and delivery. In this review we describe the goals, methods, and opportunities of multi-scale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical techniques employed for multi-scale modeling approaches used in pharmacology and present several examples illustrating the current state-of-the-art regarding drug development for: Excitable Systems (Heart); Cancer (Metastasis and Differentiation); Cancer (Angiogenesis and Drug Targeting); Metabolic Disorders; and Inflammation and Sepsis. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multi-scale models.

  18. Foundations for a multiscale collaborative Earth model

    KAUST Repository

    Afanasiev, M.; Peter, Daniel; Sager, K.; Simut, S.; Ermert, L.; Krischer, L.; Fichtner, A.

    2015-01-01

    . The CSEM as a computational framework is intended to help bridging the gap between local, regional and global tomography, and to contribute to the development of a global multiscale Earth model. While the current construction serves as a first proof

  19. Multiscale modelling of nanostructures

    International Nuclear Information System (INIS)

    Vvedensky, Dimitri D

    2004-01-01

    Most materials phenomena are manifestations of processes that are operative over a vast range of length and time scales. A complete understanding of the behaviour of materials thereby requires theoretical and computational tools that span the atomic-scale detail of first-principles methods and the more coarse-grained description provided by continuum equations. Recent efforts have focused on combining traditional methodologies-density functional theory, molecular dynamics, Monte Carlo methods and continuum descriptions-within a unified multiscale framework. This review covers the techniques that have been developed to model various aspects of materials behaviour with the ultimate aim of systematically coupling the atomistic to the continuum descriptions. The approaches described typically have been motivated by particular applications but can often be applied in wider contexts. The self-assembly of quantum dot ensembles will be used as a case study for the issues that arise and the methods used for all nanostructures. Although quantum dots can be obtained with all the standard growth methods and for a variety of material systems, their appearance is a quite selective process, involving the competition between equilibrium and kinetic effects, and the interplay between atomistic and long-range interactions. Most theoretical models have addressed particular aspects of the ordering kinetics of quantum dot ensembles, with far fewer attempts at a comprehensive synthesis of this inherently multiscale phenomenon. We conclude with an assessment of the current status of multiscale modelling strategies and highlight the main outstanding issues. (topical review)

  20. Multiscale Signal Analysis and Modeling

    CERN Document Server

    Zayed, Ahmed

    2013-01-01

    Multiscale Signal Analysis and Modeling presents recent advances in multiscale analysis and modeling using wavelets and other systems. This book also presents applications in digital signal processing using sampling theory and techniques from various function spaces, filter design, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and statistical learning theory. This book also: Discusses recently developed signal modeling techniques, such as the multiscale method for complex time series modeling, multiscale positive density estimations, Bayesian Shrinkage Strategies, and algorithms for data adaptive statistics Introduces new sampling algorithms for multidimensional signal processing Provides comprehensive coverage of wavelets with presentations on waveform design and modeling, wavelet analysis of ECG signals and wavelet filters Reviews features extraction and classification algorithms for multiscale signal and image proce...

  1. Efficient algorithms for multiscale modeling in porous media

    KAUST Repository

    Wheeler, Mary F.; Wildey, Tim; Xue, Guangri

    2010-01-01

    We describe multiscale mortar mixed finite element discretizations for second-order elliptic and nonlinear parabolic equations modeling Darcy flow in porous media. The continuity of flux is imposed via a mortar finite element space on a coarse grid scale, while the equations in the coarse elements (or subdomains) are discretized on a fine grid scale. We discuss the construction of multiscale mortar basis and extend this concept to nonlinear interface operators. We present a multiscale preconditioning strategy to minimize the computational cost associated with construction of the multiscale mortar basis. We also discuss the use of appropriate quadrature rules and approximation spaces to reduce the saddle point system to a cell-centered pressure scheme. In particular, we focus on multiscale mortar multipoint flux approximation method for general hexahedral grids and full tensor permeabilities. Numerical results are presented to verify the accuracy and efficiency of these approaches. © 2010 John Wiley & Sons, Ltd.

  2. Efficient algorithms for multiscale modeling in porous media

    KAUST Repository

    Wheeler, Mary F.

    2010-09-26

    We describe multiscale mortar mixed finite element discretizations for second-order elliptic and nonlinear parabolic equations modeling Darcy flow in porous media. The continuity of flux is imposed via a mortar finite element space on a coarse grid scale, while the equations in the coarse elements (or subdomains) are discretized on a fine grid scale. We discuss the construction of multiscale mortar basis and extend this concept to nonlinear interface operators. We present a multiscale preconditioning strategy to minimize the computational cost associated with construction of the multiscale mortar basis. We also discuss the use of appropriate quadrature rules and approximation spaces to reduce the saddle point system to a cell-centered pressure scheme. In particular, we focus on multiscale mortar multipoint flux approximation method for general hexahedral grids and full tensor permeabilities. Numerical results are presented to verify the accuracy and efficiency of these approaches. © 2010 John Wiley & Sons, Ltd.

  3. Multi-scale analysis of lung computed tomography images

    CERN Document Server

    Gori, I; Fantacci, M E; Preite Martinez, A; Retico, A; De Mitri, I; Donadio, S; Fulcheri, C

    2007-01-01

    A computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The three modules of our lung CAD system, a segmentation algorithm for lung internal region identification, a multi-scale dot-enhancement filter for nodule candidate selection and a multi-scale neural technique for false positive finding reduction, are described. The results obtained on a dataset of low-dose and thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.

  4. Multiscale information modelling for heart morphogenesis

    Energy Technology Data Exchange (ETDEWEB)

    Abdulla, T; Imms, R; Summers, R [Department of Electronic and Electrical Engineering, Loughborough University, Loughborough (United Kingdom); Schleich, J M, E-mail: T.Abdulla@lboro.ac.u [LTSI Signal and Image Processing Laboratory, University of Rennes 1, Rennes (France)

    2010-07-01

    Science is made feasible by the adoption of common systems of units. As research has become more data intensive, especially in the biomedical domain, it requires the adoption of a common system of information models, to make explicit the relationship between one set of data and another, regardless of format. This is being realised through the OBO Foundry to develop a suite of reference ontologies, and NCBO Bioportal to provide services to integrate biomedical resources and functionality to visualise and create mappings between ontology terms. Biomedical experts tend to be focused at one level of spatial scale, be it biochemistry, cell biology, or anatomy. Likewise, the ontologies they use tend to be focused at a particular level of scale. There is increasing interest in a multiscale systems approach, which attempts to integrate between different levels of scale to gain understanding of emergent effects. This is a return to physiological medicine with a computational emphasis, exemplified by the worldwide Physiome initiative, and the European Union funded Network of Excellence in the Virtual Physiological Human. However, little work has been done on how information modelling itself may be tailored to a multiscale systems approach. We demonstrate how this can be done for the complex process of heart morphogenesis, which requires multiscale understanding in both time and spatial domains. Such an effort enables the integration of multiscale metrology.

  5. Multiscale information modelling for heart morphogenesis

    International Nuclear Information System (INIS)

    Abdulla, T; Imms, R; Summers, R; Schleich, J M

    2010-01-01

    Science is made feasible by the adoption of common systems of units. As research has become more data intensive, especially in the biomedical domain, it requires the adoption of a common system of information models, to make explicit the relationship between one set of data and another, regardless of format. This is being realised through the OBO Foundry to develop a suite of reference ontologies, and NCBO Bioportal to provide services to integrate biomedical resources and functionality to visualise and create mappings between ontology terms. Biomedical experts tend to be focused at one level of spatial scale, be it biochemistry, cell biology, or anatomy. Likewise, the ontologies they use tend to be focused at a particular level of scale. There is increasing interest in a multiscale systems approach, which attempts to integrate between different levels of scale to gain understanding of emergent effects. This is a return to physiological medicine with a computational emphasis, exemplified by the worldwide Physiome initiative, and the European Union funded Network of Excellence in the Virtual Physiological Human. However, little work has been done on how information modelling itself may be tailored to a multiscale systems approach. We demonstrate how this can be done for the complex process of heart morphogenesis, which requires multiscale understanding in both time and spatial domains. Such an effort enables the integration of multiscale metrology.

  6. A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

    Science.gov (United States)

    Pârvu, Ovidiu; Gilbert, David

    2016-01-01

    Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour

  7. Multiscale Computation. Needs and Opportunities for BER Science

    Energy Technology Data Exchange (ETDEWEB)

    Scheibe, Timothy D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Smith, Jeremy C. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2015-01-01

    The Environmental Molecular Sciences Laboratory (EMSL), a scientific user facility managed by Pacific Northwest National Laboratory for the U.S. Department of Energy, Office of Biological and Environmental Research (BER), conducted a one-day workshop on August 26, 2014 on the topic of “Multiscale Computation: Needs and Opportunities for BER Science.” Twenty invited participants, from various computational disciplines within the BER program research areas, were charged with the following objectives; Identify BER-relevant models and their potential cross-scale linkages that could be exploited to better connect molecular-scale research to BER research at larger scales and; Identify critical science directions that will motivate EMSL decisions regarding future computational (hardware and software) architectures.

  8. Multiscale modelling approaches for assessing cosmetic ingredients safety.

    Science.gov (United States)

    Bois, Frédéric Y; Ochoa, Juan G Diaz; Gajewska, Monika; Kovarich, Simona; Mauch, Klaus; Paini, Alicia; Péry, Alexandre; Benito, Jose Vicente Sala; Teng, Sophie; Worth, Andrew

    2017-12-01

    The European Union's ban on animal testing for cosmetic ingredients and products has generated a strong momentum for the development of in silico and in vitro alternative methods. One of the focus of the COSMOS project was ab initio prediction of kinetics and toxic effects through multiscale pharmacokinetic modeling and in vitro data integration. In our experience, mathematical or computer modeling and in vitro experiments are complementary. We present here a summary of the main models and results obtained within the framework of the project on these topics. A first section presents our work at the organelle and cellular level. We then go toward modeling cell levels effects (monitored continuously), multiscale physiologically based pharmacokinetic and effect models, and route to route extrapolation. We follow with a short presentation of the automated KNIME workflows developed for dissemination and easy use of the models. We end with a discussion of two challenges to the field: our limited ability to deal with massive data and complex computations. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  9. Multiscale Modeling of Poromechanics in Geologic Media

    Science.gov (United States)

    Castelletto, N.; Hajibeygi, H.; Klevtsov, S.; Tchelepi, H.

    2017-12-01

    We describe a hybrid MultiScale Finite Element-Finite Volume (h-MSFE-FV) framework for the simulation of single-phase Darcy flow through deformable porous media that exhibit highly heterogeneous poromechanical properties over a wide range of length scales. In such systems, high resolution characterizations are a key requirement to obtain reliable modeling predictions and motivate the development of multiscale solution strategies to cope with the computational burden. A coupled two-field fine-scale mixed FE-FV discretization of the governing equations, namely conservation laws of linear momentum and mass, is first implemented based on a displacement-pressure formulation. After imposing a coarse-scale grid on the given fine-scale problem, for the MSFE displacement stage, the coarse-scale basis functions are obtained by solving local equilibrium problems within coarse elements. Such MSFE stage is then coupled with the MSFV method for flow, in which a dual-coarse grid is introduced to obtain approximate but conservative multiscale solutions. Robustness and accuracy of the proposed multiscale framework is demonstrated using a variety of challenging test problems.

  10. Multiscale paradigms in integrated computational materials science and engineering materials theory, modeling, and simulation for predictive design

    CERN Document Server

    Runge, Keith; Muralidharan, Krishna

    2016-01-01

    This book presents cutting-edge concepts, paradigms, and research highlights in the field of computational materials science and engineering, and provides a fresh, up-to-date perspective on solving present and future materials challenges. The chapters are written by not only pioneers in the fields of computational materials chemistry and materials science, but also experts in multi-scale modeling and simulation as applied to materials engineering. Pedagogical introductions to the different topics and continuity between the chapters are provided to ensure the appeal to a broad audience and to address the applicability of integrated computational materials science and engineering for solving real-world problems.

  11. The Feasibility of Multiscale Modeling of Tunnel Fires Using FDS 6

    DEFF Research Database (Denmark)

    Vermesi, Izabella; Colella, Francesco; Rein, Guillermo

    2014-01-01

    The HVAC component of FDS 6 was used to divide a 1.2km tunnel into a 3D near fire area and a 1D area further away from the fire in order to investigate the feasibility of multiscale modeling of tunnel fires with this new feature in FDS. The two sub-models were coupled directly. The results were...... compared with reference works on multiscale modeling and the outcome is considered positive, with a deviation of less than 5% in magnitude of relevant parameters, yet with a significant reduction of the simulation runtime. As such, the multiscale method is deemed feasible for simulating tunnel fires in FDS......6. However, the simplifications that are made in this work require further investigation in order to take full advantage of the potential of this computational method. INTRODUCTION Multiscale modeling for tunnel flows and fires has previously been studied using RANS general purpose CFD software...

  12. Multiscale modelling for tokamak pedestals

    Science.gov (United States)

    Abel, I. G.

    2018-04-01

    Pedestal modelling is crucial to predict the performance of future fusion devices. Current modelling efforts suffer either from a lack of kinetic physics, or an excess of computational complexity. To ameliorate these problems, we take a first-principles multiscale approach to the pedestal. We will present three separate sets of equations, covering the dynamics of edge localised modes (ELMs), the inter-ELM pedestal and pedestal turbulence, respectively. Precisely how these equations should be coupled to each other is covered in detail. This framework is completely self-consistent; it is derived from first principles by means of an asymptotic expansion of the fundamental Vlasov-Landau-Maxwell system in appropriate small parameters. The derivation exploits the narrowness of the pedestal region, the smallness of the thermal gyroradius and the low plasma (the ratio of thermal to magnetic pressures) typical of current pedestal operation to achieve its simplifications. The relationship between this framework and gyrokinetics is analysed, and possibilities to directly match our systems of equations onto multiscale gyrokinetics are explored. A detailed comparison between our model and other models in the literature is performed. Finally, the potential for matching this framework onto an open-field-line region is briefly discussed.

  13. Computational design and multiscale modeling of a nanoactuator using DNA actuation

    International Nuclear Information System (INIS)

    Hamdi, Mustapha

    2009-01-01

    Developments in the field of nano-biodevices coupling nanostructures and biological components are of great interest in medical nanorobotics. As the fundamentals of bio/non-bio interaction processes are still poorly understood in the design of these devices, design tools and multiscale dynamics modeling approaches are necessary at the fabrication pre-project stage. This paper proposes a new concept of optimized carbon nanotube based servomotor design for drug delivery and biomolecular transport applications. The design of an encapsulated DNA-multi-walled carbon nanotube actuator is prototyped using multiscale modeling. The system is parametrized by using a quantum level approach and characterized by using a molecular dynamics simulation. Based on the analysis of the simulation results, a servo nanoactuator using ionic current feedback is simulated and analyzed for application as a drug delivery carrier.

  14. A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

    Science.gov (United States)

    Tao, W. K.

    2017-12-01

    In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

  15. An eye model for computational dosimetry using a multi-scale voxel phantom

    International Nuclear Information System (INIS)

    Caracappa, P.F.; Rhodes, A.; Fiedler, D.

    2013-01-01

    The lens of the eye is a radiosensitive tissue with cataract formation being the major concern. Recently reduced recommended dose limits to the lens of the eye have made understanding the dose to this tissue of increased importance. Due to memory limitations, the voxel resolution of computational phantoms used for radiation dose calculations is too large to accurately represent the dimensions of the eye. A revised eye model is constructed using physiological data for the dimensions of radiosensitive tissues, and is then transformed into a high-resolution voxel model. This eye model is combined with an existing set of whole body models to form a multi-scale voxel phantom, which is used with the MCNPX code to calculate radiation dose from various exposure types. This phantom provides an accurate representation of the radiation transport through the structures of the eye. Two alternate methods of including a high-resolution eye model within an existing whole body model are developed. When the Lattice Overlay method, the simpler of the two to define, is utilized, the computational penalty in terms of speed is noticeable and the figure of merit for the eye dose tally decreases by as much as a factor of two. When the Voxel Substitution method is applied, the penalty in speed is nearly trivial and the impact on the tally figure of merit is comparatively smaller. The origin of this difference in the code behavior may warrant further investigation

  16. A review of predictive nonlinear theories for multiscale modeling of heterogeneous materials

    Energy Technology Data Exchange (ETDEWEB)

    Matouš, Karel, E-mail: kmatous@nd.edu [Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556 (United States); Geers, Marc G.D.; Kouznetsova, Varvara G. [Department of Mechanical Engineering, Eindhoven University of Technology, Eindhoven (Netherlands); Gillman, Andrew [Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556 (United States)

    2017-02-01

    Since the beginning of the industrial age, material performance and design have been in the midst of innovation of many disruptive technologies. Today's electronics, space, medical, transportation, and other industries are enriched by development, design and deployment of composite, heterogeneous and multifunctional materials. As a result, materials innovation is now considerably outpaced by other aspects from component design to product cycle. In this article, we review predictive nonlinear theories for multiscale modeling of heterogeneous materials. Deeper attention is given to multiscale modeling in space and to computational homogenization in addressing challenging materials science questions. Moreover, we discuss a state-of-the-art platform in predictive image-based, multiscale modeling with co-designed simulations and experiments that executes on the world's largest supercomputers. Such a modeling framework consists of experimental tools, computational methods, and digital data strategies. Once fully completed, this collaborative and interdisciplinary framework can be the basis of Virtual Materials Testing standards and aids in the development of new material formulations. Moreover, it will decrease the time to market of innovative products.

  17. A review of predictive nonlinear theories for multiscale modeling of heterogeneous materials

    Science.gov (United States)

    Matouš, Karel; Geers, Marc G. D.; Kouznetsova, Varvara G.; Gillman, Andrew

    2017-02-01

    Since the beginning of the industrial age, material performance and design have been in the midst of innovation of many disruptive technologies. Today's electronics, space, medical, transportation, and other industries are enriched by development, design and deployment of composite, heterogeneous and multifunctional materials. As a result, materials innovation is now considerably outpaced by other aspects from component design to product cycle. In this article, we review predictive nonlinear theories for multiscale modeling of heterogeneous materials. Deeper attention is given to multiscale modeling in space and to computational homogenization in addressing challenging materials science questions. Moreover, we discuss a state-of-the-art platform in predictive image-based, multiscale modeling with co-designed simulations and experiments that executes on the world's largest supercomputers. Such a modeling framework consists of experimental tools, computational methods, and digital data strategies. Once fully completed, this collaborative and interdisciplinary framework can be the basis of Virtual Materials Testing standards and aids in the development of new material formulations. Moreover, it will decrease the time to market of innovative products.

  18. A review of predictive nonlinear theories for multiscale modeling of heterogeneous materials

    International Nuclear Information System (INIS)

    Matouš, Karel; Geers, Marc G.D.; Kouznetsova, Varvara G.; Gillman, Andrew

    2017-01-01

    Since the beginning of the industrial age, material performance and design have been in the midst of innovation of many disruptive technologies. Today's electronics, space, medical, transportation, and other industries are enriched by development, design and deployment of composite, heterogeneous and multifunctional materials. As a result, materials innovation is now considerably outpaced by other aspects from component design to product cycle. In this article, we review predictive nonlinear theories for multiscale modeling of heterogeneous materials. Deeper attention is given to multiscale modeling in space and to computational homogenization in addressing challenging materials science questions. Moreover, we discuss a state-of-the-art platform in predictive image-based, multiscale modeling with co-designed simulations and experiments that executes on the world's largest supercomputers. Such a modeling framework consists of experimental tools, computational methods, and digital data strategies. Once fully completed, this collaborative and interdisciplinary framework can be the basis of Virtual Materials Testing standards and aids in the development of new material formulations. Moreover, it will decrease the time to market of innovative products.

  19. Variational multiscale models for charge transport.

    Science.gov (United States)

    Wei, Guo-Wei; Zheng, Qiong; Chen, Zhan; Xia, Kelin

    2012-01-01

    This work presents a few variational multiscale models for charge transport in complex physical, chemical and biological systems and engineering devices, such as fuel cells, solar cells, battery cells, nanofluidics, transistors and ion channels. An essential ingredient of the present models, introduced in an earlier paper (Bulletin of Mathematical Biology, 72, 1562-1622, 2010), is the use of differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain from the microscopic domain, meanwhile, dynamically couple discrete and continuum descriptions. Our main strategy is to construct the total energy functional of a charge transport system to encompass the polar and nonpolar free energies of solvation, and chemical potential related energy. By using the Euler-Lagrange variation, coupled Laplace-Beltrami and Poisson-Nernst-Planck (LB-PNP) equations are derived. The solution of the LB-PNP equations leads to the minimization of the total free energy, and explicit profiles of electrostatic potential and densities of charge species. To further reduce the computational complexity, the Boltzmann distribution obtained from the Poisson-Boltzmann (PB) equation is utilized to represent the densities of certain charge species so as to avoid the computationally expensive solution of some Nernst-Planck (NP) equations. Consequently, the coupled Laplace-Beltrami and Poisson-Boltzmann-Nernst-Planck (LB-PBNP) equations are proposed for charge transport in heterogeneous systems. A major emphasis of the present formulation is the consistency between equilibrium LB-PB theory and non-equilibrium LB-PNP theory at equilibrium. Another major emphasis is the capability of the reduced LB-PBNP model to fully recover the prediction of the LB-PNP model at non-equilibrium settings. To account for the fluid impact on the charge transport, we derive coupled Laplace-Beltrami, Poisson-Nernst-Planck and Navier-Stokes equations from the variational principle

  20. Variational multiscale models for charge transport

    Science.gov (United States)

    Wei, Guo-Wei; Zheng, Qiong; Chen, Zhan; Xia, Kelin

    2012-01-01

    This work presents a few variational multiscale models for charge transport in complex physical, chemical and biological systems and engineering devices, such as fuel cells, solar cells, battery cells, nanofluidics, transistors and ion channels. An essential ingredient of the present models, introduced in an earlier paper (Bulletin of Mathematical Biology, 72, 1562-1622, 2010), is the use of differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain from the microscopic domain, meanwhile, dynamically couple discrete and continuum descriptions. Our main strategy is to construct the total energy functional of a charge transport system to encompass the polar and nonpolar free energies of solvation, and chemical potential related energy. By using the Euler-Lagrange variation, coupled Laplace-Beltrami and Poisson-Nernst-Planck (LB-PNP) equations are derived. The solution of the LB-PNP equations leads to the minimization of the total free energy, and explicit profiles of electrostatic potential and densities of charge species. To further reduce the computational complexity, the Boltzmann distribution obtained from the Poisson-Boltzmann (PB) equation is utilized to represent the densities of certain charge species so as to avoid the computationally expensive solution of some Nernst-Planck (NP) equations. Consequently, the coupled Laplace-Beltrami and Poisson-Boltzmann-Nernst-Planck (LB-PBNP) equations are proposed for charge transport in heterogeneous systems. A major emphasis of the present formulation is the consistency between equilibrium LB-PB theory and non-equilibrium LB-PNP theory at equilibrium. Another major emphasis is the capability of the reduced LB-PBNP model to fully recover the prediction of the LB-PNP model at non-equilibrium settings. To account for the fluid impact on the charge transport, we derive coupled Laplace-Beltrami, Poisson-Nernst-Planck and Navier-Stokes equations from the variational principle

  1. Multiscale Modeling and Uncertainty Quantification for Nuclear Fuel Performance

    Energy Technology Data Exchange (ETDEWEB)

    Estep, Donald [Colorado State Univ., Fort Collins, CO (United States); El-Azab, Anter [Florida State Univ., Tallahassee, FL (United States); Pernice, Michael [Idaho National Lab. (INL), Idaho Falls, ID (United States); Peterson, John W. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Polyakov, Peter [Univ. of Wyoming, Laramie, WY (United States); Tavener, Simon [Colorado State Univ., Fort Collins, CO (United States); Xiu, Dongbin [Purdue Univ., West Lafayette, IN (United States); Univ. of Utah, Salt Lake City, UT (United States)

    2017-03-23

    In this project, we will address the challenges associated with constructing high fidelity multiscale models of nuclear fuel performance. We (*) propose a novel approach for coupling mesoscale and macroscale models, (*) devise efficient numerical methods for simulating the coupled system, and (*) devise and analyze effective numerical approaches for error and uncertainty quantification for the coupled multiscale system. As an integral part of the project, we will carry out analysis of the effects of upscaling and downscaling, investigate efficient methods for stochastic sensitivity analysis of the individual macroscale and mesoscale models, and carry out a posteriori error analysis for computed results. We will pursue development and implementation of solutions in software used at Idaho National Laboratories on models of interest to the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program.

  2. State-of-the-Art Report on Multi-scale Modelling of Nuclear Fuels

    International Nuclear Information System (INIS)

    Bartel, T.J.; Dingreville, R.; Littlewood, D.; Tikare, V.; Bertolus, M.; Blanc, V.; Bouineau, V.; Carlot, G.; Desgranges, C.; Dorado, B.; Dumas, J.C.; Freyss, M.; Garcia, P.; Gatt, J.M.; Gueneau, C.; Julien, J.; Maillard, S.; Martin, G.; Masson, R.; Michel, B.; Piron, J.P.; Sabathier, C.; Skorek, R.; Toffolon, C.; Valot, C.; Van Brutzel, L.; Besmann, Theodore M.; Chernatynskiy, A.; Clarno, K.; Gorti, S.B.; Radhakrishnan, B.; Devanathan, R.; Dumont, M.; Maugis, P.; El-Azab, A.; Iglesias, F.C.; Lewis, B.J.; Krack, M.; Yun, Y.; Kurata, M.; Kurosaki, K.; Largenton, R.; Lebensohn, R.A.; Malerba, L.; Oh, J.Y.; Phillpot, S.R.; Tulenko, J. S.; Rachid, J.; Stan, M.; Sundman, B.; Tonks, M.R.; Williamson, R.; Van Uffelen, P.; Welland, M.J.; Valot, Carole; Stan, Marius; Massara, Simone; Tarsi, Reka

    2015-10-01

    The Nuclear Science Committee (NSC) of the Nuclear Energy Agency (NEA) has undertaken an ambitious programme to document state-of-the-art of modelling for nuclear fuels and structural materials. The project is being performed under the Working Party on Multi-Scale Modelling of Fuels and Structural Material for Nuclear Systems (WPMM), which has been established to assess the scientific and engineering aspects of fuels and structural materials, describing multi-scale models and simulations as validated predictive tools for the design of nuclear systems, fuel fabrication and performance. The WPMM's objective is to promote the exchange of information on models and simulations of nuclear materials, theoretical and computational methods, experimental validation and related topics. It also provides member countries with up-to-date information, shared data, models, and expertise. The goal is also to assess needs for improvement and address them by initiating joint efforts. The WPMM reviews and evaluates multi-scale modelling and simulation techniques currently employed in the selection of materials used in nuclear systems. It serves to provide advice to the nuclear community on the developments needed to meet the requirements of modelling for the design of different nuclear systems. The original WPMM mandate had three components (Figure 1), with the first component currently completed, delivering a report on the state-of-the-art of modelling of structural materials. The work on modelling was performed by three expert groups, one each on Multi-Scale Modelling Methods (M3), Multi-Scale Modelling of Fuels (M2F) and Structural Materials Modelling (SMM). WPMM is now composed of three expert groups and two task forces providing contributions on multi-scale methods, modelling of fuels and modelling of structural materials. This structure will be retained, with the addition of task forces as new topics are developed. The mandate of the Expert Group on Multi-Scale Modelling of

  3. Multiscale geometric modeling of macromolecules I: Cartesian representation

    Science.gov (United States)

    Xia, Kelin; Feng, Xin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei

    2014-01-01

    This paper focuses on the geometric modeling and computational algorithm development of biomolecular structures from two data sources: Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in the Eulerian (or Cartesian) representation. Molecular surface (MS) contains non-smooth geometric singularities, such as cusps, tips and self-intersecting facets, which often lead to computational instabilities in molecular simulations, and violate the physical principle of surface free energy minimization. Variational multiscale surface definitions are proposed based on geometric flows and solvation analysis of biomolecular systems. Our approach leads to geometric and potential driven Laplace-Beltrami flows for biomolecular surface evolution and formation. The resulting surfaces are free of geometric singularities and minimize the total free energy of the biomolecular system. High order partial differential equation (PDE)-based nonlinear filters are employed for EMDB data processing. We show the efficacy of this approach in feature-preserving noise reduction. After the construction of protein multiresolution surfaces, we explore the analysis and characterization of surface morphology by using a variety of curvature definitions. Apart from the classical Gaussian curvature and mean curvature, maximum curvature, minimum curvature, shape index, and curvedness are also applied to macromolecular surface analysis for the first time. Our curvature analysis is uniquely coupled to the analysis of electrostatic surface potential, which is a by-product of our variational multiscale solvation models. As an expository investigation, we particularly emphasize the numerical algorithms and computational protocols for practical applications of the above multiscale geometric models. Such information may otherwise be scattered over the vast literature on this topic. Based on the curvature and electrostatic analysis from our multiresolution surfaces, we introduce a new concept, the

  4. Multiscale geometric modeling of macromolecules I: Cartesian representation

    Energy Technology Data Exchange (ETDEWEB)

    Xia, Kelin [Department of Mathematics, Michigan State University, MI 48824 (United States); Feng, Xin [Department of Computer Science and Engineering, Michigan State University, MI 48824 (United States); Chen, Zhan [Department of Mathematics, Michigan State University, MI 48824 (United States); Tong, Yiying [Department of Computer Science and Engineering, Michigan State University, MI 48824 (United States); Wei, Guo-Wei, E-mail: wei@math.msu.edu [Department of Mathematics, Michigan State University, MI 48824 (United States); Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824 (United States)

    2014-01-15

    This paper focuses on the geometric modeling and computational algorithm development of biomolecular structures from two data sources: Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in the Eulerian (or Cartesian) representation. Molecular surface (MS) contains non-smooth geometric singularities, such as cusps, tips and self-intersecting facets, which often lead to computational instabilities in molecular simulations, and violate the physical principle of surface free energy minimization. Variational multiscale surface definitions are proposed based on geometric flows and solvation analysis of biomolecular systems. Our approach leads to geometric and potential driven Laplace–Beltrami flows for biomolecular surface evolution and formation. The resulting surfaces are free of geometric singularities and minimize the total free energy of the biomolecular system. High order partial differential equation (PDE)-based nonlinear filters are employed for EMDB data processing. We show the efficacy of this approach in feature-preserving noise reduction. After the construction of protein multiresolution surfaces, we explore the analysis and characterization of surface morphology by using a variety of curvature definitions. Apart from the classical Gaussian curvature and mean curvature, maximum curvature, minimum curvature, shape index, and curvedness are also applied to macromolecular surface analysis for the first time. Our curvature analysis is uniquely coupled to the analysis of electrostatic surface potential, which is a by-product of our variational multiscale solvation models. As an expository investigation, we particularly emphasize the numerical algorithms and computational protocols for practical applications of the above multiscale geometric models. Such information may otherwise be scattered over the vast literature on this topic. Based on the curvature and electrostatic analysis from our multiresolution surfaces, we introduce a new concept, the

  5. Multiscale model reduction for shale gas transport in fractured media

    KAUST Repository

    Akkutlu, I. Y.

    2016-05-18

    In this paper, we develop a multiscale model reduction technique that describes shale gas transport in fractured media. Due to the pore-scale heterogeneities and processes, we use upscaled models to describe the matrix. We follow our previous work (Akkutlu et al. Transp. Porous Media 107(1), 235–260, 2015), where we derived an upscaled model in the form of generalized nonlinear diffusion model to describe the effects of kerogen. To model the interaction between the matrix and the fractures, we use Generalized Multiscale Finite Element Method (Efendiev et al. J. Comput. Phys. 251, 116–135, 2013, 2015). In this approach, the matrix and the fracture interaction is modeled via local multiscale basis functions. In Efendiev et al. (2015), we developed the GMsFEM and applied for linear flows with horizontal or vertical fracture orientations aligned with a Cartesian fine grid. The approach in Efendiev et al. (2015) does not allow handling arbitrary fracture distributions. In this paper, we (1) consider arbitrary fracture distributions on an unstructured grid; (2) develop GMsFEM for nonlinear flows; and (3) develop online basis function strategies to adaptively improve the convergence. The number of multiscale basis functions in each coarse region represents the degrees of freedom needed to achieve a certain error threshold. Our approach is adaptive in a sense that the multiscale basis functions can be added in the regions of interest. Numerical results for two-dimensional problem are presented to demonstrate the efficiency of proposed approach. © 2016 Springer International Publishing Switzerland

  6. Multiscale modeling, coarse-graining and shock wave computer simulationsin materials science

    Directory of Open Access Journals (Sweden)

    Martin O. Steinhauser

    2017-12-01

    Full Text Available My intention in this review article is to briefly discuss several major topics of presentdaycomputational materials science in order to show their importance for state-of-the-art materialsmodeling and computer simulation. The topics I discuss are multiscale modeling approaches forhierarchical systems such as biological macromolecules and related coarse-graining techniques, whichprovide an effcient means to investigate systems on the mesoscale, and shock wave physics whichhas many important and interesting multi- and interdisciplinary applications in research areas wherephysics, biology, chemistry, computer science, medicine and even engineering meet. In fact, recently,as a new emerging field, the use of coarse-grained approaches for the simulation of biologicalmacromolecules such as lipids and bilayer membranes and the investigation of their interaction withshock waves has become very popular. This emerging area of research may contribute not only toan improved understanding of the microscopic details of molecular self-assembly but may also leadto enhanced medical tumor treatments which are based on the destructive effects of High IntensityFocused Ultrasound (HIFU or shock waves when interacting with biological cells and tissue; theseare treatments which have been used in medicine for many years, but which are not well understoodfrom a fundamental physical point of view.

  7. Versatile Micromechanics Model for Multiscale Analysis of Composite Structures

    Science.gov (United States)

    Kwon, Y. W.; Park, M. S.

    2013-08-01

    A general-purpose micromechanics model was developed so that the model could be applied to various composite materials such as reinforced by particles, long fibers and short fibers as well as those containing micro voids. Additionally, the model can be used with hierarchical composite materials. The micromechanics model can be used to compute effective material properties like elastic moduli, shear moduli, Poisson's ratios, and coefficients of thermal expansion for the various composite materials. The model can also calculate the strains and stresses at the constituent material level such as fibers, particles, and whiskers from the composite level stresses and strains. The model was implemented into ABAQUS using the UMAT option for multiscale analysis. An extensive set of examples are presented to demonstrate the reliability and accuracy of the developed micromechanics model for different kinds of composite materials. Another set of examples is provided to study the multiscale analysis of composite structures.

  8. Multiscale analysis and computation for flows in heterogeneous media

    Energy Technology Data Exchange (ETDEWEB)

    Efendiev, Yalchin [Texas A & M Univ., College Station, TX (United States); Hou, T. Y. [California Inst. of Technology (CalTech), Pasadena, CA (United States); Durlofsky, L. J. [Stanford Univ., CA (United States); Tchelepi, H. [Stanford Univ., CA (United States)

    2016-08-04

    Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scale basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics. Below, we present a brief overview of each of these contributions.

  9. Integrated multi-scale modelling and simulation of nuclear fuels

    International Nuclear Information System (INIS)

    Valot, C.; Bertolus, M.; Masson, R.; Malerba, L.; Rachid, J.; Besmann, T.; Phillpot, S.; Stan, M.

    2015-01-01

    This chapter aims at discussing the objectives, implementation and integration of multi-scale modelling approaches applied to nuclear fuel materials. We will first show why the multi-scale modelling approach is required, due to the nature of the materials and by the phenomena involved under irradiation. We will then present the multiple facets of multi-scale modelling approach, while giving some recommendations with regard to its application. We will also show that multi-scale modelling must be coupled with appropriate multi-scale experiments and characterisation. Finally, we will demonstrate how multi-scale modelling can contribute to solving technology issues. (authors)

  10. Multiscale modeling of alloy solidification using a database approach

    Science.gov (United States)

    Tan, Lijian; Zabaras, Nicholas

    2007-11-01

    A two-scale model based on a database approach is presented to investigate alloy solidification. Appropriate assumptions are introduced to describe the behavior of macroscopic temperature, macroscopic concentration, liquid volume fraction and microstructure features. These assumptions lead to a macroscale model with two unknown functions: liquid volume fraction and microstructure features. These functions are computed using information from microscale solutions of selected problems. This work addresses the selection of sample problems relevant to the interested problem and the utilization of data from the microscale solution of the selected sample problems. A computationally efficient model, which is different from the microscale and macroscale models, is utilized to find relevant sample problems. In this work, the computationally efficient model is a sharp interface solidification model of a pure material. Similarities between the sample problems and the problem of interest are explored by assuming that the liquid volume fraction and microstructure features are functions of solution features extracted from the solution of the computationally efficient model. The solution features of the computationally efficient model are selected as the interface velocity and thermal gradient in the liquid at the time the sharp solid-liquid interface passes through. An analytical solution of the computationally efficient model is utilized to select sample problems relevant to solution features obtained at any location of the domain of the problem of interest. The microscale solution of selected sample problems is then utilized to evaluate the two unknown functions (liquid volume fraction and microstructure features) in the macroscale model. The temperature solution of the macroscale model is further used to improve the estimation of the liquid volume fraction and microstructure features. Interpolation is utilized in the feature space to greatly reduce the number of required

  11. Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

    Science.gov (United States)

    Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

    2011-01-01

    In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to

  12. Multiscale Modeling of UHTC: Thermal Conductivity

    Science.gov (United States)

    Lawson, John W.; Murry, Daw; Squire, Thomas; Bauschlicher, Charles W.

    2012-01-01

    We are developing a multiscale framework in computational modeling for the ultra high temperature ceramics (UHTC) ZrB2 and HfB2. These materials are characterized by high melting point, good strength, and reasonable oxidation resistance. They are candidate materials for a number of applications in extreme environments including sharp leading edges of hypersonic aircraft. In particular, we used a combination of ab initio methods, atomistic simulations and continuum computations to obtain insights into fundamental properties of these materials. Ab initio methods were used to compute basic structural, mechanical and thermal properties. From these results, a database was constructed to fit a Tersoff style interatomic potential suitable for atomistic simulations. These potentials were used to evaluate the lattice thermal conductivity of single crystals and the thermal resistance of simple grain boundaries. Finite element method (FEM) computations using atomistic results as inputs were performed with meshes constructed on SEM images thereby modeling the realistic microstructure. These continuum computations showed the reduction in thermal conductivity due to the grain boundary network.

  13. A Generalized Hybrid Multiscale Modeling Approach for Flow and Reactive Transport in Porous Media

    Science.gov (United States)

    Yang, X.; Meng, X.; Tang, Y. H.; Guo, Z.; Karniadakis, G. E.

    2017-12-01

    Using emerging understanding of biological and environmental processes at fundamental scales to advance predictions of the larger system behavior requires the development of multiscale approaches, and there is strong interest in coupling models at different scales together in a hybrid multiscale simulation framework. A limited number of hybrid multiscale simulation methods have been developed for subsurface applications, mostly using application-specific approaches for model coupling. The proposed generalized hybrid multiscale approach is designed with minimal intrusiveness to the at-scale simulators (pre-selected) and provides a set of lightweight C++ scripts to manage a complex multiscale workflow utilizing a concurrent coupling approach. The workflow includes at-scale simulators (using the lattice-Boltzmann method, LBM, at the pore and Darcy scale, respectively), scripts for boundary treatment (coupling and kriging), and a multiscale universal interface (MUI) for data exchange. The current study aims to apply the generalized hybrid multiscale modeling approach to couple pore- and Darcy-scale models for flow and mixing-controlled reaction with precipitation/dissolution in heterogeneous porous media. The model domain is packed heterogeneously that the mixing front geometry is more complex and not known a priori. To address those challenges, the generalized hybrid multiscale modeling approach is further developed to 1) adaptively define the locations of pore-scale subdomains, 2) provide a suite of physical boundary coupling schemes and 3) consider the dynamic change of the pore structures due to mineral precipitation/dissolution. The results are validated and evaluated by comparing with single-scale simulations in terms of velocities, reactive concentrations and computing cost.

  14. An approach to multiscale modelling with graph grammars.

    Science.gov (United States)

    Ong, Yongzhi; Streit, Katarína; Henke, Michael; Kurth, Winfried

    2014-09-01

    Functional-structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.

  15. 2nd International Conference on Multiscale Computational Methods for Solids and Fluids

    CERN Document Server

    2016-01-01

    This volume contains the best papers presented at the 2nd ECCOMAS International Conference on Multiscale Computations for Solids and Fluids, held June 10-12, 2015. Topics dealt with include multiscale strategy for efficient development of scientific software for large-scale computations, coupled probability-nonlinear-mechanics problems and solution methods, and modern mathematical and computational setting for multi-phase flows and fluid-structure interaction. The papers consist of contributions by six experts who taught short courses prior to the conference, along with several selected articles from other participants dealing with complementary issues, covering both solid mechanics and applied mathematics. .

  16. Multiscale Mechanics of Articular Cartilage: Potentials and Challenges of Coupling Musculoskeletal, Joint, and Microscale Computational Models

    Science.gov (United States)

    Halloran, J. P.; Sibole, S.; van Donkelaar, C. C.; van Turnhout, M. C.; Oomens, C. W. J.; Weiss, J. A.; Guilak, F.; Erdemir, A.

    2012-01-01

    Articular cartilage experiences significant mechanical loads during daily activities. Healthy cartilage provides the capacity for load bearing and regulates the mechanobiological processes for tissue development, maintenance, and repair. Experimental studies at multiple scales have provided a fundamental understanding of macroscopic mechanical function, evaluation of the micromechanical environment of chondrocytes, and the foundations for mechanobiological response. In addition, computational models of cartilage have offered a concise description of experimental data at many spatial levels under healthy and diseased conditions, and have served to generate hypotheses for the mechanical and biological function. Further, modeling and simulation provides a platform for predictive risk assessment, management of dysfunction, as well as a means to relate multiple spatial scales. Simulation-based investigation of cartilage comes with many challenges including both the computational burden and often insufficient availability of data for model development and validation. This review outlines recent modeling and simulation approaches to understand cartilage function from a mechanical systems perspective, and illustrates pathways to associate mechanics with biological function. Computational representations at single scales are provided from the body down to the microstructure, along with attempts to explore multiscale mechanisms of load sharing that dictate the mechanical environment of the cartilage and chondrocytes. PMID:22648577

  17. Multi-scale computational model of three-dimensional hemodynamics within a deformable full-body arterial network

    Energy Technology Data Exchange (ETDEWEB)

    Xiao, Nan [Department of Bioengineering, Stanford University, Stanford, CA 94305 (United States); Department of Biomedical Engineering, King’s College London, London SE1 7EH (United Kingdom); Humphrey, Jay D. [Department of Biomedical Engineering, Yale University, New Haven, CT 06520 (United States); Figueroa, C. Alberto, E-mail: alberto.figueroa@kcl.ac.uk [Department of Biomedical Engineering, King’s College London, London SE1 7EH (United Kingdom)

    2013-07-01

    In this article, we present a computational multi-scale model of fully three-dimensional and unsteady hemodynamics within the primary large arteries in the human. Computed tomography image data from two different patients were used to reconstruct a nearly complete network of the major arteries from head to foot. A linearized coupled-momentum method for fluid–structure-interaction was used to describe vessel wall deformability and a multi-domain method for outflow boundary condition specification was used to account for the distal circulation. We demonstrated that physiologically realistic results can be obtained from the model by comparing simulated quantities such as regional blood flow, pressure and flow waveforms, and pulse wave velocities to known values in the literature. We also simulated the impact of age-related arterial stiffening on wave propagation phenomena by progressively increasing the stiffness of the central arteries and found that the predicted effects on pressure amplification and pulse wave velocity are in agreement with findings in the clinical literature. This work demonstrates the feasibility of three-dimensional techniques for simulating hemodynamics in a full-body compliant arterial network.

  18. Multiscale modelling in immunology: a review.

    Science.gov (United States)

    Cappuccio, Antonio; Tieri, Paolo; Castiglione, Filippo

    2016-05-01

    One of the greatest challenges in biomedicine is to get a unified view of observations made from the molecular up to the organism scale. Towards this goal, multiscale models have been highly instrumental in contexts such as the cardiovascular field, angiogenesis, neurosciences and tumour biology. More recently, such models are becoming an increasingly important resource to address immunological questions as well. Systematic mining of the literature in multiscale modelling led us to identify three main fields of immunological applications: host-virus interactions, inflammatory diseases and their treatment and development of multiscale simulation platforms for immunological research and for educational purposes. Here, we review the current developments in these directions, which illustrate that multiscale models can consistently integrate immunological data generated at several scales, and can be used to describe and optimize therapeutic treatments of complex immune diseases. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  19. Reducing the computational requirements for simulating tunnel fires by combining multiscale modelling and multiple processor calculation

    DEFF Research Database (Denmark)

    Vermesi, Izabella; Rein, Guillermo; Colella, Francesco

    2017-01-01

    Multiscale modelling of tunnel fires that uses a coupled 3D (fire area) and 1D (the rest of the tunnel) model is seen as the solution to the numerical problem of the large domains associated with long tunnels. The present study demonstrates the feasibility of the implementation of this method...... in FDS version 6.0, a widely used fire-specific, open source CFD software. Furthermore, it compares the reduction in simulation time given by multiscale modelling with the one given by the use of multiple processor calculation. This was done using a 1200m long tunnel with a rectangular cross......-section as a demonstration case. The multiscale implementation consisted of placing a 30MW fire in the centre of a 400m long 3D domain, along with two 400m long 1D ducts on each side of it, that were again bounded by two nodes each. A fixed volume flow was defined in the upstream duct and the two models were coupled...

  20. Modeling of mesoscale dispersion effect on the piezoresistivity of carbon nanotube-polymer nanocomposites via 3D computational multiscale micromechanics methods

    International Nuclear Information System (INIS)

    Ren, Xiang; Seidel, Gary D; Chaurasia, Adarsh K; Oliva-Avilés, Andrés I; Ku-Herrera, José J; Avilés, Francis

    2015-01-01

    In uniaxial tension and compression experiments, carbon nanotube (CNT)-polymer nanocomposites have demonstrated exceptional mechanical and coupled electrostatic properties in the form of piezoresistivity. In order to better understand the correlation of the piezoresistive response with the CNT dispersion at the mesoscale, a 3D computational multiscale micromechanics model based on finite element analysis is constructed to predict the effective macroscale piezoresistive response of CNT/polymer nanocomposites. The key factors that may contribute to the overall piezoresistive response, i.e. the nanoscale electrical tunneling effect, the inherent CNT piezoresistivity and the CNT mesoscale network effect are incorporated in the model based on a 3D multiscale mechanical–electrostatic coupled code. The results not only explain how different nanoscale mechanisms influence the overall macroscale piezoresistive response through the mesoscale CNT network, but also give reason and provide bounds for the wide range of gauge factors found in the literature offering insight regarding how control of the mesoscale CNT networks can be used to tailor nanocomposite piezoresistive response. (paper)

  1. Computational multiscale modeling of intergranular cracking

    International Nuclear Information System (INIS)

    Simonovski, Igor; Cizelj, Leon

    2011-01-01

    A novel computational approach for simulation of intergranular cracks in a polycrystalline aggregate is proposed in this paper. The computational model includes a topological model of the experimentally determined microstructure of a 400 μm diameter stainless steel wire and automatic finite element discretization of the grains and grain boundaries. The microstructure was spatially characterized by X-ray diffraction contrast tomography and contains 362 grains and some 1600 grain boundaries. Available constitutive models currently include isotropic elasticity for the grain interior and cohesive behavior with damage for the grain boundaries. The experimentally determined lattice orientations are employed to distinguish between resistant low energy and susceptible high energy grain boundaries in the model. The feasibility and performance of the proposed computational approach is demonstrated by simulating the onset and propagation of intergranular cracking. The preliminary numerical results are outlined and discussed.

  2. Multiscale modeling of radiation effects in nuclear reactor structural materials

    Energy Technology Data Exchange (ETDEWEB)

    Kwon, Junhyun [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2015-10-15

    Most problems in irradiated materials originate from the atomic collision of high-energy particles and lattice atoms. This collision leads to displacement cascades through the energy transfer reaction and causes various types of defects such as vacancies, interstitials, and clusters. The behavior of the point defects created in the displacement cascades is important because these defects play a major role in a microstructural evolution and further affect the changes in material properties. Rapid advances have been made in the computational capabilities for a realistic simulation of complex physical phenomena, such as irradiation and aging effects. At the same time, progress has been made in understanding the effect of radiation in metals, especially iron-based alloys. In this work, we present some of our ongoing work in this area, which illustrates a multiscale modeling for evaluating a microstructural evolution and mechanical property changes during irradiation. Multiscale modeling approaches are briefly presented here in the following order: nuclear interaction, atomic-level interaction, atomistic modeling, microstructural evolution modeling and mechanical property modeling. This is one of many possible methods for classifying techniques. The effort in developing physical multiscale models applied to radiation damage has been focused on a single crystal or single-grain materials.

  3. Fast Multiscale Reservoir Simulations using POD-DEIM Model Reduction

    KAUST Repository

    Ghasemi, Mohammadreza

    2015-02-23

    In this paper, we present a global-local model reduction for fast multiscale reservoir simulations in highly heterogeneous porous media with applications to optimization and history matching. Our proposed approach identifies a low dimensional structure of the solution space. We introduce an auxiliary variable (the velocity field) in our model reduction that allows achieving a high degree of model reduction. The latter is due to the fact that the velocity field is conservative for any low-order reduced model in our framework. Because a typical global model reduction based on POD is a Galerkin finite element method, and thus it can not guarantee local mass conservation. This can be observed in numerical simulations that use finite volume based approaches. Discrete Empirical Interpolation Method (DEIM) is used to approximate the nonlinear functions of fine-grid functions in Newton iterations. This approach allows achieving the computational cost that is independent of the fine grid dimension. POD snapshots are inexpensively computed using local model reduction techniques based on Generalized Multiscale Finite Element Method (GMsFEM) which provides (1) a hierarchical approximation of snapshot vectors (2) adaptive computations by using coarse grids (3) inexpensive global POD operations in a small dimensional spaces on a coarse grid. By balancing the errors of the global and local reduced-order models, our new methodology can provide an error bound in simulations. Our numerical results, utilizing a two-phase immiscible flow, show a substantial speed-up and we compare our results to the standard POD-DEIM in finite volume setup.

  4. Multiscale Model Reduction with Generalized Multiscale Finite Element Methods in Geomathematics

    KAUST Repository

    Efendiev, Yalchin R.; Presho, Michael

    2015-01-01

    In this chapter, we discuss multiscale model reduction using Generalized Multiscale Finite Element Methods (GMsFEM) in a number of geomathematical applications. GMsFEM has been recently introduced (Efendiev et al. 2012) and applied to various problems. In the current chapter, we consider some of these applications and outline the basic methodological concepts.

  5. Multiscale Model Reduction with Generalized Multiscale Finite Element Methods in Geomathematics

    KAUST Repository

    Efendiev, Yalchin R.

    2015-09-02

    In this chapter, we discuss multiscale model reduction using Generalized Multiscale Finite Element Methods (GMsFEM) in a number of geomathematical applications. GMsFEM has been recently introduced (Efendiev et al. 2012) and applied to various problems. In the current chapter, we consider some of these applications and outline the basic methodological concepts.

  6. Novel Multiscale Modeling Tool Applied to Pseudomonas aeruginosa Biofilm Formation

    OpenAIRE

    Biggs, Matthew B.; Papin, Jason A.

    2013-01-01

    Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid mod...

  7. Multiscale Modeling of Composites: Toward Virtual Testing … and Beyond

    Science.gov (United States)

    LLorca, J.; González, C.; Molina-Aldareguía, J. M.; Lópes, C. S.

    2013-02-01

    Recent developments in the area of multiscale modeling of fiber-reinforced polymers are presented. The overall strategy takes advantage of the separation of length scales between different entities (ply, laminate, and component) found in composite structures. This allows us to carry out multiscale modeling by computing the properties of one entity (e.g., individual plies) at the relevant length scale, homogenizing the results into a constitutive model, and passing this information to the next length scale to determine the mechanical behavior of the larger entity (e.g., laminate). As a result, high-fidelity numerical simulations of the mechanical behavior of composite coupons and small components are nowadays feasible starting from the matrix, fiber, and interface properties and spatial distribution. Finally, the roadmap is outlined for extending the current strategy to include functional properties and processing into the simulation scheme.

  8. Microphysics in Multi-scale Modeling System with Unified Physics

    Science.gov (United States)

    Tao, Wei-Kuo

    2012-01-01

    Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.

  9. A bidirectional coupling procedure applied to multiscale respiratory modeling

    Science.gov (United States)

    Kuprat, A. P.; Kabilan, S.; Carson, J. P.; Corley, R. A.; Einstein, D. R.

    2013-07-01

    In this study, we present a novel multiscale computational framework for efficiently linking multiple lower-dimensional models describing the distal lung mechanics to imaging-based 3D computational fluid dynamics (CFDs) models of the upper pulmonary airways in order to incorporate physiologically appropriate outlet boundary conditions. The framework is an extension of the modified Newton's method with nonlinear Krylov accelerator developed by Carlson and Miller [1], Miller [2] and Scott and Fenves [3]. Our extensions include the retention of subspace information over multiple timesteps, and a special correction at the end of a timestep that allows for corrections to be accepted with verified low residual with as little as a single residual evaluation per timestep on average. In the case of a single residual evaluation per timestep, the method has zero additional computational cost compared to uncoupled or unidirectionally coupled simulations. We expect these enhancements to be generally applicable to other multiscale coupling applications where timestepping occurs. In addition we have developed a "pressure-drop" residual which allows for stable coupling of flows between a 3D incompressible CFD application and another (lower-dimensional) fluid system. We expect this residual to also be useful for coupling non-respiratory incompressible fluid applications, such as multiscale simulations involving blood flow. The lower-dimensional models that are considered in this study are sets of simple ordinary differential equations (ODEs) representing the compliant mechanics of symmetric human pulmonary airway trees. To validate the method, we compare the predictions of hybrid CFD-ODE models against an ODE-only model of pulmonary airflow in an idealized geometry. Subsequently, we couple multiple sets of ODEs describing the distal lung to an imaging-based human lung geometry. Boundary conditions in these models consist of atmospheric pressure at the mouth and intrapleural

  10. A bidirectional coupling procedure applied to multiscale respiratory modeling

    Energy Technology Data Exchange (ETDEWEB)

    Kuprat, A.P., E-mail: andrew.kuprat@pnnl.gov [Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA (United States); Kabilan, S., E-mail: senthil.kabilan@pnnl.gov [Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA (United States); Carson, J.P., E-mail: james.carson@pnnl.gov [Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA (United States); Corley, R.A., E-mail: rick.corley@pnnl.gov [Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA (United States); Einstein, D.R., E-mail: daniel.einstein@pnnl.gov [Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA (United States)

    2013-07-01

    In this study, we present a novel multiscale computational framework for efficiently linking multiple lower-dimensional models describing the distal lung mechanics to imaging-based 3D computational fluid dynamics (CFDs) models of the upper pulmonary airways in order to incorporate physiologically appropriate outlet boundary conditions. The framework is an extension of the modified Newton’s method with nonlinear Krylov accelerator developed by Carlson and Miller [1], Miller [2] and Scott and Fenves [3]. Our extensions include the retention of subspace information over multiple timesteps, and a special correction at the end of a timestep that allows for corrections to be accepted with verified low residual with as little as a single residual evaluation per timestep on average. In the case of a single residual evaluation per timestep, the method has zero additional computational cost compared to uncoupled or unidirectionally coupled simulations. We expect these enhancements to be generally applicable to other multiscale coupling applications where timestepping occurs. In addition we have developed a “pressure-drop” residual which allows for stable coupling of flows between a 3D incompressible CFD application and another (lower-dimensional) fluid system. We expect this residual to also be useful for coupling non-respiratory incompressible fluid applications, such as multiscale simulations involving blood flow. The lower-dimensional models that are considered in this study are sets of simple ordinary differential equations (ODEs) representing the compliant mechanics of symmetric human pulmonary airway trees. To validate the method, we compare the predictions of hybrid CFD–ODE models against an ODE-only model of pulmonary airflow in an idealized geometry. Subsequently, we couple multiple sets of ODEs describing the distal lung to an imaging-based human lung geometry. Boundary conditions in these models consist of atmospheric pressure at the mouth and intrapleural

  11. A bidirectional coupling procedure applied to multiscale respiratory modeling

    International Nuclear Information System (INIS)

    Kuprat, A.P.; Kabilan, S.; Carson, J.P.; Corley, R.A.; Einstein, D.R.

    2013-01-01

    In this study, we present a novel multiscale computational framework for efficiently linking multiple lower-dimensional models describing the distal lung mechanics to imaging-based 3D computational fluid dynamics (CFDs) models of the upper pulmonary airways in order to incorporate physiologically appropriate outlet boundary conditions. The framework is an extension of the modified Newton’s method with nonlinear Krylov accelerator developed by Carlson and Miller [1], Miller [2] and Scott and Fenves [3]. Our extensions include the retention of subspace information over multiple timesteps, and a special correction at the end of a timestep that allows for corrections to be accepted with verified low residual with as little as a single residual evaluation per timestep on average. In the case of a single residual evaluation per timestep, the method has zero additional computational cost compared to uncoupled or unidirectionally coupled simulations. We expect these enhancements to be generally applicable to other multiscale coupling applications where timestepping occurs. In addition we have developed a “pressure-drop” residual which allows for stable coupling of flows between a 3D incompressible CFD application and another (lower-dimensional) fluid system. We expect this residual to also be useful for coupling non-respiratory incompressible fluid applications, such as multiscale simulations involving blood flow. The lower-dimensional models that are considered in this study are sets of simple ordinary differential equations (ODEs) representing the compliant mechanics of symmetric human pulmonary airway trees. To validate the method, we compare the predictions of hybrid CFD–ODE models against an ODE-only model of pulmonary airflow in an idealized geometry. Subsequently, we couple multiple sets of ODEs describing the distal lung to an imaging-based human lung geometry. Boundary conditions in these models consist of atmospheric pressure at the mouth and intrapleural

  12. Institute for Multiscale Modeling of Biological Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Paulaitis, Michael E; Garcia-Moreno, Bertrand; Lenhoff, Abraham

    2009-12-26

    The Institute for Multiscale Modeling of Biological Interactions (IMMBI) has two primary goals: Foster interdisciplinary collaborations among faculty and their research laboratories that will lead to novel applications of multiscale simulation and modeling methods in the biological sciences and engineering; and Building on the unique biophysical/biology-based engineering foundations of the participating faculty, train scientists and engineers to apply computational methods that collectively span multiple time and length scales of biological organization. The success of IMMBI will be defined by the following: Size and quality of the applicant pool for pre-doctoral and post-doctoral fellows; Academic performance; Quality of the pre-doctoral and post-doctoral research; Impact of the research broadly and to the DOE (ASCR program) mission; Distinction of the next career step for pre-doctoral and post-doctoral fellows; and Faculty collaborations that result from IMMBI activities. Specific details about accomplishments during the three years of DOE support for IMMBI have been documented in Annual Progress Reports (April 2005, June 2006, and March 2007) and a Report for a National Academy of Sciences Review (October 2005) that were submitted to DOE on the dates indicated. An overview of these accomplishments is provided.

  13. The Goddard multi-scale modeling system with unified physics

    Directory of Open Access Journals (Sweden)

    W.-K. Tao

    2009-08-01

    Full Text Available Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1 a cloud-resolving model (CRM, (2 a regional-scale model, the NASA unified Weather Research and Forecasting Model (WRF, and (3 a coupled CRM-GCM (general circulation model, known as the Goddard Multi-scale Modeling Framework or MMF. The same cloud-microphysical processes, long- and short-wave radiative transfer and land-surface processes are applied in all of the models to study explicit cloud-radiation and cloud-surface interactive processes in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator for comparison and validation with NASA high-resolution satellite data.

    This paper reviews the development and presents some applications of the multi-scale modeling system, including results from using the multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols. In addition, use of the multi-satellite simulator to identify the strengths and weaknesses of the model-simulated precipitation processes will be discussed as well as future model developments and applications.

  14. Peridynamic Multiscale Finite Element Methods

    Energy Technology Data Exchange (ETDEWEB)

    Costa, Timothy [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bond, Stephen D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Littlewood, David John [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Moore, Stan Gerald [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-12-01

    The problem of computing quantum-accurate design-scale solutions to mechanics problems is rich with applications and serves as the background to modern multiscale science research. The prob- lem can be broken into component problems comprised of communicating across adjacent scales, which when strung together create a pipeline for information to travel from quantum scales to design scales. Traditionally, this involves connections between a) quantum electronic structure calculations and molecular dynamics and between b) molecular dynamics and local partial differ- ential equation models at the design scale. The second step, b), is particularly challenging since the appropriate scales of molecular dynamic and local partial differential equation models do not overlap. The peridynamic model for continuum mechanics provides an advantage in this endeavor, as the basic equations of peridynamics are valid at a wide range of scales limiting from the classical partial differential equation models valid at the design scale to the scale of molecular dynamics. In this work we focus on the development of multiscale finite element methods for the peridynamic model, in an effort to create a mathematically consistent channel for microscale information to travel from the upper limits of the molecular dynamics scale to the design scale. In particular, we first develop a Nonlocal Multiscale Finite Element Method which solves the peridynamic model at multiple scales to include microscale information at the coarse-scale. We then consider a method that solves a fine-scale peridynamic model to build element-support basis functions for a coarse- scale local partial differential equation model, called the Mixed Locality Multiscale Finite Element Method. Given decades of research and development into finite element codes for the local partial differential equation models of continuum mechanics there is a strong desire to couple local and nonlocal models to leverage the speed and state of the

  15. A complete categorization of multiscale models of infectious disease systems.

    Science.gov (United States)

    Garira, Winston

    2017-12-01

    Modelling of infectious disease systems has entered a new era in which disease modellers are increasingly turning to multiscale modelling to extend traditional modelling frameworks into new application areas and to achieve higher levels of detail and accuracy in characterizing infectious disease systems. In this paper we present a categorization framework for categorizing multiscale models of infectious disease systems. The categorization framework consists of five integration frameworks and five criteria. We use the categorization framework to give a complete categorization of host-level immuno-epidemiological models (HL-IEMs). This categorization framework is also shown to be applicable in categorizing other types of multiscale models of infectious diseases beyond HL-IEMs through modifying the initial categorization framework presented in this study. Categorization of multiscale models of infectious disease systems in this way is useful in bringing some order to the discussion on the structure of these multiscale models.

  16. Study on high density multi-scale calculation technique

    International Nuclear Information System (INIS)

    Sekiguchi, S.; Tanaka, Y.; Nakada, H.; Nishikawa, T.; Yamamoto, N.; Yokokawa, M.

    2004-01-01

    To understand degradation of nuclear materials under irradiation, it is essential to know as much about each phenomenon observed from multi-scale points of view; they are micro-scale in atomic-level, macro-level in structural scale and intermediate level. In this study for application to meso-scale materials (100A ∼ 2μm), computer technology approaching from micro- and macro-scales was developed including modeling and computer application using computational science and technology method. And environmental condition of grid technology for multi-scale calculation was prepared. The software and MD (molecular dynamics) stencil for verifying the multi-scale calculation were improved and their movement was confirmed. (A. Hishinuma)

  17. Computation of spatial significance of mountain objects extracted from multiscale digital elevation models

    International Nuclear Information System (INIS)

    Sathyamoorthy, Dinesh

    2014-01-01

    The derivation of spatial significance is an important aspect of geospatial analysis and hence, various methods have been proposed to compute the spatial significance of entities based on spatial distances with other entities within the cluster. This paper is aimed at studying the spatial significance of mountain objects extracted from multiscale digital elevation models (DEMs). At each scale, the value of spatial significance index SSI of a mountain object is the minimum number of morphological dilation iterations required to occupy all the other mountain objects in the terrain. The mountain object with the lowest value of SSI is the spatially most significant mountain object, indicating that it has the shortest distance to the other mountain objects. It is observed that as the area of the mountain objects reduce with increasing scale, the distances between the mountain objects increase, resulting in increasing values of SSI. The results obtained indicate that the strategic location of a mountain object at the centre of the terrain is more important than its size in determining its reach to other mountain objects and thus, its spatial significance

  18. Multiscale modeling and simulation of brain blood flow

    Energy Technology Data Exchange (ETDEWEB)

    Perdikaris, Paris, E-mail: parisp@mit.edu [Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Grinberg, Leopold, E-mail: leopoldgrinberg@us.ibm.com [IBM T.J Watson Research Center, 1 Rogers St, Cambridge, Massachusetts 02142 (United States); Karniadakis, George Em, E-mail: george-karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, Rhode Island 02912 (United States)

    2016-02-15

    The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process taking place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.

  19. 3D Multiscale Modelling of Angiogenesis and Vascular Tumour Growth

    KAUST Repository

    Perfahl, H.; Byrne, H. M.; Chen, T.; Estrella, V.; Alarcó n, T.; Lapin, A.; Gatenby, R. A.; Gillies, R. J.; Lloyd, M. C.; Maini, P. K.; Reuss, M.; Owen, M. R.

    2012-01-01

    We present a three-dimensional, multiscale model of vascular tumour growth, which couples nutrient/growth factor transport, blood flow, angiogenesis, vascular remodelling, movement of and interactions between normal and tumour cells, and nutrient-dependent cell cycle dynamics within each cell. We present computational simulations which show how a vascular network may evolve and interact with tumour and healthy cells. We also demonstrate how our model may be combined with experimental data, to predict the spatio-temporal evolution of a vascular tumour.

  20. 3D Multiscale Modelling of Angiogenesis and Vascular Tumour Growth

    KAUST Repository

    Perfahl, H.

    2012-11-01

    We present a three-dimensional, multiscale model of vascular tumour growth, which couples nutrient/growth factor transport, blood flow, angiogenesis, vascular remodelling, movement of and interactions between normal and tumour cells, and nutrient-dependent cell cycle dynamics within each cell. We present computational simulations which show how a vascular network may evolve and interact with tumour and healthy cells. We also demonstrate how our model may be combined with experimental data, to predict the spatio-temporal evolution of a vascular tumour.

  1. Fatigue of multiscale composites with secondary nanoplatelet reinforcement: 3D computational analysis

    DEFF Research Database (Denmark)

    Dai, Gaoming; Mishnaevsky, Leon, Jr.

    2014-01-01

    3D numerical simulations of fatigue damage of multiscale fiber reinforced polymer composites with secondary nanoclay reinforcement are carried out. Macro–micro FE models of the multiscale composites are generated automatically using Python based software. The effect of the nanoclay reinforcement....... Multiscale composites with exfoliated nanoreinforcement and aligned nanoplatelets ensure the better fatigue resistance than those with intercalated/clustered and randomly oriented nanoreinforcement....

  2. An Efficient Integer Coding and Computing Method for Multiscale Time Segment

    Directory of Open Access Journals (Sweden)

    TONG Xiaochong

    2016-12-01

    Full Text Available This article focus on the exist problem and status of current time segment coding, proposed a new set of approach about time segment coding: multi-scale time segment integer coding (MTSIC. This approach utilized the tree structure and the sort by size formed among integer, it reflected the relationship among the multi-scale time segments: order, include/contained, intersection, etc., and finally achieved an unity integer coding processing for multi-scale time. On this foundation, this research also studied the computing method for calculating the time relationships of MTSIC, to support an efficient calculation and query based on the time segment, and preliminary discussed the application method and prospect of MTSIC. The test indicated that, the implement of MTSIC is convenient and reliable, and the transformation between it and the traditional method is convenient, it has the very high efficiency in query and calculating.

  3. Multiscale approach including microfibril scale to assess elastic constants of cortical bone based on neural network computation and homogenization method.

    Science.gov (United States)

    Barkaoui, Abdelwahed; Chamekh, Abdessalem; Merzouki, Tarek; Hambli, Ridha; Mkaddem, Ali

    2014-03-01

    The complexity and heterogeneity of bone tissue require a multiscale modeling to understand its mechanical behavior and its remodeling mechanisms. In this paper, a novel multiscale hierarchical approach including microfibril scale based on hybrid neural network (NN) computation and homogenization equations was developed to link nanoscopic and macroscopic scales to estimate the elastic properties of human cortical bone. The multiscale model is divided into three main phases: (i) in step 0, the elastic constants of collagen-water and mineral-water composites are calculated by averaging the upper and lower Hill bounds; (ii) in step 1, the elastic properties of the collagen microfibril are computed using a trained NN simulation. Finite element calculation is performed at nanoscopic levels to provide a database to train an in-house NN program; and (iii) in steps 2-10 from fibril to continuum cortical bone tissue, homogenization equations are used to perform the computation at the higher scales. The NN outputs (elastic properties of the microfibril) are used as inputs for the homogenization computation to determine the properties of mineralized collagen fibril. The mechanical and geometrical properties of bone constituents (mineral, collagen, and cross-links) as well as the porosity were taken in consideration. This paper aims to predict analytically the effective elastic constants of cortical bone by modeling its elastic response at these different scales, ranging from the nanostructural to mesostructural levels. Our findings of the lowest scale's output were well integrated with the other higher levels and serve as inputs for the next higher scale modeling. Good agreement was obtained between our predicted results and literature data. Copyright © 2013 John Wiley & Sons, Ltd.

  4. On a multiscale approach for filter efficiency simulations

    KAUST Repository

    Iliev, Oleg

    2014-07-01

    Filtration in general, and the dead end depth filtration of solid particles out of fluid in particular, is intrinsic multiscale problem. The deposition (capturing of particles) essentially depends on local velocity, on microgeometry (pore scale geometry) of the filtering medium and on the diameter distribution of the particles. The deposited (captured) particles change the microstructure of the porous media what leads to change of permeability. The changed permeability directly influences the velocity field and pressure distribution inside the filter element. To close the loop, we mention that the velocity influences the transport and deposition of particles. In certain cases one can evaluate the filtration efficiency considering only microscale or only macroscale models, but in general an accurate prediction of the filtration efficiency requires multiscale models and algorithms. This paper discusses the single scale and the multiscale models, and presents a fractional time step discretization algorithm for the multiscale problem. The velocity within the filter element is computed at macroscale, and is used as input for the solution of microscale problems at selected locations of the porous medium. The microscale problem is solved with respect to transport and capturing of individual particles, and its solution is postprocessed to provide permeability values for macroscale computations. Results from computational experiments with an oil filter are presented and discussed.

  5. Multiscale Modeling of PEEK Using Reactive Molecular Dynamics Modeling and Micromechanics

    Science.gov (United States)

    Pisani, William A.; Radue, Matthew; Chinkanjanarot, Sorayot; Bednarcyk, Brett A.; Pineda, Evan J.; King, Julia A.; Odegard, Gregory M.

    2018-01-01

    Polyether ether ketone (PEEK) is a high-performance, semi-crystalline thermoplastic that is used in a wide range of engineering applications, including some structural components of aircraft. The design of new PEEK-based materials requires a precise understanding of the multiscale structure and behavior of semi-crystalline PEEK. Molecular Dynamics (MD) modeling can efficiently predict bulk-level properties of single phase polymers, and micromechanics can be used to homogenize those phases based on the overall polymer microstructure. In this study, MD modeling was used to predict the mechanical properties of the amorphous and crystalline phases of PEEK. The hierarchical microstructure of PEEK, which combines the aforementioned phases, was modeled using a multiscale modeling approach facilitated by NASA's MSGMC. The bulk mechanical properties of semi-crystalline PEEK predicted using MD modeling and MSGMC agree well with vendor data, thus validating the multiscale modeling approach.

  6. A Multiscale Computational Model of the Response of Swine Epidermis After Acute Irradiation

    Science.gov (United States)

    Hu, Shaowen; Cucinotta, Francis A.

    2012-01-01

    Radiation exposure from Solar Particle Events can lead to very high skin dose for astronauts on exploration missions outside the protection of the Earth s magnetic field [1]. Assessing the detrimental effects to human skin under such adverse conditions could be predicted by conducting territorial experiments on animal models. In this study we apply a computational approach to simulate the experimental data of the radiation response of swine epidermis, which is closely similar to human epidermis [2]. Incorporating experimentally measured histological and cell kinetic parameters into a multiscale tissue modeling framework, we obtain results of population kinetics and proliferation index comparable to unirradiated and acutely irradiated swine experiments [3]. It is noted the basal cell doubling time is 10 to 16 days in the intact population, but drops to 13.6 hr in the regenerating populations surviving irradiation. This complex 30-fold variation is proposed to be attributed to the shortening of the G1 phase duration. We investigate this radiation induced effect by considering at the sub-cellular level the expression and signaling of TGF-beta, as it is recognized as a key regulatory factor of tissue formation and wound healing [4]. This integrated model will allow us to test the validity of various basic biological rules at the cellular level and sub-cellular mechanisms by qualitatively comparing simulation results with published research, and should lead to a fuller understanding of the pathophysiological effects of ionizing radiation on the skin.

  7. Collaborative Multi-Scale 3d City and Infrastructure Modeling and Simulation

    Science.gov (United States)

    Breunig, M.; Borrmann, A.; Rank, E.; Hinz, S.; Kolbe, T.; Schilcher, M.; Mundani, R.-P.; Jubierre, J. R.; Flurl, M.; Thomsen, A.; Donaubauer, A.; Ji, Y.; Urban, S.; Laun, S.; Vilgertshofer, S.; Willenborg, B.; Menninghaus, M.; Steuer, H.; Wursthorn, S.; Leitloff, J.; Al-Doori, M.; Mazroobsemnani, N.

    2017-09-01

    Computer-aided collaborative and multi-scale 3D planning are challenges for complex railway and subway track infrastructure projects in the built environment. Many legal, economic, environmental, and structural requirements have to be taken into account. The stringent use of 3D models in the different phases of the planning process facilitates communication and collaboration between the stake holders such as civil engineers, geological engineers, and decision makers. This paper presents concepts, developments, and experiences gained by an interdisciplinary research group coming from civil engineering informatics and geo-informatics banding together skills of both, the Building Information Modeling and the 3D GIS world. New approaches including the development of a collaborative platform and 3D multi-scale modelling are proposed for collaborative planning and simulation to improve the digital 3D planning of subway tracks and other infrastructures. Experiences during this research and lessons learned are presented as well as an outlook on future research focusing on Building Information Modeling and 3D GIS applications for cities of the future.

  8. COLLABORATIVE MULTI-SCALE 3D CITY AND INFRASTRUCTURE MODELING AND SIMULATION

    Directory of Open Access Journals (Sweden)

    M. Breunig

    2017-09-01

    Full Text Available Computer-aided collaborative and multi-scale 3D planning are challenges for complex railway and subway track infrastructure projects in the built environment. Many legal, economic, environmental, and structural requirements have to be taken into account. The stringent use of 3D models in the different phases of the planning process facilitates communication and collaboration between the stake holders such as civil engineers, geological engineers, and decision makers. This paper presents concepts, developments, and experiences gained by an interdisciplinary research group coming from civil engineering informatics and geo-informatics banding together skills of both, the Building Information Modeling and the 3D GIS world. New approaches including the development of a collaborative platform and 3D multi-scale modelling are proposed for collaborative planning and simulation to improve the digital 3D planning of subway tracks and other infrastructures. Experiences during this research and lessons learned are presented as well as an outlook on future research focusing on Building Information Modeling and 3D GIS applications for cities of the future.

  9. Adaptive Multiscale Modeling of Geochemical Impacts on Fracture Evolution

    Science.gov (United States)

    Molins, S.; Trebotich, D.; Steefel, C. I.; Deng, H.

    2016-12-01

    Understanding fracture evolution is essential for many subsurface energy applications, including subsurface storage, shale gas production, fracking, CO2 sequestration, and geothermal energy extraction. Geochemical processes in particular play a significant role in the evolution of fractures through dissolution-driven widening, fines migration, and/or fracture sealing due to precipitation. One obstacle to understanding and exploiting geochemical fracture evolution is that it is a multiscale process. However, current geochemical modeling of fractures cannot capture this multi-scale nature of geochemical and mechanical impacts on fracture evolution, and is limited to either a continuum or pore-scale representation. Conventional continuum-scale models treat fractures as preferential flow paths, with their permeability evolving as a function (often, a cubic law) of the fracture aperture. This approach has the limitation that it oversimplifies flow within the fracture in its omission of pore scale effects while also assuming well-mixed conditions. More recently, pore-scale models along with advanced characterization techniques have allowed for accurate simulations of flow and reactive transport within the pore space (Molins et al., 2014, 2015). However, these models, even with high performance computing, are currently limited in their ability to treat tractable domain sizes (Steefel et al., 2013). Thus, there is a critical need to develop an adaptive modeling capability that can account for separate properties and processes, emergent and otherwise, in the fracture and the rock matrix at different spatial scales. Here we present an adaptive modeling capability that treats geochemical impacts on fracture evolution within a single multiscale framework. Model development makes use of the high performance simulation capability, Chombo-Crunch, leveraged by high resolution characterization and experiments. The modeling framework is based on the adaptive capability in Chombo

  10. Multiscale empirical interpolation for solving nonlinear PDEs

    KAUST Repository

    Calo, Victor M.

    2014-12-01

    In this paper, we propose a multiscale empirical interpolation method for solving nonlinear multiscale partial differential equations. The proposed method combines empirical interpolation techniques and local multiscale methods, such as the Generalized Multiscale Finite Element Method (GMsFEM). To solve nonlinear equations, the GMsFEM is used to represent the solution on a coarse grid with multiscale basis functions computed offline. Computing the GMsFEM solution involves calculating the system residuals and Jacobians on the fine grid. We use empirical interpolation concepts to evaluate these residuals and Jacobians of the multiscale system with a computational cost which is proportional to the size of the coarse-scale problem rather than the fully-resolved fine scale one. The empirical interpolation method uses basis functions which are built by sampling the nonlinear function we want to approximate a limited number of times. The coefficients needed for this approximation are computed in the offline stage by inverting an inexpensive linear system. The proposed multiscale empirical interpolation techniques: (1) divide computing the nonlinear function into coarse regions; (2) evaluate contributions of nonlinear functions in each coarse region taking advantage of a reduced-order representation of the solution; and (3) introduce multiscale proper-orthogonal-decomposition techniques to find appropriate interpolation vectors. We demonstrate the effectiveness of the proposed methods on several nonlinear multiscale PDEs that are solved with Newton\\'s methods and fully-implicit time marching schemes. Our numerical results show that the proposed methods provide a robust framework for solving nonlinear multiscale PDEs on a coarse grid with bounded error and significant computational cost reduction.

  11. Differential geometry based multiscale models.

    Science.gov (United States)

    Wei, Guo-Wei

    2010-08-01

    Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atomistic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier-Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson-Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson-Nernst-Planck equations that are

  12. Differential Geometry Based Multiscale Models

    Science.gov (United States)

    Wei, Guo-Wei

    2010-01-01

    Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atom-istic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier–Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson–Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson–Nernst–Planck equations that

  13. Application of Mortar Coupling in Multiscale Modelling of Coupled Flow, Transport, and Biofilm Growth in Porous Media

    Science.gov (United States)

    Laleian, A.; Valocchi, A. J.; Werth, C. J.

    2017-12-01

    Multiscale models of reactive transport in porous media are capable of capturing complex pore-scale processes while leveraging the efficiency of continuum-scale models. In particular, porosity changes caused by biofilm development yield complex feedbacks between transport and reaction that are difficult to quantify at the continuum scale. Pore-scale models, needed to accurately resolve these dynamics, are often impractical for applications due to their computational cost. To address this challenge, we are developing a multiscale model of biofilm growth in which non-overlapping regions at pore and continuum spatial scales are coupled with a mortar method providing continuity at interfaces. We explore two decompositions of coupled pore-scale and continuum-scale regions to study biofilm growth in a transverse mixing zone. In the first decomposition, all reaction is confined to a pore-scale region extending the transverse mixing zone length. Only solute transport occurs in the surrounding continuum-scale regions. Relative to a fully pore-scale result, we find the multiscale model with this decomposition has a reduced run time and consistent result in terms of biofilm growth and solute utilization. In the second decomposition, reaction occurs in both an up-gradient pore-scale region and a down-gradient continuum-scale region. To quantify clogging, the continuum-scale model implements empirical relations between porosity and continuum-scale parameters, such as permeability and the transverse dispersion coefficient. Solutes are sufficiently mixed at the end of the pore-scale region, such that the initial reaction rate is accurately computed using averaged concentrations in the continuum-scale region. Relative to a fully pore-scale result, we find accuracy of biomass growth in the multiscale model with this decomposition improves as the interface between pore-scale and continuum-scale regions moves downgradient where transverse mixing is more fully developed. Also, this

  14. Physics-based hybrid method for multiscale transport in porous media

    Science.gov (United States)

    Yousefzadeh, Mehrdad; Battiato, Ilenia

    2017-09-01

    Despite advancements in the development of multiscale models for flow and reactive transport in porous media, the accurate, efficient and physics-based coupling of multiple scales in hybrid models remains a major theoretical and computational challenge. Improving the predictivity of macroscale predictions by means of multiscale algorithms relative to classical at-scale models is the primary motivation for the development of multiscale simulators. Yet, very few are the quantitative studies that explicitly address the predictive capability of multiscale coupling algorithms as it is still generally not possible to have a priori estimates of the errors that are present when complex flow processes are modeled. We develop a nonintrusive pore-/continuum-scale hybrid model whose coupling error is bounded by the upscaling error, i.e. we build a predictive tightly coupled multiscale scheme. This is accomplished by slightly enlarging the subdomain where continuum-scale equations are locally invalid and analytically defining physics-based coupling conditions at the interfaces separating the two computational sub-domains, while enforcing state variable and flux continuity. The proposed multiscale coupling approach retains the advantages of domain decomposition approaches, including the use of existing solvers for each subdomain, while it gains flexibility in the choice of the numerical discretization method and maintains the coupling errors bounded by the upscaling error. We implement the coupling in finite volumes and test the proposed method by modeling flow and transport through a reactive channel and past an array of heterogeneously reactive cylinders.

  15. Microstructure-based multiscale modeling of elevated temperature deformation in aluminum alloys

    International Nuclear Information System (INIS)

    Krajewski, Paul E.; Hector, Louis G.; Du Ningning; Bower, Allan F.

    2010-01-01

    A multiscale model for predicting elevated temperature deformation in Al-Mg alloys is presented. Constitutive models are generated from a theoretical methodology and used to investigate the effects of grain size on formability. Flow data are computed with a polycrystalline, microstructure-based model which accounts for grain boundary sliding, stress-induced diffusion, and dislocation creep. Favorable agreement is found between the computed flow data and elevated temperature tensile measurements. A creep constitutive model is then fit to the computed flow data and used in finite-element simulations of two simple gas pressure forming processes, where favorable results are observed. These results are fully consistent with gas pressure forming experiments, and suggest a greater role for constitutive models, derived largely from theoretical methodologies, in the design of Al alloys with enhanced elevated temperature formability. The methodology detailed herein provides a framework for incorporation of results from atomistic-scale models of dislocation creep and diffusion.

  16. Effect of Mesoscale and Multiscale Modeling on the Performance of Kevlar Woven Fabric Subjected to Ballistic Impact: A Numerical Study

    Science.gov (United States)

    Jia, Xin; Huang, Zhengxiang; Zu, Xudong; Gu, Xiaohui; Xiao, Qiangqiang

    2013-12-01

    In this study, an optimal finite element model of Kevlar woven fabric that is more computational efficient compared with existing models was developed to simulate ballistic impact onto fabric. Kevlar woven fabric was modeled to yarn level architecture by using the hybrid elements analysis (HEA), which uses solid elements in modeling the yarns at the impact region and uses shell elements in modeling the yarns away from the impact region. Three HEA configurations were constructed, in which the solid element region was set as about one, two, and three times that of the projectile's diameter with impact velocities of 30 m/s (non-perforation case) and 200 m/s (perforation case) to determine the optimal ratio between the solid element region and the shell element region. To further reduce computational time and to maintain the necessary accuracy, three multiscale models were presented also. These multiscale models combine the local region with the yarn level architecture by using the HEA approach and the global region with homogenous level architecture. The effect of the varying ratios of the local and global area on the ballistic performance of fabric was discussed. The deformation and damage mechanisms of fabric were analyzed and compared among numerical models. Simulation results indicate that the multiscale model based on HEA accurately reproduces the baseline results and obviously decreases computational time.

  17. The Multi-Scale Model Approach to Thermohydrology at Yucca Mountain

    International Nuclear Information System (INIS)

    Glascoe, L; Buscheck, T A; Gansemer, J; Sun, Y

    2002-01-01

    The Multi-Scale Thermo-Hydrologic (MSTH) process model is a modeling abstraction of them1 hydrology (TH) of the potential Yucca Mountain repository at multiple spatial scales. The MSTH model as described herein was used for the Supplemental Science and Performance Analyses (BSC, 2001) and is documented in detail in CRWMS M and O (2000) and Glascoe et al. (2002). The model has been validated to a nested grid model in Buscheck et al. (In Review). The MSTH approach is necessary for modeling thermal hydrology at Yucca Mountain for two reasons: (1) varying levels of detail are necessary at different spatial scales to capture important TH processes and (2) a fully-coupled TH model of the repository which includes the necessary spatial detail is computationally prohibitive. The MSTH model consists of six ''submodels'' which are combined in a manner to reduce the complexity of modeling where appropriate. The coupling of these models allows for appropriate consideration of mountain-scale thermal hydrology along with the thermal hydrology of drift-scale discrete waste packages of varying heat load. Two stages are involved in the MSTH approach, first, the execution of submodels, and second, the assembly of submodels using the Multi-scale Thermohydrology Abstraction Code (MSTHAC). MSTHAC assembles the submodels in a five-step process culminating in the TH model output of discrete waste packages including a mountain-scale influence

  18. Multiscale Modeling of Carbon/Phenolic Composite Thermal Protection Materials: Atomistic to Effective Properties

    Science.gov (United States)

    Arnold, Steven M.; Murthy, Pappu L.; Bednarcyk, Brett A.; Lawson, John W.; Monk, Joshua D.; Bauschlicher, Charles W., Jr.

    2016-01-01

    Next generation ablative thermal protection systems are expected to consist of 3D woven composite architectures. It is well known that composites can be tailored to achieve desired mechanical and thermal properties in various directions and thus can be made fit-for-purpose if the proper combination of constituent materials and microstructures can be realized. In the present work, the first, multiscale, atomistically-informed, computational analysis of mechanical and thermal properties of a present day - Carbon/Phenolic composite Thermal Protection System (TPS) material is conducted. Model results are compared to measured in-plane and out-of-plane mechanical and thermal properties to validate the computational approach. Results indicate that given sufficient microstructural fidelity, along with lowerscale, constituent properties derived from molecular dynamics simulations, accurate composite level (effective) thermo-elastic properties can be obtained. This suggests that next generation TPS properties can be accurately estimated via atomistically informed multiscale analysis.

  19. Multi-scale computation methods: Their applications in lithium-ion battery research and development

    International Nuclear Information System (INIS)

    Shi Siqi; Zhao Yan; Wu Qu; Gao Jian; Liu Yue; Ju Wangwei; Ouyang Chuying; Xiao Ruijuan

    2016-01-01

    Based upon advances in theoretical algorithms, modeling and simulations, and computer technologies, the rational design of materials, cells, devices, and packs in the field of lithium-ion batteries is being realized incrementally and will at some point trigger a paradigm revolution by combining calculations and experiments linked by a big shared database, enabling accelerated development of the whole industrial chain. Theory and multi-scale modeling and simulation, as supplements to experimental efforts, can help greatly to close some of the current experimental and technological gaps, as well as predict path-independent properties and help to fundamentally understand path-independent performance in multiple spatial and temporal scales. (topical review)

  20. Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen

    Energy Technology Data Exchange (ETDEWEB)

    Plechac, Petr [Univ. of Tennessee, Knoxville, TN (United States). Dept. of Mathematics; Univ. of Delaware, Newark, DE (United States). Dept. of Mathematics; Vlachos, Dionisios [Univ. of Delaware, Newark, DE (United States). Dept. of Chemical and Biomolecular Engineering; Katsoulakis, Markos [Univ. of Massachusetts, Amherst, MA (United States). Dept. of Mathematics

    2013-09-05

    The overall objective of this project is to develop multiscale models for understanding and eventually designing complex processes for renewables. To the best of our knowledge, our work is the first attempt at modeling complex reacting systems, whose performance relies on underlying multiscale mathematics. Our specific application lies at the heart of biofuels initiatives of DOE and entails modeling of catalytic systems, to enable economic, environmentally benign, and efficient conversion of biomass into either hydrogen or valuable chemicals. Specific goals include: (i) Development of rigorous spatio-temporal coarse-grained kinetic Monte Carlo (KMC) mathematics and simulation for microscopic processes encountered in biomass transformation. (ii) Development of hybrid multiscale simulation that links stochastic simulation to a deterministic partial differential equation (PDE) model for an entire reactor. (iii) Development of hybrid multiscale simulation that links KMC simulation with quantum density functional theory (DFT) calculations. (iv) Development of parallelization of models of (i)-(iii) to take advantage of Petaflop computing and enable real world applications of complex, multiscale models. In this NCE period, we continued addressing these objectives and completed the proposed work. Main initiatives, key results, and activities are outlined.

  1. Modeling Temporal Evolution and Multiscale Structure in Networks

    DEFF Research Database (Denmark)

    Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard

    2013-01-01

    Many real-world networks exhibit both temporal evolution and multiscale structure. We propose a model for temporally correlated multifurcating hierarchies in complex networks which jointly capture both effects. We use the Gibbs fragmentation tree as prior over multifurcating trees and a change......-point model to account for the temporal evolution of each vertex. We demonstrate that our model is able to infer time-varying multiscale structure in synthetic as well as three real world time-evolving complex networks. Our modeling of the temporal evolution of hierarchies brings new insights...

  2. Multiscale Modeling of Carbon Fiber Reinforced Polymer (CFRP) for Integrated Computational Materials Engineering Process

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Jiaying; Liang, Biao; Zhang, Weizhao; Liu, Zeliang; Cheng, Puikei; Bostanabad, Ramin; Cao, Jian; Chen, Wei; Liu, Wing Kam; Su, Xuming; Zeng, Danielle; Zhao, John

    2017-10-23

    In this work, a multiscale modeling framework for CFRP is introduced to study hierarchical structure of CFRP. Four distinct scales are defined: nanoscale, microscale, mesoscale, and macroscale. Information at lower scales can be passed to higher scale, which is beneficial for studying effect of constituents on macroscale part’s mechanical property. This bottom-up modeling approach enables better understanding of CFRP from finest details. Current study focuses on microscale and mesoscale. Representative volume element is used at microscale and mesoscale to model material’s properties. At microscale, unidirection CFRP (UD) RVE is used to study properties of UD. The UD RVE can be modeled with different volumetric fraction to encounter non-uniform fiber distribution in CFRP part. Such consideration is important in modeling uncertainties at microscale level. Currently, we identified volumetric fraction as the only uncertainty parameters in UD RVE. To measure effective material properties of UD RVE, periodic boundary conditions (PBC) are applied to UD RVE to ensure convergence of obtained properties. Properties of UD is directly used at mesoscale woven RVE modeling, where each yarn is assumed to have same properties as UD. Within woven RVE, there can be many potential uncertainties parameters to consider for a physical modeling of CFRP. Currently, we will consider fiber misalignment within yarn and angle between wrap and weft yarns. PBC is applied to woven RVE to calculate its effective material properties. The effect of uncertainties are investigated quantitatively by Gaussian process. Preliminary results of UD and Woven study are analyzed for efficacy of the RVE modeling. This work is considered as the foundation for future multiscale modeling framework development for ICME project.

  3. All-Particle Multiscale Computation of Hypersonic Rarefied Flow

    Science.gov (United States)

    Jun, E.; Burt, J. M.; Boyd, I. D.

    2011-05-01

    This study examines a new hybrid particle scheme used as an alternative means of multiscale flow simulation. The hybrid particle scheme employs the direct simulation Monte Carlo (DSMC) method in rarefied flow regions and the low diffusion (LD) particle method in continuum flow regions. The numerical procedures of the low diffusion particle method are implemented within an existing DSMC algorithm. The performance of the LD-DSMC approach is assessed by studying Mach 10 nitrogen flow over a sphere with a global Knudsen number of 0.002. The hybrid scheme results show good overall agreement with results from standard DSMC and CFD computation. Subcell procedures are utilized to improve computational efficiency and reduce sensitivity to DSMC cell size in the hybrid scheme. This makes it possible to perform the LD-DSMC simulation on a much coarser mesh that leads to a significant reduction in computation time.

  4. Multi-Scale Models for the Scale Interaction of Organized Tropical Convection

    Science.gov (United States)

    Yang, Qiu

    Assessing the upscale impact of organized tropical convection from small spatial and temporal scales is a research imperative, not only for having a better understanding of the multi-scale structures of dynamical and convective fields in the tropics, but also for eventually helping in the design of new parameterization strategies to improve the next-generation global climate models. Here self-consistent multi-scale models are derived systematically by following the multi-scale asymptotic methods and used to describe the hierarchical structures of tropical atmospheric flows. The advantages of using these multi-scale models lie in isolating the essential components of multi-scale interaction and providing assessment of the upscale impact of the small-scale fluctuations onto the large-scale mean flow through eddy flux divergences of momentum and temperature in a transparent fashion. Specifically, this thesis includes three research projects about multi-scale interaction of organized tropical convection, involving tropical flows at different scaling regimes and utilizing different multi-scale models correspondingly. Inspired by the observed variability of tropical convection on multiple temporal scales, including daily and intraseasonal time scales, the goal of the first project is to assess the intraseasonal impact of the diurnal cycle on the planetary-scale circulation such as the Hadley cell. As an extension of the first project, the goal of the second project is to assess the intraseasonal impact of the diurnal cycle over the Maritime Continent on the Madden-Julian Oscillation. In the third project, the goals are to simulate the baroclinic aspects of the ITCZ breakdown and assess its upscale impact on the planetary-scale circulation over the eastern Pacific. These simple multi-scale models should be useful to understand the scale interaction of organized tropical convection and help improve the parameterization of unresolved processes in global climate models.

  5. Simulation of left atrial function using a multi-scale model of the cardiovascular system.

    Directory of Open Access Journals (Sweden)

    Antoine Pironet

    Full Text Available During a full cardiac cycle, the left atrium successively behaves as a reservoir, a conduit and a pump. This complex behavior makes it unrealistic to apply the time-varying elastance theory to characterize the left atrium, first, because this theory has known limitations, and second, because it is still uncertain whether the load independence hypothesis holds. In this study, we aim to bypass this uncertainty by relying on another kind of mathematical model of the cardiac chambers. In the present work, we describe both the left atrium and the left ventricle with a multi-scale model. The multi-scale property of this model comes from the fact that pressure inside a cardiac chamber is derived from a model of the sarcomere behavior. Macroscopic model parameters are identified from reference dog hemodynamic data. The multi-scale model of the cardiovascular system including the left atrium is then simulated to show that the physiological roles of the left atrium are correctly reproduced. This include a biphasic pressure wave and an eight-shaped pressure-volume loop. We also test the validity of our model in non basal conditions by reproducing a preload reduction experiment by inferior vena cava occlusion with the model. We compute the variation of eight indices before and after this experiment and obtain the same variation as experimentally observed for seven out of the eight indices. In summary, the multi-scale mathematical model presented in this work is able to correctly account for the three roles of the left atrium and also exhibits a realistic left atrial pressure-volume loop. Furthermore, the model has been previously presented and validated for the left ventricle. This makes it a proper alternative to the time-varying elastance theory if the focus is set on precisely representing the left atrial and left ventricular behaviors.

  6. Multiscale geometric modeling of macromolecules II: Lagrangian representation

    Science.gov (United States)

    Feng, Xin; Xia, Kelin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei

    2013-01-01

    Geometric modeling of biomolecules plays an essential role in the conceptualization of biolmolecular structure, function, dynamics and transport. Qualitatively, geometric modeling offers a basis for molecular visualization, which is crucial for the understanding of molecular structure and interactions. Quantitatively, geometric modeling bridges the gap between molecular information, such as that from X-ray, NMR and cryo-EM, and theoretical/mathematical models, such as molecular dynamics, the Poisson-Boltzmann equation and the Nernst-Planck equation. In this work, we present a family of variational multiscale geometric models for macromolecular systems. Our models are able to combine multiresolution geometric modeling with multiscale electrostatic modeling in a unified variational framework. We discuss a suite of techniques for molecular surface generation, molecular surface meshing, molecular volumetric meshing, and the estimation of Hadwiger’s functionals. Emphasis is given to the multiresolution representations of biomolecules and the associated multiscale electrostatic analyses as well as multiresolution curvature characterizations. The resulting fine resolution representations of a biomolecular system enable the detailed analysis of solvent-solute interaction, and ion channel dynamics, while our coarse resolution representations highlight the compatibility of protein-ligand bindings and possibility of protein-protein interactions. PMID:23813599

  7. Multi-scale modeling of the environmental impact and energy performance of open-loop groundwater heat pumps in urban areas

    International Nuclear Information System (INIS)

    Sciacovelli, A.; Guelpa, E.; Verda, V.

    2014-01-01

    Groundwater heat pumps are expected to play a major role in future energy scenarios. Proliferation of such systems in urban areas may generate issues related to possible interference between installations. These issues are associated with the thermal plume produced by heat pumps during operation and are particularly evident in the case of groundwater flow, because of the advection heat transfer. In this paper, the impact of an installation is investigated through a thermo-fluid dynamic model of the subsurface which considers fluid flow in the saturated unit and heat transfer in both the saturated and unsaturated units. Due to the large extension of the affected area, a multiscale numerical model that combines a three-dimensional CFD model and a network model is proposed. The thermal request of the user and the heat pump performances are considered in the multi-scale numerical model through appropriate boundary conditions imposed at the wells. Various scenarios corresponding to different operating modes of the heat pump are considered. - Highlights: • A groundwater heat pump of a skyscraper under construction is considered. • The thermal plume induced in the groundwater is evaluated using a multi-scale model. • The multi-scale model is constituted by a full 3D model and a network model. • Multi-scale permits to study large space for long time with low computational costs. • In some cases thermal plume can reduce the COP of other heat pumps of 20%

  8. A Posteriori Analysis of Adaptive Multiscale Operator Decomposition Methods for Multiphysics Problems

    Energy Technology Data Exchange (ETDEWEB)

    Donald Estep; Michael Holst; Simon Tavener

    2010-02-08

    This project was concerned with the accurate computational error estimation for numerical solutions of multiphysics, multiscale systems that couple different physical processes acting across a large range of scales relevant to the interests of the DOE. Multiscale, multiphysics models are characterized by intimate interactions between different physics across a wide range of scales. This poses significant computational challenges addressed by the proposal, including: (1) Accurate and efficient computation; (2) Complex stability; and (3) Linking different physics. The research in this project focused on Multiscale Operator Decomposition methods for solving multiphysics problems. The general approach is to decompose a multiphysics problem into components involving simpler physics over a relatively limited range of scales, and then to seek the solution of the entire system through some sort of iterative procedure involving solutions of the individual components. MOD is a very widely used technique for solving multiphysics, multiscale problems; it is heavily used throughout the DOE computational landscape. This project made a major advance in the analysis of the solution of multiscale, multiphysics problems.

  9. Self-consistent clustering analysis: an efficient multiscale scheme for inelastic heterogeneous materials

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Z.; Bessa, M. A.; Liu, W.K.

    2017-10-25

    A predictive computational theory is shown for modeling complex, hierarchical materials ranging from metal alloys to polymer nanocomposites. The theory can capture complex mechanisms such as plasticity and failure that span across multiple length scales. This general multiscale material modeling theory relies on sound principles of mathematics and mechanics, and a cutting-edge reduced order modeling method named self-consistent clustering analysis (SCA) [Zeliang Liu, M.A. Bessa, Wing Kam Liu, “Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials,” Comput. Methods Appl. Mech. Engrg. 306 (2016) 319–341]. SCA reduces by several orders of magnitude the computational cost of micromechanical and concurrent multiscale simulations, while retaining the microstructure information. This remarkable increase in efficiency is achieved with a data-driven clustering method. Computationally expensive operations are performed in the so-called offline stage, where degrees of freedom (DOFs) are agglomerated into clusters. The interaction tensor of these clusters is computed. In the online or predictive stage, the Lippmann-Schwinger integral equation is solved cluster-wise using a self-consistent scheme to ensure solution accuracy and avoid path dependence. To construct a concurrent multiscale model, this scheme is applied at each material point in a macroscale structure, replacing a conventional constitutive model with the average response computed from the microscale model using just the SCA online stage. A regularized damage theory is incorporated in the microscale that avoids the mesh and RVE size dependence that commonly plagues microscale damage calculations. The SCA method is illustrated with two cases: a carbon fiber reinforced polymer (CFRP) structure with the concurrent multiscale model and an application to fatigue prediction for additively manufactured metals. For the CFRP problem, a speed up estimated to be about

  10. Multiscale and Multiphysics Modeling of Additive Manufacturing of Advanced Materials

    Science.gov (United States)

    Liou, Frank; Newkirk, Joseph; Fan, Zhiqiang; Sparks, Todd; Chen, Xueyang; Fletcher, Kenneth; Zhang, Jingwei; Zhang, Yunlu; Kumar, Kannan Suresh; Karnati, Sreekar

    2015-01-01

    The objective of this proposed project is to research and develop a prediction tool for advanced additive manufacturing (AAM) processes for advanced materials and develop experimental methods to provide fundamental properties and establish validation data. Aircraft structures and engines demand materials that are stronger, useable at much higher temperatures, provide less acoustic transmission, and enable more aeroelastic tailoring than those currently used. Significant improvements in properties can only be achieved by processing the materials under nonequilibrium conditions, such as AAM processes. AAM processes encompass a class of processes that use a focused heat source to create a melt pool on a substrate. Examples include Electron Beam Freeform Fabrication and Direct Metal Deposition. These types of additive processes enable fabrication of parts directly from CAD drawings. To achieve the desired material properties and geometries of the final structure, assessing the impact of process parameters and predicting optimized conditions with numerical modeling as an effective prediction tool is necessary. The targets for the processing are multiple and at different spatial scales, and the physical phenomena associated occur in multiphysics and multiscale. In this project, the research work has been developed to model AAM processes in a multiscale and multiphysics approach. A macroscale model was developed to investigate the residual stresses and distortion in AAM processes. A sequentially coupled, thermomechanical, finite element model was developed and validated experimentally. The results showed the temperature distribution, residual stress, and deformation within the formed deposits and substrates. A mesoscale model was developed to include heat transfer, phase change with mushy zone, incompressible free surface flow, solute redistribution, and surface tension. Because of excessive computing time needed, a parallel computing approach was also tested. In addition

  11. Polynomial Chaos Characterization of Uncertainty in Multiscale Models and Behavior of Carbon Reinforced Composites

    Energy Technology Data Exchange (ETDEWEB)

    Mehrez, Loujaine [University of Southern California; Ghanem, Roger [University of Southern California; Aitharaju, Venkat [General Motors; Rodgers, William [General Motors

    2017-10-23

    Design of non-crimp fabric (NCF) composites entails major challenges pertaining to (1) the complex fine-scale morphology of the constituents, (2) the manufacturing-produced inconsistency of this morphology spatially, and thus (3) the ability to build reliable, robust, and efficient computational surrogate models to account for this complex nature. Traditional approaches to construct computational surrogate models have been to average over the fluctuations of the material properties at different scale lengths. This fails to account for the fine-scale features and fluctuations in morphology, material properties of the constituents, as well as fine-scale phenomena such as damage and cracks. In addition, it fails to accurately predict the scatter in macroscopic properties, which is vital to the design process and behavior prediction. In this work, funded in part by the Department of Energy, we present an approach for addressing these challenges by relying on polynomial chaos representations of both input parameters and material properties at different scales. Moreover, we emphasize the efficiency and robustness of integrating the polynomial chaos expansion with multiscale tools to perform multiscale assimilation, characterization, propagation, and prediction, all of which are necessary to construct the data-driven surrogate models required to design under the uncertainty of composites. These data-driven constructions provide an accurate map from parameters (and their uncertainties) at all scales and the system-level behavior relevant for design. While this perspective is quite general and applicable to all multiscale systems, NCF composites present a particular hierarchy of scales that permits the efficient implementation of these concepts.

  12. Bridging scales through multiscale modeling: A case study on Protein Kinase A

    Directory of Open Access Journals (Sweden)

    Sophia P Hirakis

    2015-09-01

    Full Text Available The goal of multiscale modeling in biology is to use structurally based physico-chemical models to integrate across temporal and spatial scales of biology and thereby improve mechanistic understanding of, for example, how a single mutation can alter organism-scale phenotypes. This approach may also inform therapeutic strategies or identify candidate drug targets that might otherwise have been overlooked. However, in many cases, it remains unclear how best to synthesize information obtained from various scales and analysis approaches, such as atomistic molecular models, Markov state models (MSM, subcellular network models, and whole cell models. In this paper, we use protein kinase A (PKA activation as a case study to explore how computational methods that model different physical scales can complement each other and integrate into an improved multiscale representation of the biological mechanisms. Using measured crystal structures, we show how molecular dynamics (MD simulations coupled with atomic-scale MSMs can provide conformations for Brownian dynamics (BD simulations to feed transitional states and kinetic parameters into protein-scale MSMs. We discuss how milestoning can give reaction probabilities and forward-rate constants of cAMP association events by seamlessly integrating MD and BD simulation scales. These rate constants coupled with MSMs provide a robust representation of the free energy landscape, enabling access to kinetic and thermodynamic parameters unavailable from current experimental data. These approaches have helped to illuminate the cooperative nature of PKA activation in response to distinct cAMP binding events. Collectively, this approach exemplifies a general strategy for multiscale model development that is applicable to a wide range of biological problems.

  13. Multiscale Modeling of Ceramic Matrix Composites

    Science.gov (United States)

    Bednarcyk, Brett A.; Mital, Subodh K.; Pineda, Evan J.; Arnold, Steven M.

    2015-01-01

    Results of multiscale modeling simulations of the nonlinear response of SiC/SiC ceramic matrix composites are reported, wherein the microstructure of the ceramic matrix is captured. This micro scale architecture, which contains free Si material as well as the SiC ceramic, is responsible for residual stresses that play an important role in the subsequent thermo-mechanical behavior of the SiC/SiC composite. Using the novel Multiscale Generalized Method of Cells recursive micromechanics theory, the microstructure of the matrix, as well as the microstructure of the composite (fiber and matrix) can be captured.

  14. A Physiologically Based, Multi-Scale Model of Skeletal Muscle Structure and Function

    Science.gov (United States)

    Röhrle, O.; Davidson, J. B.; Pullan, A. J.

    2012-01-01

    Models of skeletal muscle can be classified as phenomenological or biophysical. Phenomenological models predict the muscle’s response to a specified input based on experimental measurements. Prominent phenomenological models are the Hill-type muscle models, which have been incorporated into rigid-body modeling frameworks, and three-dimensional continuum-mechanical models. Biophysically based models attempt to predict the muscle’s response as emerging from the underlying physiology of the system. In this contribution, the conventional biophysically based modeling methodology is extended to include several structural and functional characteristics of skeletal muscle. The result is a physiologically based, multi-scale skeletal muscle finite element model that is capable of representing detailed, geometrical descriptions of skeletal muscle fibers and their grouping. Together with a well-established model of motor-unit recruitment, the electro-physiological behavior of single muscle fibers within motor units is computed and linked to a continuum-mechanical constitutive law. The bridging between the cellular level and the organ level has been achieved via a multi-scale constitutive law and homogenization. The effect of homogenization has been investigated by varying the number of embedded skeletal muscle fibers and/or motor units and computing the resulting exerted muscle forces while applying the same excitatory input. All simulations were conducted using an anatomically realistic finite element model of the tibialis anterior muscle. Given the fact that the underlying electro-physiological cellular muscle model is capable of modeling metabolic fatigue effects such as potassium accumulation in the T-tubular space and inorganic phosphate build-up, the proposed framework provides a novel simulation-based way to investigate muscle behavior ranging from motor-unit recruitment to force generation and fatigue. PMID:22993509

  15. A physiologically based, multi-scale model of skeletal muscle structure and function

    Directory of Open Access Journals (Sweden)

    Oliver eRöhrle

    2012-09-01

    Full Text Available Models of skeletal muscle can be classified as phenomenological or biophysical. Phenomenological models predict the muscle's response to a specified input based on experimental measurements. Prominent phenomenological models are the Hill-type muscle models, which have been incorporated into rigid-body modelling frameworks, and three-dimensional continuum-mechanical models. Biophysically based models attempt to predict the muscle's response as emerging from the underlying physiology of the system. In this contribution, the conventional biophysically based modelling methodology is extended to include several structural and functional characteristics of skeletal muscle. The result is a physiologically based, multi-scale skeletal muscle finite element model that is capable of representing detailed, geometrical descriptions of skeletal muscle fibres and their grouping. Together with a well-established model of motor unit recruitment, the electro-physiological behaviour of single muscle fibres within motor units is computed and linked to a continuum-mechanical constitutive law. The bridging between the cellular level and the organ level has been achieved via a multi-scale constitutive law and homogenisation. The effect of homogenisation has been investigated by varying the number of embedded skeletal muscle fibres and/or motor units and computing the resulting exerted muscle forces while applying the same excitatory input. All simulations were conducted using an anatomically realistic finite element model of the Tibialis Anterior muscle. Given the fact that the underlying electro-physiological cellular muscle model is capable of modelling metabolic fatigue effects such as potassium accumulation in the T-tubular space and inorganic phosphate build-up, the proposed framework provides a novel simulation-based way to investigate muscle behaviour ranging from motor unit recruitment to force generation and fatigue.

  16. A multi-scale computational model of the effects of TMS on motor cortex [version 3; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Hyeon Seo

    2017-05-01

    Full Text Available The detailed biophysical mechanisms through which transcranial magnetic stimulation (TMS activates cortical circuits are still not fully understood. Here we present a multi-scale computational model to describe and explain the activation of different pyramidal cell types in motor cortex due to TMS. Our model determines precise electric fields based on an individual head model derived from magnetic resonance imaging and calculates how these electric fields activate morphologically detailed models of different neuron types. We predict neural activation patterns for different coil orientations consistent with experimental findings. Beyond this, our model allows us to calculate activation thresholds for individual neurons and precise initiation sites of individual action potentials on the neurons’ complex morphologies. Specifically, our model predicts that cortical layer 3 pyramidal neurons are generally easier to stimulate than layer 5 pyramidal neurons, thereby explaining the lower stimulation thresholds observed for I-waves compared to D-waves. It also shows differences in the regions of activated cortical layer 5 and layer 3 pyramidal cells depending on coil orientation. Finally, it predicts that under standard stimulation conditions, action potentials are mostly generated at the axon initial segment of cortical pyramidal cells, with a much less important activation site being the part of a layer 5 pyramidal cell axon where it crosses the boundary between grey matter and white matter. In conclusion, our computational model offers a detailed account of the mechanisms through which TMS activates different cortical pyramidal cell types, paving the way for more targeted application of TMS based on individual brain morphology in clinical and basic research settings.

  17. Urban Flow and Pollutant Dispersion Simulation with Multi-scale coupling of Meteorological Model with Computational Fluid Dynamic Analysis

    Science.gov (United States)

    Liu, Yushi; Poh, Hee Joo

    2014-11-01

    The Computational Fluid Dynamics analysis has become increasingly important in modern urban planning in order to create highly livable city. This paper presents a multi-scale modeling methodology which couples Weather Research and Forecasting (WRF) Model with open source CFD simulation tool, OpenFOAM. This coupling enables the simulation of the wind flow and pollutant dispersion in urban built-up area with high resolution mesh. In this methodology meso-scale model WRF provides the boundary condition for the micro-scale CFD model OpenFOAM. The advantage is that the realistic weather condition is taken into account in the CFD simulation and complexity of building layout can be handled with ease by meshing utility of OpenFOAM. The result is validated against the Joint Urban 2003 Tracer Field Tests in Oklahoma City and there is reasonably good agreement between the CFD simulation and field observation. The coupling of WRF- OpenFOAM provide urban planners with reliable environmental modeling tool in actual urban built-up area; and it can be further extended with consideration of future weather conditions for the scenario studies on climate change impact.

  18. Computer Models in Biomechanics From Nano to Macro

    CERN Document Server

    Kuhl, Ellen

    2013-01-01

    This book contains a collection of papers that were presented at the IUTAM Symposium on “Computer Models in Biomechanics: From Nano to Macro” held at Stanford University, California, USA, from August 29 to September 2, 2011. It contains state-of-the-art papers on: - Protein and Cell Mechanics: coarse-grained model for unfolded proteins, collagen-proteoglycan structural interactions in the cornea, simulations of cell behavior on substrates - Muscle Mechanics: modeling approaches for Ca2+–regulated smooth muscle contraction, smooth muscle modeling using continuum thermodynamical frameworks, cross-bridge model describing the mechanoenergetics of actomyosin interaction, multiscale skeletal muscle modeling - Cardiovascular Mechanics: multiscale modeling of arterial adaptations by incorporating molecular mechanisms, cardiovascular tissue damage, dissection properties of aortic aneurysms, intracranial aneurysms, electromechanics of the heart, hemodynamic alterations associated with arterial remodeling followin...

  19. Multiscale modeling of emergent materials: biological and soft matter

    DEFF Research Database (Denmark)

    Murtola, Teemu; Bunker, Alex; Vattulainen, Ilpo

    2009-01-01

    In this review, we focus on four current related issues in multiscale modeling of soft and biological matter. First, we discuss how to use structural information from detailed models (or experiments) to construct coarse-grained ones in a hierarchical and systematic way. This is discussed in the c......In this review, we focus on four current related issues in multiscale modeling of soft and biological matter. First, we discuss how to use structural information from detailed models (or experiments) to construct coarse-grained ones in a hierarchical and systematic way. This is discussed...

  20. Resolving Nuclear Reactor Lifetime Extension Questions: A Combined Multiscale Modeling and Positron Characterization approach

    International Nuclear Information System (INIS)

    Wirth, B; Asoka-Kumar, P; Denison, A; Glade, S; Howell, R; Marian, J; Odette, G; Sterne, P

    2004-01-01

    The objective of this work is to determine the chemical composition of nanometer precipitates responsible for irradiation hardening and embrittlement of reactor pressure vessel steels, which threaten to limit the operating lifetime of nuclear power plants worldwide. The scientific approach incorporates computational multiscale modeling of radiation damage and microstructural evolution in Fe-Cu-Ni-Mn alloys, and experimental characterization by positron annihilation spectroscopy and small angle neutron scattering. The modeling and experimental results are

  1. Multi-scale climate modelling over Southern Africa using a variable-resolution global model

    CSIR Research Space (South Africa)

    Engelbrecht, FA

    2011-12-01

    Full Text Available -mail: fengelbrecht@csir.co.za Multi-scale climate modelling over Southern Africa using a variable-resolution global model FA Engelbrecht1, 2*, WA Landman1, 3, CJ Engelbrecht4, S Landman5, MM Bopape1, B Roux6, JL McGregor7 and M Thatcher7 1 CSIR Natural... improvement. Keywords: multi-scale climate modelling, variable-resolution atmospheric model Introduction Dynamic climate models have become the primary tools for the projection of future climate change, at both the global and regional scales. Dynamic...

  2. Multiscale musculoskeletal modelling, data–model fusion and electromyography-informed modelling

    Science.gov (United States)

    Zhang, J.; Heidlauf, T.; Sartori, M.; Besier, T.; Röhrle, O.; Lloyd, D.

    2016-01-01

    This paper proposes methods and technologies that advance the state of the art for modelling the musculoskeletal system across the spatial and temporal scales; and storing these using efficient ontologies and tools. We present population-based modelling as an efficient method to rapidly generate individual morphology from only a few measurements and to learn from the ever-increasing supply of imaging data available. We present multiscale methods for continuum muscle and bone models; and efficient mechanostatistical methods, both continuum and particle-based, to bridge the scales. Finally, we examine both the importance that muscles play in bone remodelling stimuli and the latest muscle force prediction methods that use electromyography-assisted modelling techniques to compute musculoskeletal forces that best reflect the underlying neuromuscular activity. Our proposal is that, in order to have a clinically relevant virtual physiological human, (i) bone and muscle mechanics must be considered together; (ii) models should be trained on population data to permit rapid generation and use underlying principal modes that describe both muscle patterns and morphology; and (iii) these tools need to be available in an open-source repository so that the scientific community may use, personalize and contribute to the database of models. PMID:27051510

  3. Multiscale modeling of three-dimensional genome

    Science.gov (United States)

    Zhang, Bin; Wolynes, Peter

    The genome, the blueprint of life, contains nearly all the information needed to build and maintain an entire organism. A comprehensive understanding of the genome is of paramount interest to human health and will advance progress in many areas, including life sciences, medicine, and biotechnology. The overarching goal of my research is to understand the structure-dynamics-function relationships of the human genome. In this talk, I will be presenting our efforts in moving towards that goal, with a particular emphasis on studying the three-dimensional organization, the structure of the genome with multi-scale approaches. Specifically, I will discuss the reconstruction of genome structures at both interphase and metaphase by making use of data from chromosome conformation capture experiments. Computationally modeling of chromatin fiber at atomistic level from first principles will also be presented as our effort for studying the genome structure from bottom up.

  4. Multiscale virtual particle based elastic network model (MVP-ENM) for normal mode analysis of large-sized biomolecules.

    Science.gov (United States)

    Xia, Kelin

    2017-12-20

    In this paper, a multiscale virtual particle based elastic network model (MVP-ENM) is proposed for the normal mode analysis of large-sized biomolecules. The multiscale virtual particle (MVP) model is proposed for the discretization of biomolecular density data. With this model, large-sized biomolecular structures can be coarse-grained into virtual particles such that a balance between model accuracy and computational cost can be achieved. An elastic network is constructed by assuming "connections" between virtual particles. The connection is described by a special harmonic potential function, which considers the influence from both the mass distributions and distance relations of the virtual particles. Two independent models, i.e., the multiscale virtual particle based Gaussian network model (MVP-GNM) and the multiscale virtual particle based anisotropic network model (MVP-ANM), are proposed. It has been found that in the Debye-Waller factor (B-factor) prediction, the results from our MVP-GNM with a high resolution are as good as the ones from GNM. Even with low resolutions, our MVP-GNM can still capture the global behavior of the B-factor very well with mismatches predominantly from the regions with large B-factor values. Further, it has been demonstrated that the low-frequency eigenmodes from our MVP-ANM are highly consistent with the ones from ANM even with very low resolutions and a coarse grid. Finally, the great advantage of MVP-ANM model for large-sized biomolecules has been demonstrated by using two poliovirus virus structures. The paper ends with a conclusion.

  5. Multi-scale simulation of droplet-droplet interactions and coalescence

    CSIR Research Space (South Africa)

    Musehane, Ndivhuwo M

    2016-10-01

    Full Text Available Conference on Computational and Applied Mechanics Potchefstroom 3–5 October 2016 Multi-scale simulation of droplet-droplet interactions and coalescence 1,2Ndivhuwo M. Musehane?, 1Oliver F. Oxtoby and 2Daya B. Reddy 1. Aeronautic Systems, Council... topology changes that result when droplets interact. This work endeavours to eliminate the need to use empirical correlations based on phenomenological models by developing a multi-scale model that predicts the outcome of a collision between droplets from...

  6. A Multiscale Closed-Loop Cardiovascular Model, with Applications to Heart Pacing and Hemorrhage

    Science.gov (United States)

    Canuto, Daniel; Eldredge, Jeff; Chong, Kwitae; Benharash, Peyman; Dutson, Erik

    2017-11-01

    A computational tool is developed for simulating the dynamic response of the human cardiovascular system to various stressors and injuries. The tool couples zero-dimensional models of the heart, pulmonary vasculature, and peripheral vasculature to one-dimensional models of the major systemic arteries. To simulate autonomic response, this multiscale circulatory model is integrated with a feedback model of the baroreflex, allowing control of heart rate, cardiac contractility, and peripheral impedance. The performance of the tool is demonstrated in two scenarios: increasing heart rate by stimulating the sympathetic nervous system, and an acute 10 percent hemorrhage from the left femoral artery.

  7. A generalized multiscale finite element method for elastic wave propagation in fractured media

    KAUST Repository

    Chung, Eric T.

    2016-02-26

    In this paper, we consider elastic wave propagation in fractured media applying a linear-slip model to represent the effects of fractures on the wavefield. Fractured media, typically, are highly heterogeneous due to multiple length scales. Direct numerical simulations for wave propagation in highly heterogeneous fractured media can be computationally expensive and require some type of model reduction. We develop a multiscale model reduction technique that captures the complex nature of the media (heterogeneities and fractures) in the coarse scale system. The proposed method is based on the generalized multiscale finite element method, where the multiscale basis functions are constructed to capture the fine-scale information of the heterogeneous, fractured media and effectively reduce the degrees of freedom. These multiscale basis functions are coupled via the interior penalty discontinuous Galerkin method, which provides a block-diagonal mass matrix. The latter is needed for fast computation in an explicit time discretization, which is used in our simulations. Numerical results are presented to show the performance of the presented multiscale method for fractured media. We consider several cases where fractured media contain fractures of multiple lengths. Our numerical results show that the proposed reduced-order models can provide accurate approximations for the fine-scale solution.

  8. A generalized multiscale finite element method for elastic wave propagation in fractured media

    KAUST Repository

    Chung, Eric T.; Efendiev, Yalchin R.; Gibson, Richard L.; Vasilyeva, Maria

    2016-01-01

    In this paper, we consider elastic wave propagation in fractured media applying a linear-slip model to represent the effects of fractures on the wavefield. Fractured media, typically, are highly heterogeneous due to multiple length scales. Direct numerical simulations for wave propagation in highly heterogeneous fractured media can be computationally expensive and require some type of model reduction. We develop a multiscale model reduction technique that captures the complex nature of the media (heterogeneities and fractures) in the coarse scale system. The proposed method is based on the generalized multiscale finite element method, where the multiscale basis functions are constructed to capture the fine-scale information of the heterogeneous, fractured media and effectively reduce the degrees of freedom. These multiscale basis functions are coupled via the interior penalty discontinuous Galerkin method, which provides a block-diagonal mass matrix. The latter is needed for fast computation in an explicit time discretization, which is used in our simulations. Numerical results are presented to show the performance of the presented multiscale method for fractured media. We consider several cases where fractured media contain fractures of multiple lengths. Our numerical results show that the proposed reduced-order models can provide accurate approximations for the fine-scale solution.

  9. Multiscale Modeling of Carbon Nanotube-Epoxy Nanocomposites

    Science.gov (United States)

    Fasanella, Nicholas A.

    Epoxy-composites are widely used in the aerospace industry. In order to improve upon stiffness and thermal conductivity; carbon nanotube additives to epoxies are being explored. This dissertation presents multiscale modeling techniques to study the engineering properties of single walled carbon nanotube (SWNT)-epoxy nanocomposites, consisting of pristine and covalently functionalized systems. Using Molecular Dynamics (MD), thermomechanical properties were calculated for a representative polymer unit cell. Finite Element (FE) and orientation distribution function (ODF) based methods were used in a multiscale framework to obtain macroscale properties. An epoxy network was built using the dendrimer growth approach. The epoxy model was verified by matching the experimental glass transition temperature, density, and dilatation. MD, via the constant valence force field (CVFF), was used to explore the mechanical and dilatometric effects of adding pristine and functionalized SWNTs to epoxy. Full stiffness matrices and linear coefficient of thermal expansion vectors were obtained. The Green-Kubo method was used to investigate the thermal conductivity as a function of temperature for the various nanocomposites. Inefficient phonon transport at the ends of nanotubes is an important factor in the thermal conductivity of the nanocomposites, and for this reason discontinuous nanotubes were modeled in addition to long nanotubes. To obtain continuum-scale elastic properties from the MD data, multiscale modeling was considered to give better control over the volume fraction of nanotubes, and investigate the effects of nanotube alignment. Two methods were considered; an FE based method, and an ODF based method. The FE method probabilistically assigned elastic properties of elements from the MD lattice results based on the desired volume fraction and alignment of the nanotubes. For the ODF method, a distribution function was generated based on the desired amount of nanotube alignment

  10. Experimentally-based multiscale model of the elastic moduli of bovine trabecular bone and its constituents

    Energy Technology Data Exchange (ETDEWEB)

    Hamed, Elham [University of Illinois at Urbana-Champaign, Department of Mechanical Science and Engineering, 1206 West Green Street, Urbana, IL 61801 (United States); Novitskaya, Ekaterina, E-mail: eevdokim@ucsd.edu [University of California, San Diego, Department of Mechanical and Aerospace Engineering, Materials Science and Engineering Program, 9500 Gilman Dr., La Jolla, CA 92093 (United States); Li, Jun; Jasiuk, Iwona [University of Illinois at Urbana-Champaign, Department of Mechanical Science and Engineering, 1206 West Green Street, Urbana, IL 61801 (United States); McKittrick, Joanna [University of California, San Diego, Department of Mechanical and Aerospace Engineering, Materials Science and Engineering Program, 9500 Gilman Dr., La Jolla, CA 92093 (United States)

    2015-09-01

    The elastic moduli of trabecular bone were modeled using an analytical multiscale approach. Trabecular bone was represented as a porous nanocomposite material with a hierarchical structure spanning from the collagen–mineral level to the trabecular architecture level. In parallel, compression testing was done on bovine femoral trabecular bone samples in two anatomical directions, parallel to the femoral neck axis and perpendicular to it, and the measured elastic moduli were compared with the corresponding theoretical results. To gain insights on the interaction of collagen and minerals at the nanoscale, bone samples were deproteinized or demineralized. After such processing, the treated samples remained as self-standing structures and were tested in compression. Micro-computed tomography was used to characterize the hierarchical structure of these three bone types and to quantify the amount of bone porosity. The obtained experimental data served as inputs to the multiscale model and guided us to represent bone as an interpenetrating composite material. Good agreement was found between the theory and experiments for the elastic moduli of the untreated, deproteinized, and demineralized trabecular bone. - Highlights: • A multiscale model was used to predict the elastic moduli of trabecular bone. • Samples included demineralized, deproteinized and untreated bone. • The model portrays bone as a porous, interpenetrating two phase composite. • The experimental elastic moduli for trabecular bone fell between theoretical bounds.

  11. Experimentally-based multiscale model of the elastic moduli of bovine trabecular bone and its constituents

    International Nuclear Information System (INIS)

    Hamed, Elham; Novitskaya, Ekaterina; Li, Jun; Jasiuk, Iwona; McKittrick, Joanna

    2015-01-01

    The elastic moduli of trabecular bone were modeled using an analytical multiscale approach. Trabecular bone was represented as a porous nanocomposite material with a hierarchical structure spanning from the collagen–mineral level to the trabecular architecture level. In parallel, compression testing was done on bovine femoral trabecular bone samples in two anatomical directions, parallel to the femoral neck axis and perpendicular to it, and the measured elastic moduli were compared with the corresponding theoretical results. To gain insights on the interaction of collagen and minerals at the nanoscale, bone samples were deproteinized or demineralized. After such processing, the treated samples remained as self-standing structures and were tested in compression. Micro-computed tomography was used to characterize the hierarchical structure of these three bone types and to quantify the amount of bone porosity. The obtained experimental data served as inputs to the multiscale model and guided us to represent bone as an interpenetrating composite material. Good agreement was found between the theory and experiments for the elastic moduli of the untreated, deproteinized, and demineralized trabecular bone. - Highlights: • A multiscale model was used to predict the elastic moduli of trabecular bone. • Samples included demineralized, deproteinized and untreated bone. • The model portrays bone as a porous, interpenetrating two phase composite. • The experimental elastic moduli for trabecular bone fell between theoretical bounds

  12. Multiscale approach to equilibrating model polymer melts

    DEFF Research Database (Denmark)

    Svaneborg, Carsten; Ali Karimi-Varzaneh, Hossein; Hojdis, Nils

    2016-01-01

    We present an effective and simple multiscale method for equilibrating Kremer Grest model polymer melts of varying stiffness. In our approach, we progressively equilibrate the melt structure above the tube scale, inside the tube and finally at the monomeric scale. We make use of models designed...

  13. SOMAR-LES: A framework for multi-scale modeling of turbulent stratified oceanic flows

    Science.gov (United States)

    Chalamalla, Vamsi K.; Santilli, Edward; Scotti, Alberto; Jalali, Masoud; Sarkar, Sutanu

    2017-12-01

    A new multi-scale modeling technique, SOMAR-LES, is presented in this paper. Localized grid refinement gives SOMAR (the Stratified Ocean Model with Adaptive Resolution) access to small scales of the flow which are normally inaccessible to general circulation models (GCMs). SOMAR-LES drives a LES (Large Eddy Simulation) on SOMAR's finest grids, forced with large scale forcing from the coarser grids. Three-dimensional simulations of internal tide generation, propagation and scattering are performed to demonstrate this multi-scale modeling technique. In the case of internal tide generation at a two-dimensional bathymetry, SOMAR-LES is able to balance the baroclinic energy budget and accurately model turbulence losses at only 10% of the computational cost required by a non-adaptive solver running at SOMAR-LES's fine grid resolution. This relative cost is significantly reduced in situations with intermittent turbulence or where the location of the turbulence is not known a priori because SOMAR-LES does not require persistent, global, high resolution. To illustrate this point, we consider a three-dimensional bathymetry with grids adaptively refined along the tidally generated internal waves to capture remote mixing in regions of wave focusing. The computational cost in this case is found to be nearly 25 times smaller than that of a non-adaptive solver at comparable resolution. In the final test case, we consider the scattering of a mode-1 internal wave at an isolated two-dimensional and three-dimensional topography, and we compare the results with Legg (2014) numerical experiments. We find good agreement with theoretical estimates. SOMAR-LES is less dissipative than the closure scheme employed by Legg (2014) near the bathymetry. Depending on the flow configuration and resolution employed, a reduction of more than an order of magnitude in computational costs is expected, relative to traditional existing solvers.

  14. Integrating intracellular dynamics using CompuCell3D and Bionetsolver: applications to multiscale modelling of cancer cell growth and invasion.

    Directory of Open Access Journals (Sweden)

    Vivi Andasari

    Full Text Available In this paper we present a multiscale, individual-based simulation environment that integrates CompuCell3D for lattice-based modelling on the cellular level and Bionetsolver for intracellular modelling. CompuCell3D or CC3D provides an implementation of the lattice-based Cellular Potts Model or CPM (also known as the Glazier-Graner-Hogeweg or GGH model and a Monte Carlo method based on the metropolis algorithm for system evolution. The integration of CC3D for cellular systems with Bionetsolver for subcellular systems enables us to develop a multiscale mathematical model and to study the evolution of cell behaviour due to the dynamics inside of the cells, capturing aspects of cell behaviour and interaction that is not possible using continuum approaches. We then apply this multiscale modelling technique to a model of cancer growth and invasion, based on a previously published model of Ramis-Conde et al. (2008 where individual cell behaviour is driven by a molecular network describing the dynamics of E-cadherin and β-catenin. In this model, which we refer to as the centre-based model, an alternative individual-based modelling technique was used, namely, a lattice-free approach. In many respects, the GGH or CPM methodology and the approach of the centre-based model have the same overall goal, that is to mimic behaviours and interactions of biological cells. Although the mathematical foundations and computational implementations of the two approaches are very different, the results of the presented simulations are compatible with each other, suggesting that by using individual-based approaches we can formulate a natural way of describing complex multi-cell, multiscale models. The ability to easily reproduce results of one modelling approach using an alternative approach is also essential from a model cross-validation standpoint and also helps to identify any modelling artefacts specific to a given computational approach.

  15. Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®

    Energy Technology Data Exchange (ETDEWEB)

    Stander, Nielen; Basudhar, Anirban; Basu, Ushnish; Gandikota, Imtiaz; Savic, Vesna; Sun, Xin; Choi, Kyoo Sil; Hu, Xiaohua; Pourboghrat, F.; Park, Taejoon; Mapar, Aboozar; Kumar, Shavan; Ghassemi-Armaki, Hassan; Abu-Farha, Fadi

    2015-09-14

    Ever-tightening regulations on fuel economy, and the likely future regulation of carbon emissions, demand persistent innovation in vehicle design to reduce vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials, by adding material diversity and composite materials, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing plate thickness while retaining sufficient strength and ductility required for durability and safety. A project to develop computational material models for advanced high strength steel is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the US Department of Energy. Under this program, new Third Generation Advanced High Strength Steel (i.e., 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. The objectives of the project are to integrate atomistic, microstructural, forming and performance models to create an integrated computational materials engineering (ICME) toolkit for 3GAHSS. The mechanical properties of Advanced High Strength Steels (AHSS) are controlled by many factors, including phase composition and distribution in the overall microstructure, volume fraction, size and morphology of phase constituents as well as stability of the metastable retained austenite phase. The complex phase transformation and deformation mechanisms in these steels make the well-established traditional techniques obsolete, and a multi-scale microstructure-based modeling approach following the ICME [0]strategy was therefore chosen in this project. Multi-scale modeling as a major area of research and development is an outgrowth of the Comprehensive

  16. Multi-scale damage modelling in a ceramic matrix composite using a finite-element microstructure meshfree methodology

    Science.gov (United States)

    2016-01-01

    The problem of multi-scale modelling of damage development in a SiC ceramic fibre-reinforced SiC matrix ceramic composite tube is addressed, with the objective of demonstrating the ability of the finite-element microstructure meshfree (FEMME) model to introduce important aspects of the microstructure into a larger scale model of the component. These are particularly the location, orientation and geometry of significant porosity and the load-carrying capability and quasi-brittle failure behaviour of the fibre tows. The FEMME model uses finite-element and cellular automata layers, connected by a meshfree layer, to efficiently couple the damage in the microstructure with the strain field at the component level. Comparison is made with experimental observations of damage development in an axially loaded composite tube, studied by X-ray computed tomography and digital volume correlation. Recommendations are made for further development of the model to achieve greater fidelity to the microstructure. This article is part of the themed issue ‘Multiscale modelling of the structural integrity of composite materials’. PMID:27242308

  17. Information Management Workflow and Tools Enabling Multiscale Modeling Within ICME Paradigm

    Science.gov (United States)

    Arnold, Steven M.; Bednarcyk, Brett A.; Austin, Nic; Terentjev, Igor; Cebon, Dave; Marsden, Will

    2016-01-01

    With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Fortunately, material information management systems and physics-based multiscale modeling methods have kept pace with the growing user demands. Herein, recent efforts to establish workflow for and demonstrate a unique set of web application tools for linking NASA GRC's Integrated Computational Materials Engineering (ICME) Granta MI database schema and NASA GRC's Integrated multiscale Micromechanics Analysis Code (ImMAC) software toolset are presented. The goal is to enable seamless coupling between both test data and simulation data, which is captured and tracked automatically within Granta MI®, with full model pedigree information. These tools, and this type of linkage, are foundational to realizing the full potential of ICME, in which materials processing, microstructure, properties, and performance are coupled to enable application-driven design and optimization of materials and structures.

  18. A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

    Science.gov (United States)

    Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

    2014-01-01

    Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569

  19. Hybrid continuum–molecular modelling of multiscale internal gas flows

    International Nuclear Information System (INIS)

    Patronis, Alexander; Lockerby, Duncan A.; Borg, Matthew K.; Reese, Jason M.

    2013-01-01

    We develop and apply an efficient multiscale method for simulating a large class of low-speed internal rarefied gas flows. The method is an extension of the hybrid atomistic–continuum approach proposed by Borg et al. (2013) [28] for the simulation of micro/nano flows of high-aspect ratio. The major new extensions are: (1) incorporation of fluid compressibility; (2) implementation using the direct simulation Monte Carlo (DSMC) method for dilute rarefied gas flows, and (3) application to a broader range of geometries, including periodic, non-periodic, pressure-driven, gravity-driven and shear-driven internal flows. The multiscale method is applied to micro-scale gas flows through a periodic converging–diverging channel (driven by an external acceleration) and a non-periodic channel with a bend (driven by a pressure difference), as well as the flow between two eccentric cylinders (with the inner rotating relative to the outer). In all these cases there exists a wide variation of Knudsen number within the geometries, as well as substantial compressibility despite the Mach number being very low. For validation purposes, our multiscale simulation results are compared to those obtained from full-scale DSMC simulations: very close agreement is obtained in all cases for all flow variables considered. Our multiscale simulation is an order of magnitude more computationally efficient than the full-scale DSMC for the first and second test cases, and two orders of magnitude more efficient for the third case

  20. Multiscale numerical modeling of Ce3+-inhibitor release from novel corrosion protection coatings

    International Nuclear Information System (INIS)

    Trenado, Carlos; Wittmar, Matthias; Veith, Michael; Strauss, Daniel J; Rosero-Navarro, Nataly C; Aparicio, Mario; Durán, Alicia; Castro, Yolanda

    2011-01-01

    A novel hybrid sol–gel coating has recently been introduced as an alternative to high toxic chromate-based corrosion protection systems. In this paper, we propose a multiscale computational model to estimate the amount and time scale of inhibitor release of the active corrosion protection coating. Moreover, we study the release rate under the influence of parameters such as porosity and viscosity, which have recently been implicated in the stability of the coating. Numerical simulations obtained with the model predicted experimental release tests and recent findings on the compromise between inhibitor concentration and the stability of the coating

  1. Multiscale modeling of materials. Materials Research Society symposium proceedings: Volume 538

    International Nuclear Information System (INIS)

    Bulatov, V.V.; Diaz de la Rubia, T.; Phillips, R.; Kaxiras, E.; Ghoniem, N.

    1999-01-01

    The symposium, Multiscale Modeling of Materials, was held at the 1998 MRS Fall Meeting in Boston, Massachusetts, November 30 to December 3. Though multiple scale models are not new the topic has recently taken on a new sense of urgency. This is in large part due to the recognition that brute force computational approaches often fall short of allowing for direct simulation of both the characteristic structures and temporal processes found in real materials. As a result, a number of hybrid approaches are now finding favor in which ideas borrowed from distinct disciplines or modeling paradigms are unified to produce more powerful techniques. Topics included are modeling dislocation properties and behavior, defect dynamics and microstructural evolution, crystal defects and interfaces, novel methods for materials modeling, and non-crystalline and nanocrystalline materials. Eighty papers have been processed separately for inclusion on the data base

  2. Multiscale agent-based cancer modeling.

    Science.gov (United States)

    Zhang, Le; Wang, Zhihui; Sagotsky, Jonathan A; Deisboeck, Thomas S

    2009-04-01

    Agent-based modeling (ABM) is an in silico technique that is being used in a variety of research areas such as in social sciences, economics and increasingly in biomedicine as an interdisciplinary tool to study the dynamics of complex systems. Here, we describe its applicability to integrative tumor biology research by introducing a multi-scale tumor modeling platform that understands brain cancer as a complex dynamic biosystem. We summarize significant findings of this work, and discuss both challenges and future directions for ABM in the field of cancer research.

  3. Multi-scale Modeling of Plasticity in Tantalum.

    Energy Technology Data Exchange (ETDEWEB)

    Lim, Hojun [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Battaile, Corbett Chandler. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Carroll, Jay [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Buchheit, Thomas E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Boyce, Brad [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Weinberger, Christopher [Drexel Univ., Philadelphia, PA (United States)

    2015-12-01

    In this report, we present a multi-scale computational model to simulate plastic deformation of tantalum and validating experiments. In atomistic/ dislocation level, dislocation kink- pair theory is used to formulate temperature and strain rate dependent constitutive equations. The kink-pair theory is calibrated to available data from single crystal experiments to produce accurate and convenient constitutive laws. The model is then implemented into a BCC crystal plasticity finite element method (CP-FEM) model to predict temperature and strain rate dependent yield stresses of single and polycrystalline tantalum and compared with existing experimental data from the literature. Furthermore, classical continuum constitutive models describing temperature and strain rate dependent flow behaviors are fit to the yield stresses obtained from the CP-FEM polycrystal predictions. The model is then used to conduct hydro- dynamic simulations of Taylor cylinder impact test and compared with experiments. In order to validate the proposed tantalum CP-FEM model with experiments, we introduce a method for quantitative comparison of CP-FEM models with various experimental techniques. To mitigate the effects of unknown subsurface microstructure, tantalum tensile specimens with a pseudo-two-dimensional grain structure and grain sizes on the order of millimeters are used. A technique combining an electron back scatter diffraction (EBSD) and high resolution digital image correlation (HR-DIC) is used to measure the texture and sub-grain strain fields upon uniaxial tensile loading at various applied strains. Deformed specimens are also analyzed with optical profilometry measurements to obtain out-of- plane strain fields. These high resolution measurements are directly compared with large-scale CP-FEM predictions. This computational method directly links fundamental dislocation physics to plastic deformations in the grain-scale and to the engineering-scale applications. Furthermore, direct

  4. Multiscale simulation of protein hydration using the SWINGER dynamical clustering algorithm

    NARCIS (Netherlands)

    Zavadlav, Julija; Marrink, Siewert J; Praprotnik, Matej

    To perform computationally efficient concurrent multiscale simulations of biological macromolecules in solution, where the all-atom (AT) models are coupled to supramolecular coarse-grained (SCG) solvent models, previous studies resorted to a modified AT water models, such as the bundled-SPC models,

  5. Model-to-model interface for multiscale materials modeling

    Energy Technology Data Exchange (ETDEWEB)

    Antonelli, Perry Edward [Iowa State Univ., Ames, IA (United States)

    2017-12-17

    A low-level model-to-model interface is presented that will enable independent models to be linked into an integrated system of models. The interface is based on a standard set of functions that contain appropriate export and import schemas that enable models to be linked with no changes to the models themselves. These ideas are presented in the context of a specific multiscale material problem that couples atomistic-based molecular dynamics calculations to continuum calculations of fluid ow. These simulations will be used to examine the influence of interactions of the fluid with an adjacent solid on the fluid ow. The interface will also be examined by adding it to an already existing modeling code, Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and comparing it with our own molecular dynamics code.

  6. A stochastic multiscale framework for modeling flow through random heterogeneous porous media

    International Nuclear Information System (INIS)

    Ganapathysubramanian, B.; Zabaras, N.

    2009-01-01

    Flow through porous media is ubiquitous, occurring from large geological scales down to the microscopic scales. Several critical engineering phenomena like contaminant spread, nuclear waste disposal and oil recovery rely on accurate analysis and prediction of these multiscale phenomena. Such analysis is complicated by inherent uncertainties as well as the limited information available to characterize the system. Any realistic modeling of these transport phenomena has to resolve two key issues: (i) the multi-length scale variations in permeability that these systems exhibit, and (ii) the inherently limited information available to quantify these property variations that necessitates posing these phenomena as stochastic processes. A stochastic variational multiscale formulation is developed to incorporate uncertain multiscale features. A stochastic analogue to a mixed multiscale finite element framework is used to formulate the physical stochastic multiscale process. Recent developments in linear and non-linear model reduction techniques are used to convert the limited information available about the permeability variation into a viable stochastic input model. An adaptive sparse grid collocation strategy is used to efficiently solve the resulting stochastic partial differential equations (SPDEs). The framework is applied to analyze flow through random heterogeneous media when only limited statistics about the permeability variation are given

  7. Multi-scale computation methods: Their applications in lithium-ion battery research and development

    Science.gov (United States)

    Siqi, Shi; Jian, Gao; Yue, Liu; Yan, Zhao; Qu, Wu; Wangwei, Ju; Chuying, Ouyang; Ruijuan, Xiao

    2016-01-01

    Based upon advances in theoretical algorithms, modeling and simulations, and computer technologies, the rational design of materials, cells, devices, and packs in the field of lithium-ion batteries is being realized incrementally and will at some point trigger a paradigm revolution by combining calculations and experiments linked by a big shared database, enabling accelerated development of the whole industrial chain. Theory and multi-scale modeling and simulation, as supplements to experimental efforts, can help greatly to close some of the current experimental and technological gaps, as well as predict path-independent properties and help to fundamentally understand path-independent performance in multiple spatial and temporal scales. Project supported by the National Natural Science Foundation of China (Grant Nos. 51372228 and 11234013), the National High Technology Research and Development Program of China (Grant No. 2015AA034201), and Shanghai Pujiang Program, China (Grant No. 14PJ1403900).

  8. Conformal-Based Surface Morphing and Multi-Scale Representation

    Directory of Open Access Journals (Sweden)

    Ka Chun Lam

    2014-05-01

    Full Text Available This paper presents two algorithms, based on conformal geometry, for the multi-scale representations of geometric shapes and surface morphing. A multi-scale surface representation aims to describe a 3D shape at different levels of geometric detail, which allows analyzing or editing surfaces at the global or local scales effectively. Surface morphing refers to the process of interpolating between two geometric shapes, which has been widely applied to estimate or analyze deformations in computer graphics, computer vision and medical imaging. In this work, we propose two geometric models for surface morphing and multi-scale representation for 3D surfaces. The basic idea is to represent a 3D surface by its mean curvature function, H, and conformal factor function λ, which uniquely determine the geometry of the surface according to Riemann surface theory. Once we have the (λ, H parameterization of the surface, post-processing of the surface can be done directly on the conformal parameter domain. In particular, the problem of multi-scale representations of shapes can be reduced to the signal filtering on the λ and H parameters. On the other hand, the surface morphing problem can be transformed to an interpolation process of two sets of (λ, H parameters. We test the proposed algorithms on 3D human face data and MRI-derived brain surfaces. Experimental results show that our proposed methods can effectively obtain multi-scale surface representations and give natural surface morphing results.

  9. Multiscale Modeling using Molecular Dynamics and Dual Domain Material Point Method

    Energy Technology Data Exchange (ETDEWEB)

    Dhakal, Tilak Raj [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Theoretical Division. Fluid Dynamics and Solid Mechanics Group, T-3; Rice Univ., Houston, TX (United States)

    2016-07-07

    For problems involving large material deformation rate, the material deformation time scale can be shorter than the material takes to reach a thermodynamical equilibrium. For such problems, it is difficult to obtain a constitutive relation. History dependency become important because of thermodynamic non-equilibrium. Our goal is to build a multi-scale numerical method which can bypass the need for a constitutive relation. In conclusion, multi-scale simulation method is developed based on the dual domain material point (DDMP). Molecular dynamics (MD) simulation is performed to calculate stress. Since the communication among material points is not necessary, the computation can be done embarrassingly parallel in CPU-GPU platform.

  10. A computational systems biology software platform for multiscale modeling and simulation: Integrating whole-body physiology, disease biology, and molecular reaction networks

    Directory of Open Access Journals (Sweden)

    Thomas eEissing

    2011-02-01

    Full Text Available Today, in silico studies and trial simulations already complement experimental approaches in pharmaceutical R&D and have become indispensable tools for decision making and communication with regulatory agencies. While biology is multi-scale by nature, project work and software tools usually focus on isolated aspects of drug action, such as pharmacokinetics at the organism scale or pharmacodynamic interaction on the molecular level. We present a modeling and simulation software platform consisting of PK-Sim® and MoBi® capable of building and simulating models that integrate across biological scales. A prototypical multiscale model for the progression of a pancreatic tumor and its response to pharmacotherapy is constructed and virtual patients are treated with a prodrug activated by hepatic metabolization. Tumor growth is driven by signal transduction leading to cell cycle transition and proliferation. Free tumor concentrations of the active metabolite inhibit Raf kinase in the signaling cascade and thereby cell cycle progression. In a virtual clinical study, the individual therapeutic outcome of the chemotherapeutic intervention is simulated for a large population with heterogeneous genomic background. Thereby, the platform allows efficient model building and integration of biological knowledge and prior data from all biological scales. Experimental in vitro model systems can be linked with observations in animal experiments and clinical trials. The interplay between patients, diseases, and drugs and topics with high clinical relevance such as the role of pharmacogenomics, drug-drug or drug-metabolite interactions can be addressed using this mechanistic, insight driven multiscale modeling approach.

  11. Integration of multiscale dendritic spine structure and function data into systems biology models

    Directory of Open Access Journals (Sweden)

    James J Mancuso

    2014-11-01

    Full Text Available Comprising 1011 neurons with 1014 synaptic connections the human brain is the ultimate systems biology puzzle. An increasing body of evidence highlights the observation that changes in brain function, both normal and pathological, consistently correlate with dynamic changes in neuronal anatomy. Anatomical changes occur on a full range of scales from the trafficking of individual proteins, to alterations in synaptic morphology both individually and on a systems level, to reductions in long distance connectivity and brain volume. The major sites of contact for synapsing neurons are dendritic spines, which provide an excellent metric for the number and strength of signaling connections between elements of functional neuronal circuits. A comprehensive model of anatomical changes and their functional consequences would be a holy grail for the field of systems neuroscience but its realization appears far on the horizon. Various imaging technologies have advanced to allow for multi-scale visualization of brain plasticity and pathology, but computational analysis of the massive big data sets involved forms the bottleneck toward the creation of multiscale models of brain structure and function. While a full accounting of techniques and progress toward a comprehensive model of brain anatomy and function is beyond the scope of this or any other single paper, this review serves to highlight the opportunities for analysis of neuronal spine anatomy and function provided by new imaging technologies and the high-throughput application of older technologies while surveying the strengths and weaknesses of currently available computational analytical tools and room for future improvement.

  12. Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media

    KAUST Repository

    Gao, Kai

    2015-04-14

    It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both boundaries and the interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale medium property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.

  13. Towards an integrated multiscale simulation of turbulent clouds on PetaScale computers

    International Nuclear Information System (INIS)

    Wang Lianping; Ayala, Orlando; Parishani, Hossein; Gao, Guang R; Kambhamettu, Chandra; Li Xiaoming; Rossi, Louis; Orozco, Daniel; Torres, Claudio; Grabowski, Wojciech W; Wyszogrodzki, Andrzej A; Piotrowski, Zbigniew

    2011-01-01

    The development of precipitating warm clouds is affected by several effects of small-scale air turbulence including enhancement of droplet-droplet collision rate by turbulence, entrainment and mixing at the cloud edges, and coupling of mechanical and thermal energies at various scales. Large-scale computation is a viable research tool for quantifying these multiscale processes. Specifically, top-down large-eddy simulations (LES) of shallow convective clouds typically resolve scales of turbulent energy-containing eddies while the effects of turbulent cascade toward viscous dissipation are parameterized. Bottom-up hybrid direct numerical simulations (HDNS) of cloud microphysical processes resolve fully the dissipation-range flow scales but only partially the inertial subrange scales. it is desirable to systematically decrease the grid length in LES and increase the domain size in HDNS so that they can be better integrated to address the full range of scales and their coupling. In this paper, we discuss computational issues and physical modeling questions in expanding the ranges of scales realizable in LES and HDNS, and in bridging LES and HDNS. We review our on-going efforts in transforming our simulation codes towards PetaScale computing, in improving physical representations in LES and HDNS, and in developing better methods to analyze and interpret the simulation results.

  14. A rate-dependent multi-scale crack model for concrete

    NARCIS (Netherlands)

    Karamnejad, A.; Nguyen, V.P.; Sluys, L.J.

    2013-01-01

    A multi-scale numerical approach for modeling cracking in heterogeneous quasi-brittle materials under dynamic loading is presented. In the model, a discontinuous crack model is used at macro-scale to simulate fracture and a gradient-enhanced damage model has been used at meso-scale to simulate

  15. Residual-driven online generalized multiscale finite element methods

    KAUST Repository

    Chung, Eric T.

    2015-09-08

    The construction of local reduced-order models via multiscale basis functions has been an area of active research. In this paper, we propose online multiscale basis functions which are constructed using the offline space and the current residual. Online multiscale basis functions are constructed adaptively in some selected regions based on our error indicators. We derive an error estimator which shows that one needs to have an offline space with certain properties to guarantee that additional online multiscale basis function will decrease the error. This error decrease is independent of physical parameters, such as the contrast and multiple scales in the problem. The offline spaces are constructed using Generalized Multiscale Finite Element Methods (GMsFEM). We show that if one chooses a sufficient number of offline basis functions, one can guarantee that additional online multiscale basis functions will reduce the error independent of contrast. We note that the construction of online basis functions is motivated by the fact that the offline space construction does not take into account distant effects. Using the residual information, we can incorporate the distant information provided the offline approximation satisfies certain properties. In the paper, theoretical and numerical results are presented. Our numerical results show that if the offline space is sufficiently large (in terms of the dimension) such that the coarse space contains all multiscale spectral basis functions that correspond to small eigenvalues, then the error reduction by adding online multiscale basis function is independent of the contrast. We discuss various ways computing online multiscale basis functions which include a use of small dimensional offline spaces.

  16. Model reduction of multiscale chemical langevin equations: a numerical case study.

    Science.gov (United States)

    Sotiropoulos, Vassilios; Contou-Carrere, Marie-Nathalie; Daoutidis, Prodromos; Kaznessis, Yiannis N

    2009-01-01

    Two very important characteristics of biological reaction networks need to be considered carefully when modeling these systems. First, models must account for the inherent probabilistic nature of systems far from the thermodynamic limit. Often, biological systems cannot be modeled with traditional continuous-deterministic models. Second, models must take into consideration the disparate spectrum of time scales observed in biological phenomena, such as slow transcription events and fast dimerization reactions. In the last decade, significant efforts have been expended on the development of stochastic chemical kinetics models to capture the dynamics of biomolecular systems, and on the development of robust multiscale algorithms, able to handle stiffness. In this paper, the focus is on the dynamics of reaction sets governed by stiff chemical Langevin equations, i.e., stiff stochastic differential equations. These are particularly challenging systems to model, requiring prohibitively small integration step sizes. We describe and illustrate the application of a semianalytical reduction framework for chemical Langevin equations that results in significant gains in computational cost.

  17. Multiscale modeling of porous ceramics using movable cellular automaton method

    Science.gov (United States)

    Smolin, Alexey Yu.; Smolin, Igor Yu.; Smolina, Irina Yu.

    2017-10-01

    The paper presents a multiscale model for porous ceramics based on movable cellular automaton method, which is a particle method in novel computational mechanics of solid. The initial scale of the proposed approach corresponds to the characteristic size of the smallest pores in the ceramics. At this scale, we model uniaxial compression of several representative samples with an explicit account of pores of the same size but with the unique position in space. As a result, we get the average values of Young's modulus and strength, as well as the parameters of the Weibull distribution of these properties at the current scale level. These data allow us to describe the material behavior at the next scale level were only the larger pores are considered explicitly, while the influence of small pores is included via effective properties determined earliar. If the pore size distribution function of the material has N maxima we need to perform computations for N-1 levels in order to get the properties step by step from the lowest scale up to the macroscale. The proposed approach was applied to modeling zirconia ceramics with bimodal pore size distribution. The obtained results show correct behavior of the model sample at the macroscale.

  18. Application of computer-aided multi-scale modelling framework – Aerosol case study

    DEFF Research Database (Denmark)

    Heitzig, Martina; Sin, Gürkan; Glarborg, Peter

    2011-01-01

    Model-based computer aided product-process engineering has attained increased importance in a number of industries, including pharmaceuticals, petrochemicals, fine chemicals, polymers, biotechnology, food, energy and water. This trend is set to continue due to the substantial benefits computer-aided...... methods provide. The key prerequisite of computer-aided product-process engineering is however the availability of models of different types, forms and application modes. The development of the models required for the systems under investigation tends to be a challenging and time-consuming task involving...... numerous steps, expert skills and different modelling tools. This motivates the development of a computer-aided modelling framework that supports the user during model development, documentation, analysis, identification, application and re-use with the goal to increase the efficiency of the modelling...

  19. Numerical Simulations of a Multiscale Model of Stratified Langmuir Circulation

    Science.gov (United States)

    Malecha, Ziemowit; Chini, Gregory; Julien, Keith

    2012-11-01

    Langmuir circulation (LC), a prominent form of wind and surface-wave driven shear turbulence in the ocean surface boundary layer (BL), is commonly modeled using the Craik-Leibovich (CL) equations, a phase-averaged variant of the Navier-Stokes (NS) equations. Although surface-wave filtering renders the CL equations more amenable to simulation than are the instantaneous NS equations, simulations in wide domains, hundreds of times the BL depth, currently earn the ``grand challenge'' designation. To facilitate simulations of LC in such spatially-extended domains, we have derived multiscale CL equations by exploiting the scale separation between submesoscale and BL flows in the upper ocean. The numerical algorithm for simulating this multiscale model resembles super-parameterization schemes used in meteorology, but retains a firm mathematical basis. We have validated our algorithm and here use it to perform multiscale simulations of the interaction between LC and upper ocean density stratification. ZMM, GPC, KJ gratefully acknowledge funding from NSF CMG Award 0934827.

  20. Multi-scale modeling for sustainable chemical production.

    Science.gov (United States)

    Zhuang, Kai; Bakshi, Bhavik R; Herrgård, Markus J

    2013-09-01

    With recent advances in metabolic engineering, it is now technically possible to produce a wide portfolio of existing petrochemical products from biomass feedstock. In recent years, a number of modeling approaches have been developed to support the engineering and decision-making processes associated with the development and implementation of a sustainable biochemical industry. The temporal and spatial scales of modeling approaches for sustainable chemical production vary greatly, ranging from metabolic models that aid the design of fermentative microbial strains to material and monetary flow models that explore the ecological impacts of all economic activities. Research efforts that attempt to connect the models at different scales have been limited. Here, we review a number of existing modeling approaches and their applications at the scales of metabolism, bioreactor, overall process, chemical industry, economy, and ecosystem. In addition, we propose a multi-scale approach for integrating the existing models into a cohesive framework. The major benefit of this proposed framework is that the design and decision-making at each scale can be informed, guided, and constrained by simulations and predictions at every other scale. In addition, the development of this multi-scale framework would promote cohesive collaborations across multiple traditionally disconnected modeling disciplines to achieve sustainable chemical production. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Multiscale Computational Analysis of Nitrogen and Oxygen Gas-Phase Thermochemistry in Hypersonic Flows

    Science.gov (United States)

    Bender, Jason D.

    Understanding hypersonic aerodynamics is important for the design of next-generation aerospace vehicles for space exploration, national security, and other applications. Ground-level experimental studies of hypersonic flows are difficult and expensive; thus, computational science plays a crucial role in this field. Computational fluid dynamics (CFD) simulations of extremely high-speed flows require models of chemical and thermal nonequilibrium processes, such as dissociation of diatomic molecules and vibrational energy relaxation. Current models are outdated and inadequate for advanced applications. We describe a multiscale computational study of gas-phase thermochemical processes in hypersonic flows, starting at the atomic scale and building systematically up to the continuum scale. The project was part of a larger effort centered on collaborations between aerospace scientists and computational chemists. We discuss the construction of potential energy surfaces for the N4, N2O2, and O4 systems, focusing especially on the multi-dimensional fitting problem. A new local fitting method named L-IMLS-G2 is presented and compared with a global fitting method. Then, we describe the theory of the quasiclassical trajectory (QCT) approach for modeling molecular collisions. We explain how we implemented the approach in a new parallel code for high-performance computing platforms. Results from billions of QCT simulations of high-energy N2 + N2, N2 + N, and N2 + O2 collisions are reported and analyzed. Reaction rate constants are calculated and sets of reactive trajectories are characterized at both thermal equilibrium and nonequilibrium conditions. The data shed light on fundamental mechanisms of dissociation and exchange reactions -- and their coupling to internal energy transfer processes -- in thermal environments typical of hypersonic flows. We discuss how the outcomes of this investigation and other related studies lay a rigorous foundation for new macroscopic models for

  2. Revisiting of Multiscale Static Analysis of Notched Laminates Using the Generalized Method of Cells

    Science.gov (United States)

    Naghipour Ghezeljeh, Paria; Arnold, Steven M.; Pineda, Evan J.

    2016-01-01

    Composite material systems generally exhibit a range of behavior on different length scales (from constituent level to macro); therefore, a multiscale framework is beneficial for the design and engineering of these material systems. The complex nature of the observed composite failure during experiments suggests the need for a three-dimensional (3D) multiscale model to attain a reliable prediction. However, the size of a multiscale three-dimensional finite element model can become prohibitively large and computationally costly. Two-dimensional (2D) models are preferred due to computational efficiency, especially if many different configurations have to be analyzed for an in-depth damage tolerance and durability design study. In this study, various 2D and 3D multiscale analyses will be employed to conduct a detailed investigation into the tensile failure of a given multidirectional, notched carbon fiber reinforced polymer laminate. Threedimensional finite element analysis is typically considered more accurate than a 2D finite element model, as compared with experiments. Nevertheless, in the absence of adequate mesh refinement, large differences may be observed between a 2D and 3D analysis, especially for a shear-dominated layup. This observed difference has not been widely addressed in previous literature and is the main focus of this paper.

  3. Multi-scale modeling strategies in materials science—The ...

    Indian Academy of Sciences (India)

    Unknown

    Multi-scale models; quasicontinuum method; finite elements. 1. Introduction ... boundary with external stresses, and the interaction of a lattice dislocation with a grain ..... mum value of se over the elements that touch node α. The acceleration of ...

  4. Multiscale Modeling of Wear Degradation in Cylinder Liners

    KAUST Repository

    Moraes, Alvaro

    2014-03-20

    Every mechanical system is naturally subjected to some kind of wear process that, at some point, will cause failure in the system if no monitoring or treatment process is applied. Since failures often lead to high economical costs, it is essential both to predict and to avoid them. To achieve this, a monitoring system of the wear level should be implemented to decrease the risk of failure. In this work, we take a first step into the development of a multiscale indirect inference methodology for state-dependent Markovian pure jump processes. This allows us to model the evolution of the wear level and to identify when the system reaches some critical level that triggers a maintenance response. Since the likelihood function of a discretely observed pure jump process does not have an expression that is simple enough for standard nonsampling optimization methods, we approximate this likelihood by expressions from upscaled models of the data. We use the Master Equation (ME) to assess the goodness-of-fit and to compute the distribution of the hitting time to the critical level.

  5. Modeling and Simulation of High Dimensional Stochastic Multiscale PDE Systems at the Exascale

    Energy Technology Data Exchange (ETDEWEB)

    Kevrekidis, Ioannis [Princeton Univ., NJ (United States)

    2017-03-22

    The thrust of the proposal was to exploit modern data-mining tools in a way that will create a systematic, computer-assisted approach to the representation of random media -- and also to the representation of the solutions of an array of important physicochemical processes that take place in/on such media. A parsimonious representation/parametrization of the random media links directly (via uncertainty quantification tools) to good sampling of the distribution of random media realizations. It also links directly to modern multiscale computational algorithms (like the equation-free approach that has been developed in our group) and plays a crucial role in accelerating the scientific computation of solutions of nonlinear PDE models (deterministic or stochastic) in such media – both solutions in particular realizations of the random media, and estimation of the statistics of the solutions over multiple realizations (e.g. expectations).

  6. Multi-scale Modelling of Segmentation

    DEFF Research Database (Denmark)

    Hartmann, Martin; Lartillot, Olivier; Toiviainen, Petri

    2016-01-01

    pieces. In a second experiment on non-real-time segmentation, musicians indicated boundaries and their strength for six examples. Kernel density estimation was used to develop multi-scale segmentation models. Contrary to previous research, no relationship was found between boundary strength and boundary......While listening to music, people often unwittingly break down musical pieces into constituent chunks such as verses and choruses. Music segmentation studies have suggested that some consensus regarding boundary perception exists, despite individual differences. However, neither the effects...

  7. A Liver-centric Multiscale Modeling Framework for Xenobiotics

    Science.gov (United States)

    We describe a multi-scale framework for modeling acetaminophen-induced liver toxicity. Acetaminophen is a widely used analgesic. Overdose of acetaminophen can result in liver injury via its biotransformation into toxic product, which further induce massive necrosis. Our study foc...

  8. Multi-Scale Computational Modeling of Ni-Base Superalloy Brazed Joints for Gas Turbine Applications

    Science.gov (United States)

    Riggs, Bryan

    Brazed joints are commonly used in the manufacture and repair of aerospace components including high temperature gas turbine components made of Ni-base superalloys. For such critical applications, it is becoming increasingly important to account for the mechanical strength and reliability of the brazed joint. However, material properties of brazed joints are not readily available and methods for evaluating joint strength such as those listed in AWS C3.2 have inherent challenges compared with testing bulk materials. In addition, joint strength can be strongly influenced by the degree of interaction between the filler metal (FM) and the base metal (BM), the joint design, and presence of flaws or defects. As a result, there is interest in the development of a multi-scale computational model to predict the overall mechanical behavior and fitness-for-service of brazed joints. Therefore, the aim of this investigation was to generate data and methodology to support such a model for Ni-base superalloy brazed joints with conventional Ni-Cr-B based FMs. Based on a review of the technical literature a multi-scale modeling approach was proposed to predict the overall performance of brazed joints by relating mechanical properties to the brazed joint microstructure. This approach incorporates metallurgical characterization, thermodynamic/kinetic simulations, mechanical testing, fracture mechanics and finite element analysis (FEA) modeling to estimate joint properties based on the initial BM/FM composition and brazing process parameters. Experimental work was carried out in each of these areas to validate the multi-scale approach and develop improved techniques for quantifying brazed joint properties. Two Ni-base superalloys often used in gas turbine applications, Inconel 718 and CMSX-4, were selected for study and vacuum furnace brazed using two common FMs, BNi-2 and BNi-9. Metallurgical characterization of these brazed joints showed two primary microstructural regions; a soft

  9. Multiscale Shannon's Entropy Modeling of Orientation and Distance in Steel Fiber Micro-Tomography Data.

    Science.gov (United States)

    Chiverton, John P; Ige, Olubisi; Barnett, Stephanie J; Parry, Tony

    2017-11-01

    This paper is concerned with the modeling and analysis of the orientation and distance between steel fibers in X-ray micro-tomography data. The advantage of combining both orientation and separation in a model is that it helps provide a detailed understanding of how the steel fibers are arranged, which is easy to compare. The developed models are designed to summarize the randomness of the orientation distribution of the steel fibers both locally and across an entire volume based on multiscale entropy. Theoretical modeling, simulation, and application to real imaging data are shown here. The theoretical modeling of multiscale entropy for orientation includes a proof showing the final form of the multiscale taken over a linear range of scales. A series of image processing operations are also included to overcome interslice connectivity issues to help derive the statistical descriptions of the orientation distributions of the steel fibers. The results demonstrate that multiscale entropy provides unique insights into both simulated and real imaging data of steel fiber reinforced concrete.

  10. Evaluating 20th Century precipitation characteristics between multi-scale atmospheric models with different land-atmosphere coupling

    Science.gov (United States)

    Phillips, M.; Denning, A. S.; Randall, D. A.; Branson, M.

    2016-12-01

    Multi-scale models of the atmosphere provide an opportunity to investigate processes that are unresolved by traditional Global Climate Models while at the same time remaining viable in terms of computational resources for climate-length time scales. The MMF represents a shift away from large horizontal grid spacing in traditional GCMs that leads to overabundant light precipitation and lack of heavy events, toward a model where precipitation intensity is allowed to vary over a much wider range of values. Resolving atmospheric motions on the scale of 4 km makes it possible to recover features of precipitation, such as intense downpours, that were previously only obtained by computationally expensive regional simulations. These heavy precipitation events may have little impact on large-scale moisture and energy budgets, but are outstanding in terms of interaction with the land surface and potential impact on human life. Three versions of the Community Earth System Model were used in this study; the standard CESM, the multi-scale `Super-Parameterized' CESM where large-scale parameterizations have been replaced with a 2D cloud-permitting model, and a multi-instance land version of the SP-CESM where each column of the 2D CRM is allowed to interact with an individual land unit. These simulations were carried out using prescribed Sea Surface Temperatures for the period from 1979-2006 with daily precipitation saved for all 28 years. Comparisons of the statistical properties of precipitation between model architectures and against observations from rain gauges were made, with specific focus on detection and evaluation of extreme precipitation events.

  11. Multiscale modeling of graphene- and nanotube-based reinforced polymer nanocomposites

    Energy Technology Data Exchange (ETDEWEB)

    Montazeri, A. [Computational Physical Sciences Research Laboratory, School of Nano-Science, Institute for Research in Fundamental Sciences (IPM), Tehran (Iran, Islamic Republic of); Rafii-Tabar, H., E-mail: rafii-tabar@nano.ipm.ac.ir [Computational Physical Sciences Research Laboratory, School of Nano-Science, Institute for Research in Fundamental Sciences (IPM), Tehran (Iran, Islamic Republic of); Department of Medical Physics and Biomedical Engineering, and Research Centre for Medical Nanotechnology and Tissue Engineering, Shahid Beheshti University of Medical Sciences, Evin, Tehran (Iran, Islamic Republic of)

    2011-10-31

    A combination of molecular dynamics, molecular structural mechanics, and finite element method is employed to compute the elastic constants of a polymeric nanocomposite embedded with graphene sheets, and carbon nanotubes. The model is first applied to study the effect of inclusion of graphene sheets on the Young modulus of the composite. To explore the significance of the nanofiller geometry, the elastic constants of nanotube-based and graphene-based polymer composites are computed under identical conditions. The reinforcement role of these nanofillers is also investigated in transverse directions. Moreover, the dependence of the nanocomposite's axial Young modulus on the presence of ripples on the surface of the embedded graphene sheets, due to thermal fluctuations, is examined via MD simulations. Finally, we have also studied the effect of sliding motion of graphene layers on the elastic constants of the nanocomposite. -- Highlights: → A hierarchical MD/FEM multiscale model of nanocomposites is developed. → At low nanofiller content, graphene layers perform significantly better than CNTs. → Ripples in the graphene layers reduce the Young modulus of nanocomposites. → The elastic moduli is considerably affected by the shear of graphene layers.

  12. Multiscale modeling of graphene- and nanotube-based reinforced polymer nanocomposites

    International Nuclear Information System (INIS)

    Montazeri, A.; Rafii-Tabar, H.

    2011-01-01

    A combination of molecular dynamics, molecular structural mechanics, and finite element method is employed to compute the elastic constants of a polymeric nanocomposite embedded with graphene sheets, and carbon nanotubes. The model is first applied to study the effect of inclusion of graphene sheets on the Young modulus of the composite. To explore the significance of the nanofiller geometry, the elastic constants of nanotube-based and graphene-based polymer composites are computed under identical conditions. The reinforcement role of these nanofillers is also investigated in transverse directions. Moreover, the dependence of the nanocomposite's axial Young modulus on the presence of ripples on the surface of the embedded graphene sheets, due to thermal fluctuations, is examined via MD simulations. Finally, we have also studied the effect of sliding motion of graphene layers on the elastic constants of the nanocomposite. -- Highlights: → A hierarchical MD/FEM multiscale model of nanocomposites is developed. → At low nanofiller content, graphene layers perform significantly better than CNTs. → Ripples in the graphene layers reduce the Young modulus of nanocomposites. → The elastic moduli is considerably affected by the shear of graphene layers.

  13. Toward combining thematic information with hierarchical multiscale segmentations using tree Markov random field model

    Science.gov (United States)

    Zhang, Xueliang; Xiao, Pengfeng; Feng, Xuezhi

    2017-09-01

    It has been a common idea to produce multiscale segmentations to represent the various geographic objects in high-spatial resolution remote sensing (HR) images. However, it remains a great challenge to automatically select the proper segmentation scale(s) just according to the image information. In this study, we propose a novel way of information fusion at object level by combining hierarchical multiscale segmentations with existed thematic information produced by classification or recognition. The tree Markov random field (T-MRF) model is designed for the multiscale combination framework, through which the object type is determined as close as the existed thematic information. At the same time, the object boundary is jointly determined by the thematic labels and the multiscale segments through the minimization of the energy function. The benefits of the proposed T-MRF combination model include: (1) reducing the dependence of segmentation scale selection when utilizing multiscale segmentations; (2) exploring the hierarchical context naturally imbedded in the multiscale segmentations. The HR images in both urban and rural areas are used in the experiments to show the effectiveness of the proposed combination framework on these two aspects.

  14. Multiscale network model for simulating liquid water and water vapour transfer properties of porous materials

    NARCIS (Netherlands)

    Carmeliet, J.; Descamps, F.; Houvenaghel, G.

    1999-01-01

    A multiscale network model is presented to model unsaturated moisture transfer in hygroscopic capillary-porous materials showing a broad pore-size distribution. Both capillary effects and water sorption phenomena, water vapour and liquid water transfer are considered. The multiscale approach is

  15. Computer Aided Multi-scale Design of SiC-Si3N4 Nanoceramic Composites for High-Temperature Structural Applications

    Energy Technology Data Exchange (ETDEWEB)

    Vikas Tomer; John Renaud

    2010-08-31

    temperature dependent strength and microstructural stability was also significantly depended upon the dispersion of new phases at grain boundaries. The material design framework incorporates high temperature creep and mechanical strength data in order to develop a collaborative multiscale framework of morphology optimization. The work also incorporates a computer aided material design dataset development procedure where a systematic dataset on material properties and morphology correlation could be obtained depending upon a material processing scientist's requirements. Two different aspects covered under this requirement are: (1) performing morphology related analyses at the nanoscale and at the microscale to develop a multiscale material design and analyses capability; (2) linking material behavior analyses with the developed design tool to form a set of material design problems that illustrate the range of material design dataset development that could be performed. Overall, a software based methodology to design microstructure of particle based ceramic nanocomposites has been developed. This methodology has been shown to predict changes in phase morphologies required for achieving optimal balance of conflicting properties such as minimal creep strain rate and high fracture strength at high temperatures. The methodology incorporates complex material models including atomistic approaches. The methodology will be useful to design materials for high temperature applications including those of interest to DoE while significantly reducing cost of expensive experiments.

  16. Multiscale modelling of DNA mechanics

    International Nuclear Information System (INIS)

    Dršata, Tomáš; Lankaš, Filip

    2015-01-01

    Mechanical properties of DNA are important not only in a wide range of biological processes but also in the emerging field of DNA nanotechnology. We review some of the recent developments in modeling these properties, emphasizing the multiscale nature of the problem. Modern atomic resolution, explicit solvent molecular dynamics simulations have contributed to our understanding of DNA fine structure and conformational polymorphism. These simulations may serve as data sources to parameterize rigid base models which themselves have undergone major development. A consistent buildup of larger entities involving multiple rigid bases enables us to describe DNA at more global scales. Free energy methods to impose large strains on DNA, as well as bead models and other approaches, are also briefly discussed. (topical review)

  17. ANALYSIS/MODEL COVER SHEET, MULTISCALE THERMOHYDROLOGIC MODEL

    International Nuclear Information System (INIS)

    Buscheck, T.A.

    2001-01-01

    The purpose of the Multiscale Thermohydrologic Model (MSTHM) is to describe the thermohydrologic evolution of the near-field environment (NFE) and engineered barrier system (EBS) throughout the potential high-level nuclear waste repository at Yucca Mountain for a particular engineering design (CRWMS M andO 2000c). The process-level model will provide thermohydrologic (TH) information and data (such as in-drift temperature, relative humidity, liquid saturation, etc.) for use in other technical products. This data is provided throughout the entire repository area as a function of time. The MSTHM couples the Smeared-heat-source Drift-scale Thermal-conduction (SDT), Line-average-heat-source Drift-scale Thermohydrologic (LDTH), Discrete-heat-source Drift-scale Thermal-conduction (DDT), and Smeared-heat-source Mountain-scale Thermal-conduction (SMT) submodels such that the flow of water and water vapor through partially-saturated fractured rock is considered. The MSTHM accounts for 3-D drift-scale and mountain-scale heat flow, repository-scale variability of stratigraphy and infiltration flux, and waste package (WP)-to-WP variability in heat output from WPs. All submodels use the nonisothermal unsaturated-saturated flow and transport (NUFT) simulation code. The MSTHM is implemented in several data-processing steps. The four major steps are: (1) submodel input-file preparation, (2) execution of the four submodel families with the use of the NUFT code, (3) execution of the multiscale thermohydrologic abstraction code (MSTHAC), and (4) binning and post-processing (i.e., graphics preparation) of the output from MSTHAC. Section 6 describes the MSTHM in detail. The objectives of this Analyses and Model Report (AMR) are to investigate near field (NF) and EBS thermohydrologic environments throughout the repository area at various evolution periods, and to provide TH data that may be used in other process model reports

  18. A Liver-Centric Multiscale Modeling Framework for Xenobiotics.

    Directory of Open Access Journals (Sweden)

    James P Sluka

    Full Text Available We describe a multi-scale, liver-centric in silico modeling framework for acetaminophen pharmacology and metabolism. We focus on a computational model to characterize whole body uptake and clearance, liver transport and phase I and phase II metabolism. We do this by incorporating sub-models that span three scales; Physiologically Based Pharmacokinetic (PBPK modeling of acetaminophen uptake and distribution at the whole body level, cell and blood flow modeling at the tissue/organ level and metabolism at the sub-cellular level. We have used standard modeling modalities at each of the three scales. In particular, we have used the Systems Biology Markup Language (SBML to create both the whole-body and sub-cellular scales. Our modeling approach allows us to run the individual sub-models separately and allows us to easily exchange models at a particular scale without the need to extensively rework the sub-models at other scales. In addition, the use of SBML greatly facilitates the inclusion of biological annotations directly in the model code. The model was calibrated using human in vivo data for acetaminophen and its sulfate and glucuronate metabolites. We then carried out extensive parameter sensitivity studies including the pairwise interaction of parameters. We also simulated population variation of exposure and sensitivity to acetaminophen. Our modeling framework can be extended to the prediction of liver toxicity following acetaminophen overdose, or used as a general purpose pharmacokinetic model for xenobiotics.

  19. Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Kai, E-mail: kaigao87@gmail.com [Department of Geology and Geophysics, Texas A& M University, College Station, TX 77843 (United States); Fu, Shubin, E-mail: shubinfu89@gmail.com [Department of Mathematics, Texas A& M University, College Station, TX 77843 (United States); Gibson, Richard L., E-mail: gibson@tamu.edu [Department of Geology and Geophysics, Texas A& M University, College Station, TX 77843 (United States); Chung, Eric T., E-mail: tschung@math.cuhk.edu.hk [Department of Mathematics, The Chinese University of Hong Kong, Shatin, NT (Hong Kong); Efendiev, Yalchin, E-mail: efendiev@math.tamu.edu [Department of Mathematics, Texas A& M University, College Station, TX 77843 (United States); Numerical Porous Media SRI Center (NumPor), King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)

    2015-08-15

    It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale medium property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.

  20. Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media

    International Nuclear Information System (INIS)

    Gao, Kai; Fu, Shubin; Gibson, Richard L.; Chung, Eric T.; Efendiev, Yalchin

    2015-01-01

    It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale medium property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system

  1. A multiscale method for modeling high-aspect-ratio micro/nano flows

    Science.gov (United States)

    Lockerby, Duncan; Borg, Matthew; Reese, Jason

    2012-11-01

    In this paper we present a new multiscale scheme for simulating micro/nano flows of high aspect ratio in the flow direction, e.g. within long ducts, tubes, or channels, of varying section. The scheme consists of applying a simple hydrodynamic description over the entire domain, and allocating micro sub-domains in very small ``slices'' of the channel. Every micro element is a molecular dynamics simulation (or other appropriate model, e.g., a direct simulation Monte Carlo method for micro-channel gas flows) over the local height of the channel/tube. The number of micro elements as well as their streamwise position is chosen to resolve the geometrical features of the macro channel. While there is no direct communication between individual micro elements, coupling occurs via an iterative imposition of mass and momentum-flux conservation on the macro scale. The greater the streamwise scale of the geometry, the more significant is the computational speed-up when compared to a full MD simulation. We test our new multiscale method on the case of a converging/diverging nanochannel conveying a simple Lennard-Jones liquid. We validate the results from our simulations by comparing them to a full MD simulation of the same test case. Supported by EPSRC Programme Grant, EP/I011927/1.

  2. Towards practical multiscale approach for analysis of reinforced concrete structures

    Science.gov (United States)

    Moyeda, Arturo; Fish, Jacob

    2017-12-01

    We present a novel multiscale approach for analysis of reinforced concrete structural elements that overcomes two major hurdles in utilization of multiscale technologies in practice: (1) coupling between material and structural scales due to consideration of large representative volume elements (RVE), and (2) computational complexity of solving complex nonlinear multiscale problems. The former is accomplished using a variant of computational continua framework that accounts for sizeable reinforced concrete RVEs by adjusting the location of quadrature points. The latter is accomplished by means of reduced order homogenization customized for structural elements. The proposed multiscale approach has been verified against direct numerical simulations and validated against experimental results.

  3. Modeling of heterogeneous elastic materials by the multiscale hp-adaptive finite element method

    Science.gov (United States)

    Klimczak, Marek; Cecot, Witold

    2018-01-01

    We present an enhancement of the multiscale finite element method (MsFEM) by combining it with the hp-adaptive FEM. Such a discretization-based homogenization technique is a versatile tool for modeling heterogeneous materials with fast oscillating elasticity coefficients. No assumption on periodicity of the domain is required. In order to avoid direct, so-called overkill mesh computations, a coarse mesh with effective stiffness matrices is used and special shape functions are constructed to account for the local heterogeneities at the micro resolution. The automatic adaptivity (hp-type at the macro resolution and h-type at the micro resolution) increases efficiency of computation. In this paper details of the modified MsFEM are presented and a numerical test performed on a Fichera corner domain is presented in order to validate the proposed approach.

  4. An Online Generalized Multiscale Discontinuous Galerkin Method (GMsDGM) for Flows in Heterogeneous Media

    KAUST Repository

    Chung, Eric T.

    2017-02-07

    Offline computation is an essential component in most multiscale model reduction techniques. However, there are multiscale problems in which offline procedure is insufficient to give accurate representations of solutions, due to the fact that offline computations are typically performed locally and global information is missing in these offline information. To tackle this difficulty, we develop an online local adaptivity technique for local multiscale model reduction problems. We design new online basis functions within Discontinuous Galerkin method based on local residuals and some optimally estimates. The resulting basis functions are able to capture the solution efficiently and accurately, and are added to the approximation iteratively. Moreover, we show that the iterative procedure is convergent with a rate independent of physical scales if the initial space is chosen carefully. Our analysis also gives a guideline on how to choose the initial space. We present some numerical examples to show the performance of the proposed method.

  5. Multiscale forward electromagnetic model of uterine contractions during pregnancy

    International Nuclear Information System (INIS)

    La Rosa, Patricio S; Eswaran, Hari; Preissl, Hubert; Nehorai, Arye

    2012-01-01

    Analyzing and monitoring uterine contractions during pregnancy is relevant to the field of reproductive health assessment. Its clinical importance is grounded in the need to reliably predict the onset of labor at term and pre-term. Preterm births can cause health problems or even be fatal for the fetus. Currently, there are no objective methods for consistently predicting the onset of labor based on sensing of the mechanical or electrophysiological aspects of uterine contractions. Therefore, modeling uterine contractions could help to better interpret such measurements and to develop more accurate methods for predicting labor. In this work, we develop a multiscale forward electromagnetic model of myometrial contractions during pregnancy. In particular, we introduce a model of myometrial current source densities and compute its magnetic field and action potential at the abdominal surface, using Maxwell’s equations and a four-compartment volume conductor geometry. To model the current source density at the myometrium we use a bidomain approach. We consider a modified version of the Fitzhugh-Nagumo (FHN) equation for modeling ionic currents in each myocyte, assuming a plateau-type transmembrane potential, and we incorporate the anisotropic nature of the uterus by designing conductivity-tensor fields. We illustrate our modeling approach considering a spherical uterus and one pacemaker located in the fundus. We obtained a travelling transmembrane potential depolarizing from −56 mV to −16 mV and an average potential in the plateau area of −25 mV with a duration, before hyperpolarization, of 35 s, which is a good approximation with respect to the average recorded transmembrane potentials at term reported in the technical literature. Similarly, the percentage of myometrial cells contracting as a function of time had the same symmetric properties and duration as the intrauterine pressure waveforms of a pregnant human myometrium at term. We introduced a multiscale

  6. Multi-scale modeling of composites

    DEFF Research Database (Denmark)

    Azizi, Reza

    A general method to obtain the homogenized response of metal-matrix composites is developed. It is assumed that the microscopic scale is sufficiently small compared to the macroscopic scale such that the macro response does not affect the micromechanical model. Therefore, the microscopic scale......-Mandel’s energy principle is used to find macroscopic operators based on micro-mechanical analyses using the finite element method under generalized plane strain condition. A phenomenologically macroscopic model for metal matrix composites is developed based on constitutive operators describing the elastic...... to plastic deformation. The macroscopic operators found, can be used to model metal matrix composites on the macroscopic scale using a hierarchical multi-scale approach. Finally, decohesion under tension and shear loading is studied using a cohesive law for the interface between matrix and fiber....

  7. msBP: An R Package to Perform Bayesian Nonparametric Inference Using Multiscale Bernstein Polynomials Mixtures

    Directory of Open Access Journals (Sweden)

    Antonio Canale

    2017-06-01

    Full Text Available msBP is an R package that implements a new method to perform Bayesian multiscale nonparametric inference introduced by Canale and Dunson (2016. The method, based on mixtures of multiscale beta dictionary densities, overcomes the drawbacks of Pólya trees and inherits many of the advantages of Dirichlet process mixture models. The key idea is that an infinitely-deep binary tree is introduced, with a beta dictionary density assigned to each node of the tree. Using a multiscale stick-breaking characterization, stochastically decreasing weights are assigned to each node. The result is an infinite mixture model. The package msBP implements a series of basic functions to deal with this family of priors such as random densities and numbers generation, creation and manipulation of binary tree objects, and generic functions to plot and print the results. In addition, it implements the Gibbs samplers for posterior computation to perform multiscale density estimation and multiscale testing of group differences described in Canale and Dunson (2016.

  8. Multiscale mechanistic modeling in pharmaceutical research and development.

    Science.gov (United States)

    Kuepfer, Lars; Lippert, Jörg; Eissing, Thomas

    2012-01-01

    Discontinuation of drug development projects due to lack of efficacy or adverse events is one of the main cost drivers in pharmaceutical research and development (R&D). Investments have to be written-off and contribute to the total costs of a successful drug candidate receiving marketing authorization and allowing return on invest. A vital risk for pharmaceutical innovator companies is late stage clinical failure since costs for individual clinical trials may exceed the one billion Euro threshold. To guide investment decisions and to safeguard maximum medical benefit and safety for patients recruited in clinical trials, it is therefore essential to understand the clinical consequences of all information and data generated. The complexity of the physiological and pathophysiological processes and the sheer amount of information available overcharge the mental capacity of any human being and prevent a prediction of the success in clinical development. A rigorous integration of knowledge, assumption, and experimental data into computational models promises a significant improvement of the rationalization of decision making in pharmaceutical industry. We here give an overview of the current status of modeling and simulation in pharmaceutical R&D and outline the perspectives of more recent developments in mechanistic modeling. Specific modeling approaches for different biological scales ranging from intracellular processes to whole organism physiology are introduced and an example for integrative multiscale modeling of therapeutic efficiency in clinical oncology trials is showcased.

  9. A case study on the influence of multiscale modelling in design and structural analysis

    DEFF Research Database (Denmark)

    Nicholas, Paul; Zwierzycki, Mateusz; La Magna, Riccardo

    2017-01-01

    . To illustrate the concept of multi-scale modelling, the prototype of a bridge structure that was realised making use of this information transfer between models will be presented. The prototype primarily takes advantage of the geometric and material stiffening effect of incremental metal forming. The local......The current paper discusses the role of multi-scale modelling within the context of design and structural analysis. Depending on the level of detail, a design model may retain, lose or enhance key information. The term multi-scale refers to the break-down of a design and analysis task into multiple...... levels of detail and the transfer of this information between models. Focusing on the influence that different models have on the analysed performance of the structure, the paper will discuss the advantages and trade-offs of coupling multiple levels of abstraction in terms of design and structure...

  10. Multiscale Biological Materials

    DEFF Research Database (Denmark)

    Frølich, Simon

    of multiscale biological systems have been investigated and new research methods for automated Rietveld refinement and diffraction scattering computed tomography developed. The composite nature of biological materials was investigated at the atomic scale by looking at the consequences of interactions between...

  11. Modeling and simulation of high dimensional stochastic multiscale PDE systems at the exascale

    Energy Technology Data Exchange (ETDEWEB)

    Zabaras, Nicolas J. [Cornell Univ., Ithaca, NY (United States)

    2016-11-08

    Predictive Modeling of multiscale and Multiphysics systems requires accurate data driven characterization of the input uncertainties, and understanding of how they propagate across scales and alter the final solution. This project develops a rigorous mathematical framework and scalable uncertainty quantification algorithms to efficiently construct realistic low dimensional input models, and surrogate low complexity systems for the analysis, design, and control of physical systems represented by multiscale stochastic PDEs. The work can be applied to many areas including physical and biological processes, from climate modeling to systems biology.

  12. Multi-scale modeling of the thermo-mechanical behavior of particle-based composites

    International Nuclear Information System (INIS)

    Di Paola, F.

    2010-01-01

    The aim of this work was to perform numerical simulations of the thermal and mechanical behavior of a particle-based nuclear fuel. This is a refractory composite material made of UO 2 spherical particles which are coated with two layers of pyrocarbon and embedded in a graphite matrix at a high volume fraction (45%). The objective was to develop a multi-scale modeling of this composite material which can estimate its mean behavior as well as the heterogeneity of the local mechanical variables. The first part of this work was dedicated to the modeling of the microstructure in 3D. To do this, we developed tools to generate random distributions of spheres, meshes and to characterize the morphology of the microstructure towards the finite element code Cast3M. A hundred of numerical samples of the composite were created. The second part was devoted to the characterization of the thermo-elastic behavior by the finite element modeling of the samples. We studied the influence of different modeling parameters, one of them is the boundary conditions. We proposed a method to vanish the boundary conditions effects from the computed solution by analyzing it on an internal sub-volume of the sample obtained by erosion. Then, we determined the effective properties (elastic moduli, thermal conductivity and thermal expansion) and the stress distribution within the matrix. Finally, in the third part we proposed a multi-scale modeling to determine the mean values and the variance and covariance of the local mechanical variables for any macroscopic load. This statistical approach have been used to estimate the intra-phase distribution of these variables in the composite material. (author) [fr

  13. Multi-scale modeling of the thermo-mechanical behavior of particle-based composites

    International Nuclear Information System (INIS)

    Di Paola, F.

    2010-11-01

    The aim of this work was to perform numerical simulations of the thermal and mechanical behavior of a particle-based nuclear fuel. This is a refractory composite material made of UO 2 spherical particles which are coated with two layers of pyrocarbon and embedded in a graphite matrix at a high volume fraction (45 %). The objective was to develop a multi-scale modeling of this composite material which can estimate its mean behavior as well as the heterogeneity of the local mechanical variables. The first part of this work was dedicated to the modeling of the microstructure in 3D. To do this, we developed tools to generate random distributions of spheres, meshes and to characterize the morphology of the microstructure towards the finite element code Cast3M. A hundred of numerical samples of the composite were created. The second part was devoted to the characterization of the thermo-elastic behavior by the finite element modeling of the samples. We studied the influence of different modeling parameters, one of them is the boundary conditions. We proposed a method to vanish the boundary conditions effects from the computed solution by analyzing it on an internal sub-volume of the sample obtained by erosion. Then, we determined the effective properties (elastic moduli, thermal conductivity and thermal expansion) and the stress distribution within the matrix. Finally, in the third part we proposed a multi-scale modeling to determine the mean values and the variance and covariance of the local mechanical variables for any macroscopic load. This statistical approach have been used to estimate the intra-phase distribution of these variables in the composite material. (author)

  14. Computational approach on PEB process in EUV resist: multi-scale simulation

    Science.gov (United States)

    Kim, Muyoung; Moon, Junghwan; Choi, Joonmyung; Lee, Byunghoon; Jeong, Changyoung; Kim, Heebom; Cho, Maenghyo

    2017-03-01

    For decades, downsizing has been a key issue for high performance and low cost of semiconductor, and extreme ultraviolet lithography is one of the promising candidates to achieve the goal. As a predominant process in extreme ultraviolet lithography on determining resolution and sensitivity, post exposure bake has been mainly studied by experimental groups, but development of its photoresist is at the breaking point because of the lack of unveiled mechanism during the process. Herein, we provide theoretical approach to investigate underlying mechanism on the post exposure bake process in chemically amplified resist, and it covers three important reactions during the process: acid generation by photo-acid generator dissociation, acid diffusion, and deprotection. Density functional theory calculation (quantum mechanical simulation) was conducted to quantitatively predict activation energy and probability of the chemical reactions, and they were applied to molecular dynamics simulation for constructing reliable computational model. Then, overall chemical reactions were simulated in the molecular dynamics unit cell, and final configuration of the photoresist was used to predict the line edge roughness. The presented multiscale model unifies the phenomena of both quantum and atomic scales during the post exposure bake process, and it will be helpful to understand critical factors affecting the performance of the resulting photoresist and design the next-generation material.

  15. Emerging Trends in Heart Valve Engineering: Part IV. Computational Modeling and Experimental Studies.

    Science.gov (United States)

    Kheradvar, Arash; Groves, Elliott M; Falahatpisheh, Ahmad; Mofrad, Mohammad K; Hamed Alavi, S; Tranquillo, Robert; Dasi, Lakshmi P; Simmons, Craig A; Jane Grande-Allen, K; Goergen, Craig J; Baaijens, Frank; Little, Stephen H; Canic, Suncica; Griffith, Boyce

    2015-10-01

    In this final portion of an extensive review of heart valve engineering, we focus on the computational methods and experimental studies related to heart valves. The discussion begins with a thorough review of computational modeling and the governing equations of fluid and structural interaction. We then move onto multiscale and disease specific modeling. Finally, advanced methods related to in vitro testing of the heart valves are reviewed. This section of the review series is intended to illustrate application of computational methods and experimental studies and their interrelation for studying heart valves.

  16. Generalized Multiscale Finite Element Methods for Wave Propagation in Heterogeneous Media

    KAUST Repository

    Chung, Eric T.

    2014-11-13

    Numerical modeling of wave propagation in heterogeneous media is important in many applications. Due to their complex nature, direct numerical simulations on the fine grid are prohibitively expensive. It is therefore important to develop efficient and accurate methods that allow the use of coarse grids. In this paper, we present a multiscale finite element method for wave propagation on a coarse grid. The proposed method is based on the generalized multiscale finite element method (GMsFEM) (see [Y. Efendiev, J. Galvis, and T. Hou, J. Comput. Phys., 251 (2012), pp. 116--135]). To construct multiscale basis functions, we start with two snapshot spaces in each coarse-grid block, where one represents the degrees of freedom on the boundary and the other represents the degrees of freedom in the interior. We use local spectral problems to identify important modes in each snapshot space. These local spectral problems are different from each other and their formulations are based on the analysis. To the best of knowledge, this is the first time that multiple snapshot spaces and multiple spectral problems are used and necessary for efficient computations. Using the dominant modes from local spectral problems, multiscale basis functions are constructed to represent the solution space locally within each coarse block. These multiscale basis functions are coupled via the symmetric interior penalty discontinuous Galerkin method which provides a block diagonal mass matrix and, consequently, results in fast computations in an explicit time discretization. Our methods\\' stability and spectral convergence are rigorously analyzed. Numerical examples are presented to show our methods\\' performance. We also test oversampling strategies. In particular, we discuss how the modes from different snapshot spaces can affect the proposed methods\\' accuracy.

  17. A Multi-Scale Computational Study on the Mechanism of Streptococcus pneumoniae Nicotinamidase (SpNic)

    OpenAIRE

    Ion, Bogdan; Kazim, Erum; Gauld, James

    2014-01-01

    Nicotinamidase (Nic) is a key zinc-dependent enzyme in NAD metabolism that catalyzes the hydrolysis of nicotinamide to give nicotinic acid. A multi-scale computational approach has been used to investigate the catalytic mechanism, substrate binding and roles of active site residues of Nic from Streptococcus pneumoniae (SpNic). In particular, density functional theory (DFT), molecular dynamics (MD) and ONIOM quantum mechanics/molecular mechanics (QM/MM) methods have been employed. The o...

  18. Parallel multiscale simulations of a brain aneurysm

    Energy Technology Data Exchange (ETDEWEB)

    Grinberg, Leopold [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States); Fedosov, Dmitry A. [Institute of Complex Systems and Institute for Advanced Simulation, Forschungszentrum Jülich, Jülich 52425 (Germany); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States)

    2013-07-01

    Cardiovascular pathologies, such as a brain aneurysm, are affected by the global blood circulation as well as by the local microrheology. Hence, developing computational models for such cases requires the coupling of disparate spatial and temporal scales often governed by diverse mathematical descriptions, e.g., by partial differential equations (continuum) and ordinary differential equations for discrete particles (atomistic). However, interfacing atomistic-based with continuum-based domain discretizations is a challenging problem that requires both mathematical and computational advances. We present here a hybrid methodology that enabled us to perform the first multiscale simulations of platelet depositions on the wall of a brain aneurysm. The large scale flow features in the intracranial network are accurately resolved by using the high-order spectral element Navier–Stokes solver NεκTαr. The blood rheology inside the aneurysm is modeled using a coarse-grained stochastic molecular dynamics approach (the dissipative particle dynamics method) implemented in the parallel code LAMMPS. The continuum and atomistic domains overlap with interface conditions provided by effective forces computed adaptively to ensure continuity of states across the interface boundary. A two-way interaction is allowed with the time-evolving boundary of the (deposited) platelet clusters tracked by an immersed boundary method. The corresponding heterogeneous solvers (NεκTαr and LAMMPS) are linked together by a computational multilevel message passing interface that facilitates modularity and high parallel efficiency. Results of multiscale simulations of clot formation inside the aneurysm in a patient-specific arterial tree are presented. We also discuss the computational challenges involved and present scalability results of our coupled solver on up to 300 K computer processors. Validation of such coupled atomistic-continuum models is a main open issue that has to be addressed in

  19. Parallel multiscale simulations of a brain aneurysm

    International Nuclear Information System (INIS)

    Grinberg, Leopold; Fedosov, Dmitry A.; Karniadakis, George Em

    2013-01-01

    Cardiovascular pathologies, such as a brain aneurysm, are affected by the global blood circulation as well as by the local microrheology. Hence, developing computational models for such cases requires the coupling of disparate spatial and temporal scales often governed by diverse mathematical descriptions, e.g., by partial differential equations (continuum) and ordinary differential equations for discrete particles (atomistic). However, interfacing atomistic-based with continuum-based domain discretizations is a challenging problem that requires both mathematical and computational advances. We present here a hybrid methodology that enabled us to perform the first multiscale simulations of platelet depositions on the wall of a brain aneurysm. The large scale flow features in the intracranial network are accurately resolved by using the high-order spectral element Navier–Stokes solver NεκTαr. The blood rheology inside the aneurysm is modeled using a coarse-grained stochastic molecular dynamics approach (the dissipative particle dynamics method) implemented in the parallel code LAMMPS. The continuum and atomistic domains overlap with interface conditions provided by effective forces computed adaptively to ensure continuity of states across the interface boundary. A two-way interaction is allowed with the time-evolving boundary of the (deposited) platelet clusters tracked by an immersed boundary method. The corresponding heterogeneous solvers (NεκTαr and LAMMPS) are linked together by a computational multilevel message passing interface that facilitates modularity and high parallel efficiency. Results of multiscale simulations of clot formation inside the aneurysm in a patient-specific arterial tree are presented. We also discuss the computational challenges involved and present scalability results of our coupled solver on up to 300 K computer processors. Validation of such coupled atomistic-continuum models is a main open issue that has to be addressed in

  20. Multiscale modeling of nerve agent hydrolysis mechanisms: a tale of two Nobel Prizes

    Science.gov (United States)

    Field, Martin J.; Wymore, Troy W.

    2014-10-01

    The 2013 Nobel Prize in Chemistry was awarded for the development of multiscale models for complex chemical systems, whereas the 2013 Peace Prize was given to the Organisation for the Prohibition of Chemical Weapons for their efforts to eliminate chemical warfare agents. This review relates the two by introducing the field of multiscale modeling and highlighting its application to the study of the biological mechanisms by which selected chemical weapon agents exert their effects at an atomic level.

  1. Multiscale vision model for event detection and reconstruction in two-photon imaging data

    DEFF Research Database (Denmark)

    Brazhe, Alexey; Mathiesen, Claus; Lind, Barbara Lykke

    2014-01-01

    on a modified multiscale vision model, an object detection framework based on the thresholding of wavelet coefficients and hierarchical trees of significant coefficients followed by nonlinear iterative partial object reconstruction, for the analysis of two-photon calcium imaging data. The framework is discussed...... of the multiscale vision model is similar in the denoising, but provides a better segmenation of the image into meaningful objects, whereas other methods need to be combined with dedicated thresholding and segmentation utilities....

  2. Computational multiscale modeling of fluids and solids theory and applications

    CERN Document Server

    Steinhauser, Martin Oliver

    2017-01-01

    The idea of the book is to provide a comprehensive overview of computational physics methods and techniques, that are used for materials modeling on different length and time scales. Each chapter first provides an overview of the basic physical principles which are the basis for the numerical and mathematical modeling on the respective length-scale. The book includes the micro-scale, the meso-scale and the macro-scale, and the chapters follow this classification. The book explains in detail many tricks of the trade of some of the most important methods and techniques that are used to simulate materials on the perspective levels of spatial and temporal resolution. Case studies are included to further illustrate some methods or theoretical considerations. Example applications for all techniques are provided, some of which are from the author’s own contributions to some of the research areas. The second edition has been expanded by new sections in computational models on meso/macroscopic scales for ocean and a...

  3. Residual-driven online generalized multiscale finite element methods

    KAUST Repository

    Chung, Eric T.; Efendiev, Yalchin R.; Leung, Wing Tat

    2015-01-01

    In the paper, theoretical and numerical results are presented. Our numerical results show that if the offline space is sufficiently large (in terms of the dimension) such that the coarse space contains all multiscale spectral basis functions that correspond to small eigenvalues, then the error reduction by adding online multiscale basis function is independent of the contrast. We discuss various ways computing online multiscale basis functions which include a use of small dimensional offline spaces.

  4. Modeling complex biological flows in multi-scale systems using the APDEC framework

    Science.gov (United States)

    Trebotich, David

    2006-09-01

    We have developed advanced numerical algorithms to model biological fluids in multiscale flow environments using the software framework developed under the SciDAC APDEC ISIC. The foundation of our computational effort is an approach for modeling DNA laden fluids as ''bead-rod'' polymers whose dynamics are fully coupled to an incompressible viscous solvent. The method is capable of modeling short range forces and interactions between particles using soft potentials and rigid constraints. Our methods are based on higher-order finite difference methods in complex geometry with adaptivity, leveraging algorithms and solvers in the APDEC Framework. Our Cartesian grid embedded boundary approach to incompressible viscous flow in irregular geometries has also been interfaced to a fast and accurate level-sets method within the APDEC Framework for extracting surfaces from volume renderings of medical image data and used to simulate cardio-vascular and pulmonary flows in critical anatomies.

  5. Multiscale Lattice Boltzmann method for flow simulations in highly heterogenous porous media

    KAUST Repository

    Li, Jun; Brown, Donald; Calo, Victor M.; Efendiev, Yalchin R.; Illiev, Oleg

    2013-01-01

    .g., water and oil) are modeled using cohesive or repulsive forces, respectively. The relative permeability can be computed using pore-scale simulations and seamlessly applied for intermediate and Darcy-scale simulations. A multiscale LBM that can reduce

  6. Generalized multiscale finite element methods: Oversampling strategies

    KAUST Repository

    Efendiev, Yalchin R.; Galvis, Juan; Li, Guanglian; Presho, Michael

    2014-01-01

    In this paper, we propose oversampling strategies in the generalized multiscale finite element method (GMsFEM) framework. The GMsFEM, which has been recently introduced in Efendiev et al. (2013b) [Generalized Multiscale Finite Element Methods, J. Comput. Phys., vol. 251, pp. 116-135, 2013], allows solving multiscale parameter-dependent problems at a reduced computational cost by constructing a reduced-order representation of the solution on a coarse grid. The main idea of the method consists of (1) the construction of snapshot space, (2) the construction of the offline space, and (3) construction of the online space (the latter for parameter-dependent problems). In Efendiev et al. (2013b) [Generalized Multiscale Finite Element Methods, J. Comput. Phys., vol. 251, pp. 116-135, 2013], it was shown that the GMsFEM provides a flexible tool to solve multiscale problems with a complex input space by generating appropriate snapshot, offline, and online spaces. In this paper, we develop oversampling techniques to be used in this context (see Hou and Wu (1997) where oversampling is introduced for multiscale finite element methods). It is known (see Hou and Wu (1997)) that the oversampling can improve the accuracy of multiscale methods. In particular, the oversampling technique uses larger regions (larger than the target coarse block) in constructing local basis functions. Our motivation stems from the analysis presented in this paper, which shows that when using oversampling techniques in the construction of the snapshot space and offline space, GMsFEM will converge independent of small scales and high contrast under certain assumptions. We consider the use of a multiple eigenvalue problems to improve the convergence and discuss their relation to single spectral problems that use oversampled regions. The oversampling procedures proposed in this paper differ from those in Hou and Wu (1997). In particular, the oversampling domains are partially used in constructing local

  7. Multi-scale finite element modeling allows the mechanics of amphibian neurulation to be elucidated

    International Nuclear Information System (INIS)

    Chen Xiaoguang; Wayne Brodland, G

    2008-01-01

    The novel multi-scale computational approach introduced here makes possible a new means for testing hypotheses about the forces that drive specific morphogenetic movements. A 3D model based on this approach is used to investigate neurulation in the axolotl (Ambystoma mexicanum), a type of amphibian. The model is based on geometric data from 3D surface reconstructions of live embryos and from serial sections. Tissue properties are described by a system of cell-based constitutive equations, and parameters in the equations are determined from physical tests. The model includes the effects of Shroom-activated neural ridge reshaping and lamellipodium-driven convergent extension. A typical whole-embryo model consists of 10 239 elements and to run its 100 incremental time steps requires 2 days. The model shows that a normal phenotype does not result if lamellipodium forces are uniform across the width of the neural plate; but it can result if the lamellipodium forces decrease from a maximum value at the mid-sagittal plane to zero at the plate edge. Even the seemingly simple motions of neurulation are found to contain important features that would remain hidden, they were not studied using an advanced computational model. The present model operates in a setting where data are extremely sparse and an important outcome of the study is a better understanding of the role of computational models in such environments

  8. Multi-scale finite element modeling allows the mechanics of amphibian neurulation to be elucidated

    Science.gov (United States)

    Chen, Xiaoguang; Brodland, G. Wayne

    2008-03-01

    The novel multi-scale computational approach introduced here makes possible a new means for testing hypotheses about the forces that drive specific morphogenetic movements. A 3D model based on this approach is used to investigate neurulation in the axolotl (Ambystoma mexicanum), a type of amphibian. The model is based on geometric data from 3D surface reconstructions of live embryos and from serial sections. Tissue properties are described by a system of cell-based constitutive equations, and parameters in the equations are determined from physical tests. The model includes the effects of Shroom-activated neural ridge reshaping and lamellipodium-driven convergent extension. A typical whole-embryo model consists of 10 239 elements and to run its 100 incremental time steps requires 2 days. The model shows that a normal phenotype does not result if lamellipodium forces are uniform across the width of the neural plate; but it can result if the lamellipodium forces decrease from a maximum value at the mid-sagittal plane to zero at the plate edge. Even the seemingly simple motions of neurulation are found to contain important features that would remain hidden, they were not studied using an advanced computational model. The present model operates in a setting where data are extremely sparse and an important outcome of the study is a better understanding of the role of computational models in such environments.

  9. Adaptive Remodeling of Achilles Tendon: A Multi-scale Computational Model.

    Directory of Open Access Journals (Sweden)

    Stuart R Young

    2016-09-01

    Full Text Available While it is known that musculotendon units adapt to their load environments, there is only a limited understanding of tendon adaptation in vivo. Here we develop a computational model of tendon remodeling based on the premise that mechanical damage and tenocyte-mediated tendon damage and repair processes modify the distribution of its collagen fiber lengths. We explain how these processes enable the tendon to geometrically adapt to its load conditions. Based on known biological processes, mechanical and strain-dependent proteolytic fiber damage are incorporated into our tendon model. Using a stochastic model of fiber repair, it is assumed that mechanically damaged fibers are repaired longer, whereas proteolytically damaged fibers are repaired shorter, relative to their pre-damage length. To study adaptation of tendon properties to applied load, our model musculotendon unit is a simplified three-component Hill-type model of the human Achilles-soleus unit. Our model results demonstrate that the geometric equilibrium state of the Achilles tendon can coincide with minimization of the total metabolic cost of muscle activation. The proposed tendon model independently predicts rates of collagen fiber turnover that are in general agreement with in vivo experimental measurements. While the computational model here only represents a first step in a new approach to understanding the complex process of tendon remodeling in vivo, given these findings, it appears likely that the proposed framework may itself provide a useful theoretical foundation for developing valuable qualitative and quantitative insights into tendon physiology and pathology.

  10. Sustainable design and manufacturing of multifunctional polymer nanocomposite coatings: A multiscale systems approach

    Science.gov (United States)

    Xiao, Jie

    Polymer nanocomposites have a great potential to be a dominant coating material in a wide range of applications in the automotive, aerospace, ship-making, construction, and pharmaceutical industries. However, how to realize design sustainability of this type of nanostructured materials and how to ensure the true optimality of the product quality and process performance in coating manufacturing remain as a mountaintop area. The major challenges arise from the intrinsic multiscale nature of the material-process-product system and the need to manipulate the high levels of complexity and uncertainty in design and manufacturing processes. This research centers on the development of a comprehensive multiscale computational methodology and a computer-aided tool set that can facilitate multifunctional nanocoating design and application from novel function envisioning and idea refinement, to knowledge discovery and design solution derivation, and further to performance testing in industrial applications and life cycle analysis. The principal idea is to achieve exceptional system performance through concurrent characterization and optimization of materials, product and associated manufacturing processes covering a wide range of length and time scales. Multiscale modeling and simulation techniques ranging from microscopic molecular modeling to classical continuum modeling are seamlessly coupled. The tight integration of different methods and theories at individual scales allows the prediction of macroscopic coating performance from the fundamental molecular behavior. Goal-oriented design is also pursued by integrating additional methods for bio-inspired dynamic optimization and computational task management that can be implemented in a hierarchical computing architecture. Furthermore, multiscale systems methodologies are developed to achieve the best possible material application towards sustainable manufacturing. Automotive coating manufacturing, that involves paint spay and

  11. Generalized multiscale finite element method. Symmetric interior penalty coupling

    KAUST Repository

    Efendiev, Yalchin R.; Galvis, Juan; Lazarov, Raytcho D.; Moon, M.; Sarkis, Marcus V.

    2013-01-01

    Motivated by applications to numerical simulations of flows in highly heterogeneous porous media, we develop multiscale finite element methods for second order elliptic equations. We discuss a multiscale model reduction technique in the framework of the discontinuous Galerkin finite element method. We propose two different finite element spaces on the coarse mesh. The first space is based on a local eigenvalue problem that uses an interior weighted L2-norm and a boundary weighted L2-norm for computing the "mass" matrix. The second choice is based on generation of a snapshot space and subsequent selection of a subspace of a reduced dimension. The approximation with these multiscale spaces is based on the discontinuous Galerkin finite element method framework. We investigate the stability and derive error estimates for the methods and further experimentally study their performance on a representative number of numerical examples. © 2013 Elsevier Inc.

  12. Generalized multiscale finite element method. Symmetric interior penalty coupling

    KAUST Repository

    Efendiev, Yalchin R.

    2013-12-01

    Motivated by applications to numerical simulations of flows in highly heterogeneous porous media, we develop multiscale finite element methods for second order elliptic equations. We discuss a multiscale model reduction technique in the framework of the discontinuous Galerkin finite element method. We propose two different finite element spaces on the coarse mesh. The first space is based on a local eigenvalue problem that uses an interior weighted L2-norm and a boundary weighted L2-norm for computing the "mass" matrix. The second choice is based on generation of a snapshot space and subsequent selection of a subspace of a reduced dimension. The approximation with these multiscale spaces is based on the discontinuous Galerkin finite element method framework. We investigate the stability and derive error estimates for the methods and further experimentally study their performance on a representative number of numerical examples. © 2013 Elsevier Inc.

  13. Multiscale thermohydrologic model: addressing variability and uncertainty at Yucca Mountain

    International Nuclear Information System (INIS)

    Buscheck, T; Rosenberg, N D; Gansemer, J D; Sun, Y

    2000-01-01

    Performance assessment and design evaluation require a modeling tool that simultaneously accounts for processes occurring at a scale of a few tens of centimeters around individual waste packages and emplacement drifts, and also on behavior at the scale of the mountain. Many processes and features must be considered, including non-isothermal, multiphase-flow in rock of variable saturation and thermal radiation in open cavities. Also, given the nature of the fractured rock at Yucca Mountain, a dual-permeability approach is needed to represent permeability. A monolithic numerical model with all these features requires too large a computational cost to be an effective simulation tool, one that is used to examine sensitivity to key model assumptions and parameters. We have developed a multi-scale modeling approach that effectively simulates 3D discrete-heat-source, mountain-scale thermohydrologic behavior at Yucca Mountain and captures the natural variability of the site consistent with what we know from site characterization and waste-package-to-waste-package variability in heat output. We describe this approach and present results examining the role of infiltration flux, the most important natural-system parameter with respect to how thermohydrologic behavior influences the performance of the repository

  14. Concurrent multiscale modeling of microstructural effects on localization behavior in finite deformation solid mechanics

    Science.gov (United States)

    Alleman, Coleman N.; Foulk, James W.; Mota, Alejandro; Lim, Hojun; Littlewood, David J.

    2018-02-01

    The heterogeneity in mechanical fields introduced by microstructure plays a critical role in the localization of deformation. To resolve this incipient stage of failure, it is therefore necessary to incorporate microstructure with sufficient resolution. On the other hand, computational limitations make it infeasible to represent the microstructure in the entire domain at the component scale. In this study, the authors demonstrate the use of concurrent multiscale modeling to incorporate explicit, finely resolved microstructure in a critical region while resolving the smoother mechanical fields outside this region with a coarser discretization to limit computational cost. The microstructural physics is modeled with a high-fidelity model that incorporates anisotropic crystal elasticity and rate-dependent crystal plasticity to simulate the behavior of a stainless steel alloy. The component-scale material behavior is treated with a lower fidelity model incorporating isotropic linear elasticity and rate-independent J2 plasticity. The microstructural and component scale subdomains are modeled concurrently, with coupling via the Schwarz alternating method, which solves boundary-value problems in each subdomain separately and transfers solution information between subdomains via Dirichlet boundary conditions. In this study, the framework is applied to model incipient localization in tensile specimens during necking.

  15. Multiscale crystal defect dynamics: A coarse-grained lattice defect model based on crystal microstructure

    Science.gov (United States)

    Lyu, Dandan; Li, Shaofan

    2017-10-01

    Crystal defects have microstructure, and this microstructure should be related to the microstructure of the original crystal. Hence each type of crystals may have similar defects due to the same failure mechanism originated from the same microstructure, if they are under the same loading conditions. In this work, we propose a multiscale crystal defect dynamics (MCDD) model that models defects by considering its intrinsic microstructure derived from the microstructure or material genome of the original perfect crystal. The main novelties of present work are: (1) the discrete exterior calculus and algebraic topology theory are used to construct a scale-up (coarse-grained) dual lattice model for crystal defects, which may represent all possible defect modes inside a crystal; (2) a higher order Cauchy-Born rule (up to the fourth order) is adopted to construct atomistic-informed constitutive relations for various defect process zones, and (3) an hierarchical strain gradient theory based finite element formulation is developed to support an hierarchical multiscale cohesive (process) zone model for various defects in a unified formulation. The efficiency of MCDD computational algorithm allows us to simulate dynamic defect evolution at large scale while taking into account atomistic interaction. The MCDD model has been validated by comparing of the results of MCDD simulations with that of molecular dynamics (MD) in the cases of nanoindentation and uniaxial tension. Numerical simulations have shown that MCDD model can predict dislocation nucleation induced instability and inelastic deformation, and thus it may provide an alternative solution to study crystal plasticity.

  16. Anatomy and Physiology of Multiscale Modeling and Simulation in Systems Medicine.

    Science.gov (United States)

    Mizeranschi, Alexandru; Groen, Derek; Borgdorff, Joris; Hoekstra, Alfons G; Chopard, Bastien; Dubitzky, Werner

    2016-01-01

    Systems medicine is the application of systems biology concepts, methods, and tools to medical research and practice. It aims to integrate data and knowledge from different disciplines into biomedical models and simulations for the understanding, prevention, cure, and management of complex diseases. Complex diseases arise from the interactions among disease-influencing factors across multiple levels of biological organization from the environment to molecules. To tackle the enormous challenges posed by complex diseases, we need a modeling and simulation framework capable of capturing and integrating information originating from multiple spatiotemporal and organizational scales. Multiscale modeling and simulation in systems medicine is an emerging methodology and discipline that has already demonstrated its potential in becoming this framework. The aim of this chapter is to present some of the main concepts, requirements, and challenges of multiscale modeling and simulation in systems medicine.

  17. Multiscale Mathematical Modeling in Dental Tissue Engineering: Toward Computer-Aided Design of a Regenerative System Based on Hydroxyapatite Granules, Focussing on Early and Mid-Term Stiffness Recovery.

    Science.gov (United States)

    Scheiner, Stefan; Komlev, Vladimir S; Gurin, Alexey N; Hellmich, Christian

    2016-01-01

    We here explore for the very first time how an advanced multiscale mathematical modeling approach may support the design of a provenly successful tissue engineering concept for mandibular bone. The latter employs double-porous, potentially cracked, single millimeter-sized granules packed into an overall conglomerate-type scaffold material, which is then gradually penetrated and partially replaced by newly grown bone tissue. During this process, the newly developing scaffold-bone compound needs to attain the stiffness of mandibular bone under normal physiological conditions. In this context, the question arises how the compound stiffness is driven by the key design parameters of the tissue engineering system: macroporosity, crack density, as well as scaffold resorption/bone formation rates. We here tackle this question by combining the latest state-of-the-art mathematical modeling techniques in the field of multiscale micromechanics, into an unprecedented suite of highly efficient, semi-analytically defined computation steps resolving several levels of hierarchical organization, from the millimeter- down to the nanometer-scale. This includes several types of homogenization schemes, namely such for porous polycrystals with elongated solid elements, for cracked matrix-inclusion composites, as well as for assemblies of coated spherical compounds. Together with the experimentally known stiffnesses of hydroxyapatite crystals and mandibular bone tissue, the new mathematical model suggests that early stiffness recovery (i.e., within several weeks) requires total avoidance of microcracks in the hydroxyapatite scaffolds, while mid-term stiffness recovery (i.e., within several months) is additionally promoted by provision of small granule sizes, in combination with high bone formation and low scaffold resorption rates.

  18. Multiscale mathematical modeling in dental tissue engineering: towards computer-aided design of a regenerative system based on hydroxyapatite granules, focusing on early and mid-term stiffness recovery

    Directory of Open Access Journals (Sweden)

    Stefan Scheiner

    2016-09-01

    Full Text Available We here explore for the very first time how an advanced multiscale mathematical modeling approach may support the design of a provenly successful tissue engineering concept for mandibular bone. The latter employs double-porous, potentially cracked, single millimeter-sized granules packed into an overall scaffold material, which is then gradually penetrated and partially replaced by newly grown bone tissue. During this process, the newly developing scaffold-bone compound needs to attain the stiffness of mandibular bone under normal physiological conditions; and the question arises how the compound stiffness is driven by the key design parameters of the tissue engineering system: macroporosity, crack density, as well as scaffold resorption/bone formation rates. We here tackle this question by combining the latest state-of-the-art mathematical modeling techniques in the field of multiscale micromechanics, into an unprecedented suite of highly efficient, semi-analytically defined computation steps resolving several levels of hierarchical organization, from the millimeter down to the nanometer scale. This includes several types of homogenization schemes, namely such for porous polycrystals with elongated solid elements, for cracked matrix-inclusion composites, as well as for assemblies of coated spherical compounds. Together with the experimentally known stiffnesses of hydroxyapatite crystals and mandibular bone tissue, the new mathematical model suggests that early stiffness recovery (i.e within several weeks requires total avoidance of microcracks in the hydroxyapatite scaffolds, while mid-term stiffness recovery (i.e. within several months can also be achieved through provision of small granule sizes, in combination with high bone formation and low scaffold resorption rates.

  19. Multiscale modeling of pedestrian dynamics

    CERN Document Server

    Cristiani, Emiliano; Tosin, Andrea

    2014-01-01

    This book presents mathematical models and numerical simulations of crowd dynamics. The core topic is the development of a new multiscale paradigm, which bridges the microscopic and macroscopic scales taking the most from each of them for capturing the relevant clues of complexity of crowds. The background idea is indeed that most of the complex trends exhibited by crowds are due to an intrinsic interplay between individual and collective behaviors. The modeling approach promoted in this book pursues actively this intuition and profits from it for designing general mathematical structures susceptible of application also in fields different from the inspiring original one. The book considers also the two most traditional points of view: the microscopic one, in which pedestrians are tracked individually, and the macroscopic one, in which pedestrians are assimilated to a continuum. Selected existing models are critically analyzed. The work is addressed to researchers and graduate students.

  20. Multi-scale modeling of dispersed gas-liquid two-phase flow

    NARCIS (Netherlands)

    Deen, N.G.; Sint Annaland, van M.; Kuipers, J.A.M.

    2004-01-01

    In this work the concept of multi-scale modeling is demonstrated. The idea of this approach is to use different levels of modeling, each developed to study phenomena at a certain length scale. Information obtained at the level of small length scales can be used to provide closure information at the

  1. Bayesian data assimilation for stochastic multiscale models of transport in porous media.

    Energy Technology Data Exchange (ETDEWEB)

    Marzouk, Youssef M. (Massachusetts Institute of Technology, Cambridge, MA); van Bloemen Waanders, Bart Gustaaf (Sandia National Laboratories, Albuquerque NM); Parno, Matthew (Massachusetts Institute of Technology, Cambridge, MA); Ray, Jaideep; Lefantzi, Sophia; Salazar, Luke (Sandia National Laboratories, Albuquerque NM); McKenna, Sean Andrew (Sandia National Laboratories, Albuquerque NM); Klise, Katherine A. (Sandia National Laboratories, Albuquerque NM)

    2011-10-01

    filter. We conclude with a demonstration of the use of multiscale stochastic finite elements to reconstruct permeability fields. This method, though computationally intensive, is general and can be used for multiscale inference in cases where a subgrid model cannot be constructed.

  2. Mechanical Properties of Graphene Nanoplatelet/Carbon Fiber/Epoxy Hybrid Composites: Multiscale Modeling and Experiments

    Science.gov (United States)

    Hadden, C. M.; Klimek-McDonald, D. R.; Pineda, E. J.; King, J. A.; Reichanadter, A. M.; Miskioglu, I.; Gowtham, S.; Odegard, G. M.

    2015-01-01

    Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.

  3. Mechanical Properties of Graphene Nanoplatelet Carbon Fiber Epoxy Hybrid Composites: Multiscale Modeling and Experiments

    Science.gov (United States)

    Hadden, Cameron M.; Klimek-McDonald, Danielle R.; Pineda, Evan J.; King, Julie A.; Reichanadter, Alex M.; Miskioglu, Ibrahim; Gowtham, S.; Odegard, Gregory M.

    2015-01-01

    Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.

  4. Computational modeling and engineering in pediatric and congenital heart disease.

    Science.gov (United States)

    Marsden, Alison L; Feinstein, Jeffrey A

    2015-10-01

    Recent methodological advances in computational simulations are enabling increasingly realistic simulations of hemodynamics and physiology, driving increased clinical utility. We review recent developments in the use of computational simulations in pediatric and congenital heart disease, describe the clinical impact in modeling in single-ventricle patients, and provide an overview of emerging areas. Multiscale modeling combining patient-specific hemodynamics with reduced order (i.e., mathematically and computationally simplified) circulatory models has become the de-facto standard for modeling local hemodynamics and 'global' circulatory physiology. We review recent advances that have enabled faster solutions, discuss new methods (e.g., fluid structure interaction and uncertainty quantification), which lend realism both computationally and clinically to results, highlight novel computationally derived surgical methods for single-ventricle patients, and discuss areas in which modeling has begun to exert its influence including Kawasaki disease, fetal circulation, tetralogy of Fallot (and pulmonary tree), and circulatory support. Computational modeling is emerging as a crucial tool for clinical decision-making and evaluation of novel surgical methods and interventions in pediatric cardiology and beyond. Continued development of modeling methods, with an eye towards clinical needs, will enable clinical adoption in a wide range of pediatric and congenital heart diseases.

  5. Multiphysics/multiscale multifluid computations

    International Nuclear Information System (INIS)

    Yadigaroglu, George

    2014-01-01

    Regarding experimentation, interesting examples of multi-scale approaches are found: the small-scale experiments to understand the mechanisms of counter-current flow limitations (CCFL) such as the growth of instabilities on films, droplet entrainment, etc; meso-scale experiments to quantify the CCFL conditions in typical geometries such as tubes and gaps between parallel plates, and finally full-scale experimentation in a typical reactor geometry - the UPTF tests. Another example is the mixing of the atmosphere produced by plumes and jets in a reactor containment: one needs first basic turbulence information that can be obtained at the microscopic level; follow medium-scale experiments to understand the behaviour of jets and plumes; finally reactor-scale tests can be conducted in facilities such as PANDA at PSI, in Switzerland to study the phenomena at large scale

  6. Multi-scale multi-physics computational chemistry simulation based on ultra-accelerated quantum chemical molecular dynamics method for structural materials in boiling water reactor

    International Nuclear Information System (INIS)

    Miyamoto, Akira; Sato, Etsuko; Sato, Ryo; Inaba, Kenji; Hatakeyama, Nozomu

    2014-01-01

    In collaboration with experimental experts we have reported in the present conference (Hatakeyama, N. et al., “Experiment-integrated multi-scale, multi-physics computational chemistry simulation applied to corrosion behaviour of BWR structural materials”) the results of multi-scale multi-physics computational chemistry simulations applied to the corrosion behaviour of BWR structural materials. In macro-scale, a macroscopic simulator of anode polarization curve was developed to solve the spatially one-dimensional electrochemical equations on the material surface in continuum level in order to understand the corrosion behaviour of typical BWR structural material, SUS304. The experimental anode polarization behaviours of each pure metal were reproduced by fitting all the rates of electrochemical reactions and then the anode polarization curve of SUS304 was calculated by using the same parameters and found to reproduce the experimental behaviour successfully. In meso-scale, a kinetic Monte Carlo (KMC) simulator was applied to an actual-time simulation of the morphological corrosion behaviour under the influence of an applied voltage. In micro-scale, an ultra-accelerated quantum chemical molecular dynamics (UA-QCMD) code was applied to various metallic oxide surfaces of Fe 2 O 3 , Fe 3 O 4 , Cr 2 O 3 modelled as same as water molecules and dissolved metallic ions on the surfaces, then the dissolution and segregation behaviours were successfully simulated dynamically by using UA-QCMD. In this paper we describe details of the multi-scale, multi-physics computational chemistry method especially the UA-QCMD method. This method is approximately 10,000,000 times faster than conventional first-principles molecular dynamics methods based on density-functional theory (DFT), and the accuracy was also validated for various metals and metal oxides compared with DFT results. To assure multi-scale multi-physics computational chemistry simulation based on the UA-QCMD method for

  7. International Conference on Multiscale Methods and Partial Differential Equations.

    Energy Technology Data Exchange (ETDEWEB)

    Thomas Hou

    2006-12-12

    The International Conference on Multiscale Methods and Partial Differential Equations (ICMMPDE for short) was held at IPAM, UCLA on August 26-27, 2005. The conference brought together researchers, students and practitioners with interest in the theoretical, computational and practical aspects of multiscale problems and related partial differential equations. The conference provided a forum to exchange and stimulate new ideas from different disciplines, and to formulate new challenging multiscale problems that will have impact in applications.

  8. A Multiscale Model for Virus Capsid Dynamics

    Directory of Open Access Journals (Sweden)

    Changjun Chen

    2010-01-01

    Full Text Available Viruses are infectious agents that can cause epidemics and pandemics. The understanding of virus formation, evolution, stability, and interaction with host cells is of great importance to the scientific community and public health. Typically, a virus complex in association with its aquatic environment poses a fabulous challenge to theoretical description and prediction. In this work, we propose a differential geometry-based multiscale paradigm to model complex biomolecule systems. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum domain of the fluid mechanical description of the aquatic environment from the microscopic discrete domain of the atomistic description of the biomolecule. A multiscale action functional is constructed as a unified framework to derive the governing equations for the dynamics of different scales. We show that the classical Navier-Stokes equation for the fluid dynamics and Newton's equation for the molecular dynamics can be derived from the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows.

  9. A multiscale model for virus capsid dynamics.

    Science.gov (United States)

    Chen, Changjun; Saxena, Rishu; Wei, Guo-Wei

    2010-01-01

    Viruses are infectious agents that can cause epidemics and pandemics. The understanding of virus formation, evolution, stability, and interaction with host cells is of great importance to the scientific community and public health. Typically, a virus complex in association with its aquatic environment poses a fabulous challenge to theoretical description and prediction. In this work, we propose a differential geometry-based multiscale paradigm to model complex biomolecule systems. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum domain of the fluid mechanical description of the aquatic environment from the microscopic discrete domain of the atomistic description of the biomolecule. A multiscale action functional is constructed as a unified framework to derive the governing equations for the dynamics of different scales. We show that the classical Navier-Stokes equation for the fluid dynamics and Newton's equation for the molecular dynamics can be derived from the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows.

  10. Development and application of a multiscale model for the magnetic fusion edge plasma region

    International Nuclear Information System (INIS)

    Hasenbeck, Felix Martin Michael

    2016-01-01

    Plasma edge particle and energy transport perpendicular to the magnetic field plays a decisive role for the performance and lifetime of a magnetic fusion reactor. For the particles, classical and neoclassical theories underestimate the associated radial transport by at least an order of magnitude. Drift fluid models, including mesoscale processes on scales down to tenths of millimeters and microseconds, account for the experimentally found level of radial transport; however, numerical simulations for typical reactor scales (of the order of seconds and centimeters) are computationally very expensive. Large scale code simulations are less costly but usually lack an adequate model for the radial transport. The multiscale model presented in this work aims at improving the description of radial particle transport in large scale codes by including the effects of averaged local drift fluid dynamics on the macroscale profiles. The multiscale balances are derived from a generic multiscale model for a fluid, using the Braginskii closure for a collisional, magnetized plasma, and the assumptions of the B2 code model (macroscale balances) and the model of the local version of the drift fluid code ATTEMPT (mesoscale balances). A combined concurrent-sequential coupling procedure is developed for the implementation of the multiscale model within a coupled code system. An algorithm for the determination of statistically stationary states and adequate averaging intervals for the mesoscale data is outlined and tested, proving that it works consistently and efficiently. The general relation between mesoscale and macroscale dynamics is investigated exemplarily by means of a passive scalar system. While mesoscale processes are convective in this system, earlier studies for small Kubo numbers K<<1 have shown that the macroscale behavior is diffusive. In this work it is demonstrated by numerical experiments that also in the regime of large Kubo numbers K<<1 the macroscale transport

  11. Development and application of a multiscale model for the magnetic fusion edge plasma region

    Energy Technology Data Exchange (ETDEWEB)

    Hasenbeck, Felix Martin Michael

    2016-07-01

    Plasma edge particle and energy transport perpendicular to the magnetic field plays a decisive role for the performance and lifetime of a magnetic fusion reactor. For the particles, classical and neoclassical theories underestimate the associated radial transport by at least an order of magnitude. Drift fluid models, including mesoscale processes on scales down to tenths of millimeters and microseconds, account for the experimentally found level of radial transport; however, numerical simulations for typical reactor scales (of the order of seconds and centimeters) are computationally very expensive. Large scale code simulations are less costly but usually lack an adequate model for the radial transport. The multiscale model presented in this work aims at improving the description of radial particle transport in large scale codes by including the effects of averaged local drift fluid dynamics on the macroscale profiles. The multiscale balances are derived from a generic multiscale model for a fluid, using the Braginskii closure for a collisional, magnetized plasma, and the assumptions of the B2 code model (macroscale balances) and the model of the local version of the drift fluid code ATTEMPT (mesoscale balances). A combined concurrent-sequential coupling procedure is developed for the implementation of the multiscale model within a coupled code system. An algorithm for the determination of statistically stationary states and adequate averaging intervals for the mesoscale data is outlined and tested, proving that it works consistently and efficiently. The general relation between mesoscale and macroscale dynamics is investigated exemplarily by means of a passive scalar system. While mesoscale processes are convective in this system, earlier studies for small Kubo numbers K<<1 have shown that the macroscale behavior is diffusive. In this work it is demonstrated by numerical experiments that also in the regime of large Kubo numbers K<<1 the macroscale transport

  12. Advanced computational modelling for drying processes – A review

    International Nuclear Information System (INIS)

    Defraeye, Thijs

    2014-01-01

    Highlights: • Understanding the product dehydration process is a key aspect in drying technology. • Advanced modelling thereof plays an increasingly important role for developing next-generation drying technology. • Dehydration modelling should be more energy-oriented. • An integrated “nexus” modelling approach is needed to produce more energy-smart products. • Multi-objective process optimisation requires development of more complete multiphysics models. - Abstract: Drying is one of the most complex and energy-consuming chemical unit operations. R and D efforts in drying technology have skyrocketed in the past decades, as new drivers emerged in this industry next to procuring prime product quality and high throughput, namely reduction of energy consumption and carbon footprint as well as improving food safety and security. Solutions are sought in optimising existing technologies or developing new ones which increase energy and resource efficiency, use renewable energy, recuperate waste heat and reduce product loss, thus also the embodied energy therein. Novel tools are required to push such technological innovations and their subsequent implementation. Particularly computer-aided drying process engineering has a large potential to develop next-generation drying technology, including more energy-smart and environmentally-friendly products and dryers systems. This review paper deals with rapidly emerging advanced computational methods for modelling dehydration of porous materials, particularly for foods. Drying is approached as a combined multiphysics, multiscale and multiphase problem. These advanced methods include computational fluid dynamics, several multiphysics modelling methods (e.g. conjugate modelling), multiscale modelling and modelling of material properties and the associated propagation of material property variability. Apart from the current challenges for each of these, future perspectives should be directed towards material property

  13. Multiscale modelling and experimentation of hydrogen embrittlement in aerospace materials

    Science.gov (United States)

    Jothi, Sathiskumar

    Pulse plated nickel and nickel based superalloys have been used extensively in the Ariane 5 space launcher engines. Large structural Ariane 5 space launcher engine components such as combustion chambers with complex microstructures have usually been manufactured using electrodeposited nickel with advanced pulse plating techniques with smaller parts made of nickel based superalloys joined or welded to the structure to fabricate Ariane 5 space launcher engines. One of the major challenges in manufacturing these space launcher components using newly developed materials is a fundamental understanding of how different materials and microstructures react with hydrogen during welding which can lead to hydrogen induced cracking. The main objective of this research has been to examine and interpret the effects of microstructure on hydrogen diffusion and hydrogen embrittlement in (i) nickel based superalloy 718, (ii) established and (iii) newly developed grades of pulse plated nickel used in the Ariane 5 space launcher engine combustion chamber. Also, the effect of microstructures on hydrogen induced hot and cold cracking and weldability of three different grades of pulse plated nickel were investigated. Multiscale modelling and experimental methods have been used throughout. The effect of microstructure on hydrogen embrittlement was explored using an original multiscale numerical model (exploiting synthetic and real microstructures) and a wide range of material characterization techniques including scanning electron microscopy, 2D and 3D electron back scattering diffraction, in-situ and ex-situ hydrogen charged slow strain rate tests, thermal spectroscopy analysis and the Varestraint weldability test. This research shows that combined multiscale modelling and experimentation is required for a fundamental understanding of microstructural effects in hydrogen embrittlement in these materials. Methods to control the susceptibility to hydrogen induced hot and cold cracking and

  14. Developing a novel hierarchical approach for multiscale structural reliability predictions for ultra-high consequence applications

    Energy Technology Data Exchange (ETDEWEB)

    Emery, John M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Coffin, Peter [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Robbins, Brian A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Carroll, Jay [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Field, Richard V. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jeremy Yoo, Yung Suk [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kacher, Josh [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-09-01

    Microstructural variabilities are among the predominant sources of uncertainty in structural performance and reliability. We seek to develop efficient algorithms for multiscale calcu- lations for polycrystalline alloys such as aluminum alloy 6061-T6 in environments where ductile fracture is the dominant failure mode. Our approach employs concurrent multiscale methods, but does not focus on their development. They are a necessary but not sufficient ingredient to multiscale reliability predictions. We have focused on how to efficiently use concurrent models for forward propagation because practical applications cannot include fine-scale details throughout the problem domain due to exorbitant computational demand. Our approach begins with a low-fidelity prediction at the engineering scale that is sub- sequently refined with multiscale simulation. The results presented in this report focus on plasticity and damage at the meso-scale, efforts to expedite Monte Carlo simulation with mi- crostructural considerations, modeling aspects regarding geometric representation of grains and second-phase particles, and contrasting algorithms for scale coupling.

  15. Multiscale high-order/low-order (HOLO) algorithms and applications

    International Nuclear Information System (INIS)

    Chacón, L.; Chen, G.; Knoll, D.A.; Newman, C.; Park, H.; Taitano, W.; Willert, J.A.; Womeldorff, G.

    2017-01-01

    We review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.

  16. Multiscale high-order/low-order (HOLO) algorithms and applications

    Energy Technology Data Exchange (ETDEWEB)

    Chacón, L., E-mail: chacon@lanl.gov [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Chen, G.; Knoll, D.A.; Newman, C.; Park, H.; Taitano, W. [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Willert, J.A. [Institute for Defense Analyses, Alexandria, VA 22311 (United States); Womeldorff, G. [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States)

    2017-02-01

    We review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.

  17. Modeling multiscale evolution of numerous voids in shocked brittle material.

    Science.gov (United States)

    Yu, Yin; Wang, Wenqiang; He, Hongliang; Lu, Tiecheng

    2014-04-01

    The influence of the evolution of numerous voids on macroscopic properties of materials is a multiscale problem that challenges computational research. A shock-wave compression model for brittle material, which can obtain both microscopic evolution and macroscopic shock properties, was developed using discrete element methods (lattice model). Using a model interaction-parameter-mapping procedure, qualitative features, as well as trends in the calculated shock-wave profiles, are shown to agree with experimental results. The shock wave splits into an elastic wave and a deformation wave in porous brittle materials, indicating significant shock plasticity. Void collapses in the deformation wave were the natural reason for volume shrinkage and deformation. However, media slippage and rotation deformations indicated by complex vortex patterns composed of relative velocity vectors were also confirmed as an important source of shock plasticity. With increasing pressure, the contribution from slippage deformation to the final plastic strain increased. Porosity was found to determine the amplitude of the elastic wave; porosity and shock stress together determine propagation speed of the deformation wave, as well as stress and strain on the final equilibrium state. Thus, shock behaviors of porous brittle material can be systematically designed for specific applications.

  18. A Multiscale Enrichment Procedure for Nonlinear Monotone Operators

    KAUST Repository

    Efendiev, Yalchin R.

    2014-03-11

    In this paper, multiscale finite element methods (MsFEMs) and domain decomposition techniques are developed for a class of nonlinear elliptic problems with high-contrast coefficients. In the process, existing work on linear problems [Y. Efendiev, J. Galvis, R. Lazarov, S. Margenov and J. Ren, Robust two-level domain decomposition preconditioners for high-contrast anisotropic flows in multiscale media. Submitted.; Y. Efendiev, J. Galvis and X. Wu, J. Comput. Phys. 230 (2011) 937–955; J. Galvis and Y. Efendiev, SIAM Multiscale Model. Simul. 8 (2010) 1461–1483.] is extended to treat a class of nonlinear elliptic operators. The proposed method requires the solutions of (small dimension and local) nonlinear eigenvalue problems in order to systematically enrich the coarse solution space. Convergence of the method is shown to relate to the dimension of the coarse space (due to the enrichment procedure) as well as the coarse mesh size. In addition, it is shown that the coarse mesh spaces can be effectively used in two-level domain decomposition preconditioners. A number of numerical results are presented to complement the analysis.

  19. Multi-Scale Modelling of the Gamma Radiolysis of Nitrate Solutions

    OpenAIRE

    Horne, Gregory; Donoclift, Thomas; Sims, Howard E.; M. Orr, Robin; Pimblott, Simon

    2016-01-01

    A multi-scale modelling approach has been developed for the extended timescale long-term radiolysis of aqueous systems. The approach uses a combination of stochastic track structure and track chemistry as well as deterministic homogeneous chemistry techniques and involves four key stages; radiation track structure simulation, the subsequent physicochemical processes, nonhomogeneous diffusion-reaction kinetic evolution, and homogeneous bulk chemistry modelling. The first three components model...

  20. Multiscale modeling of θ' precipitation in Al-Cu binary alloys

    International Nuclear Information System (INIS)

    Vaithyanathan, V.; Wolverton, C.; Chen, L.Q.

    2004-01-01

    We present a multiscale model for studying the growth and coarsening of θ' precipitates in Al-Cu alloys. Our approach utilizes a novel combination of the mesoscale phase-field method with atomistic approaches such as first-principles total energy and linear response calculations, as well as a mixed-space cluster expansion coupled with Monte Carlo simulations. We give quantitative first-principles predictions of: (i) bulk energetics of the Al-Cu solid solution and θ ' precipitate phases, (ii) interfacial energies of the coherent and semi-coherent θ ' /Al interfaces, and (iii) stress-free misfit strains and coherency strain energies of the θ ' /Al system. These first-principles data comprise all the necessary energetic information to construct our phase-field model of microstructural evolution. Using our multiscale approach, we elucidate the effects of various energetic contributions on the equilibrium shape of θ ' precipitates, finding that both the elastic energy and interfacial energy anisotropy contributions play critical roles in determining the aspect ratio of θ ' precipitates. Additionally, we have performed a quantitative study of the morphology of two-dimensional multi-precipitate microstructures during growth and coarsening, and compared the calculated results with experimentally observed morphologies. Our multiscale first-principles/phase-field method is completely general and should therefore be applicable to a wide variety of problems in microstructural evolution

  1. A multiscale modelling approach to understand atherosclerosis formation: A patient-specific case study in the aortic bifurcation

    Science.gov (United States)

    Alimohammadi, Mona; Pichardo-Almarza, Cesar; Agu, Obiekezie; Díaz-Zuccarini, Vanessa

    2017-01-01

    Atherogenesis, the formation of plaques in the wall of blood vessels, starts as a result of lipid accumulation (low-density lipoprotein cholesterol) in the vessel wall. Such accumulation is related to the site of endothelial mechanotransduction, the endothelial response to mechanical stimuli and haemodynamics, which determines biochemical processes regulating the vessel wall permeability. This interaction between biomechanical and biochemical phenomena is complex, spanning different biological scales and is patient-specific, requiring tools able to capture such mathematical and biological complexity in a unified framework. Mathematical models offer an elegant and efficient way of doing this, by taking into account multifactorial and multiscale processes and mechanisms, in order to capture the fundamentals of plaque formation in individual patients. In this study, a mathematical model to understand plaque and calcification locations is presented: this model provides a strong interpretability and physical meaning through a multiscale, complex index or metric (the penetration site of low-density lipoprotein cholesterol, expressed as volumetric flux). Computed tomography scans of the aortic bifurcation and iliac arteries are analysed and compared with the results of the multifactorial model. The results indicate that the model shows potential to predict the majority of the plaque locations, also not predicting regions where plaques are absent. The promising results from this case study provide a proof of concept that can be applied to a larger patient population. PMID:28427316

  2. Multiscale model for pedestrian and infection dynamics during air travel

    Science.gov (United States)

    Namilae, Sirish; Derjany, Pierrot; Mubayi, Anuj; Scotch, Mathew; Srinivasan, Ashok

    2017-05-01

    In this paper we develop a multiscale model combining social-force-based pedestrian movement with a population level stochastic infection transmission dynamics framework. The model is then applied to study the infection transmission within airplanes and the transmission of the Ebola virus through casual contacts. Drastic limitations on air-travel during epidemics, such as during the 2014 Ebola outbreak in West Africa, carry considerable economic and human costs. We use the computational model to evaluate the effects of passenger movement within airplanes and air-travel policies on the geospatial spread of infectious diseases. We find that boarding policy by an airline is more critical for infection propagation compared to deplaning policy. Enplaning in two sections resulted in fewer infections than the currently followed strategy with multiple zones. In addition, we found that small commercial airplanes are better than larger ones at reducing the number of new infections in a flight. Aggregated results indicate that passenger movement strategies and airplane size predicted through these network models can have significant impact on an event like the 2014 Ebola epidemic. The methodology developed here is generic and can be readily modified to incorporate the impact from the outbreak of other directly transmitted infectious diseases.

  3. Multiscale sampling model for motion integration.

    Science.gov (United States)

    Sherbakov, Lena; Yazdanbakhsh, Arash

    2013-09-30

    Biologically plausible strategies for visual scene integration across spatial and temporal domains continues to be a challenging topic. The fundamental question we address is whether classical problems in motion integration, such as the aperture problem, can be solved in a model that samples the visual scene at multiple spatial and temporal scales in parallel. We hypothesize that fast interareal connections that allow feedback of information between cortical layers are the key processes that disambiguate motion direction. We developed a neural model showing how the aperture problem can be solved using different spatial sampling scales between LGN, V1 layer 4, V1 layer 6, and area MT. Our results suggest that multiscale sampling, rather than feedback explicitly, is the key process that gives rise to end-stopped cells in V1 and enables area MT to solve the aperture problem without the need for calculating intersecting constraints or crafting intricate patterns of spatiotemporal receptive fields. Furthermore, the model explains why end-stopped cells no longer emerge in the absence of V1 layer 6 activity (Bolz & Gilbert, 1986), why V1 layer 4 cells are significantly more end-stopped than V1 layer 6 cells (Pack, Livingstone, Duffy, & Born, 2003), and how it is possible to have a solution to the aperture problem in area MT with no solution in V1 in the presence of driving feedback. In summary, while much research in the field focuses on how a laminar architecture can give rise to complicated spatiotemporal receptive fields to solve problems in the motion domain, we show that one can reframe motion integration as an emergent property of multiscale sampling achieved concurrently within lamina and across multiple visual areas.

  4. Multi-scale salient feature extraction on mesh models

    KAUST Repository

    Yang, Yongliang; Shen, ChaoHui

    2012-01-01

    We present a new method of extracting multi-scale salient features on meshes. It is based on robust estimation of curvature on multiple scales. The coincidence between salient feature and the scale of interest can be established straightforwardly, where detailed feature appears on small scale and feature with more global shape information shows up on large scale. We demonstrate this multi-scale description of features accords with human perception and can be further used for several applications as feature classification and viewpoint selection. Experiments exhibit that our method as a multi-scale analysis tool is very helpful for studying 3D shapes. © 2012 Springer-Verlag.

  5. Multiscale Simulation of Breaking Wave Impacts

    DEFF Research Database (Denmark)

    Lindberg, Ole

    compare reasonably well. The incompressible and inviscid ALE-WLS model is coupled with the potential flow model of Engsig-Karup et al. [2009], to perform multiscale calculation of breaking wave impacts on a vertical breakwater. The potential flow model provides accurate calculation of the wave...... with a potential flow model to provide multiscale calculation of forces from breaking wave impacts on structures....

  6. Multi-scale habitat selection modeling: A review and outlook

    Science.gov (United States)

    Kevin McGarigal; Ho Yi Wan; Kathy A. Zeller; Brad C. Timm; Samuel A. Cushman

    2016-01-01

    Scale is the lens that focuses ecological relationships. Organisms select habitat at multiple hierarchical levels and at different spatial and/or temporal scales within each level. Failure to properly address scale dependence can result in incorrect inferences in multi-scale habitat selection modeling studies.

  7. Topology Optimization Using Multiscale Finite Element Method for High-Contrast Media

    DEFF Research Database (Denmark)

    Lazarov, Boyan Stefanov

    2014-01-01

    The focus of this paper is on the applicability of multiscale finite element coarse spaces for reducing the computational burden in topology optimization. The coarse spaces are obtained by solving a set of local eigenvalue problems on overlapping patches covering the computational domain. The app......The focus of this paper is on the applicability of multiscale finite element coarse spaces for reducing the computational burden in topology optimization. The coarse spaces are obtained by solving a set of local eigenvalue problems on overlapping patches covering the computational domain...

  8. Multi-scale modelling of non-uniform consolidation of uncured toughened unidirectional prepregs

    Science.gov (United States)

    Sorba, G.; Binetruy, C.; Syerko, E.; Leygue, A.; Comas-Cardona, S.; Belnoue, J. P.-H.; Nixon-Pearson, O. J.; Ivanov, D. S.; Hallett, S. R.; Advani, S. G.

    2018-05-01

    the sample edge with the multi-scale compaction model after one time step [3]. The ply distortion and resin flow observed in Fig.1 is qualitatively retrieved by the computational model.

  9. Training Systems Modelers through the Development of a Multi-scale Chagas Disease Risk Model

    Science.gov (United States)

    Hanley, J.; Stevens-Goodnight, S.; Kulkarni, S.; Bustamante, D.; Fytilis, N.; Goff, P.; Monroy, C.; Morrissey, L. A.; Orantes, L.; Stevens, L.; Dorn, P.; Lucero, D.; Rios, J.; Rizzo, D. M.

    2012-12-01

    The goal of our NSF-sponsored Division of Behavioral and Cognitive Sciences grant is to create a multidisciplinary approach to develop spatially explicit models of vector-borne disease risk using Chagas disease as our model. Chagas disease is a parasitic disease endemic to Latin America that afflicts an estimated 10 million people. The causative agent (Trypanosoma cruzi) is most commonly transmitted to humans by blood feeding triatomine insect vectors. Our objectives are: (1) advance knowledge on the multiple interacting factors affecting the transmission of Chagas disease, and (2) provide next generation genomic and spatial analysis tools applicable to the study of other vector-borne diseases worldwide. This funding is a collaborative effort between the RSENR (UVM), the School of Engineering (UVM), the Department of Biology (UVM), the Department of Biological Sciences (Loyola (New Orleans)) and the Laboratory of Applied Entomology and Parasitology (Universidad de San Carlos). Throughout this five-year study, multi-educational groups (i.e., high school, undergraduate, graduate, and postdoctoral) will be trained in systems modeling. This systems approach challenges students to incorporate environmental, social, and economic as well as technical aspects and enables modelers to simulate and visualize topics that would either be too expensive, complex or difficult to study directly (Yasar and Landau 2003). We launch this research by developing a set of multi-scale, epidemiological models of Chagas disease risk using STELLA® software v.9.1.3 (isee systems, inc., Lebanon, NH). We use this particular system dynamics software as a starting point because of its simple graphical user interface (e.g., behavior-over-time graphs, stock/flow diagrams, and causal loops). To date, high school and undergraduate students have created a set of multi-scale (i.e., homestead, village, and regional) disease models. Modeling the system at multiple spatial scales forces recognition that

  10. Density-Dependent Formulation of Dispersion-Repulsion Interactions in Hybrid Multiscale Quantum/Molecular Mechanics (QM/MM) Models.

    Science.gov (United States)

    Curutchet, Carles; Cupellini, Lorenzo; Kongsted, Jacob; Corni, Stefano; Frediani, Luca; Steindal, Arnfinn Hykkerud; Guido, Ciro A; Scalmani, Giovanni; Mennucci, Benedetta

    2018-03-13

    Mixed multiscale quantum/molecular mechanics (QM/MM) models are widely used to explore the structure, reactivity, and electronic properties of complex chemical systems. Whereas such models typically include electrostatics and potentially polarization in so-called electrostatic and polarizable embedding approaches, respectively, nonelectrostatic dispersion and repulsion interactions are instead commonly described through classical potentials despite their quantum mechanical origin. Here we present an extension of the Tkatchenko-Scheffler semiempirical van der Waals (vdW TS ) scheme aimed at describing dispersion and repulsion interactions between quantum and classical regions within a QM/MM polarizable embedding framework. Starting from the vdW TS expression, we define a dispersion and a repulsion term, both of them density-dependent and consistently based on a Lennard-Jones-like potential. We explore transferable atom type-based parametrization strategies for the MM parameters, based on either vdW TS calculations performed on isolated fragments or on a direct estimation of the parameters from atomic polarizabilities taken from a polarizable force field. We investigate the performance of the implementation by computing self-consistent interaction energies for the S22 benchmark set, designed to represent typical noncovalent interactions in biological systems, in both equilibrium and out-of-equilibrium geometries. Overall, our results suggest that the present implementation is a promising strategy to include dispersion and repulsion in multiscale QM/MM models incorporating their explicit dependence on the electronic density.

  11. Asymptotic Expansion Homogenization for Multiscale Nuclear Fuel Analysis

    International Nuclear Information System (INIS)

    2015-01-01

    Engineering scale nuclear fuel performance simulations can benefit by utilizing high-fidelity models running at a lower length scale. Lower length-scale models provide a detailed view of the material behavior that is used to determine the average material response at the macroscale. These lower length-scale calculations may provide insight into material behavior where experimental data is sparse or nonexistent. This multiscale approach is especially useful in the nuclear field, since irradiation experiments are difficult and expensive to conduct. The lower length-scale models complement the experiments by influencing the types of experiments required and by reducing the total number of experiments needed. This multiscale modeling approach is a central motivation in the development of the BISON-MARMOT fuel performance codes at Idaho National Laboratory. These codes seek to provide more accurate and predictive solutions for nuclear fuel behavior. One critical aspect of multiscale modeling is the ability to extract the relevant information from the lower length-scale sim- ulations. One approach, the asymptotic expansion homogenization (AEH) technique, has proven to be an effective method for determining homogenized material parameters. The AEH technique prescribes a system of equations to solve at the microscale that are used to compute homogenized material constants for use at the engineering scale. In this work, we employ AEH to explore the effect of evolving microstructural thermal conductivity and elastic constants on nuclear fuel performance. We show that the AEH approach fits cleanly into the BISON and MARMOT codes and provides a natural, multidimensional homogenization capability.

  12. Multiscale equation-free algorithms for molecular dynamics

    Science.gov (United States)

    Abi Mansour, Andrew

    Molecular dynamics is a physics-based computational tool that has been widely employed to study the dynamics and structure of macromolecules and their assemblies at the atomic scale. However, the efficiency of molecular dynamics simulation is limited because of the broad spectrum of timescales involved. To overcome this limitation, an equation-free algorithm is presented for simulating these systems using a multiscale model cast in terms of atomistic and coarse-grained variables. Both variables are evolved in time in such a way that the cross-talk between short and long scales is preserved. In this way, the coarse-grained variables guide the evolution of the atom-resolved states, while the latter provide the Newtonian physics for the former. While the atomistic variables are evolved using short molecular dynamics runs, time advancement at the coarse-grained level is achieved with a scheme that uses information from past and future states of the system while accounting for both the stochastic and deterministic features of the coarse-grained dynamics. To complete the multiscale cycle, an atom-resolved state consistent with the updated coarse-grained variables is recovered using algorithms from mathematical optimization. This multiscale paradigm is extended to nanofluidics using concepts from hydrodynamics, and it is demonstrated for macromolecular and nanofluidic systems. A toolkit is developed for prototyping these algorithms, which are then implemented within the GROMACS simulation package and released as an open source multiscale simulator.

  13. Relational grounding facilitates development of scientifically useful multiscale models

    Directory of Open Access Journals (Sweden)

    Lam Tai

    2011-09-01

    Full Text Available Abstract We review grounding issues that influence the scientific usefulness of any biomedical multiscale model (MSM. Groundings are the collection of units, dimensions, and/or objects to which a variable or model constituent refers. To date, models that primarily use continuous mathematics rely heavily on absolute grounding, whereas those that primarily use discrete software paradigms (e.g., object-oriented, agent-based, actor typically employ relational grounding. We review grounding issues and identify strategies to address them. We maintain that grounding issues should be addressed at the start of any MSM project and should be reevaluated throughout the model development process. We make the following points. Grounding decisions influence model flexibility, adaptability, and thus reusability. Grounding choices should be influenced by measures, uncertainty, system information, and the nature of available validation data. Absolute grounding complicates the process of combining models to form larger models unless all are grounded absolutely. Relational grounding facilitates referent knowledge embodiment within computational mechanisms but requires separate model-to-referent mappings. Absolute grounding can simplify integration by forcing common units and, hence, a common integration target, but context change may require model reengineering. Relational grounding enables synthesis of large, composite (multi-module models that can be robust to context changes. Because biological components have varying degrees of autonomy, corresponding components in MSMs need to do the same. Relational grounding facilitates achieving such autonomy. Biomimetic analogues designed to facilitate translational research and development must have long lifecycles. Exploring mechanisms of normal-to-disease transition requires model components that are grounded relationally. Multi-paradigm modeling requires both hyperspatial and relational grounding.

  14. What is at stake in multi-scale approaches

    International Nuclear Information System (INIS)

    Jamet, Didier

    2008-01-01

    Full text of publication follows: Multi-scale approaches amount to analyzing physical phenomena at small space and time scales in order to model their effects at larger scales. This approach is very general in physics and engineering; one of the best examples of success of this approach is certainly statistical physics that allows to recover classical thermodynamics and to determine the limits of application of classical thermodynamics. Getting access to small scale information aims at reducing the models' uncertainty but it has a cost: fine scale models may be more complex than larger scale models and their resolution may require the development of specific and possibly expensive methods, numerical simulation techniques and experiments. For instance, in applications related to nuclear engineering, the application of computational fluid dynamics instead of cruder models is a formidable engineering challenge because it requires resorting to high performance computing. Likewise, in two-phase flow modeling, the techniques of direct numerical simulation, where all the interfaces are tracked individually and where all turbulence scales are captured, are getting mature enough to be considered for averaged modeling purposes. However, resolving small scale problems is a necessary step but it is not sufficient in a multi-scale approach. An important modeling challenge is to determine how to treat small scale data in order to get relevant information for larger scale models. For some applications, such as single-phase turbulence or transfers in porous media, this up-scaling approach is known and is now used rather routinely. However, in two-phase flow modeling, the up-scaling approach is not as mature and specific issues must be addressed that raise fundamental questions. This will be discussed and illustrated. (author)

  15. Multiscale modeling of the dynamics of multicellular systems

    Science.gov (United States)

    Kosztin, Ioan

    2011-03-01

    Describing the biomechanical properties of cellular systems, regarded as complex highly viscoelastic materials, is a difficult problem of great conceptual and practical value. Here we present a novel approach, referred to as the Cellular Particle Dynamics (CPD) method, for: (i) quantitatively relating biomechanical properties at the cell level to those at the multicellular and tissue level, and (ii) describing and predicting the time evolution of multicellular systems that undergo biomechanical relaxations. In CPD cells are modeled as an ensemble of cellular particles (CPs) that interact via short range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through integration of their equations of motion. Cell and multicellular level biomechanical properties (e.g., viscosity, surface tension and shear modulus) are determined through the combined use of experiments and theory of continuum viscoelastic media. The same biomechanical properties are also ``measured'' computationally by employing the CPD method, the results being expressed in terms of CPD parameters. Once these parameters have been calibrated experimentally, the formalism provides a systematic framework to predict the time evolution of complex multicellular systems during shape-changing biomechanical transformations. By design, the CPD method is rather flexible and most suitable for multiscale modeling of multicellular system. The spatial level of detail of the system can be easily tuned by changing the number of CPs in a cell. Thus, CPD can be used equally well to describe both cell level processes (e.g., the adhesion of two cells) and tissue level processes (e.g., the formation of 3D constructs of millions of cells through bioprinting). Work supported by NSF [FIBR-0526854 and PHY-0957914

  16. Multiscale simulation of DC corona discharge and ozone generation from nanostructures

    Science.gov (United States)

    Wang, Pengxiang

    simulation of corona discharges from nanostructures, a one-dimensional (1-D) multiscale model is used due to the prohibitive computational expense associated with two-dimensional (2-D) modeling. Near the nanoscale discharge electrode surface, a kinetic model based on PIC-MCC is used due to a relatively large Knudsen number in this region. Far away from the nanoscale discharge electrode, a continuum model is used since the Knudsen number is very small there. The multiscale modeling results are compared with experimental data. The quantitative agreement in positive discharges and qualitative agreement in negative discharges validate the modeling approach. The mechanism of sustaining the discharge process from nanostructures is revealed and is found to be different from that of discharge from micro- or macro-sized electrodes. Finally, the corona plasma model is combined with a plasma chemistry model and a transport model to predict the ozone production from the nanoscale corona. The dependence of ozone production on the applied potential and air velocity is studied. The electric field distribution in a 2-D multiscale domain (from nanoscale to microscale) is predicted by solving the Poisson's equation using a finite difference scheme. The discretized linear equations are solved using a multigrid method under the framework of PETSc on a paralleled supercomputer. Although the Poisson solver is able to resolve the multiscale field, the prohibitively long computation time limits the use of a 2-D solver in the current PIC-MCC scheme.

  17. Vision 2040: A Roadmap for Integrated, Multiscale Modeling and Simulation of Materials and Systems

    Science.gov (United States)

    Liu, Xuan; Furrer, David; Kosters, Jared; Holmes, Jack

    2018-01-01

    Over the last few decades, advances in high-performance computing, new materials characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) and additive manufacturing have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. While these advances have driven significant progress in the development of aerospace components and systems, that progress has been limited by persistent technology and infrastructure challenges that must be overcome to realize the full potential of integrated materials and systems design and simulation modeling throughout the supply chain. As a result, NASA's Transformational Tools and Technology (TTT) Project sponsored a study (performed by a diverse team led by Pratt & Whitney) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This report describes the findings of this 2040 Vision study (e.g., the 2040 vision state; the required interdependent core technical work areas, Key Element (KE); identified gaps and actions to close those gaps; and major recommendations) which constitutes a community consensus document as it is a result of over 450 professionals input obtain via: 1) four society workshops (AIAA, NAFEMS, and two TMS), 2) community-wide survey, and 3) the establishment of 9 expert panels (one per KE) consisting on average of 10 non-team members from academia, government and industry to review, update content, and prioritize gaps and actions. The study envisions the development of a cyber-physical-social ecosystem comprised of experimentally verified and validated computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost

  18. Multi-scale dynamic modeling of atmospheric pollution in urban environment

    International Nuclear Information System (INIS)

    Thouron, Laetitia

    2017-01-01

    Urban air pollution has been identified as an important cause of health impacts, including premature deaths. In particular, ambient concentrations of gaseous pollutants such as nitrogen dioxide (NO 2 ) and particulate matter (PM10 and PM2.5) are regulated, which means that emission reduction strategies must be put in place to reduce these concentrations in places where the corresponding regulations are not respected. Besides, air pollution can contribute to the contamination of other media, for example through the contribution of atmospheric deposition to runoff contamination. The multifactorial and multi-scale aspects of urban make the pollution sources difficult to identify. Indeed, the urban environment is a heterogeneous space characterized by complex architectural structures (old buildings alongside a more modern building, residential, commercial, industrial zones, roads, etc.), non-uniform atmospheric pollutant emissions and therefore the population exposure to pollution is variable in space and time. The modeling of urban air pollution aims to understand the origin of pollutants, their spatial extent and their concentration/deposition levels. Some pollutants have long residence times and can stay several weeks in the atmosphere (PM2.5) and therefore be transported over long distances, while others are more local (NO x in the vicinity of traffic). The spatial distribution of a pollutant will therefore depend on several factors, and in particular on the surfaces encountered. Air quality depends strongly on weather, buildings (canyon-street) and emissions. The aim of this thesis is to address some of these aspects by modeling: (1) urban background pollution with a transport-chemical model (Polyphemus / POLAIR3D), which makes it possible to estimate atmospheric pollutants by type of urban surfaces (roofs, walls and roadways), (2) street-level pollution by explicitly integrating the effects of the building in a three-dimensional way with a multi-scale model of

  19. Multi-scale modeling with cellular automata: The complex automata approach

    NARCIS (Netherlands)

    Hoekstra, A.G.; Falcone, J.-L.; Caiazzo, A.; Chopard, B.

    2008-01-01

    Cellular Automata are commonly used to describe complex natural phenomena. In many cases it is required to capture the multi-scale nature of these phenomena. A single Cellular Automata model may not be able to efficiently simulate a wide range of spatial and temporal scales. It is our goal to

  20. Multiscale analysis of heart rate dynamics: entropy and time irreversibility measures.

    Science.gov (United States)

    Costa, Madalena D; Peng, Chung-Kang; Goldberger, Ary L

    2008-06-01

    Cardiovascular signals are largely analyzed using traditional time and frequency domain measures. However, such measures fail to account for important properties related to multiscale organization and non-equilibrium dynamics. The complementary role of conventional signal analysis methods and emerging multiscale techniques, is, therefore, an important frontier area of investigation. The key finding of this presentation is that two recently developed multiscale computational tools--multiscale entropy and multiscale time irreversibility--are able to extract information from cardiac interbeat interval time series not contained in traditional methods based on mean, variance or Fourier spectrum (two-point correlation) techniques. These new methods, with careful attention to their limitations, may be useful in diagnostics, risk stratification and detection of toxicity of cardiac drugs.

  1. Coherent multiscale image processing using dual-tree quaternion wavelets.

    Science.gov (United States)

    Chan, Wai Lam; Choi, Hyeokho; Baraniuk, Richard G

    2008-07-01

    The dual-tree quaternion wavelet transform (QWT) is a new multiscale analysis tool for geometric image features. The QWT is a near shift-invariant tight frame representation whose coefficients sport a magnitude and three phases: two phases encode local image shifts while the third contains image texture information. The QWT is based on an alternative theory for the 2-D Hilbert transform and can be computed using a dual-tree filter bank with linear computational complexity. To demonstrate the properties of the QWT's coherent magnitude/phase representation, we develop an efficient and accurate procedure for estimating the local geometrical structure of an image. We also develop a new multiscale algorithm for estimating the disparity between a pair of images that is promising for image registration and flow estimation applications. The algorithm features multiscale phase unwrapping, linear complexity, and sub-pixel estimation accuracy.

  2. Reproducibility in Computational Neuroscience Models and Simulations

    Science.gov (United States)

    McDougal, Robert A.; Bulanova, Anna S.; Lytton, William W.

    2016-01-01

    Objective Like all scientific research, computational neuroscience research must be reproducible. Big data science, including simulation research, cannot depend exclusively on journal articles as the method to provide the sharing and transparency required for reproducibility. Methods Ensuring model reproducibility requires the use of multiple standard software practices and tools, including version control, strong commenting and documentation, and code modularity. Results Building on these standard practices, model sharing sites and tools have been developed that fit into several categories: 1. standardized neural simulators, 2. shared computational resources, 3. declarative model descriptors, ontologies and standardized annotations; 4. model sharing repositories and sharing standards. Conclusion A number of complementary innovations have been proposed to enhance sharing, transparency and reproducibility. The individual user can be encouraged to make use of version control, commenting, documentation and modularity in development of models. The community can help by requiring model sharing as a condition of publication and funding. Significance Model management will become increasingly important as multiscale models become larger, more detailed and correspondingly more difficult to manage by any single investigator or single laboratory. Additional big data management complexity will come as the models become more useful in interpreting experiments, thus increasing the need to ensure clear alignment between modeling data, both parameters and results, and experiment. PMID:27046845

  3. Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility

    Science.gov (United States)

    Kou, Jisheng; Sun, Shuyu

    2016-08-01

    In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from the microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young-Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young-Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young-Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally, numerical tests

  4. Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility

    KAUST Repository

    Kou, Jisheng

    2016-05-10

    In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from the microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young-Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young-Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young-Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally, numerical tests

  5. Computational engineering

    CERN Document Server

    2014-01-01

    The book presents state-of-the-art works in computational engineering. Focus is on mathematical modeling, numerical simulation, experimental validation and visualization in engineering sciences. In particular, the following topics are presented: constitutive models and their implementation into finite element codes, numerical models in nonlinear elasto-dynamics including seismic excitations, multiphase models in structural engineering and multiscale models of materials systems, sensitivity and reliability analysis of engineering structures, the application of scientific computing in urban water management and hydraulic engineering, and the application of genetic algorithms for the registration of laser scanner point clouds.

  6. Multiscale Thermohydrologic Model

    Energy Technology Data Exchange (ETDEWEB)

    T. Buscheck

    2004-10-12

    The purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. Thus, the goal is to predict the range of possible thermal-hydrologic conditions across the repository; this is quite different from predicting a single expected thermal-hydrologic response. The MSTHM calculates the following thermal-hydrologic parameters: temperature, relative humidity, liquid-phase saturation, evaporation rate, air-mass fraction, gas-phase pressure, capillary pressure, and liquid- and gas-phase fluxes (Table 1-1). These thermal-hydrologic parameters are required to support ''Total System Performance Assessment (TSPA) Model/Analysis for the License Application'' (BSC 2004 [DIRS 168504]). The thermal-hydrologic parameters are determined as a function of position along each of the emplacement drifts and as a function of waste package type. These parameters are determined at various reference locations within the emplacement drifts, including the waste package and drip-shield surfaces and in the invert. The parameters are also determined at various defined locations in the adjoining host rock. The MSTHM uses data obtained from the data tracking numbers (DTNs) listed in Table 4.1-1. The majority of those DTNs were generated from the following analyses and model reports: (1) ''UZ Flow Model and Submodels'' (BSC 2004 [DIRS 169861]); (2) ''Development of Numerical Grids for UZ Flow and Transport Modeling'' (BSC 2004); (3) ''Calibrated Properties Model'' (BSC 2004 [DIRS 169857]); (4) ''Thermal Conductivity of the Potential Repository Horizon'' (BSC 2004 [DIRS 169854]); (5) ''Thermal Conductivity of the Non-Repository Lithostratigraphic Layers

  7. Multi-scale simulation for homogenization of cement media

    International Nuclear Information System (INIS)

    Abballe, T.

    2011-01-01

    To solve diffusion problems on cement media, two scales must be taken into account: a fine scale, which describes the micrometers wide microstructures present in the media, and a work scale, which is usually a few meters long. Direct numerical simulations are almost impossible because of the huge computational resources (memory, CPU time) required to assess both scales at the same time. To overcome this problem, we present in this thesis multi-scale resolution methods using both Finite Volumes and Finite Elements, along with their efficient implementations. More precisely, we developed a multi-scale simulation tool which uses the SALOME platform to mesh domains and post-process data, and the parallel calculation code MPCube to solve problems. This SALOME/MPCube tool can solve automatically and efficiently multi-scale simulations. Parallel structure of computer clusters can be use to dispatch the more time-consuming tasks. We optimized most functions to account for cement media specificities. We presents numerical experiments on various cement media samples, e.g. mortar and cement paste. From these results, we manage to compute a numerical effective diffusivity of our cement media and to reconstruct a fine scale solution. (author) [fr

  8. Foundations for a multiscale collaborative Earth model

    KAUST Repository

    Afanasiev, M.

    2015-11-11

    of the CSEM development, the broad global updates mostly act to remove artefacts from the assembly of the initial CSEM. During the future evolution of the CSEM, the reference data set will be used to account for the influence of small-scale refinements on large-scale global structure. The CSEM as a computational framework is intended to help bridging the gap between local, regional and global tomography, and to contribute to the development of a global multiscale Earth model. While the current construction serves as a first proof of concept, future refinements and additions will require community involvement, which is welcome at this stage already.

  9. Multi-Scale Modeling of the Gamma Radiolysis of Nitrate Solutions.

    Science.gov (United States)

    Horne, Gregory P; Donoclift, Thomas A; Sims, Howard E; Orr, Robin M; Pimblott, Simon M

    2016-11-17

    A multiscale modeling approach has been developed for the extended time scale long-term radiolysis of aqueous systems. The approach uses a combination of stochastic track structure and track chemistry as well as deterministic homogeneous chemistry techniques and involves four key stages: radiation track structure simulation, the subsequent physicochemical processes, nonhomogeneous diffusion-reaction kinetic evolution, and homogeneous bulk chemistry modeling. The first three components model the physical and chemical evolution of an isolated radiation chemical track and provide radiolysis yields, within the extremely low dose isolated track paradigm, as the input parameters for a bulk deterministic chemistry model. This approach to radiation chemical modeling has been tested by comparison with the experimentally observed yield of nitrite from the gamma radiolysis of sodium nitrate solutions. This is a complex radiation chemical system which is strongly dependent on secondary reaction processes. The concentration of nitrite is not just dependent upon the evolution of radiation track chemistry and the scavenging of the hydrated electron and its precursors but also on the subsequent reactions of the products of these scavenging reactions with other water radiolysis products. Without the inclusion of intratrack chemistry, the deterministic component of the multiscale model is unable to correctly predict experimental data, highlighting the importance of intratrack radiation chemistry in the chemical evolution of the irradiated system.

  10. Bayesian inference on multiscale models for poisson intensity estimation: applications to photon-limited image denoising.

    Science.gov (United States)

    Lefkimmiatis, Stamatios; Maragos, Petros; Papandreou, George

    2009-08-01

    We present an improved statistical model for analyzing Poisson processes, with applications to photon-limited imaging. We build on previous work, adopting a multiscale representation of the Poisson process in which the ratios of the underlying Poisson intensities (rates) in adjacent scales are modeled as mixtures of conjugate parametric distributions. Our main contributions include: 1) a rigorous and robust regularized expectation-maximization (EM) algorithm for maximum-likelihood estimation of the rate-ratio density parameters directly from the noisy observed Poisson data (counts); 2) extension of the method to work under a multiscale hidden Markov tree model (HMT) which couples the mixture label assignments in consecutive scales, thus modeling interscale coefficient dependencies in the vicinity of image edges; 3) exploration of a 2-D recursive quad-tree image representation, involving Dirichlet-mixture rate-ratio densities, instead of the conventional separable binary-tree image representation involving beta-mixture rate-ratio densities; and 4) a novel multiscale image representation, which we term Poisson-Haar decomposition, that better models the image edge structure, thus yielding improved performance. Experimental results on standard images with artificially simulated Poisson noise and on real photon-limited images demonstrate the effectiveness of the proposed techniques.

  11. Bayesian Uncertainty Quantification for Subsurface Inversion Using a Multiscale Hierarchical Model

    KAUST Repository

    Mondal, Anirban

    2014-07-03

    We consider a Bayesian approach to nonlinear inverse problems in which the unknown quantity is a random field (spatial or temporal). The Bayesian approach contains a natural mechanism for regularization in the form of prior information, can incorporate information from heterogeneous sources and provide a quantitative assessment of uncertainty in the inverse solution. The Bayesian setting casts the inverse solution as a posterior probability distribution over the model parameters. The Karhunen-Loeve expansion is used for dimension reduction of the random field. Furthermore, we use a hierarchical Bayes model to inject multiscale data in the modeling framework. In this Bayesian framework, we show that this inverse problem is well-posed by proving that the posterior measure is Lipschitz continuous with respect to the data in total variation norm. Computational challenges in this construction arise from the need for repeated evaluations of the forward model (e.g., in the context of MCMC) and are compounded by high dimensionality of the posterior. We develop two-stage reversible jump MCMC that has the ability to screen the bad proposals in the first inexpensive stage. Numerical results are presented by analyzing simulated as well as real data from hydrocarbon reservoir. This article has supplementary material available online. © 2014 American Statistical Association and the American Society for Quality.

  12. Efficient Integration of Coupled Electrical-chemical Systems in Multiscale Neuronal Simulations

    Directory of Open Access Journals (Sweden)

    Ekaterina Brocke

    2016-09-01

    Full Text Available Multiscale modeling and simulations in neuroscience is gaining scientific attention due to its growing importance and unexplored capabilities. For instance, it can help to acquire better understanding of biological phenomena that have important features at multiple scales of time and space. This includes synaptic plasticity, memory formation and modulation, homeostasis. There are several ways to organize multiscale simulations depending on the scientific problem and the system to be modeled. One of the possibilities is to simulate different components of a multiscale system simultaneously and exchange data when required. The latter may become a challenging task for several reasons. One of them is that the components of a multiscale system usually span different spatial and temporal scales, such that rigorous analysis of possible coupling solutions is required. For certain classes of problems a number of coupling mechanisms have been proposed and successfully used. However, a strict mathematical theory is missing in many cases. Recent work in the field has not so far investigated artifacts that may arise during coupled integration of different approximation methods. Moreover, the coupling of widely used numerical fixed step size solvers may lead to unexpected inefficiency. In this paper we address the question of possible numerical artifacts that can arise during the integration of a coupled system. We develop an efficient strategy to couple the components of a multiscale test system. We introduce an efficient coupling method based on the second-order backward differentiation formula numerical approximation. The method uses an adaptive step size integration with an error estimation proposed by Skelboe (2000. The method shows a significant advantage over conventional fixed step size solvers used for similar problems. We explore different coupling strategies that define the organization of computations between system components. We study the

  13. A phenomenological variational multiscale constitutive model for intergranular failure in nanocrystalline materials

    KAUST Repository

    Siddiq, A.; El Sayed, Tamer S.

    2013-01-01

    We present a variational multiscale constitutive model that accounts for intergranular failure in nanocrystalline fcc metals due to void growth and coalescence in the grain boundary region. Following previous work by the authors, a nanocrystalline

  14. A MULTISCALE FRAMEWORK FOR THE STOCHASTIC ASSIMILATION AND MODELING OF UNCERTAINTY ASSOCIATED NCF COMPOSITE MATERIALS

    Energy Technology Data Exchange (ETDEWEB)

    Mehrez, Loujaine [University of Southern California; Ghanem, Roger [University of Southern California; McAuliffe, Colin [Altair Engineering, Inc.; Aitharaju, Venkat [General Motors; Rodgers, William [General Motors

    2016-06-06

    multiscale framework to construct stochastic macroscopic constitutive material models is proposed. A spectral projection approach, specifically polynomial chaos expansion, has been used to construct explicit functional relationships between the homogenized properties and input parameters from finer scales. A homogenization engine embedded in Multiscale Designer, software for composite materials, has been used for the upscaling process. The framework is demonstrated using non-crimp fabric composite materials by constructing probabilistic models of the homogenized properties of a non-crimp fabric laminate in terms of the input parameters together with the homogenized properties from finer scales.

  15. Multiscale modeling for the prediction of casting defects in investment cast aluminum alloys

    International Nuclear Information System (INIS)

    Hamilton, R.W.; See, D.; Butler, S.; Lee, P.D.

    2003-01-01

    Macroscopic modeling of heat transfer and fluid flow is now routinely used for the prediction of macroscopic defects in castings, while microscopic models are used to investigate the effects of alloy changes on typical microstructures. By combining these two levels of modeling it is possible to simulate the casting process over a wider range of spatial and temporal scales. This paper presents a multiscale model where micromodels for dendrite arm spacing and microporosity are incorporated into a macromodel of heat transfer and in order to predict the as cast microstructure and prevalence of microscopic defects, specifically porosity. The approach is applied to aluminum alloy (L169) investment castings. The models are compared with results obtained by optical image analysis of prepared slices, and X-ray tomography of volume samples from the experiments. Multiscale modeling is shown to provide the designer with a useful tool to improve the properties of the final casting by testing how altering the casting process affects the final microstructure including porosity

  16. Multiscale mechanics of dynamical metamaterials

    NARCIS (Netherlands)

    Geers, M.G.D.; Kouznetsova, V.; Sridhar, A.; Krushynska, A.; Kleiber, M.; Burczynski, T.; Wilde, K.; Gorski, J.; Winkelmann, K.; Smakosz, L.

    2016-01-01

    This contribution focuses on the computational multi-scale solution of wave propagation phenomena in dynamic metamaterials. Taking the Bloch-Floquet solution for the standard elastic case as a point of departure, an extended scheme is presented to solve for heterogeneous visco-elastic materials. The

  17. A multi-scale modeling of surface effect via the modified boundary Cauchy-Born model

    Energy Technology Data Exchange (ETDEWEB)

    Khoei, A.R., E-mail: arkhoei@sharif.edu; Aramoon, A.

    2012-10-01

    In this paper, a new multi-scale approach is presented based on the modified boundary Cauchy-Born (MBCB) technique to model the surface effects of nano-structures. The salient point of the MBCB model is the definition of radial quadrature used in the surface elements which is an indicator of material behavior. The characteristics of quadrature are derived by interpolating data from atoms laid in a circular support around the quadrature, in a least-square scene. The total-Lagrangian formulation is derived for the equivalent continua by employing the Cauchy-Born hypothesis for calculating the strain energy density function of the continua. The numerical results of the proposed method are compared with direct atomistic and finite element simulation results to indicate that the proposed technique provides promising results for modeling surface effects of nano-structures. - Highlights: Black-Right-Pointing-Pointer A multi-scale approach is presented to model the surface effects in nano-structures. Black-Right-Pointing-Pointer The total-Lagrangian formulation is derived by employing the Cauchy-Born hypothesis. Black-Right-Pointing-Pointer The radial quadrature is used to model the material behavior in surface elements. Black-Right-Pointing-Pointer The quadrature characteristics are derived using the data at the atomistic level.

  18. Multiscale Molecular Dynamics Model for Heterogeneous Charged Systems

    Science.gov (United States)

    Stanton, L. G.; Glosli, J. N.; Murillo, M. S.

    2018-04-01

    Modeling matter across large length scales and timescales using molecular dynamics simulations poses significant challenges. These challenges are typically addressed through the use of precomputed pair potentials that depend on thermodynamic properties like temperature and density; however, many scenarios of interest involve spatiotemporal variations in these properties, and such variations can violate assumptions made in constructing these potentials, thus precluding their use. In particular, when a system is strongly heterogeneous, most of the usual simplifying assumptions (e.g., spherical potentials) do not apply. Here, we present a multiscale approach to orbital-free density functional theory molecular dynamics (OFDFT-MD) simulations that bridges atomic, interionic, and continuum length scales to allow for variations in hydrodynamic quantities in a consistent way. Our multiscale approach enables simulations on the order of micron length scales and 10's of picosecond timescales, which exceeds current OFDFT-MD simulations by many orders of magnitude. This new capability is then used to study the heterogeneous, nonequilibrium dynamics of a heated interface characteristic of an inertial-confinement-fusion capsule containing a plastic ablator near a fuel layer composed of deuterium-tritium ice. At these scales, fundamental assumptions of continuum models are explored; features such as the separation of the momentum fields among the species and strong hydrogen jetting from the plastic into the fuel region are observed, which had previously not been seen in hydrodynamic simulations.

  19. Multiscale Modeling of Ultra High Temperature Ceramics (UHTC) ZrB2 and HfB2: Application to Lattice Thermal Conductivity

    Science.gov (United States)

    Lawson, John W.; Daw, Murray S.; Squire, Thomas H.; Bauschlicher, Charles W.

    2012-01-01

    We are developing a multiscale framework in computational modeling for the ultra high temperature ceramics (UHTC) ZrB2 and HfB2. These materials are characterized by high melting point, good strength, and reasonable oxidation resistance. They are candidate materials for a number of applications in extreme environments including sharp leading edges of hypersonic aircraft. In particular, we used a combination of ab initio methods, atomistic simulations and continuum computations to obtain insights into fundamental properties of these materials. Ab initio methods were used to compute basic structural, mechanical and thermal properties. From these results, a database was constructed to fit a Tersoff style interatomic potential suitable for atomistic simulations. These potentials were used to evaluate the lattice thermal conductivity of single crystals and the thermal resistance of simple grain boundaries. Finite element method (FEM) computations using atomistic results as inputs were performed with meshes constructed on SEM images thereby modeling the realistic microstructure. These continuum computations showed the reduction in thermal conductivity due to the grain boundary network.

  20. Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth

    International Nuclear Information System (INIS)

    Cruz, Roberto de la; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás

    2017-01-01

    The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction–diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction–diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge

  1. 3D multiscale crack propagation using the XFEM applied to a gas turbine blade

    Science.gov (United States)

    Holl, Matthias; Rogge, Timo; Loehnert, Stefan; Wriggers, Peter; Rolfes, Raimund

    2014-01-01

    This work presents a new multiscale technique to investigate advancing cracks in three dimensional space. This fully adaptive multiscale technique is designed to take into account cracks of different length scales efficiently, by enabling fine scale domains locally in regions of interest, i.e. where stress concentrations and high stress gradients occur. Due to crack propagation, these regions change during the simulation process. Cracks are modeled using the extended finite element method, such that an accurate and powerful numerical tool is achieved. Restricting ourselves to linear elastic fracture mechanics, the -integral yields an accurate solution of the stress intensity factors, and with the criterion of maximum hoop stress, a precise direction of growth. If necessary, the on the finest scale computed crack surface is finally transferred to the corresponding scale. In a final step, the model is applied to a quadrature point of a gas turbine blade, to compute crack growth on the microscale of a real structure.

  2. APPLICATION OF THE MODELS-3 COMMUNITY MULTI-SCALE AIR QUALITY (CMAQ) MODEL SYSTEM TO SOS/NASHVILLE 1999

    Science.gov (United States)

    The Models-3 Community Multi-scale Air Quality (CMAQ) model, first released by the USEPA in 1999 (Byun and Ching. 1999), continues to be developed and evaluated. The principal components of the CMAQ system include a comprehensive emission processor known as the Sparse Matrix O...

  3. A multiscale modeling approach for biomolecular systems

    Energy Technology Data Exchange (ETDEWEB)

    Bowling, Alan, E-mail: bowling@uta.edu; Haghshenas-Jaryani, Mahdi, E-mail: mahdi.haghshenasjaryani@mavs.uta.edu [The University of Texas at Arlington, Department of Mechanical and Aerospace Engineering (United States)

    2015-04-15

    This paper presents a new multiscale molecular dynamic model for investigating the effects of external interactions, such as contact and impact, during stepping and docking of motor proteins and other biomolecular systems. The model retains the mass properties ensuring that the result satisfies Newton’s second law. This idea is presented using a simple particle model to facilitate discussion of the rigid body model; however, the particle model does provide insights into particle dynamics at the nanoscale. The resulting three-dimensional model predicts a significant decrease in the effect of the random forces associated with Brownian motion. This conclusion runs contrary to the widely accepted notion that the motor protein’s movements are primarily the result of thermal effects. This work focuses on the mechanical aspects of protein locomotion; the effect ATP hydrolysis is estimated as internal forces acting on the mechanical model. In addition, the proposed model can be numerically integrated in a reasonable amount of time. Herein, the differences between the motion predicted by the old and new modeling approaches are compared using a simplified model of myosin V.

  4. Multiscale Modeling of Wear Degradation

    KAUST Repository

    Moraes, Alvaro; Ruggeri, Fabrizio; Tempone, Raul; Vilanova, Pedro

    2016-01-01

    Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.

  5. Multiscale Modeling of Wear Degradation

    KAUST Repository

    Moraes, Alvaro; Ruggeri, Fabrizio; Tempone, Raul; Vilanova, Pedro

    2015-01-01

    Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.

  6. Multiscale Modeling of Wear Degradation

    KAUST Repository

    Moraes, Alvaro

    2015-01-07

    Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.

  7. Multiscale Modeling of Wear Degradation

    KAUST Repository

    Moraes, Alvaro

    2014-01-06

    Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.

  8. Multiscale Modeling of Wear Degradation

    KAUST Repository

    Moraes, Alvaro

    2016-01-06

    Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.

  9. Computational models of the pulmonary circulation: Insights and the move towards clinically directed studies

    Science.gov (United States)

    Tawhai, Merryn H.; Clark, Alys R.; Burrowes, Kelly S.

    2011-01-01

    Biophysically-based computational models provide a tool for integrating and explaining experimental data, observations, and hypotheses. Computational models of the pulmonary circulation have evolved from minimal and efficient constructs that have been used to study individual mechanisms that contribute to lung perfusion, to sophisticated multi-scale and -physics structure-based models that predict integrated structure-function relationships within a heterogeneous organ. This review considers the utility of computational models in providing new insights into the function of the pulmonary circulation, and their application in clinically motivated studies. We review mathematical and computational models of the pulmonary circulation based on their application; we begin with models that seek to answer questions in basic science and physiology and progress to models that aim to have clinical application. In looking forward, we discuss the relative merits and clinical relevance of computational models: what important features are still lacking; and how these models may ultimately be applied to further increasing our understanding of the mechanisms occurring in disease of the pulmonary circulation. PMID:22034608

  10. Improved convergence of gradient-based reconstruction using multi-scale models

    International Nuclear Information System (INIS)

    Cunningham, G.S.; Hanson, K.M.; Koyfman, I.

    1996-01-01

    Geometric models have received increasing attention in medical imaging for tasks such as segmentation, reconstruction, restoration, and registration. In order to determine the best configuration of the geometric model in the context of any of these tasks, one needs to perform a difficult global optimization of an energy function that may have many local minima. Explicit models of geometry, also called deformable models, snakes, or active contours, have been used extensively to solve image segmentation problems in a non-Bayesian framework. Researchers have seen empirically that multi-scale analysis is useful for convergence to a configuration that is near the global minimum. In this type of analysis, the image data are convolved with blur functions of increasing resolution, and an optimal configuration of the snake is found for each blurred image. The configuration obtained using the highest resolution blur is used as the solution to the global optimization problem. In this article, the authors use explicit models of geometry for a variety of Bayesian estimation problems, including image segmentation, reconstruction and restoration. The authors introduce a multi-scale approach that blurs the geometric model, rather than the image data, and show that this approach turns a global, highly nonquadratic optimization into a sequence of local, approximately quadratic problems that converge to the global minimum. The result is a deterministic, robust, and efficient optimization strategy applicable to a wide variety of Bayesian estimation problems in which geometric models of images are an important component

  11. Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth

    Science.gov (United States)

    de la Cruz, Roberto; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás

    2017-12-01

    The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of

  12. A Multiscale Agent-Based in silico Model of Liver Fibrosis Progression

    International Nuclear Information System (INIS)

    Dutta-Moscato, Joyeeta; Solovyev, Alexey; Mi, Qi; Nishikawa, Taichiro; Soto-Gutierrez, Alejandro; Fox, Ira J.; Vodovotz, Yoram

    2014-01-01

    Chronic hepatic inflammation involves a complex interplay of inflammatory and mechanical influences, ultimately manifesting in a characteristic histopathology of liver fibrosis. We created an agent-based model (ABM) of liver tissue in order to computationally examine the consequence of liver inflammation. Our liver fibrosis ABM (LFABM) is comprised of literature-derived rules describing molecular and histopathological aspects of inflammation and fibrosis in a section of chemically injured liver. Hepatocytes are modeled as agents within hexagonal lobules. Injury triggers an inflammatory reaction, which leads to activation of local Kupffer cells and recruitment of monocytes from circulation. Portal fibroblasts and hepatic stellate cells are activated locally by the products of inflammation. The various agents in the simulation are regulated by above-threshold concentrations of pro- and anti-inflammatory cytokines and damage-associated molecular pattern molecules. The simulation progresses from chronic inflammation to collagen deposition, exhibiting periportal fibrosis followed by bridging fibrosis, and culminating in disruption of the regular lobular structure. The ABM exhibited key histopathological features observed in liver sections from rats treated with carbon tetrachloride (CCl 4 ). An in silico “tension test” for the hepatic lobules predicted an overall increase in tissue stiffness, in line with clinical elastography literature and published studies in CCl 4 -treated rats. Therapy simulations suggested differential anti-fibrotic effects of neutralizing tumor necrosis factor alpha vs. enhancing M2 Kupffer cells. We conclude that a computational model of liver inflammation on a structural skeleton of physical forces can recapitulate key histopathological and macroscopic properties of CCl 4 -injured liver. This multiscale approach linking molecular and chemomechanical stimuli enables a model that could be used to gain translationally relevant insights into

  13. Magnetic hysteresis at the domain scale of a multi-scale material model for magneto-elastic behaviour

    Energy Technology Data Exchange (ETDEWEB)

    Vanoost, D., E-mail: dries.vanoost@kuleuven-kulak.be [KU Leuven Technology Campus Ostend, ReMI Research Group, Oostende B-8400 (Belgium); KU Leuven Kulak, Wave Propagation and Signal Processing Research Group, Kortrijk B-8500 (Belgium); Steentjes, S. [Institute of Electrical Machines, RWTH Aachen University, Aachen D-52062 (Germany); Peuteman, J. [KU Leuven Technology Campus Ostend, ReMI Research Group, Oostende B-8400 (Belgium); KU Leuven, Department of Electrical Engineering, Electrical Energy and Computer Architecture, Heverlee B-3001 (Belgium); Gielen, G. [KU Leuven, Department of Electrical Engineering, Microelectronics and Sensors, Heverlee B-3001 (Belgium); De Gersem, H. [KU Leuven Kulak, Wave Propagation and Signal Processing Research Group, Kortrijk B-8500 (Belgium); TU Darmstadt, Institut für Theorie Elektromagnetischer Felder, Darmstadt D-64289 (Germany); Pissoort, D. [KU Leuven Technology Campus Ostend, ReMI Research Group, Oostende B-8400 (Belgium); KU Leuven, Department of Electrical Engineering, Microelectronics and Sensors, Heverlee B-3001 (Belgium); Hameyer, K. [Institute of Electrical Machines, RWTH Aachen University, Aachen D-52062 (Germany)

    2016-09-15

    This paper proposes a multi-scale energy-based material model for poly-crystalline materials. Describing the behaviour of poly-crystalline materials at three spatial scales of dominating physical mechanisms allows accounting for the heterogeneity and multi-axiality of the material behaviour. The three spatial scales are the poly-crystalline, grain and domain scale. Together with appropriate scale transitions rules and models for local magnetic behaviour at each scale, the model is able to describe the magneto-elastic behaviour (magnetostriction and hysteresis) at the macroscale, although the data input is merely based on a set of physical constants. Introducing a new energy density function that describes the demagnetisation field, the anhysteretic multi-scale energy-based material model is extended to the hysteretic case. The hysteresis behaviour is included at the domain scale according to the micro-magnetic domain theory while preserving a valid description for the magneto-elastic coupling. The model is verified using existing measurement data for different mechanical stress levels. - Highlights: • A ferromagnetic hysteretic energy-based multi-scale material model is proposed. • The hysteresis is obtained by new proposed hysteresis energy density function. • Avoids tedious parameter identification.

  14. Cellular potts models multiscale extensions and biological applications

    CERN Document Server

    Scianna, Marco

    2013-01-01

    A flexible, cell-level, and lattice-based technique, the cellular Potts model accurately describes the phenomenological mechanisms involved in many biological processes. Cellular Potts Models: Multiscale Extensions and Biological Applications gives an interdisciplinary, accessible treatment of these models, from the original methodologies to the latest developments. The book first explains the biophysical bases, main merits, and limitations of the cellular Potts model. It then proposes several innovative extensions, focusing on ways to integrate and interface the basic cellular Potts model at the mesoscopic scale with approaches that accurately model microscopic dynamics. These extensions are designed to create a nested and hybrid environment, where the evolution of a biological system is realistically driven by the constant interplay and flux of information between the different levels of description. Through several biological examples, the authors demonstrate a qualitative and quantitative agreement with t...

  15. SU-F-18C-15: Model-Based Multiscale Noise Reduction On Low Dose Cone Beam Projection

    International Nuclear Information System (INIS)

    Yao, W; Farr, J

    2014-01-01

    Purpose: To improve image quality of low dose cone beam CT for patient positioning in radiation therapy. Methods: In low dose cone beam CT (CBCT) imaging systems, Poisson process governs the randomness of photon fluence at x-ray source and the detector because of the independent binomial process of photon absorption in medium. On a CBCT projection, the variance of fluence consists of the variance of noiseless imaging structure and that of Poisson noise, which is proportional to the mean (noiseless) of the fluence at the detector. This requires multiscale filters to smoothen noise while keeping the structure information of the imaged object. We used a mathematical model of Poisson process to design multiscale filters and established the balance of noise correction and structure blurring. The algorithm was checked with low dose kilo-voltage CBCT projections acquired from a Varian OBI system. Results: From the investigation of low dose CBCT of a Catphan phantom and patients, it showed that our model-based multiscale technique could efficiently reduce noise and meanwhile keep the fine structure of the imaged object. After the image processing, the number of visible line pairs in Catphan phantom scanned with 4 ms pulse time was similar to that scanned with 32 ms, and soft tissue structure from simulated 4 ms patient head-and-neck images was also comparable with scanned 20 ms ones. Compared with fixed-scale technique, the image quality from multiscale one was improved. Conclusion: Use of projection-specific multiscale filters can reach better balance on noise reduction and structure information loss. The image quality of low dose CBCT can be improved by using multiscale filters

  16. Assessing multiscale complexity of short heart rate variability series through a model-based linear approach

    Science.gov (United States)

    Porta, Alberto; Bari, Vlasta; Ranuzzi, Giovanni; De Maria, Beatrice; Baselli, Giuseppe

    2017-09-01

    We propose a multiscale complexity (MSC) method assessing irregularity in assigned frequency bands and being appropriate for analyzing the short time series. It is grounded on the identification of the coefficients of an autoregressive model, on the computation of the mean position of the poles generating the components of the power spectral density in an assigned frequency band, and on the assessment of its distance from the unit circle in the complex plane. The MSC method was tested on simulations and applied to the short heart period (HP) variability series recorded during graded head-up tilt in 17 subjects (age from 21 to 54 years, median = 28 years, 7 females) and during paced breathing protocols in 19 subjects (age from 27 to 35 years, median = 31 years, 11 females) to assess the contribution of time scales typical of the cardiac autonomic control, namely in low frequency (LF, from 0.04 to 0.15 Hz) and high frequency (HF, from 0.15 to 0.5 Hz) bands to the complexity of the cardiac regulation. The proposed MSC technique was compared to a traditional model-free multiscale method grounded on information theory, i.e., multiscale entropy (MSE). The approach suggests that the reduction of HP variability complexity observed during graded head-up tilt is due to a regularization of the HP fluctuations in LF band via a possible intervention of sympathetic control and the decrement of HP variability complexity observed during slow breathing is the result of the regularization of the HP variations in both LF and HF bands, thus implying the action of physiological mechanisms working at time scales even different from that of respiration. MSE did not distinguish experimental conditions at time scales larger than 1. Over a short time series MSC allows a more insightful association between cardiac control complexity and physiological mechanisms modulating cardiac rhythm compared to a more traditional tool such as MSE.

  17. Multiscale eddy simulation for moist atmospheric convection: Preliminary investigation

    Energy Technology Data Exchange (ETDEWEB)

    Stechmann, Samuel N., E-mail: stechmann@wisc.edu [Department of Mathematics, University of Wisconsin-Madison (United States); Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison (United States)

    2014-08-15

    A multiscale computational framework is designed for simulating atmospheric convection and clouds. In this multiscale framework, large eddy simulation (LES) is used to model the coarse scales of 100 m and larger, and a stochastic, one-dimensional turbulence (ODT) model is used to represent the fine scales of 100 m and smaller. Coupled and evolving together, these two components provide a multiscale eddy simulation (MES). Through its fine-scale turbulence and moist thermodynamics, MES allows coarse grid cells to be partially cloudy and to encompass cloudy–clear air mixing on scales down to 1 m; in contrast, in typical LES such fine-scale processes are not represented or are parameterized using bulk deterministic closures. To illustrate MES and investigate its multiscale dynamics, a shallow cumulus cloud field is simulated. The fine-scale variability is seen to take a plausible form, with partially cloudy grid cells prominent near cloud edges and cloud top. From earlier theoretical work, this mixing of cloudy and clear air is believed to have an important impact on buoyancy. However, contrary to expectations based on earlier theoretical studies, the mean statistics of the bulk cloud field are essentially the same in MES and LES; possible reasons for this are discussed, including possible limitations in the present formulation of MES. One difference between LES and MES is seen in the coarse-scale turbulent kinetic energy, which appears to grow slowly in time due to incoherent stochastic fluctuations in the buoyancy. This and other considerations suggest the need for some type of spatial and/or temporal filtering to attenuate undersampling of the stochastic fine-scale processes.

  18. Multiscale eddy simulation for moist atmospheric convection: Preliminary investigation

    International Nuclear Information System (INIS)

    Stechmann, Samuel N.

    2014-01-01

    A multiscale computational framework is designed for simulating atmospheric convection and clouds. In this multiscale framework, large eddy simulation (LES) is used to model the coarse scales of 100 m and larger, and a stochastic, one-dimensional turbulence (ODT) model is used to represent the fine scales of 100 m and smaller. Coupled and evolving together, these two components provide a multiscale eddy simulation (MES). Through its fine-scale turbulence and moist thermodynamics, MES allows coarse grid cells to be partially cloudy and to encompass cloudy–clear air mixing on scales down to 1 m; in contrast, in typical LES such fine-scale processes are not represented or are parameterized using bulk deterministic closures. To illustrate MES and investigate its multiscale dynamics, a shallow cumulus cloud field is simulated. The fine-scale variability is seen to take a plausible form, with partially cloudy grid cells prominent near cloud edges and cloud top. From earlier theoretical work, this mixing of cloudy and clear air is believed to have an important impact on buoyancy. However, contrary to expectations based on earlier theoretical studies, the mean statistics of the bulk cloud field are essentially the same in MES and LES; possible reasons for this are discussed, including possible limitations in the present formulation of MES. One difference between LES and MES is seen in the coarse-scale turbulent kinetic energy, which appears to grow slowly in time due to incoherent stochastic fluctuations in the buoyancy. This and other considerations suggest the need for some type of spatial and/or temporal filtering to attenuate undersampling of the stochastic fine-scale processes

  19. Land-Atmosphere Coupling in the Multi-Scale Modelling Framework

    Science.gov (United States)

    Kraus, P. M.; Denning, S.

    2015-12-01

    The Multi-Scale Modeling Framework (MMF), in which cloud-resolving models (CRMs) are embedded within general circulation model (GCM) gridcells to serve as the model's cloud parameterization, has offered a number of benefits to GCM simulations. The coupling of these cloud-resolving models directly to land surface model instances, rather than passing averaged atmospheric variables to a single instance of a land surface model, the logical next step in model development, has recently been accomplished. This new configuration offers conspicuous improvements to estimates of precipitation and canopy through-fall, but overall the model exhibits warm surface temperature biases and low productivity.This work presents modifications to a land-surface model that take advantage of the new multi-scale modeling framework, and accommodate the change in spatial scale from a typical GCM range of ~200 km to the CRM grid-scale of 4 km.A parameterization is introduced to apportion modeled surface radiation into direct-beam and diffuse components. The diffuse component is then distributed among the land-surface model instances within each GCM cell domain. This substantially reduces the number excessively low light values provided to the land-surface model when cloudy conditions are modeled in the CRM, associated with its 1-D radiation scheme. The small spatial scale of the CRM, ~4 km, as compared with the typical ~200 km GCM scale, provides much more realistic estimates of precipitation intensity, this permits the elimination of a model parameterization of canopy through-fall. However, runoff at such scales can no longer be considered as an immediate flow to the ocean. Allowing sub-surface water flow between land-surface instances within the GCM domain affords better realism and also reduces temperature and productivity biases.The MMF affords a number of opportunities to land-surface modelers, providing both the advantages of direct simulation at the 4 km scale and a much reduced

  20. Development of a multi-scale simulation model of tube hydroforming for superconducting RF cavities

    Energy Technology Data Exchange (ETDEWEB)

    Kim, H.S. [Department of Materials Science and Engineering, The Ohio State University, Columbus, OH (United States); Sumption, M.D., E-mail: sumption.3@osu.edu [Department of Materials Science and Engineering, The Ohio State University, Columbus, OH (United States); Bong, H.J. [Department of Materials Science and Engineering, The Ohio State University, Columbus, OH (United States); Lim, H. [Sandia National Laboratories, Albuquerque, NM (United States); Collings, E.W. [Department of Materials Science and Engineering, The Ohio State University, Columbus, OH (United States)

    2017-01-02

    This work focuses on finite element modeling of the hydroforming process for niobium tubes intended for use in superconducting radio frequency (SRF) cavities. The hydroforming of tubular samples into SRF-relevant shapes involves the complex geometries and loading conditions which develop during the deformation, as well as anisotropic materials properties. Numerical description of the process entails relatively complex numerical simulations. A crystal plasticity (CP) model was constructed that included the evolution of crystallographic orientation during deformation as well as the anisotropy of tubes in all directions and loading conditions. In this work we demonstrate a multi-scale simulation approach which uses both microscopic CP and macroscopic continuum models. In this approach a CP model (developed and implemented into ABAQUS using UMAT) was used for determining the flow stress curve only under bi-axial loading in order to reduce the computing time. The texture of the materials obtained using orientation imaging microscopy (OIM) and tensile test data were inputs for this model. Continuum FE analysis of tube hydroforming using the obtained constitutive equation from the CP modeling was then performed and compared to the results of hydraulic bulge testing. The results show that high quality predictions of the deformation under hydroforming of Nb tubes can be obtained using CP-FEM based on their known texture and the results of tensile tests. The importance of the CP-FEM based approach is that it reduces the need for hydraulic bulge testing, using a relatively simple computational approach.

  1. Development of a multi-scale simulation model of tube hydroforming for superconducting RF cavities

    International Nuclear Information System (INIS)

    Kim, H.S.; Sumption, M.D.; Bong, H.J.; Lim, H.; Collings, E.W.

    2017-01-01

    This work focuses on finite element modeling of the hydroforming process for niobium tubes intended for use in superconducting radio frequency (SRF) cavities. The hydroforming of tubular samples into SRF-relevant shapes involves the complex geometries and loading conditions which develop during the deformation, as well as anisotropic materials properties. Numerical description of the process entails relatively complex numerical simulations. A crystal plasticity (CP) model was constructed that included the evolution of crystallographic orientation during deformation as well as the anisotropy of tubes in all directions and loading conditions. In this work we demonstrate a multi-scale simulation approach which uses both microscopic CP and macroscopic continuum models. In this approach a CP model (developed and implemented into ABAQUS using UMAT) was used for determining the flow stress curve only under bi-axial loading in order to reduce the computing time. The texture of the materials obtained using orientation imaging microscopy (OIM) and tensile test data were inputs for this model. Continuum FE analysis of tube hydroforming using the obtained constitutive equation from the CP modeling was then performed and compared to the results of hydraulic bulge testing. The results show that high quality predictions of the deformation under hydroforming of Nb tubes can be obtained using CP-FEM based on their known texture and the results of tensile tests. The importance of the CP-FEM based approach is that it reduces the need for hydraulic bulge testing, using a relatively simple computational approach.

  2. Relating system-to-CFD coupled code analyses to theoretical framework of a multi-scale method

    International Nuclear Information System (INIS)

    Cadinu, F.; Kozlowski, T.; Dinh, T.N.

    2007-01-01

    Over past decades, analyses of transient processes and accidents in a nuclear power plant have been performed, to a significant extent and with a great success, by means of so called system codes, e.g. RELAP5, CATHARE, ATHLET codes. These computer codes, based on a multi-fluid model of two-phase flow, provide an effective, one-dimensional description of the coolant thermal-hydraulics in the reactor system. For some components in the system, wherever needed, the effect of multi-dimensional flow is accounted for through approximate models. The later are derived from scaled experiments conducted for selected accident scenarios. Increasingly, however, we have to deal with newer and ever more complex accident scenarios. In some such cases the system codes fail to serve as simulation vehicle, largely due to its deficient treatment of multi-dimensional flow (in e.g. downcomer, lower plenum). A possible way of improvement is to use the techniques of Computational Fluid Dynamics (CFD). Based on solving Navier-Stokes equations, CFD codes have been developed and used, broadly, to perform analysis of multi-dimensional flow, dominantly in non-nuclear industry and for single-phase flow applications. It is clear that CFD simulations can not substitute system codes but just complement them. Given the intrinsic multi-scale nature of this problem, we propose to relate it to the more general field of research on multi-scale simulations. Even though multi-scale methods are developed on case-by-case basis, the need for a unified framework brought to the development of the heterogeneous multi-scale method (HMM)

  3. MULTISCALE SPARSE APPEARANCE MODELING AND SIMULATION OF PATHOLOGICAL DEFORMATIONS

    Directory of Open Access Journals (Sweden)

    Rami Zewail

    2017-08-01

    Full Text Available Machine learning and statistical modeling techniques has drawn much interest within the medical imaging research community. However, clinically-relevant modeling of anatomical structures continues to be a challenging task. This paper presents a novel method for multiscale sparse appearance modeling in medical images with application to simulation of pathological deformations in X-ray images of human spine. The proposed appearance model benefits from the non-linear approximation power of Contourlets and its ability to capture higher order singularities to achieve a sparse representation while preserving the accuracy of the statistical model. Independent Component Analysis is used to extract statistical independent modes of variations from the sparse Contourlet-based domain. The new model is then used to simulate clinically-relevant pathological deformations in radiographic images.

  4. Multi-time, multi-scale correlation functions in turbulence and in turbulent models

    NARCIS (Netherlands)

    Biferale, L.; Boffetta, G.; Celani, A.; Toschi, F.

    1999-01-01

    A multifractal-like representation for multi-time, multi-scale velocity correlation in turbulence and dynamical turbulent models is proposed. The importance of subleading contributions to time correlations is highlighted. The fulfillment of the dynamical constraints due to the equations of motion is

  5. Towards Faster FEM Simulation of Thin Film Superconductors: A Multiscale Approach

    DEFF Research Database (Denmark)

    Rodriguez Zermeno, Victor Manuel; Mijatovic, Nenad; Træholt, Chresten

    2011-01-01

    This work presents a method to simulate the electromagnetic properties of superconductors with high aspect ratio such as the commercially available second generation superconducting YBCO tapes. The method is based on a multiscale representation for both thickness and width of the superconducting...... at considerable lower computational time. Several test cases were simulated including transport current, externally applied magnetic field and a combination of both. The results are in good agreement with recently published numerical simulations. The computational time to solve the present multiscale approach...

  6. A multiscale quantum mechanics/electromagnetics method for device simulations.

    Science.gov (United States)

    Yam, ChiYung; Meng, Lingyi; Zhang, Yu; Chen, GuanHua

    2015-04-07

    Multiscale modeling has become a popular tool for research applying to different areas including materials science, microelectronics, biology, chemistry, etc. In this tutorial review, we describe a newly developed multiscale computational method, incorporating quantum mechanics into electronic device modeling with the electromagnetic environment included through classical electrodynamics. In the quantum mechanics/electromagnetics (QM/EM) method, the regions of the system where active electron scattering processes take place are treated quantum mechanically, while the surroundings are described by Maxwell's equations and a semiclassical drift-diffusion model. The QM model and the EM model are solved, respectively, in different regions of the system in a self-consistent manner. Potential distributions and current densities at the interface between QM and EM regions are employed as the boundary conditions for the quantum mechanical and electromagnetic simulations, respectively. The method is illustrated in the simulation of several realistic systems. In the case of junctionless field-effect transistors, transfer characteristics are obtained and a good agreement between experiments and simulations is achieved. Optical properties of a tandem photovoltaic cell are studied and the simulations demonstrate that multiple QM regions are coupled through the classical EM model. Finally, the study of a carbon nanotube-based molecular device shows the accuracy and efficiency of the QM/EM method.

  7. Multiscale Concrete Modeling of Aging Degradation

    Energy Technology Data Exchange (ETDEWEB)

    Hammi, Yousseff [Mississippi State Univ., Mississippi State, MS (United States); Gullett, Philipp [Mississippi State Univ., Mississippi State, MS (United States); Horstemeyer, Mark F. [Mississippi State Univ., Mississippi State, MS (United States)

    2015-07-31

    In this work a numerical finite element framework is implemented to enable the integration of coupled multiscale and multiphysics transport processes. A User Element subroutine (UEL) in Abaqus is used to simultaneously solve stress equilibrium, heat conduction, and multiple diffusion equations for 2D and 3D linear and quadratic elements. Transport processes in concrete structures and their degradation mechanisms are presented along with the discretization of the governing equations. The multiphysics modeling framework is theoretically extended to the linear elastic fracture mechanics (LEFM) by introducing the eXtended Finite Element Method (XFEM) and based on the XFEM user element implementation of Giner et al. [2009]. A damage model that takes into account the damage contribution from the different degradation mechanisms is theoretically developed. The total contribution of damage is forwarded to a Multi-Stage Fatigue (MSF) model to enable the assessment of the fatigue life and the deterioration of reinforced concrete structures in a nuclear power plant. Finally, two examples are presented to illustrate the developed multiphysics user element implementation and the XFEM implementation of Giner et al. [2009].

  8. Multiscale Models for the Two-Stream Instability

    Science.gov (United States)

    Joseph, Ilon; Dimits, Andris; Banks, Jeffrey; Berger, Richard; Brunner, Stephan; Chapman, Thomas

    2017-10-01

    Interpenetrating streams of plasma found in many important scenarios in nature and in the laboratory can develop kinetic two-stream instabilities that exchange momentum and energy between the streams. A quasilinear model for the electrostatic two-stream instability is under development as a component of a multiscale model that couples fluid simulations to kinetic theory. Parameters of the model will be validated with comparison to full kinetic simulations using LOKI and efficient strategies for numerical solution of the quasilinear model and for coupling to the fluid model will be discussed. Extending the kinetic models into the collisional regime requires an efficient treatment of the collision operator. Useful reductions of the collision operator relative to the full multi-species Landau-Fokker-Plank operator are being explored. These are further motivated both by careful consideration of the parameter orderings relevant to two-stream scenarios and by the particular 2D+2V phase space used in the LOKI code. Prepared for US DOE by LLNL under Contract DE-AC52-07NA27344 and LDRD project 17- ERD-081.

  9. How computational models can help unlock biological systems.

    Science.gov (United States)

    Brodland, G Wayne

    2015-12-01

    With computation models playing an ever increasing role in the advancement of science, it is important that researchers understand what it means to model something; recognize the implications of the conceptual, mathematical and algorithmic steps of model construction; and comprehend what models can and cannot do. Here, we use examples to show that models can serve a wide variety of roles, including hypothesis testing, generating new insights, deepening understanding, suggesting and interpreting experiments, tracing chains of causation, doing sensitivity analyses, integrating knowledge, and inspiring new approaches. We show that models can bring together information of different kinds and do so across a range of length scales, as they do in multi-scale, multi-faceted embryogenesis models, some of which connect gene expression, the cytoskeleton, cell properties, tissue mechanics, morphogenetic movements and phenotypes. Models cannot replace experiments nor can they prove that particular mechanisms are at work in a given situation. But they can demonstrate whether or not a proposed mechanism is sufficient to produce an observed phenomenon. Although the examples in this article are taken primarily from the field of embryo mechanics, most of the arguments and discussion are applicable to any form of computational modelling. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

  10. Review on modeling development for multiscale chemical reactions coupled transport phenomena in solid oxide fuel cells

    International Nuclear Information System (INIS)

    Andersson, Martin; Yuan, Jinliang; Sunden, Bengt

    2010-01-01

    A literature study is performed to compile the state-of-the-art, as well as future potential, in SOFC modeling. Principles behind various transport processes such as mass, heat, momentum and charge as well as for electrochemical and internal reforming reactions are described. A deeper investigation is made to find out potentials and challenges using a multiscale approach to model solid oxide fuel cells (SOFCs) and combine the accuracy at microscale with the calculation speed at macroscale to design SOFCs, based on a clear understanding of transport phenomena, chemical reactions and functional requirements. Suitable methods are studied to model SOFCs covering various length scales. Coupling methods between different approaches and length scales by multiscale models are outlined. Multiscale modeling increases the understanding for detailed transport phenomena, and can be used to make a correct decision on the specific design and control of operating conditions. It is expected that the development and production costs will be decreased and the energy efficiency be increased (reducing running cost) as the understanding of complex physical phenomena increases. It is concluded that the connection between numerical modeling and experiments is too rare and also that material parameters in most cases are valid only for standard materials and not for the actual SOFC component microstructures.

  11. Long-term Stable Conservative Multiscale Methods for Vortex Flows

    Science.gov (United States)

    2017-10-31

    Computing Department, Florida State (January 2016) - L. Rebholz, SIAM Southeast 2016, Special session on Recent advances in fluid flow and...Multiscale Methods for Vortex Flows (x) Material has been given an OPSEC review and it has been determined to be non sensitive and, except for...distribution is unlimited. UU UU UU UU 31-10-2017 1-Aug-2014 31-Jul-2017 Final Report: Long-term Stable Conservative Multiscale Methods for Vortex Flows

  12. Multiscale Pressure-Balanced Structures in Three-dimensional Magnetohydrodynamic Turbulence

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Liping; Zhang, Lei; Feng, Xueshang [SIGMA Weather Group, State Key Laboratory for Space Weather, National Space Science Center, Chinese Academy of Sciences, 100190, Beijing (China); He, Jiansen; Tu, Chuanyi; Wang, Linghua [School of Earth and Space Sciences, Peking University, 100871 Beijing (China); Li, Shengtai [Theoretical Division, MS B284, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Marsch, Eckart [Institute for Experimental and Applied Physics, Christian Albrechts University at Kiel, D-24118 Kiel (Germany); Wang, Xin, E-mail: jshept@gmail.com [School of Space and Environment, Beihang University, 100191 Beijing (China)

    2017-02-10

    Observations of solar wind turbulence indicate the existence of multiscale pressure-balanced structures (PBSs) in the solar wind. In this work, we conduct a numerical simulation to investigate multiscale PBSs and in particular their formation in compressive magnetohydrodynamic turbulence. By the use of the higher-order Godunov code Athena, a driven compressible turbulence with an imposed uniform guide field is simulated. The simulation results show that both the magnetic pressure and the thermal pressure exhibit a turbulent spectrum with a Kolmogorov-like power law, and that in many regions of the simulation domain they are anticorrelated. The computed wavelet cross-coherence spectra of the magnetic pressure and the thermal pressure, as well as their space series, indicate the existence of multiscale PBSs, with the small PBSs being embedded in the large ones. These multiscale PBSs are likely to be related to the highly oblique-propagating slow-mode waves, as the traced multiscale PBS is found to be traveling in a certain direction at a speed consistent with that predicted theoretically for a slow-mode wave propagating in the same direction.

  13. A New Computationally Frugal Method For Sensitivity Analysis Of Environmental Models

    Science.gov (United States)

    Rakovec, O.; Hill, M. C.; Clark, M. P.; Weerts, A.; Teuling, R.; Borgonovo, E.; Uijlenhoet, R.

    2013-12-01

    Effective and efficient parameter sensitivity analysis methods are crucial to understand the behaviour of complex environmental models and use of models in risk assessment. This paper proposes a new computationally frugal method for analyzing parameter sensitivity: the Distributed Evaluation of Local Sensitivity Analysis (DELSA). The DELSA method can be considered a hybrid of local and global methods, and focuses explicitly on multiscale evaluation of parameter sensitivity across the parameter space. Results of the DELSA method are compared with the popular global, variance-based Sobol' method and the delta method. We assess the parameter sensitivity of both (1) a simple non-linear reservoir model with only two parameters, and (2) five different "bucket-style" hydrologic models applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both the synthetic and real-world examples, the global Sobol' method and the DELSA method provide similar sensitivities, with the DELSA method providing more detailed insight at much lower computational cost. The ability to understand how sensitivity measures vary through parameter space with modest computational requirements provides exciting new opportunities.

  14. Prediction of irradiation damage effects by multi-scale modelling: EURATOM 3 Framework integrated project perfect

    International Nuclear Information System (INIS)

    Massoud, J.P.; Bugat, St.; Marini, B.; Lidbury, D.; Van Dyck, St.; Debarberis, L.

    2008-01-01

    Full text of publication follows. In nuclear PWRs, materials undergo degradation due to severe irradiation conditions that may limit their operational life. Utilities operating these reactors must quantify the aging and the potential degradations of reactor pressure vessels and also of internal structures to ensure safe and reliable plant operation. The EURATOM 6. Framework Integrated Project PERFECT (Prediction of Irradiation Damage Effects in Reactor Components) addresses irradiation damage in RPV materials and components by multi-scale modelling. This state-of-the-art approach offers potential advantages over the conventional empirical methods used in current practice of nuclear plant lifetime management. Launched in January 2004, this 48-month project is focusing on two main components of nuclear power plants which are subject to irradiation damage: the ferritic steel reactor pressure vessel and the austenitic steel internals. This project is also an opportunity to integrate the fragmented research and experience that currently exists within Europe in the field of numerical simulation of radiation damage and creates the links with international organisations involved in similar projects throughout the world. Continuous progress in the physical understanding of the phenomena involved in irradiation damage and continuous progress in computer sciences make possible the development of multi-scale numerical tools able to simulate the effects of irradiation on materials microstructure. The consequences of irradiation on mechanical and corrosion properties of materials are also tentatively modelled using such multi-scale modelling. But it requires to develop different mechanistic models at different levels of physics and engineering and to extend the state of knowledge in several scientific fields. And the links between these different kinds of models are particularly delicate to deal with and need specific works. Practically the main objective of PERFECT is to build

  15. Multivariate and multiscale data assimilation in terrestrial systems: a review.

    Science.gov (United States)

    Montzka, Carsten; Pauwels, Valentijn R N; Franssen, Harrie-Jan Hendricks; Han, Xujun; Vereecken, Harry

    2012-11-26

    More and more terrestrial observational networks are being established to monitor climatic, hydrological and land-use changes in different regions of the World. In these networks, time series of states and fluxes are recorded in an automated manner, often with a high temporal resolution. These data are important for the understanding of water, energy, and/or matter fluxes, as well as their biological and physical drivers and interactions with and within the terrestrial system. Similarly, the number and accuracy of variables, which can be observed by spaceborne sensors, are increasing. Data assimilation (DA) methods utilize these observations in terrestrial models in order to increase process knowledge as well as to improve forecasts for the system being studied. The widely implemented automation in observing environmental states and fluxes makes an operational computation more and more feasible, and it opens the perspective of short-time forecasts of the state of terrestrial systems. In this paper, we review the state of the art with respect to DA focusing on the joint assimilation of observational data precedents from different spatial scales and different data types. An introduction is given to different DA methods, such as the Ensemble Kalman Filter (EnKF), Particle Filter (PF) and variational methods (3/4D-VAR). In this review, we distinguish between four major DA approaches: (1) univariate single-scale DA (UVSS), which is the approach used in the majority of published DA applications, (2) univariate multiscale DA (UVMS) referring to a methodology which acknowledges that at least some of the assimilated data are measured at a different scale than the computational grid scale, (3) multivariate single-scale DA (MVSS) dealing with the assimilation of at least two different data types, and (4) combined multivariate multiscale DA (MVMS). Finally, we conclude with a discussion on the advantages and disadvantages of the assimilation of multiple data types in a

  16. Multivariate and Multiscale Data Assimilation in Terrestrial Systems: A Review

    Directory of Open Access Journals (Sweden)

    Harry Vereecken

    2012-11-01

    Full Text Available More and more terrestrial observational networks are being established to monitor climatic, hydrological and land-use changes in different regions of the World. In these networks, time series of states and fluxes are recorded in an automated manner, often with a high temporal resolution. These data are important for the understanding of water, energy, and/or matter fluxes, as well as their biological and physical drivers and interactions with and within the terrestrial system. Similarly, the number and accuracy of variables, which can be observed by spaceborne sensors, are increasing. Data assimilation (DA methods utilize these observations in terrestrial models in order to increase process knowledge as well as to improve forecasts for the system being studied. The widely implemented automation in observing environmental states and fluxes makes an operational computation more and more feasible, and it opens the perspective of short-time forecasts of the state of terrestrial systems. In this paper, we review the state of the art with respect to DA focusing on the joint assimilation of observational data precedents from different spatial scales and different data types. An introduction is given to different DA methods, such as the Ensemble Kalman Filter (EnKF, Particle Filter (PF and variational methods (3/4D-VAR. In this review, we distinguish between four major DA approaches: (1 univariate single-scale DA (UVSS, which is the approach used in the majority of published DA applications, (2 univariate multiscale DA (UVMS referring to a methodology which acknowledges that at least some of the assimilated data are measured at a different scale than the computational grid scale, (3 multivariate single-scale DA (MVSS dealing with the assimilation of at least two different data types, and (4 combined multivariate multiscale DA (MVMS. Finally, we conclude with a discussion on the advantages and disadvantages of the assimilation of multiple data types in a

  17. Predictive Multiscale Modeling of Nanocellulose Based Materials and Systems

    International Nuclear Information System (INIS)

    Kovalenko, Andriy

    2014-01-01

    Cellulose Nanocrysals (CNC) is a renewable biodegradable biopolymer with outstanding mechanical properties made from highly abundant natural source, and therefore is very attractive as reinforcing additive to replace petroleum-based plastics in biocomposite materials, foams, and gels. Large-scale applications of CNC are currently limited due to its low solubility in non-polar organic solvents used in existing polymerization technologies. The solvation properties of CNC can be improved by chemical modification of its surface. Development of effective surface modifications has been rather slow because extensive chemical modifications destabilize the hydrogen bonding network of cellulose and deteriorate the mechanical properties of CNC. We employ predictive multiscale theory, modeling, and simulation to gain a fundamental insight into the effect of CNC surface modifications on hydrogen bonding, CNC crystallinity, solvation thermodynamics, and CNC compatibilization with the existing polymerization technologies, so as to rationally design green nanomaterials with improved solubility in non-polar solvents, controlled liquid crystal ordering and optimized extrusion properties. An essential part of this multiscale modeling approach is the statistical- mechanical 3D-RISM-KH molecular theory of solvation, coupled with quantum mechanics, molecular mechanics, and multistep molecular dynamics simulation. The 3D-RISM-KH theory provides predictive modeling of both polar and non-polar solvents, solvent mixtures, and electrolyte solutions in a wide range of concentrations and thermodynamic states. It properly accounts for effective interactions in solution such as steric effects, hydrophobicity and hydrophilicity, hydrogen bonding, salt bridges, buffer, co-solvent, and successfully predicts solvation effects and processes in bulk liquids, solvation layers at solid surface, and in pockets and other inner spaces of macromolecules and supramolecular assemblies. This methodology

  18. Predictive Multiscale Modeling of Nanocellulose Based Materials and Systems

    Science.gov (United States)

    Kovalenko, Andriy

    2014-08-01

    Cellulose Nanocrysals (CNC) is a renewable biodegradable biopolymer with outstanding mechanical properties made from highly abundant natural source, and therefore is very attractive as reinforcing additive to replace petroleum-based plastics in biocomposite materials, foams, and gels. Large-scale applications of CNC are currently limited due to its low solubility in non-polar organic solvents used in existing polymerization technologies. The solvation properties of CNC can be improved by chemical modification of its surface. Development of effective surface modifications has been rather slow because extensive chemical modifications destabilize the hydrogen bonding network of cellulose and deteriorate the mechanical properties of CNC. We employ predictive multiscale theory, modeling, and simulation to gain a fundamental insight into the effect of CNC surface modifications on hydrogen bonding, CNC crystallinity, solvation thermodynamics, and CNC compatibilization with the existing polymerization technologies, so as to rationally design green nanomaterials with improved solubility in non-polar solvents, controlled liquid crystal ordering and optimized extrusion properties. An essential part of this multiscale modeling approach is the statistical- mechanical 3D-RISM-KH molecular theory of solvation, coupled with quantum mechanics, molecular mechanics, and multistep molecular dynamics simulation. The 3D-RISM-KH theory provides predictive modeling of both polar and non-polar solvents, solvent mixtures, and electrolyte solutions in a wide range of concentrations and thermodynamic states. It properly accounts for effective interactions in solution such as steric effects, hydrophobicity and hydrophilicity, hydrogen bonding, salt bridges, buffer, co-solvent, and successfully predicts solvation effects and processes in bulk liquids, solvation layers at solid surface, and in pockets and other inner spaces of macromolecules and supramolecular assemblies. This methodology

  19. A Multiscale Agent-Based in silico Model of Liver Fibrosis Progression

    Energy Technology Data Exchange (ETDEWEB)

    Dutta-Moscato, Joyeeta [Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, University of Pittsburgh, Pittsburgh, PA (United States); Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Solovyev, Alexey [Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Mathematics, University of Pittsburgh, Pittsburgh, PA (United States); Mi, Qi [Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, PA (United States); Nishikawa, Taichiro [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, Children’s Hospital of Pittsburgh, Pittsburgh, PA (United States); Soto-Gutierrez, Alejandro [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Pathology, University of Pittsburgh, Pittsburgh, PA (United States); Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA (United States); Fox, Ira J. [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, Children’s Hospital of Pittsburgh, Pittsburgh, PA (United States); Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA (United States); Vodovotz, Yoram, E-mail: vodovotzy@upmc.edu [Department of Surgery, University of Pittsburgh, Pittsburgh, PA (United States); Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States)

    2014-05-30

    Chronic hepatic inflammation involves a complex interplay of inflammatory and mechanical influences, ultimately manifesting in a characteristic histopathology of liver fibrosis. We created an agent-based model (ABM) of liver tissue in order to computationally examine the consequence of liver inflammation. Our liver fibrosis ABM (LFABM) is comprised of literature-derived rules describing molecular and histopathological aspects of inflammation and fibrosis in a section of chemically injured liver. Hepatocytes are modeled as agents within hexagonal lobules. Injury triggers an inflammatory reaction, which leads to activation of local Kupffer cells and recruitment of monocytes from circulation. Portal fibroblasts and hepatic stellate cells are activated locally by the products of inflammation. The various agents in the simulation are regulated by above-threshold concentrations of pro- and anti-inflammatory cytokines and damage-associated molecular pattern molecules. The simulation progresses from chronic inflammation to collagen deposition, exhibiting periportal fibrosis followed by bridging fibrosis, and culminating in disruption of the regular lobular structure. The ABM exhibited key histopathological features observed in liver sections from rats treated with carbon tetrachloride (CCl{sub 4}). An in silico “tension test” for the hepatic lobules predicted an overall increase in tissue stiffness, in line with clinical elastography literature and published studies in CCl{sub 4}-treated rats. Therapy simulations suggested differential anti-fibrotic effects of neutralizing tumor necrosis factor alpha vs. enhancing M2 Kupffer cells. We conclude that a computational model of liver inflammation on a structural skeleton of physical forces can recapitulate key histopathological and macroscopic properties of CCl{sub 4}-injured liver. This multiscale approach linking molecular and chemomechanical stimuli enables a model that could be used to gain translationally relevant

  20. Discrete-continuum multiscale model for transport, biomass development and solid restructuring in porous media

    Science.gov (United States)

    Ray, Nadja; Rupp, Andreas; Prechtel, Alexander

    2017-09-01

    Upscaling transport in porous media including both biomass development and simultaneous structural changes in the solid matrix is extremely challenging. This is because both affect the medium's porosity as well as mass transport parameters and flow paths. We address this challenge by means of a multiscale model. At the pore scale, the local discontinuous Galerkin (LDG) method is used to solve differential equations describing particularly the bacteria's and the nutrient's development. Likewise, a sticky agent tightening together solid or bio cells is considered. This is combined with a cellular automaton method (CAM) capturing structural changes of the underlying computational domain stemming from biomass development and solid restructuring. Findings from standard homogenization theory are applied to determine the medium's characteristic time- and space-dependent properties. Investigating these results enhances our understanding of the strong interplay between a medium's functional properties and its geometric structure. Finally, integrating such properties as model parameters into models defined on a larger scale enables reflecting the impact of pore scale processes on the larger scale.

  1. Stochastic processes, multiscale modeling, and numerical methods for computational cellular biology

    CERN Document Server

    2017-01-01

    This book focuses on the modeling and mathematical analysis of stochastic dynamical systems along with their simulations. The collected chapters will review fundamental and current topics and approaches to dynamical systems in cellular biology. This text aims to develop improved mathematical and computational methods with which to study biological processes. At the scale of a single cell, stochasticity becomes important due to low copy numbers of biological molecules, such as mRNA and proteins that take part in biochemical reactions driving cellular processes. When trying to describe such biological processes, the traditional deterministic models are often inadequate, precisely because of these low copy numbers. This book presents stochastic models, which are necessary to account for small particle numbers and extrinsic noise sources. The complexity of these models depend upon whether the biochemical reactions are diffusion-limited or reaction-limited. In the former case, one needs to adopt the framework of s...

  2. Multiscale phenomenology of the cosmic web

    NARCIS (Netherlands)

    Aragón-Calvo, Miguel A.; van de Weygaert, Rien; Jones, Bernard J. T.

    2010-01-01

    We analyse the structure and connectivity of the distinct morphologies that define the cosmic web. With the help of our multiscale morphology filter (MMF), we dissect the matter distribution of a cosmological Lambda cold dark matter N-body computer simulation into cluster, filaments and walls. The

  3. Multi-scale modelling and numerical simulation of electronic kinetic transport

    International Nuclear Information System (INIS)

    Duclous, R.

    2009-11-01

    This research thesis which is at the interface between numerical analysis, plasma physics and applied mathematics, deals with the kinetic modelling and numerical simulations of the electron energy transport and deposition in laser-produced plasmas, having in view the processes of fuel assembly to temperature and density conditions necessary to ignite fusion reactions. After a brief review of the processes at play in the collisional kinetic theory of plasmas, with a focus on basic models and methods to implement, couple and validate them, the author focuses on the collective aspect related to the free-streaming electron transport equation in the non-relativistic limit as well as in the relativistic regime. He discusses the numerical development and analysis of the scheme for the Vlasov-Maxwell system, and the selection of a validation procedure and numerical tests. Then, he investigates more specific aspects of the collective transport: the multi-specie transport, submitted to phase-space discontinuities. Dealing with the multi-scale physics of electron transport with collision source terms, he validates the accuracy of a fast Monte Carlo multi-grid solver for the Fokker-Planck-Landau electron-electron collision operator. He reports realistic simulations for the kinetic electron transport in the frame of the shock ignition scheme, the development and validation of a reduced electron transport angular model. He finally explores the relative importance of the processes involving electron-electron collisions at high energy by means a multi-scale reduced model with relativistic Boltzmann terms

  4. Generalized multiscale finite element methods (GMsFEM)

    KAUST Repository

    Efendiev, Yalchin R.; Galvis, Juan; Hou, Thomasyizhao

    2013-01-01

    In this paper, we propose a general approach called Generalized Multiscale Finite Element Method (GMsFEM) for performing multiscale simulations for problems without scale separation over a complex input space. As in multiscale finite element methods (MsFEMs), the main idea of the proposed approach is to construct a small dimensional local solution space that can be used to generate an efficient and accurate approximation to the multiscale solution with a potentially high dimensional input parameter space. In the proposed approach, we present a general procedure to construct the offline space that is used for a systematic enrichment of the coarse solution space in the online stage. The enrichment in the online stage is performed based on a spectral decomposition of the offline space. In the online stage, for any input parameter, a multiscale space is constructed to solve the global problem on a coarse grid. The online space is constructed via a spectral decomposition of the offline space and by choosing the eigenvectors corresponding to the largest eigenvalues. The computational saving is due to the fact that the construction of the online multiscale space for any input parameter is fast and this space can be re-used for solving the forward problem with any forcing and boundary condition. Compared with the other approaches where global snapshots are used, the local approach that we present in this paper allows us to eliminate unnecessary degrees of freedom on a coarse-grid level. We present various examples in the paper and some numerical results to demonstrate the effectiveness of our method. © 2013 Elsevier Inc.

  5. Generalized multiscale finite element methods (GMsFEM)

    KAUST Repository

    Efendiev, Yalchin R.

    2013-10-01

    In this paper, we propose a general approach called Generalized Multiscale Finite Element Method (GMsFEM) for performing multiscale simulations for problems without scale separation over a complex input space. As in multiscale finite element methods (MsFEMs), the main idea of the proposed approach is to construct a small dimensional local solution space that can be used to generate an efficient and accurate approximation to the multiscale solution with a potentially high dimensional input parameter space. In the proposed approach, we present a general procedure to construct the offline space that is used for a systematic enrichment of the coarse solution space in the online stage. The enrichment in the online stage is performed based on a spectral decomposition of the offline space. In the online stage, for any input parameter, a multiscale space is constructed to solve the global problem on a coarse grid. The online space is constructed via a spectral decomposition of the offline space and by choosing the eigenvectors corresponding to the largest eigenvalues. The computational saving is due to the fact that the construction of the online multiscale space for any input parameter is fast and this space can be re-used for solving the forward problem with any forcing and boundary condition. Compared with the other approaches where global snapshots are used, the local approach that we present in this paper allows us to eliminate unnecessary degrees of freedom on a coarse-grid level. We present various examples in the paper and some numerical results to demonstrate the effectiveness of our method. © 2013 Elsevier Inc.

  6. Evaluation of convergence behavior of metamodeling techniques for bridging scales in multi-scale multimaterial simulation

    International Nuclear Information System (INIS)

    Sen, Oishik; Davis, Sean; Jacobs, Gustaaf; Udaykumar, H.S.

    2015-01-01

    The effectiveness of several metamodeling techniques, viz. the Polynomial Stochastic Collocation method, Adaptive Stochastic Collocation method, a Radial Basis Function Neural Network, a Kriging Method and a Dynamic Kriging Method is evaluated. This is done with the express purpose of using metamodels to bridge scales between micro- and macro-scale models in a multi-scale multimaterial simulation. The rate of convergence of the error when used to reconstruct hypersurfaces of known functions is studied. For sufficiently large number of training points, Stochastic Collocation methods generally converge faster than the other metamodeling techniques, while the DKG method converges faster when the number of input points is less than 100 in a two-dimensional parameter space. Because the input points correspond to computationally expensive micro/meso-scale computations, the DKG is favored for bridging scales in a multi-scale solver

  7. Multiscale modelling for better hygrothermal prediction of porous building materials

    Directory of Open Access Journals (Sweden)

    Belarbi Rafik

    2018-01-01

    Full Text Available The aim of this work is to understand the influence of the microstructuralgeometric parameters of porous building materials on the mechanisms of coupled heat, air and moisture transfers, in order to predict behavior of the building to control and improve it in its durability. For this a multi-scale approach is implemented. It consists of mastering the dominant physical phenomena and their interactions on the microscopic scale. Followed by a dual-scale modelling, microscopic-macroscopic, of coupled heat, air and moisture transfers that takes into account the intrinsic properties and microstructural topology of the material using X-ray tomography combined with the correlation of 3D images were undertaken. In fact, the hygromorphicbehavior under hydric solicitations was considered. In this context, a model of coupled heat, air and moisture transfer in porous building materials was developed using the periodic homogenization technique. These informations were subsequently implemented in a dynamic computation simulation that model the hygrothermalbehaviourof material at the scale of the envelopes and indoor air quality of building. Results reveals that is essential to consider the local behaviors of materials, but also to be able to measure and quantify the evolution of its properties on a macroscopic scale from the youngest age of the material. In addition, comparisons between experimental and numerical temperature and relative humidity profilesin multilayers wall and in building envelopes were undertaken. Good agreements were observed.

  8. Sustainable Manufacturing via Multi-Scale, Physics-Based Process Modeling and Manufacturing-Informed Design

    Energy Technology Data Exchange (ETDEWEB)

    None

    2017-04-01

    This factsheet describes a project that developed and demonstrated a new manufacturing-informed design framework that utilizes advanced multi-scale, physics-based process modeling to dramatically improve manufacturing productivity and quality in machining operations while reducing the cost of machined components.

  9. A multiscale and multiphysics numerical framework for modelling of hygrothermal ageing in laminated composites

    NARCIS (Netherlands)

    Barcelos Carneiro M Rocha, Iuri; van der Meer, F.P.; Nijssen, RPL; Sluijs, Bert

    2017-01-01

    In this work, a numerical framework for modelling of hygrothermal ageing in laminated composites is proposed. The model consists of a macroscopic diffusion analysis based on Fick's second law coupled with a multiscale FE2 stress analysis in order to take microscopic degradation

  10. An Integrative, Multi-Scale Computational Model of a Swimming Lamprey Fully Coupled to Its Fluid Environment and Incorporating Proprioceptive Feedback

    Science.gov (United States)

    Hamlet, C. L.; Hoffman, K.; Fauci, L.; Tytell, E.

    2016-02-01

    The lamprey is a model organism for both neurophysiology and locomotion studies. To study the role of sensory feedback as an organism moves through its environment, a 2D, integrative, multi-scale model of an anguilliform swimmer driven by neural activation from a central pattern generator (CPG) is constructed. The CPG in turn drives muscle kinematics and is fully coupled to the surrounding fluid. The system is numerically evolved in time using an immersed boundary framework producing an emergent swimming mode. Proprioceptive feedback to the CPG based on experimental observations adjust the activation signal as the organism interacts with its environment. Effects on the speed, stability and cost (metabolic work) of swimming due to nonlinear dependencies associated with muscle force development combined with proprioceptive feedback to neural activation are estimated and examined.

  11. A multiscale coupled finite-element and phase-field framework to modeling stressed grain growth in polycrystalline thin films

    Energy Technology Data Exchange (ETDEWEB)

    Jamshidian, M., E-mail: jamshidian@cc.iut.ac.ir [Department of Mechanical Engineering, Isfahan University of Technology, Isfahan 84156-83111 (Iran, Islamic Republic of); Institute of Structural Mechanics, Bauhaus-University Weimar, Marienstrasse 15, 99423 Weimar (Germany); Thamburaja, P., E-mail: prakash.thamburaja@gmail.com [Department of Mechanical & Materials Engineering, Universiti Kebangsaan Malaysia (UKM), Bangi 43600 (Malaysia); Rabczuk, T., E-mail: timon.rabczuk@tdt.edu.vn [Division of Computational Mechanics, Ton Duc Thang University, Ho Chi Minh City (Viet Nam); Faculty of Civil Engineering, Ton Duc Thang University, Ho Chi Minh City (Viet Nam)

    2016-12-15

    A previously-developed finite-deformation- and crystal-elasticity-based constitutive theory for stressed grain growth in cubic polycrystalline bodies has been augmented to include a description of excess surface energy and grain-growth stagnation mechanisms through the use of surface effect state variables in a thermodynamically-consistent manner. The constitutive theory was also implemented into a multiscale coupled finite-element and phase-field computational framework. With the material parameters in the constitutive theory suitably calibrated, our three-dimensional numerical simulations show that the constitutive model is able to accurately predict the experimentally-determined evolution of crystallographic texture and grain size statistics in polycrystalline copper thin films deposited on polyimide substrate and annealed at high-homologous temperatures. In particular, our numerical analyses show that the broad texture transition observed in the annealing experiments of polycrystalline thin films is caused by grain growth stagnation mechanisms. - Graphical abstract: - Highlights: • Developing a theory for stressed grain growth in polycrystalline thin films. • Implementation into a multiscale coupled finite-element and phase-field framework. • Quantitative reproduction of the experimental grain growth data by simulations. • Revealing the cause of texture transition to be due to the stagnation mechanisms.

  12. Multiscale empirical interpolation for solving nonlinear PDEs

    KAUST Repository

    Calo, Victor M.; Efendiev, Yalchin R.; Galvis, Juan; Ghommem, Mehdi

    2014-01-01

    residuals and Jacobians on the fine grid. We use empirical interpolation concepts to evaluate these residuals and Jacobians of the multiscale system with a computational cost which is proportional to the size of the coarse-scale problem rather than the fully

  13. Evaluating and Improving Cloud Processes in the Multi-Scale Modeling Framework

    Energy Technology Data Exchange (ETDEWEB)

    Ackerman, Thomas P. [Univ. of Washington, Seattle, WA (United States)

    2015-03-01

    The research performed under this grant was intended to improve the embedded cloud model in the Multi-scale Modeling Framework (MMF) for convective clouds by using a 2-moment microphysics scheme rather than the single moment scheme used in all the MMF runs to date. The technical report and associated documents describe the results of testing the cloud resolving model with fixed boundary conditions and evaluation of model results with data. The overarching conclusion is that such model evaluations are problematic because errors in the forcing fields control the results so strongly that variations in parameterization values cannot be usefully constrained

  14. Predicting FLDs Using a Multiscale Modeling Scheme

    Science.gov (United States)

    Wu, Z.; Loy, C.; Wang, E.; Hegadekatte, V.

    2017-09-01

    The measurement of a single forming limit diagram (FLD) requires significant resources and is time consuming. We have developed a multiscale modeling scheme to predict FLDs using a combination of limited laboratory testing, crystal plasticity (VPSC) modeling, and dual sequential-stage finite element (ABAQUS/Explicit) modeling with the Marciniak-Kuczynski (M-K) criterion to determine the limit strain. We have established a means to work around existing limitations in ABAQUS/Explicit by using an anisotropic yield locus (e.g., BBC2008) in combination with the M-K criterion. We further apply a VPSC model to reduce the number of laboratory tests required to characterize the anisotropic yield locus. In the present work, we show that the predicted FLD is in excellent agreement with the measured FLD for AA5182 in the O temper. Instead of 13 different tests as for a traditional FLD determination within Novelis, our technique uses just four measurements: tensile properties in three orientations; plane strain tension; biaxial bulge; and the sheet crystallographic texture. The turnaround time is consequently far less than for the traditional laboratory measurement of the FLD.

  15. Multiscale modeling of polyisoprene on graphite

    International Nuclear Information System (INIS)

    Pandey, Yogendra Narayan; Brayton, Alexander; Doxastakis, Manolis; Burkhart, Craig; Papakonstantopoulos, George J.

    2014-01-01

    The local dynamics and the conformational properties of polyisoprene next to a smooth graphite surface constructed by graphene layers are studied by a multiscale methodology. First, fully atomistic molecular dynamics simulations of oligomers next to the surface are performed. Subsequently, Monte Carlo simulations of a systematically derived coarse-grained model generate numerous uncorrelated structures for polymer systems. A new reverse backmapping strategy is presented that reintroduces atomistic detail. Finally, multiple extensive fully atomistic simulations with large systems of long macromolecules are employed to examine local dynamics in proximity to graphite. Polyisoprene repeat units arrange close to a parallel configuration with chains exhibiting a distribution of contact lengths. Efficient Monte Carlo algorithms with the coarse-grain model are capable of sampling these distributions for any molecular weight in quantitative agreement with predictions from atomistic models. Furthermore, molecular dynamics simulations with well-equilibrated systems at all length-scales support an increased dynamic heterogeneity that is emerging from both intermolecular interactions with the flat surface and intramolecular cooperativity. This study provides a detailed comprehensive picture of polyisoprene on a flat surface and consists of an effort to characterize such systems in atomistic detail

  16. Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids

    Energy Technology Data Exchange (ETDEWEB)

    Jablonowski, Christiane [Univ. of Michigan, Ann Arbor, MI (United States)

    2015-07-14

    The research investigates and advances strategies how to bridge the scale discrepancies between local, regional and global phenomena in climate models without the prohibitive computational costs of global cloud-resolving simulations. In particular, the research explores new frontiers in computational geoscience by introducing high-order Adaptive Mesh Refinement (AMR) techniques into climate research. AMR and statically-adapted variable-resolution approaches represent an emerging trend for atmospheric models and are likely to become the new norm in future-generation weather and climate models. The research advances the understanding of multi-scale interactions in the climate system and showcases a pathway how to model these interactions effectively with advanced computational tools, like the Chombo AMR library developed at the Lawrence Berkeley National Laboratory. The research is interdisciplinary and combines applied mathematics, scientific computing and the atmospheric sciences. In this research project, a hierarchy of high-order atmospheric models on cubed-sphere computational grids have been developed that serve as an algorithmic prototype for the finite-volume solution-adaptive Chombo-AMR approach. The foci of the investigations have lied on the characteristics of both static mesh adaptations and dynamically-adaptive grids that can capture flow fields of interest like tropical cyclones. Six research themes have been chosen. These are (1) the introduction of adaptive mesh refinement techniques into the climate sciences, (2) advanced algorithms for nonhydrostatic atmospheric dynamical cores, (3) an assessment of the interplay between resolved-scale dynamical motions and subgrid-scale physical parameterizations, (4) evaluation techniques for atmospheric model hierarchies, (5) the comparison of AMR refinement strategies and (6) tropical cyclone studies with a focus on multi-scale interactions and variable-resolution modeling. The results of this research project

  17. A fast random walk algorithm for computing the pulsed-gradient spin-echo signal in multiscale porous media.

    Science.gov (United States)

    Grebenkov, Denis S

    2011-02-01

    A new method for computing the signal attenuation due to restricted diffusion in a linear magnetic field gradient is proposed. A fast random walk (FRW) algorithm for simulating random trajectories of diffusing spin-bearing particles is combined with gradient encoding. As random moves of a FRW are continuously adapted to local geometrical length scales, the method is efficient for simulating pulsed-gradient spin-echo experiments in hierarchical or multiscale porous media such as concrete, sandstones, sedimentary rocks and, potentially, brain or lungs. Copyright © 2010 Elsevier Inc. All rights reserved.

  18. A multi-scale energy demand model suggests sharing market risks with intelligent energy cooperatives

    NARCIS (Netherlands)

    G. Methenitis (Georgios); M. Kaisers (Michael); J.A. La Poutré (Han)

    2015-01-01

    textabstractIn this paper, we propose a multi-scale model of energy demand that is consistent with observations at a macro scale, in our use-case standard load profiles for (residential) electric loads. We employ the model to study incentives to assume the risk of volatile market prices for

  19. Multiscale Modeling of Mesoscale and Interfacial Phenomena

    Science.gov (United States)

    Petsev, Nikolai Dimitrov

    we provide a novel and general framework for multiscale modeling of systems featuring one or more dissolved species. This makes it possible to retain molecular detail for parts of the problem that require it while using a simple, continuum description for parts where high detail is unnecessary, reducing the number of degrees of freedom (i.e. number of particles) dramatically. This opens the possibility for modeling ion transport in biological processes and biomolecule assembly in ionic solution, as well as electrokinetic phenomena at interfaces such as corrosion. The number of particles in the system is further reduced through an integrated boundary approach, which we apply to colloidal suspensions. In this thesis, we describe this general framework for multiscale modeling single- and multicomponent systems, provide several simple equilibrium and non-equilibrium case studies, and discuss future applications.

  20. Multiscale singularity trees

    DEFF Research Database (Denmark)

    Somchaipeng, Kerawit; Sporring, Jon; Johansen, Peter

    2007-01-01

    We propose MultiScale Singularity Trees (MSSTs) as a structure to represent images, and we propose an algorithm for image comparison based on comparing MSSTs. The algorithm is tested on 3 public image databases and compared to 2 state-of-theart methods. We conclude that the computational complexity...... of our algorithm only allows for the comparison of small trees, and that the results of our method are comparable with state-of-the-art using much fewer parameters for image representation....

  1. Toward multiscale modelings of grain-fluid systems

    Science.gov (United States)

    Chareyre, Bruno; Yuan, Chao; Montella, Eduard P.; Salager, Simon

    2017-06-01

    Computationally efficient methods have been developed for simulating partially saturated granular materials in the pendular regime. In contrast, one hardly avoid expensive direct resolutions of 2-phase fluid dynamics problem for mixed pendular-funicular situations or even saturated regimes. Following previous developments for single-phase flow, a pore-network approach of the coupling problems is described. The geometry and movements of phases and interfaces are described on the basis of a tetrahedrization of the pore space, introducing elementary objects such as bridge, meniscus, pore body and pore throat, together with local rules of evolution. As firmly established local rules are still missing on some aspects (entry capillary pressure and pore-scale pressure-saturation relations, forces on the grains, or kinetics of transfers in mixed situations) a multi-scale numerical framework is introduced, enhancing the pore-network approach with the help of direct simulations. Small subsets of a granular system are extracted, in which multiphase scenario are solved using the Lattice-Boltzman method (LBM). In turns, a global problem is assembled and solved at the network scale, as illustrated by a simulated primary drainage.

  2. Stochastic scalar mixing models accounting for turbulent frequency multiscale fluctuations

    International Nuclear Information System (INIS)

    Soulard, Olivier; Sabel'nikov, Vladimir; Gorokhovski, Michael

    2004-01-01

    Two new scalar micromixing models accounting for a turbulent frequency scale distribution are investigated. These models were derived by Sabel'nikov and Gorokhovski [Second International Symposium on Turbulence and Shear FLow Phenomena, Royal Institute of technology (KTH), Stockholm, Sweden, June 27-29, 2001] using a multiscale extension of the classical interaction by exchange with the mean (IEM) and Langevin models. They are, respectively, called Extended IEM (EIEM) and Extended Langevin (ELM) models. The EIEM and ELM models are tested against DNS results in the case of the decay of a homogeneous scalar field in homogeneous turbulence. This comparison leads to a reformulation of the law governing the mixing frequency distribution. Finally, the asymptotic behaviour of the modeled PDF is discussed

  3. Multiscale time-splitting strategy for multiscale multiphysics processes of two-phase flow in fractured media

    KAUST Repository

    Sun, S.; Kou, J.; Yu, B.

    2011-01-01

    The temporal discretization scheme is one important ingredient of efficient simulator for two-phase flow in the fractured porous media. The application of single-scale temporal scheme is restricted by the rapid changes of the pressure and saturation in the fractured system with capillarity. In this paper, we propose a multi-scale time splitting strategy to simulate multi-scale multi-physics processes of two-phase flow in fractured porous media. We use the multi-scale time schemes for both the pressure and saturation equations; that is, a large time-step size is employed for the matrix domain, along with a small time-step size being applied in the fractures. The total time interval is partitioned into four temporal levels: the first level is used for the pressure in the entire domain, the second level matching rapid changes of the pressure in the fractures, the third level treating the response gap between the pressure and the saturation, and the fourth level applied for the saturation in the fractures. This method can reduce the computational cost arisen from the implicit solution of the pressure equation. Numerical examples are provided to demonstrate the efficiency of the proposed method.

  4. A hybrid model for dissolved oxygen prediction in aquaculture based on multi-scale features

    Directory of Open Access Journals (Sweden)

    Chen Li

    2018-03-01

    Full Text Available To increase prediction accuracy of dissolved oxygen (DO in aquaculture, a hybrid model based on multi-scale features using ensemble empirical mode decomposition (EEMD is proposed. Firstly, original DO datasets are decomposed by EEMD and we get several components. Secondly, these components are used to reconstruct four terms including high frequency term, intermediate frequency term, low frequency term and trend term. Thirdly, according to the characteristics of high and intermediate frequency terms, which fluctuate violently, the least squares support vector machine (LSSVR is used to predict the two terms. The fluctuation of low frequency term is gentle and periodic, so it can be modeled by BP neural network with an optimal mind evolutionary computation (MEC-BP. Then, the trend term is predicted using grey model (GM because it is nearly linear. Finally, the prediction values of DO datasets are calculated by the sum of the forecasting values of all terms. The experimental results demonstrate that our hybrid model outperforms EEMD-ELM (extreme learning machine based on EEMD, EEMD-BP and MEC-BP models based on the mean absolute error (MAE, mean absolute percentage error (MAPE, mean square error (MSE and root mean square error (RMSE. Our hybrid model is proven to be an effective approach to predict aquaculture DO.

  5. From the direct numerical simulation to system codes-perspective for the multi-scale analysis of LWR thermal hydraulics

    International Nuclear Information System (INIS)

    Bestion, D.

    2010-01-01

    A multi-scale analysis of water-cooled reactor thermal hydraulics can be used to take advantage of increased computer power and improved simulation tools, including Direct Numerical Simulation (DNS), Computational Fluid Dynamics (CFD) (in both open and porous mediums), and system thermalhydraulic codes. This paper presents a general strategy for this procedure for various thermalhydraulic scales. A short state of the art is given for each scale, and the role of the scale in the overall multi-scale analysis process is defined. System thermalhydraulic codes will remain a privileged tool for many investigations related to safety. CFD in porous medium is already being frequently used for core thermal hydraulics, either in 3D modules of system codes or in component codes. CFD in open medium allows zooming on some reactor components in specific situations, and may be coupled to the system and component scales. Various modeling approaches exist in the domain from DNS to CFD which may be used to improve the understanding of flow processes, and as a basis for developing more physically based models for macroscopic tools. A few examples are given to illustrate the multi-scale approach. Perspectives for the future are drawn from the present state of the art and directions for future research and development are given

  6. Combining computer modelling and cardiac imaging to understand right ventricular pump function.

    Science.gov (United States)

    Walmsley, John; van Everdingen, Wouter; Cramer, Maarten J; Prinzen, Frits W; Delhaas, Tammo; Lumens, Joost

    2017-10-01

    Right ventricular (RV) dysfunction is a strong predictor of outcome in heart failure and is a key determinant of exercise capacity. Despite these crucial findings, the RV remains understudied in the clinical, experimental, and computer modelling literature. This review outlines how recent advances in using computer modelling and cardiac imaging synergistically help to understand RV function in health and disease. We begin by highlighting the complexity of interactions that make modelling the RV both challenging and necessary, and then summarize the multiscale modelling approaches used to date to simulate RV pump function in the context of these interactions. We go on to demonstrate how these modelling approaches in combination with cardiac imaging have improved understanding of RV pump function in pulmonary arterial hypertension, arrhythmogenic right ventricular cardiomyopathy, dyssynchronous heart failure and cardiac resynchronization therapy, hypoplastic left heart syndrome, and repaired tetralogy of Fallot. We conclude with a perspective on key issues to be addressed by computational models of the RV in the near future. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: journals.permissions@oup.com.

  7. Multiscale Modeling of a Conditionally Disordered pH-Sensing Chaperone

    OpenAIRE

    Ahlstrom, Logan S.; Law, Sean M.; Dickson, Alex; Brooks, Charles L.

    2015-01-01

    The pH-sensing chaperone HdeA promotes the survival of enteropathogenic bacteria during transit through the harshly acidic environment of the mammalian stomach. At low pH, HdeA transitions from an inactive, folded, dimer to chaperone-active, disordered, monomers to protect against the acid-induced aggregation of periplasmic proteins. Toward achieving a detailed mechanistic understanding of the pH response of HdeA, we develop a multiscale modeling approach to capture its pH-dependent thermodyn...

  8. Physically based multiscale-viscoplastic model for metals and steel alloys: Theory and computation

    Science.gov (United States)

    Abed, Farid H.

    The main requirement of large deformation problems such as high-speed machining, impact, and various primarily metal forming, is to develop constitutive relations which are widely applicable and capable of accounting for complex paths of deformation. Achieving such desirable goals for material like metals and steel alloys involves a comprehensive study of their microstructures and experimental observations under different loading conditions. In general, metal structures display a strong rate- and temperature-dependence when deformed non-uniformly into the inelastic range. This effect has important implications for an increasing number of applications in structural and engineering mechanics. The mechanical behavior of these applications cannot be characterized by classical (rate-independent) continuum theories because they incorporate no 'material length scales'. It is therefore necessary to develop a rate-dependent (viscoplasticity) continuum theory bridging the gap between the classical continuum theories and the microstructure simulations. Physically based vicoplasticity models for different types of metals (body centered cubic, face centered cubic and hexagonal close-packed) and steel alloys are derived in this work for this purpose. We adopt a multi-scale, hierarchical thermodynamic consistent framework to construct the material constitutive relations for the rate-dependent behavior. The concept of thermal activation energy, dislocations interactions mechanisms and the role of dislocations dynamics in crystals are used in the derivation process taking into consideration the contribution of the plastic strain evolution of dislocation density to the flow stress of polycrystalline metals. Material length scales are implicitly introduced into the governing equations through material rate-dependency (viscosity). The proposed framework is implemented into the commercially well-known finite element software ABAQUS. The finite element simulations of material

  9. A Novel Multiscale Ensemble Carbon Price Prediction Model Integrating Empirical Mode Decomposition, Genetic Algorithm and Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Bangzhu Zhu

    2012-02-01

    Full Text Available Due to the movement and complexity of the carbon market, traditional monoscale forecasting approaches often fail to capture its nonstationary and nonlinear properties and accurately describe its moving tendencies. In this study, a multiscale ensemble forecasting model integrating empirical mode decomposition (EMD, genetic algorithm (GA and artificial neural network (ANN is proposed to forecast carbon price. Firstly, the proposed model uses EMD to decompose carbon price data into several intrinsic mode functions (IMFs and one residue. Then, the IMFs and residue are composed into a high frequency component, a low frequency component and a trend component which have similar frequency characteristics, simple components and strong regularity using the fine-to-coarse reconstruction algorithm. Finally, those three components are predicted using an ANN trained by GA, i.e., a GAANN model, and the final forecasting results can be obtained by the sum of these three forecasting results. For verification and testing, two main carbon future prices with different maturity in the European Climate Exchange (ECX are used to test the effectiveness of the proposed multiscale ensemble forecasting model. Empirical results obtained demonstrate that the proposed multiscale ensemble forecasting model can outperform the single random walk (RW, ARIMA, ANN and GAANN models without EMD preprocessing and the ensemble ARIMA model with EMD preprocessing.

  10. FEM × DEM: a new efficient multi-scale approach for geotechnical problems with strain localization

    Directory of Open Access Journals (Sweden)

    Nguyen Trung Kien

    2017-01-01

    Full Text Available The paper presents a multi-scale modeling of Boundary Value Problem (BVP approach involving cohesive-frictional granular materials in the FEM × DEM multi-scale framework. On the DEM side, a 3D model is defined based on the interactions of spherical particles. This DEM model is built through a numerical homogenization process applied to a Volume Element (VE. It is then paired with a Finite Element code. Using this numerical tool that combines two scales within the same framework, we conducted simulations of biaxial and pressuremeter tests on a cohesive-frictional granular medium. In these cases, it is known that strain localization does occur at the macroscopic level, but since FEMs suffer from severe mesh dependency as soon as shear band starts to develop, the second gradient regularization technique has been used. As a consequence, the objectivity of the computation with respect to mesh dependency is restored.

  11. A Multi-Scale Energy Food Systems Modeling Framework For Climate Adaptation

    Science.gov (United States)

    Siddiqui, S.; Bakker, C.; Zaitchik, B. F.; Hobbs, B. F.; Broaddus, E.; Neff, R.; Haskett, J.; Parker, C.

    2016-12-01

    Our goal is to understand coupled system dynamics across scales in a manner that allows us to quantify the sensitivity of critical human outcomes (nutritional satisfaction, household economic well-being) to development strategies and to climate or market induced shocks in sub-Saharan Africa. We adopt both bottom-up and top-down multi-scale modeling approaches focusing our efforts on food, energy, water (FEW) dynamics to define, parameterize, and evaluate modeled processes nationally as well as across climate zones and communities. Our framework comprises three complementary modeling techniques spanning local, sub-national and national scales to capture interdependencies between sectors, across time scales, and on multiple levels of geographic aggregation. At the center is a multi-player micro-economic (MME) partial equilibrium model for the production, consumption, storage, and transportation of food, energy, and fuels, which is the focus of this presentation. We show why such models can be very useful for linking and integrating across time and spatial scales, as well as a wide variety of models including an agent-based model applied to rural villages and larger population centers, an optimization-based electricity infrastructure model at a regional scale, and a computable general equilibrium model, which is applied to understand FEW resources and economic patterns at national scale. The MME is based on aggregating individual optimization problems for relevant players in an energy, electricity, or food market and captures important food supply chain components of trade and food distribution accounting for infrastructure and geography. Second, our model considers food access and utilization by modeling food waste and disaggregating consumption by income and age. Third, the model is set up to evaluate the effects of seasonality and system shocks on supply, demand, infrastructure, and transportation in both energy and food.

  12. The role of alpha-rhythm states in perceptual learning: insights from experiments and computational models

    Science.gov (United States)

    Sigala, Rodrigo; Haufe, Sebastian; Roy, Dipanjan; Dinse, Hubert R.; Ritter, Petra

    2014-01-01

    During the past two decades growing evidence indicates that brain oscillations in the alpha band (~10 Hz) not only reflect an “idle” state of cortical activity, but also take a more active role in the generation of complex cognitive functions. A recent study shows that more than 60% of the observed inter-subject variability in perceptual learning can be ascribed to ongoing alpha activity. This evidence indicates a significant role of alpha oscillations for perceptual learning and hence motivates to explore the potential underlying mechanisms. Hence, it is the purpose of this review to highlight existent evidence that ascribes intrinsic alpha oscillations a role in shaping our ability to learn. In the review, we disentangle the alpha rhythm into different neural signatures that control information processing within individual functional building blocks of perceptual learning. We further highlight computational studies that shed light on potential mechanisms regarding how alpha oscillations may modulate information transfer and connectivity changes relevant for learning. To enable testing of those model based hypotheses, we emphasize the need for multidisciplinary approaches combining assessment of behavior and multi-scale neuronal activity, active modulation of ongoing brain states and computational modeling to reveal the mathematical principles of the complex neuronal interactions. In particular we highlight the relevance of multi-scale modeling frameworks such as the one currently being developed by “The Virtual Brain” project. PMID:24772077

  13. The role of alpha-rhythm states in perceptual learning: insights from experiments and computational models

    Directory of Open Access Journals (Sweden)

    Rodrigo eSigala

    2014-04-01

    Full Text Available During the past two decades growing evidence indicates that brain oscillations in the alpha band (~10 Hz not only reflect an ‘idle’ state of cortical activity, but also take a more active role in the generation of complex cognitive functions. A recent study shows that more than 60% of the observed inter-subject variability in perceptual learning can be ascribed to ongoing alpha activity. This evidence indicates a significant role of alpha oscillations for perceptual learning and hence motivates to explore the potential underlying mechanisms. Hence, it is the purpose of this review to highlight existent evidence that ascribes intrinsic alpha oscillations a role in shaping our ability to learn. In the review, we disentangle the alpha rhythm into different neural signatures that control information processing within individual functional building blocks of perceptual learning. We further highlight computational studies that shed light on potential mechanisms regarding how alpha oscillations may modulate information transfer and connectivity changes relevant for learning. To enable testing of those model based hypotheses, we emphasize the need for multidisciplinary approaches combining assessment of behavior and multi-scale neuronal activity, active modulation of ongoing brain states and computational modeling to reveal the mathematical principles of the complex neuronal interactions. In particular we highlight the relevance of multi-scale modeling frameworks such as the one currently being developed by The Virtual Brain project.

  14. Framework for adaptive multiscale analysis of nonhomogeneous point processes.

    Science.gov (United States)

    Helgason, Hannes; Bartroff, Jay; Abry, Patrice

    2011-01-01

    We develop the methodology for hypothesis testing and model selection in nonhomogeneous Poisson processes, with an eye toward the application of modeling and variability detection in heart beat data. Modeling the process' non-constant rate function using templates of simple basis functions, we develop the generalized likelihood ratio statistic for a given template and a multiple testing scheme to model-select from a family of templates. A dynamic programming algorithm inspired by network flows is used to compute the maximum likelihood template in a multiscale manner. In a numerical example, the proposed procedure is nearly as powerful as the super-optimal procedures that know the true template size and true partition, respectively. Extensions to general history-dependent point processes is discussed.

  15. Industrial process system assessment: bridging process engineering and life cycle assessment through multiscale modeling.

    Science.gov (United States)

    The Industrial Process System Assessment (IPSA) methodology is a multiple step allocation approach for connecting information from the production line level up to the facility level and vice versa using a multiscale model of process systems. The allocation procedure assigns inpu...

  16. Multiscale Simulation Framework for Coupled Fluid Flow and Mechanical Deformation

    Energy Technology Data Exchange (ETDEWEB)

    Hou, Thomas [California Inst. of Technology (CalTech), Pasadena, CA (United States); Efendiev, Yalchin [Stanford Univ., CA (United States); Tchelepi, Hamdi [Texas A & M Univ., College Station, TX (United States); Durlofsky, Louis [Stanford Univ., CA (United States)

    2016-05-24

    Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scale basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics.

  17. Three-Phase Carbon Fiber Amine Functionalized Carbon Nanotubes Epoxy Composite: Processing, Characterisation, and Multiscale Modeling

    Directory of Open Access Journals (Sweden)

    Kamal Sharma

    2014-01-01

    Full Text Available The present paper discusses the key issues of carbon nanotube (CNT dispersion and effect of functionalisation on the mechanical properties of multiscale carbon epoxy composites. In this study, CNTs were added in epoxy matrix and further reinforced with carbon fibres. Predetermined amounts of optimally amine functionalised CNTs were dispersed in epoxy matrix, and unidirectional carbon fiber laminates were produced. The effect of the presence of CNTs (1.0 wt% in the resin was reflected by pronounced increase in Young’s modulus, inter-laminar shear strength, and flexural modulus by 51.46%, 39.62%, and 38.04%, respectively. However, 1.5 wt% CNT loading in epoxy resin decreased the overall properties of the three-phase composites. A combination of Halpin-Tsai equations and micromechanics modeling approach was also used to evaluate the mechanical properties of multiscale composites and the differences between the predicted and experimental values are reported. These multiscale composites are likely to be used for potential missile and aerospace structural applications.

  18. Development of high-resolution multi-scale modelling system for simulation of coastal-fluvial urban flooding

    Science.gov (United States)

    Comer, Joanne; Indiana Olbert, Agnieszka; Nash, Stephen; Hartnett, Michael

    2017-02-01

    Urban developments in coastal zones are often exposed to natural hazards such as flooding. In this research, a state-of-the-art, multi-scale nested flood (MSN_Flood) model is applied to simulate complex coastal-fluvial urban flooding due to combined effects of tides, surges and river discharges. Cork city on Ireland's southwest coast is a study case. The flood modelling system comprises a cascade of four dynamically linked models that resolve the hydrodynamics of Cork Harbour and/or its sub-region at four scales: 90, 30, 6 and 2 m. Results demonstrate that the internalization of the nested boundary through the use of ghost cells combined with a tailored adaptive interpolation technique creates a highly dynamic moving boundary that permits flooding and drying of the nested boundary. This novel feature of MSN_Flood provides a high degree of choice regarding the location of the boundaries to the nested domain and therefore flexibility in model application. The nested MSN_Flood model through dynamic downscaling facilitates significant improvements in accuracy of model output without incurring the computational expense of high spatial resolution over the entire model domain. The urban flood model provides full characteristics of water levels and flow regimes necessary for flood hazard identification and flood risk assessment.

  19. Examining Multiscale Movement Coordination in Collaborative Problem Solving

    DEFF Research Database (Denmark)

    Wiltshire, Travis; Steffensen, Sune Vork

    2017-01-01

    During collaborative problem solving (CPS), coordination occurs at different spatial and temporal scales. This multiscale coordination should, at least on some scales, play a functional role in facilitating effective collaboration outcomes. To evaluate this, we conducted a study of computer...

  20. A Multiscale Finite Element Model Validation Method of Composite Cable-Stayed Bridge Based on Structural Health Monitoring System

    Directory of Open Access Journals (Sweden)

    Rumian Zhong

    2015-01-01

    Full Text Available A two-step response surface method for multiscale finite element model (FEM updating and validation is presented with respect to Guanhe Bridge, a composite cable-stayed bridge in the National Highway number G15, in China. Firstly, the state equations of both multiscale and single-scale FEM are established based on the basic equation in structural dynamic mechanics to update the multiscale coupling parameters and structural parameters. Secondly, based on the measured data from the structural health monitoring (SHM system, a Monte Carlo simulation is employed to analyze the uncertainty quantification and transmission, where the uncertainties of the multiscale FEM and measured data were considered. The results indicate that the relative errors between the calculated and measured frequencies are less than 2%, and the overlap ratio indexes of each modal frequency are larger than 80% without the average absolute value of relative errors. These demonstrate that the proposed method can be applied to validate the multiscale FEM, and the validated FEM can reflect the current conditions of the real bridge; thus it can be used as the basis for bridge health monitoring, damage prognosis (DP, and safety prognosis (SP.

  1. A multi-scale model for correlation in B cell VDJ usage of zebrafish

    International Nuclear Information System (INIS)

    Pan, Keyao; Deem, Michael W

    2011-01-01

    The zebrafish (Danio rerio) is one of the model animals used for the study of immunology because the dynamics in the adaptive immune system of zebrafish are similar to that in higher animals. In this work, we built a multi-scale model to simulate the dynamics of B cells in the primary and secondary immune responses of zebrafish. We use this model to explain the reported correlation between VDJ usage of B cell repertoires in individual zebrafish. We use a delay ordinary differential equation (ODE) system to model the immune responses in the 6-month lifespan of a zebrafish. This mean field theory gives the number of high-affinity B cells as a function of time during an infection. The sequences of those B cells are then taken from a distribution calculated by a 'microscopic' random energy model. This generalized NK model shows that mature B cells specific to one antigen largely possess a single VDJ recombination. The model allows first-principle calculation of the probability, p, that two zebrafish responding to the same antigen will select the same VDJ recombination. This probability p increases with the B cell population size and the B cell selection intensity. The probability p decreases with the B cell hypermutation rate. The multi-scale model predicts correlations in the immune system of the zebrafish that are highly similar to that from experiment

  2. A multi-scale model for correlation in B cell VDJ usage of zebrafish

    Science.gov (United States)

    Pan, Keyao; Deem, Michael W.

    2011-10-01

    The zebrafish (Danio rerio) is one of the model animals used for the study of immunology because the dynamics in the adaptive immune system of zebrafish are similar to that in higher animals. In this work, we built a multi-scale model to simulate the dynamics of B cells in the primary and secondary immune responses of zebrafish. We use this model to explain the reported correlation between VDJ usage of B cell repertoires in individual zebrafish. We use a delay ordinary differential equation (ODE) system to model the immune responses in the 6-month lifespan of a zebrafish. This mean field theory gives the number of high-affinity B cells as a function of time during an infection. The sequences of those B cells are then taken from a distribution calculated by a 'microscopic' random energy model. This generalized NK model shows that mature B cells specific to one antigen largely possess a single VDJ recombination. The model allows first-principle calculation of the probability, p, that two zebrafish responding to the same antigen will select the same VDJ recombination. This probability p increases with the B cell population size and the B cell selection intensity. The probability p decreases with the B cell hypermutation rate. The multi-scale model predicts correlations in the immune system of the zebrafish that are highly similar to that from experiment.

  3. Multiscale image-based modeling and simulation of gas flow and particle transport in the human lungs

    Science.gov (United States)

    Tawhai, Merryn H; Hoffman, Eric A

    2013-01-01

    Improved understanding of structure and function relationships in the human lungs in individuals and sub-populations is fundamentally important to the future of pulmonary medicine. Image-based measures of the lungs can provide sensitive indicators of localized features, however to provide a better prediction of lung response to disease, treatment and environment, it is desirable to integrate quantifiable regional features from imaging with associated value-added high-level modeling. With this objective in mind, recent advances in computational fluid dynamics (CFD) of the bronchial airways - from a single bifurcation symmetric model to a multiscale image-based subject-specific lung model - will be reviewed. The interaction of CFD models with local parenchymal tissue expansion - assessed by image registration - allows new understanding of the interplay between environment, hot spots where inhaled aerosols could accumulate, and inflammation. To bridge ventilation function with image-derived central airway structure in CFD, an airway geometrical modeling method that spans from the model ‘entrance’ to the terminal bronchioles will be introduced. Finally, the effects of turbulent flows and CFD turbulence models on aerosol transport and deposition will be discussed. CFD simulation of airflow and particle transport in the human lung has been pursued by a number of research groups, whose interest has been in studying flow physics and airways resistance, improving drug delivery, or investigating which populations are most susceptible to inhaled pollutants. The three most important factors that need to be considered in airway CFD studies are lung structure, regional lung function, and flow characteristics. Their correct treatment is important because the transport of therapeutic or pollutant particles is dependent on the characteristics of the flow by which they are transported; and the airflow in the lungs is dependent on the geometry of the airways and how ventilation

  4. Multiscale Support Vector Learning With Projection Operator Wavelet Kernel for Nonlinear Dynamical System Identification.

    Science.gov (United States)

    Lu, Zhao; Sun, Jing; Butts, Kenneth

    2016-02-03

    A giant leap has been made in the past couple of decades with the introduction of kernel-based learning as a mainstay for designing effective nonlinear computational learning algorithms. In view of the geometric interpretation of conditional expectation and the ubiquity of multiscale characteristics in highly complex nonlinear dynamic systems [1]-[3], this paper presents a new orthogonal projection operator wavelet kernel, aiming at developing an efficient computational learning approach for nonlinear dynamical system identification. In the framework of multiresolution analysis, the proposed projection operator wavelet kernel can fulfill the multiscale, multidimensional learning to estimate complex dependencies. The special advantage of the projection operator wavelet kernel developed in this paper lies in the fact that it has a closed-form expression, which greatly facilitates its application in kernel learning. To the best of our knowledge, it is the first closed-form orthogonal projection wavelet kernel reported in the literature. It provides a link between grid-based wavelets and mesh-free kernel-based methods. Simulation studies for identifying the parallel models of two benchmark nonlinear dynamical systems confirm its superiority in model accuracy and sparsity.

  5. A mathematical framework for multiscale science and engineering: the variational multiscale method and interscale transfer operators

    International Nuclear Information System (INIS)

    Shadid, John Nicolas; Lehoucq, Richard B.; Christon, Mark Allen; Slepoy, Alexander; Bochev, Pavel Blagoveston; Collis, Samuel Scott; Wagner, Gregory John

    2004-01-01

    Existing approaches in multiscale science and engineering have evolved from a range of ideas and solutions that are reflective of their original problem domains. As a result, research in multiscale science has followed widely diverse and disjoint paths, which presents a barrier to cross pollination of ideas and application of methods outside their application domains. The status of the research environment calls for an abstract mathematical framework that can provide a common language to formulate and analyze multiscale problems across a range of scientific and engineering disciplines. In such a framework, critical common issues arising in multiscale problems can be identified, explored and characterized in an abstract setting. This type of overarching approach would allow categorization and clarification of existing models and approximations in a landscape of seemingly disjoint, mutually exclusive and ad hoc methods. More importantly, such an approach can provide context for both the development of new techniques and their critical examination. As with any new mathematical framework, it is necessary to demonstrate its viability on problems of practical importance. At Sandia, lab-centric, prototype application problems in fluid mechanics, reacting flows, magnetohydrodynamics (MHD), shock hydrodynamics and materials science span an important subset of DOE Office of Science applications and form an ideal proving ground for new approaches in multiscale science.

  6. Comparison of single- and multi-scale models for the prediction of the Culicoides biting midge distribution in Germany

    Directory of Open Access Journals (Sweden)

    Renke Lühken

    2016-05-01

    Full Text Available This study analysed Culicoides presence-absence data from 46 sampling sites in Germany, where monitoring was carried out from April 2007 until May 2008. Culicoides presence-absence data were analysed in relation to land cover data, in order to study whether the prevalence of biting midges is correlated to land cover data with respect to the trapping sites. We differentiated eight scales, i.e. buffer zones with radii of 0.5, 1, 2, 3, 4, 5, 7.5 and 10 km, around each site, and chose several land cover variables. For each species, we built eight single-scale models (i.e. predictor variables from one of the eight scales for each model based on averaged, generalised linear models and two multiscale models (i.e. predictor variables from all of the eight scales based on averaged, generalised linear models and generalised linear models with random forest variable selection. There were no significant differences between performance indicators of models built with land cover data from different buffer zones around the trapping sites. However, the overall performance of multi-scale models was higher than the alternatives. Furthermore, these models mostly achieved the best performance for the different species using the index area under the receiver operating characteristic curve. However, as also presented in this study, the relevance of the different variables could significantly differ between various scales, including the number of species affected and the positive or negative direction. This is an even more severe problem if multi-scale models are concerned, in which one model can have the same variable at different scales but with different directions, i.e. negative and positive direction of the same variable at different scales. However, multi-scale modelling is a promising approach to model the distribution of Culicoides species, accounting much more for the ecology of biting midges, which uses different resources (breeding sites, hosts, etc. at

  7. Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network.

    Science.gov (United States)

    Du, Xiaofeng; Qu, Xiaobo; He, Yifan; Guo, Di

    2018-03-06

    Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods.

  8. Multi-scale modeling and analysis of convective boiling: towards the prediction of CHF in rod bundles

    International Nuclear Information System (INIS)

    Niceno, B.; Sato, Y.; Badillo, A.; Andreani, M.

    2010-01-01

    In this paper we describe current activities on the project Multi-Scale Modeling and Analysis of convective boiling (MSMA), conducted jointly by the Paul Scherrer Institute (PSI) and the Swiss Nuclear Utilities (Swissnuclear). The long-term aim of the MSMA project is to formulate improved closure laws for Computational Fluid Dynamics (CFD) simulations for prediction of convective boiling and eventually of the Critical Heat Flux (CHF). As boiling is controlled by the competition of numerous phenomena at various length and time scales, a multi-scale approach is employed to tackle the problem at different scales. In the MSMA project, the scales on which we focus range from the CFD scale (macro-scale), bubble size scale (meso-scale), liquid micro-layer and triple interline scale (micro-scale), and molecular scale (nano-scale). The current focus of the project is on micro- and meso- scales modeling. The numerical framework comprises a highly efficient, parallel DNS solver, the PSI-BOIL code. The code has incorporated an Immersed Boundary Method (IBM) to tackle complex geometries. For simulation of meso-scales (bubbles), we use the Constrained Interpolation Profile method: Conservative Semi-Lagrangian 2nd order (CIP-CSL2). The phase change is described either by applying conventional jump conditions at the interface, or by using the Phase Field (PF) approach. In this work, we present selected results for flows in complex geometry using the IBM, selected bubbly flow simulations using the CIP-CSL2 method and results for phase change using the PF approach. In the subsequent stage of the project, the importance of effects of nano-scale processes on the global boiling heat transfer will be evaluated. To validate the models, more experimental information will be needed in the future, so it is expected that the MSMA project will become the seed for a long-term, combined theoretical and experimental program

  9. A Multiscale Enrichment Procedure for Nonlinear Monotone Operators

    KAUST Repository

    Efendiev, Yalchin R.; Galvis, J.; Presho, M.; Zhou, J.

    2014-01-01

    . Galvis, R. Lazarov, S. Margenov and J. Ren, Robust two-level domain decomposition preconditioners for high-contrast anisotropic flows in multiscale media. Submitted.; Y. Efendiev, J. Galvis and X. Wu, J. Comput. Phys. 230 (2011) 937–955; J. Galvis and Y

  10. Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata.

    Science.gov (United States)

    Leempoel, Kevin; Parisod, Christian; Geiser, Céline; Joost, Stéphane

    2018-02-01

    Plant species are known to adapt locally to their environment, particularly in mountainous areas where conditions can vary drastically over short distances. The climate of such landscapes being largely influenced by topography, using fine-scale models to evaluate environmental heterogeneity may help detecting adaptation to micro-habitats. Here, we applied a multiscale landscape genomic approach to detect evidence of local adaptation in the alpine plant Biscutella laevigata . The two gene pools identified, experiencing limited gene flow along a 1-km ridge, were different in regard to several habitat features derived from a very high resolution (VHR) digital elevation model (DEM). A correlative approach detected signatures of selection along environmental gradients such as altitude, wind exposure, and solar radiation, indicating adaptive pressures likely driven by fine-scale topography. Using a large panel of DEM-derived variables as ecologically relevant proxies, our results highlighted the critical role of spatial resolution. These high-resolution multiscale variables indeed indicate that the robustness of associations between genetic loci and environmental features depends on spatial parameters that are poorly documented. We argue that the scale issue is critical in landscape genomics and that multiscale ecological variables are key to improve our understanding of local adaptation in highly heterogeneous landscapes.

  11. PSI-BOIL, a building block towards the multi-scale modeling of flow boiling phenomena

    International Nuclear Information System (INIS)

    Niceno, Bojan; Andreani, Michele; Prasser, Horst-Michael

    2008-01-01

    Full text of publication follows: In these work we report the current status of the Swiss project Multi-scale Modeling Analysis (MSMA), jointly financed by PSI and Swissnuclear. The project aims at addressing the multi-scale (down to nano-scale) modelling of convective boiling phenomena, and the development of physically-based closure laws for the physical scales appropriate to the problem considered, to be used within Computational Fluid Dynamics (CFD) codes. The final goal is to construct a new computational tool, called Parallel Simulator of Boiling phenomena (PSI-BOIL) for the direct simulation of processes all the way down to the small-scales of interest and an improved CFD code for the mechanistic prediction of two-phase flow and heat transfer in the fuel rod bundle of a nuclear reactor. An improved understanding of the physics of boiling will be gained from the theoretical work as well as from novel small- and medium scale experiments targeted to assist the development of closure laws. PSI-BOIL is a computer program designed for efficient simulation of turbulent fluid flow and heat transfer phenomena in simple geometries. Turbulence is simulated directly (DNS) and its efficiency plays a vital role in a successful simulation. Having high performance as one of the main prerequisites, PSIBOIL is tailored in such a way to be as efficient a tool as possible, relying on well-established numerical techniques and sacrificing all the features which are not essential for the success of this project and which might slow down the solution procedure. The governing equations are discretized in space with orthogonal staggered finite volume method. Time discretization is performed with projection method, the most obvious a the most widely used choice for DNS. Systems of linearized equation, stemming from the discretization of governing equations, are solved with the Additive Correction Multigrid (ACM). methods. Two distinguished features of PSI-BOIL are the possibility to

  12. Multi-Scale Model of Galactic Cosmic Ray Effects on the Hippocampus

    Science.gov (United States)

    Cucinotta, Francis

    An important concern for risk assessment from galactic cosmic ray (GCR) exposures is impacts to the central nervous systems including changes in cognition, and associations with increased risk of Alzheimer’s disease (AD). AD, which affects about 50 percent of the population above age 80-yr, is a degenerative disease that worsens with time after initial onset leading to death, and has no known cure. AD is difficult to detect at early stages, and the small number of epidemiology studies that have considered the possibility have not identified an association with low dose radiation. However, experimental studies in transgenic mice suggest the possibility exits. We discuss modeling approaches to consider mechanisms whereby GCR would accelerate the occurrence of AD to earlier ages. Biomarkers of AD include Amyloid beta plaques, and neurofibrillary tangles (NFT) made up of aggregates of the hyper-phosphorylated form of the micro-tubule associated, tau protein. Related markers include synaptic degeneration, dendritic spine loss, and neuronal cell loss through apoptosis. GCR may affect these processes by causing oxidative stress, aberrant signaling following DNA damage, and chronic neuro-inflammation. Cell types considered in multi-scale models are neurons, astrocytes, and microglia. We developed biochemical and cell kinetics models of DNA damage signaling related to glycogen synthase kinase-3 beta and neuro-inflammation, and considered approaches to develop computer simulations of GCR induced cell interactions and their relationships to Amyloid beta plaques and NFTs. Comparison of model results to experimental data for the age specific development of plaques in transgenic mice and predictions of space radiation effects will be discussed.

  13. Commercial Implementation of Model-Based Manufacturing of Nanostructured Metals

    Energy Technology Data Exchange (ETDEWEB)

    Lowe, Terry C. [Los Alamos National Laboratory

    2012-07-24

    Computational modeling is an essential tool for commercial production of nanostructured metals. Strength is limited by imperfections at the high strength levels that are achievable in nanostructured metals. Processing to achieve homogeneity at the micro- and nano-scales is critical. Manufacturing of nanostructured metals is intrinsically a multi-scale problem. Manufacturing of nanostructured metal products requires computer control, monitoring and modeling. Large scale manufacturing of bulk nanostructured metals by Severe Plastic Deformation is a multi-scale problem. Computational modeling at all scales is essential. Multiple scales of modeling must be integrated to predict and control nanostructural, microstructural, macrostructural product characteristics and production processes.

  14. Multiscale Model Selection for High-Frequency Financial Data of a Large Tick Stock by Means of the Jensen–Shannon Metric

    Directory of Open Access Journals (Sweden)

    Gianbiagio Curato

    2014-01-01

    Full Text Available Modeling financial time series at different time scales is still an open challenge. The choice of a suitable indicator quantifying the distance between the model and the data is therefore of fundamental importance for selecting models. In this paper, we propose a multiscale model selection method based on the Jensen–Shannon distance in order to select the model that is able to better reproduce the distribution of price changes at different time scales. Specifically, we consider the problem of modeling the ultra high frequency dynamics of an asset with a large tick-to-price ratio. We study the price process at different time scales and compute the Jensen–Shannon distance between the original dataset and different models, showing that the coupling between spread and returns is important to model return distribution at different time scales of observation, ranging from the scale of single transactions to the daily time scale.

  15. Multiscale integration of -omic, imaging, and clinical data in biomedical informatics.

    Science.gov (United States)

    Phan, John H; Quo, Chang F; Cheng, Chihwen; Wang, May Dongmei

    2012-01-01

    This paper reviews challenges and opportunities in multiscale data integration for biomedical informatics. Biomedical data can come from different biological origins, data acquisition technologies, and clinical applications. Integrating such data across multiple scales (e.g., molecular, cellular/tissue, and patient) can lead to more informed decisions for personalized, predictive, and preventive medicine. However, data heterogeneity, community standards in data acquisition, and computational complexity are big challenges for such decision making. This review describes genomic and proteomic (i.e., molecular), histopathological imaging (i.e., cellular/tissue), and clinical (i.e., patient) data; it includes case studies for single-scale (e.g., combining genomic or histopathological image data), multiscale (e.g., combining histopathological image and clinical data), and multiscale and multiplatform (e.g., the Human Protein Atlas and The Cancer Genome Atlas) data integration. Numerous opportunities exist in biomedical informatics research focusing on integration of multiscale and multiplatform data.

  16. Multi-Scale Parameter Identification of Lithium-Ion Battery Electric Models Using a PSO-LM Algorithm

    Directory of Open Access Journals (Sweden)

    Wen-Jing Shen

    2017-03-01

    Full Text Available This paper proposes a multi-scale parameter identification algorithm for the lithium-ion battery (LIB electric model by using a combination of particle swarm optimization (PSO and Levenberg-Marquardt (LM algorithms. Two-dimensional Poisson equations with unknown parameters are used to describe the potential and current density distribution (PDD of the positive and negative electrodes in the LIB electric model. The model parameters are difficult to determine in the simulation due to the nonlinear complexity of the model. In the proposed identification algorithm, PSO is used for the coarse-scale parameter identification and the LM algorithm is applied for the fine-scale parameter identification. The experiment results show that the multi-scale identification not only improves the convergence rate and effectively escapes from the stagnation of PSO, but also overcomes the local minimum entrapment drawback of the LM algorithm. The terminal voltage curves from the PDD model with the identified parameter values are in good agreement with those from the experiments at different discharge/charge rates.

  17. Patentability aspects of computational cancer models

    Science.gov (United States)

    Lishchuk, Iryna

    2017-07-01

    Multiscale cancer models, implemented in silico, simulate tumor progression at various spatial and temporal scales. Having the innovative substance and possessing the potential of being applied as decision support tools in clinical practice, patenting and obtaining patent rights in cancer models seems prima facie possible. What legal hurdles the cancer models need to overcome for being patented we inquire from this paper.

  18. Three-dimensional direct numerical simulation of electromagnetically driven multiscale shallow layer flows: Numerical modeling and physical properties

    Science.gov (United States)

    Lardeau, Sylvain; Ferrari, Simone; Rossi, Lionel

    2008-12-01

    Three-dimensional (3D) direct numerical simulations of a flow driven by multiscale electromagnetic forcing are performed in order to reproduce with maximum accuracy the quasi-two-dimensional (2D) flow generated by the same multiscale forcing in the laboratory. The method presented is based on a 3D description of the flow and the electromagnetic forcing. Very good agreements between our simulations and the experiments are found both on velocity and acceleration field, this last comparison being, to our knowledge, done for the first time. Such agreement requires that both experiments and simulations are carefully performed and, more importantly, that the underlying simplification to model the experiments and the multiscale electromagnetic forcing do not introduce significant errors. The results presented in this paper differ significantly from previous 2D direct numerical simulation in which a classical linear Rayleigh friction modeling term was used to mimic the effect of the wall-normal friction. Indeed, purely 2D simulations are found to underestimate the Reynolds number and, due to the dominance of nonhomogeneous bottom friction, lead to the wrong physical mechanism. For the range of conditions presented in this paper, the Reynolds number, defined by the ratio between acceleration and viscous terms, remains the order of unity, and the Hartmann number, defined by the ratio between electromagnetic force terms and viscous terms, is about 2. The main conclusion is that 3D simulations are required to model the (3D) electromagnetic forces and the wall-normal shear. Indeed, even if the flow is quasi-2D in terms of energy, a full 3D approach is required to simulate these shallow layer flows driven by multiscale electromagnetic forcing. In the range of forcing intensity investigated in this paper, these multiscale flows remain quasi-2D, with negligible energy in the wall-normal velocity component. It is also shown that the driving terms are the electromagnetic forcing and

  19. High resolution multi-scale air quality modelling for all streets in Denmark

    DEFF Research Database (Denmark)

    Jensen, Steen Solvang; Ketzel, Matthias; Becker, Thomas

    2017-01-01

    The annual concentrations of NO2, PM2.5 and PM10 in 2012 have for the first time been modelled for all 2.4 million addresses in Denmark based on a multi-scale air quality modelling approach. All addresses include residential, industrial, institutional, shop, school, restaurant addresses etc...... concentrations of NO2 for the five available street monitoring stations are within −27% to +12%. The model results were also verified with comparisons with previous model results for NO2 at 98 selected streets in Copenhagen and 31 streets in Aalborg. The verification showed good correlation in Copenhagen (r2 = 0...

  20. Particle-based methods for multiscale modeling of blood flow in the circulation and in devices: challenges and future directions. Sixth International Bio-Fluid Mechanics Symposium and Workshop March 28-30, 2008 Pasadena, California.

    Science.gov (United States)

    Yamaguchi, Takami; Ishikawa, Takuji; Imai, Y; Matsuki, N; Xenos, Mikhail; Deng, Yuefan; Bluestein, Danny

    2010-03-01

    A major computational challenge for a multiscale modeling is the coupling of disparate length and timescales between molecular mechanics and macroscopic transport, spanning the spatial and temporal scales characterizing the complex processes taking place in flow-induced blood clotting. Flow and pressure effects on a cell-like platelet can be well represented by a continuum mechanics model down to the order of the micrometer level. However, the molecular effects of adhesion/aggregation bonds are on the order of nanometer. A successful multiscale model of platelet response to flow stresses in devices and the ensuing clotting responses should be able to characterize the clotting reactions and their interactions with the flow. This paper attempts to describe a few of the computational methods that were developed in recent years and became available to researchers in the field. They differ from traditional approaches that dominate the field by expanding on prevailing continuum-based approaches, or by completely departing from them, yielding an expanding toolkit that may facilitate further elucidation of the underlying mechanisms of blood flow and the cellular response to it. We offer a paradigm shift by adopting a multidisciplinary approach with fluid dynamics simulations coupled to biophysical and biochemical transport.

  1. Multiscale modeling of dislocation processes in BCC tantalum: bridging atomistic and mesoscale simulations

    International Nuclear Information System (INIS)

    Yang, L H; Tang, M; Moriarty, J A

    2001-01-01

    Plastic deformation in bcc metals at low temperatures and high-strain rates is controlled by the motion of a/2 screw dislocations, and understanding the fundamental atomistic processes of this motion is essential to develop predictive multiscale models of crystal plasticity. The multiscale modeling approach presented here for bcc Ta is based on information passing, where results of simulations at the atomic scale are used in simulations of plastic deformation at mesoscopic length scales via dislocation dynamics (DD). The relevant core properties of a/2 screw dislocations in Ta have been obtained using quantum-based interatomic potentials derived from model generalized pseudopotential theory and an ab-initio data base together with an accurate Green's-function simulation method that implements flexible boundary conditions. In particular, the stress-dependent activation enthalpy for the lowest-energy kink-pair mechanism has been calculated and fitted to a revealing analytic form. This is the critical quantity determining dislocation mobility in the DD simulations, and the present activation enthalpy is found to be in good agreement with the previous empirical form used to explain the temperature dependence of the yield stress

  2. Analysis of global multiscale finite element methods for wave equations with continuum spatial scales

    KAUST Repository

    Jiang, Lijian; Efendiev, Yalchin; Ginting, Victor

    2010-01-01

    In this paper, we discuss a numerical multiscale approach for solving wave equations with heterogeneous coefficients. Our interest comes from geophysics applications and we assume that there is no scale separation with respect to spatial variables. To obtain the solution of these multiscale problems on a coarse grid, we compute global fields such that the solution smoothly depends on these fields. We present a Galerkin multiscale finite element method using the global information and provide a convergence analysis when applied to solve the wave equations. We investigate the relation between the smoothness of the global fields and convergence rates of the global Galerkin multiscale finite element method for the wave equations. Numerical examples demonstrate that the use of global information renders better accuracy for wave equations with heterogeneous coefficients than the local multiscale finite element method. © 2010 IMACS.

  3. Analysis of global multiscale finite element methods for wave equations with continuum spatial scales

    KAUST Repository

    Jiang, Lijian

    2010-08-01

    In this paper, we discuss a numerical multiscale approach for solving wave equations with heterogeneous coefficients. Our interest comes from geophysics applications and we assume that there is no scale separation with respect to spatial variables. To obtain the solution of these multiscale problems on a coarse grid, we compute global fields such that the solution smoothly depends on these fields. We present a Galerkin multiscale finite element method using the global information and provide a convergence analysis when applied to solve the wave equations. We investigate the relation between the smoothness of the global fields and convergence rates of the global Galerkin multiscale finite element method for the wave equations. Numerical examples demonstrate that the use of global information renders better accuracy for wave equations with heterogeneous coefficients than the local multiscale finite element method. © 2010 IMACS.

  4. Shaken but not stirred: Multiscale habitat suitability modeling of sympatric marten species (Martes martes and Martes foina) in the northern Iberian Peninsula

    Science.gov (United States)

    Maria Vergara; Samuel A. Cushman; Fermin Urra; Aritz Ruiz-Gonzalez

    2016-01-01

    Multispecies and multiscale habitat suitability models (HSM) are important to identify the environmental variables and scales influencing habitat selection and facilitate the comparison of closely related species with different ecological requirements. Objectives This study explores the multiscale relationships of habitat suitability for the pine (Martes...

  5. Prediction of irradiation induced microstructures in the AgCu model alloy using a multiscale method coupling atomistic and phase field modelling

    OpenAIRE

    Demange, Gilles; Pontikis, Vassilis; Lunéville, Laurence; Simeone, David

    2016-01-01

    In this work, a multiscale approach based on phase field was developed to simulate the microstructure's evolution under irradiation in binary systems, from atomic to microstructural scale. For that purpose, an efficient numerical scheme was developed. In the case of AgCu alloy under Krypton ions irradiation, phenomenological parameters were computed using atomistic methods, as a function of the temperature and the irradiation flux. As a result, we predicted the influence of the irradiation fl...

  6. Aerosol-cloud interactions in a multi-scale modeling framework

    Science.gov (United States)

    Lin, G.; Ghan, S. J.

    2017-12-01

    Atmospheric aerosols play an important role in changing the Earth's climate through scattering/absorbing solar and terrestrial radiation and interacting with clouds. However, quantification of the aerosol effects remains one of the most uncertain aspects of current and future climate projection. Much of the uncertainty results from the multi-scale nature of aerosol-cloud interactions, which is very challenging to represent in traditional global climate models (GCMs). In contrast, the multi-scale modeling framework (MMF) provides a viable solution, which explicitly resolves the cloud/precipitation in the cloud resolved model (CRM) embedded in the GCM grid column. In the MMF version of community atmospheric model version 5 (CAM5), aerosol processes are treated with a parameterization, called the Explicit Clouds Parameterized Pollutants (ECPP). It uses the cloud/precipitation statistics derived from the CRM to treat the cloud processing of aerosols on the GCM grid. However, this treatment treats clouds on the CRM grid but aerosols on the GCM grid, which is inconsistent with the reality that cloud-aerosol interactions occur on the cloud scale. To overcome the limitation, here, we propose a new aerosol treatment in the MMF: Explicit Clouds Explicit Aerosols (ECEP), in which we resolve both clouds and aerosols explicitly on the CRM grid. We first applied the MMF with ECPP to the Accelerated Climate Modeling for Energy (ACME) model to have an MMF version of ACME. Further, we also developed an alternative version of ACME-MMF with ECEP. Based on these two models, we have conducted two simulations: one with the ECPP and the other with ECEP. Preliminary results showed that the ECEP simulations tend to predict higher aerosol concentrations than ECPP simulations, because of the more efficient vertical transport from the surface to the higher atmosphere but the less efficient wet removal. We also found that the cloud droplet number concentrations are also different between the

  7. Computer Aided Modelling – Opportunities and Challenges

    DEFF Research Database (Denmark)

    Cameron, Ian; Gani, Rafiqul

    2011-01-01

    -based solutions to significant problems? The important issues of workflow and data flow are discussed together with fit-for-purpose model development. As well, the lack of tools around multiscale modelling provides opportunities for the development of efficient tools to address such challenges. The ability...

  8. Microstructure representations for sound absorbing fibrous media: 3D and 2D multiscale modelling and experiments

    Science.gov (United States)

    Zieliński, Tomasz G.

    2017-11-01

    The paper proposes and investigates computationally-efficient microstructure representations for sound absorbing fibrous media. Three-dimensional volume elements involving non-trivial periodic arrangements of straight fibres are examined as well as simple two-dimensional cells. It has been found that a simple 2D quasi-representative cell can provide similar predictions as a volume element which is in general much more geometrically accurate for typical fibrous materials. The multiscale modelling allowed to determine the effective speeds and damping of acoustic waves propagating in such media, which brings up a discussion on the correlation between the speed, penetration range and attenuation of sound waves. Original experiments on manufactured copper-wire samples are presented and the microstructure-based calculations of acoustic absorption are compared with the corresponding experimental results. In fact, the comparison suggested the microstructure modifications leading to representations with non-uniformly distributed fibres.

  9. The Explicit-Cloud Parameterized-Pollutant hybrid approach for aerosol-cloud interactions in multiscale modeling framework models: tracer transport results

    International Nuclear Information System (INIS)

    Jr, William I Gustafson; Berg, Larry K; Easter, Richard C; Ghan, Steven J

    2008-01-01

    All estimates of aerosol indirect effects on the global energy balance have either completely neglected the influence of aerosol on convective clouds or treated the influence in a highly parameterized manner. Embedding cloud-resolving models (CRMs) within each grid cell of a global model provides a multiscale modeling framework for treating both the influence of aerosols on convective as well as stratiform clouds and the influence of clouds on the aerosol, but treating the interactions explicitly by simulating all aerosol processes in the CRM is computationally prohibitive. An alternate approach is to use horizontal statistics (e.g., cloud mass flux, cloud fraction, and precipitation) from the CRM simulation to drive a single-column parameterization of cloud effects on the aerosol and then use the aerosol profile to simulate aerosol effects on clouds within the CRM. Here, we present results from the first component of the Explicit-Cloud Parameterized-Pollutant parameterization to be developed, which handles vertical transport of tracers by clouds. A CRM with explicit tracer transport serves as a benchmark. We show that this parameterization, driven by the CRM's cloud mass fluxes, reproduces the CRM tracer transport significantly better than a single-column model that uses a conventional convective cloud parameterization

  10. The Explicit-Cloud Parameterized-Pollutant hybrid approach for aerosol-cloud interactions in multiscale modeling framework models: tracer transport results

    Energy Technology Data Exchange (ETDEWEB)

    Jr, William I Gustafson; Berg, Larry K; Easter, Richard C; Ghan, Steven J [Atmospheric Science and Global Change Division, Pacific Northwest National Laboratory, PO Box 999, MSIN K9-30, Richland, WA (United States)], E-mail: William.Gustafson@pnl.gov

    2008-04-15

    All estimates of aerosol indirect effects on the global energy balance have either completely neglected the influence of aerosol on convective clouds or treated the influence in a highly parameterized manner. Embedding cloud-resolving models (CRMs) within each grid cell of a global model provides a multiscale modeling framework for treating both the influence of aerosols on convective as well as stratiform clouds and the influence of clouds on the aerosol, but treating the interactions explicitly by simulating all aerosol processes in the CRM is computationally prohibitive. An alternate approach is to use horizontal statistics (e.g., cloud mass flux, cloud fraction, and precipitation) from the CRM simulation to drive a single-column parameterization of cloud effects on the aerosol and then use the aerosol profile to simulate aerosol effects on clouds within the CRM. Here, we present results from the first component of the Explicit-Cloud Parameterized-Pollutant parameterization to be developed, which handles vertical transport of tracers by clouds. A CRM with explicit tracer transport serves as a benchmark. We show that this parameterization, driven by the CRM's cloud mass fluxes, reproduces the CRM tracer transport significantly better than a single-column model that uses a conventional convective cloud parameterization.

  11. Multiscale Phase Inversion of Seismic Data

    KAUST Repository

    Fu, Lei

    2017-12-02

    We present a scheme for multiscale phase inversion (MPI) of seismic data that is less sensitive to the unmodeled physics of wave propagation and a poor starting model than standard full waveform inversion (FWI). To avoid cycle-skipping, the multiscale strategy temporally integrates the traces several times, i.e. high-order integration, to produce low-boost seismograms that are used as input data for the initial iterations of MPI. As the iterations proceed, higher frequencies in the data are boosted by using integrated traces of lower order as the input data. The input data are also filtered into different narrow frequency bands for the MPI implementation. At low frequencies, we show that MPI with windowed reflections approximates wave equation inversion of the reflection traveltimes, except no traveltime picking is needed. Numerical results with synthetic acoustic data show that MPI is more robust than conventional multiscale FWI when the initial model is far from the true model. Results from synthetic viscoacoustic and elastic data show that MPI is less sensitive than FWI to some of the unmodeled physics. Inversion of marine data shows that MPI is more robust and produces modestly more accurate results than FWI for this data set.

  12. Microstructural analysis of TRISO particles using multi-scale X-ray computed tomography

    Energy Technology Data Exchange (ETDEWEB)

    Lowe, T., E-mail: tristan.lowe@manchester.ac.uk [Manchester X-ray Imaging Facility, School of Materials, University of Manchester, M13 9PL (United Kingdom); Bradley, R.S. [Manchester X-ray Imaging Facility, School of Materials, University of Manchester, M13 9PL (United Kingdom); Yue, S. [Manchester X-ray Imaging Facility, School of Materials, University of Manchester, M13 9PL (United Kingdom); The Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot, Oxfordshire OX11 0FA (United Kingdom); Barii, K. [School of Mechanical Engineering, University of Manchester, M13 9PL (United Kingdom); Gelb, J. [Zeiss Xradia Inc., Pleasanton, CA (United States); Rohbeck, N. [Manchester X-ray Imaging Facility, School of Materials, University of Manchester, M13 9PL (United Kingdom); Turner, J. [School of Mechanical Engineering, University of Manchester, M13 9PL (United Kingdom); Withers, P.J. [Manchester X-ray Imaging Facility, School of Materials, University of Manchester, M13 9PL (United Kingdom); The Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot, Oxfordshire OX11 0FA (United Kingdom)

    2015-06-15

    TRISO particles, a composite nuclear fuel built up by ceramic and graphitic layers, have outstanding high temperature resistance. TRISO fuel is the key technology for High Temperature Reactors (HTRs) and the Generation IV Very High Temperature Reactor (VHTR) variant. TRISO offers unparalleled containment of fission products and is extremely robust during accident conditions. An understanding of the thermal performance and mechanical properties of TRISO fuel requires a detailed knowledge of pore sizes, their distribution and interconnectivity. Here 50 nm, nano-, and 1 μm resolution, micro-computed tomography (CT), have been used to quantify non-destructively porosity of a surrogate TRISO particle at the 0.3–10 μm and 3–100 μm scales respectively. This indicates that pore distributions can reliably be measured down to a size approximately 3 times the pixel size which is consistent with the segmentation process. Direct comparison with Scanning Electron Microscopy (SEM) sections indicates that destructive sectioning can introduce significant levels of coarse damage, especially in the pyrolytic carbon layers. Further comparative work is required to identify means of minimizing such damage for SEM studies. Finally since it is non-destructive, multi-scale time-lapse X-ray CT opens the possibility of intermittently tracking the degradation of TRISO structure under thermal cycles or radiation conditions in order to validate models of degradation such as kernel movement. X-ray CT in-situ experimentation of TRISO particles under load and temperature could also be used to understand the internal changes that occur in the particles under accident conditions.

  13. Mixed multiscale finite element methods using approximate global information based on partial upscaling

    KAUST Repository

    Jiang, Lijian; Efendiev, Yalchin; Mishev, IIya

    2009-01-01

    The use of limited global information in multiscale simulations is needed when there is no scale separation. Previous approaches entail fine-scale simulations in the computation of the global information. The computation of the global information

  14. Multi-Scale Modeling of an Integrated 3D Braided Composite with Applications to Helicopter Arm

    Science.gov (United States)

    Zhang, Diantang; Chen, Li; Sun, Ying; Zhang, Yifan; Qian, Kun

    2017-10-01

    A study is conducted with the aim of developing multi-scale analytical method for designing the composite helicopter arm with three-dimensional (3D) five-directional braided structure. Based on the analysis of 3D braided microstructure, the multi-scale finite element modeling is developed. Finite element analysis on the load capacity of 3D five-directional braided composites helicopter arm is carried out using the software ABAQUS/Standard. The influences of the braiding angle and loading condition on the stress and strain distribution of the helicopter arm are simulated. The results show that the proposed multi-scale method is capable of accurately predicting the mechanical properties of 3D braided composites, validated by the comparison the stress-strain curves of meso-scale RVCs. Furthermore, it is found that the braiding angle is an important factor affecting the mechanical properties of 3D five-directional braided composite helicopter arm. Based on the optimized structure parameters, the nearly net-shaped composite helicopter arm is fabricated using a novel resin transfer mould (RTM) process.

  15. Statistical CT noise reduction with multiscale decomposition and penalized weighted least squares in the projection domain

    International Nuclear Information System (INIS)

    Tang Shaojie; Tang Xiangyang

    2012-01-01

    Purposes: The suppression of noise in x-ray computed tomography (CT) imaging is of clinical relevance for diagnostic image quality and the potential for radiation dose saving. Toward this purpose, statistical noise reduction methods in either the image or projection domain have been proposed, which employ a multiscale decomposition to enhance the performance of noise suppression while maintaining image sharpness. Recognizing the advantages of noise suppression in the projection domain, the authors propose a projection domain multiscale penalized weighted least squares (PWLS) method, in which the angular sampling rate is explicitly taken into consideration to account for the possible variation of interview sampling rate in advanced clinical or preclinical applications. Methods: The projection domain multiscale PWLS method is derived by converting an isotropic diffusion partial differential equation in the image domain into the projection domain, wherein a multiscale decomposition is carried out. With adoption of the Markov random field or soft thresholding objective function, the projection domain multiscale PWLS method deals with noise at each scale. To compensate for the degradation in image sharpness caused by the projection domain multiscale PWLS method, an edge enhancement is carried out following the noise reduction. The performance of the proposed method is experimentally evaluated and verified using the projection data simulated by computer and acquired by a CT scanner. Results: The preliminary results show that the proposed projection domain multiscale PWLS method outperforms the projection domain single-scale PWLS method and the image domain multiscale anisotropic diffusion method in noise reduction. In addition, the proposed method can preserve image sharpness very well while the occurrence of “salt-and-pepper” noise and mosaic artifacts can be avoided. Conclusions: Since the interview sampling rate is taken into account in the projection domain

  16. Multi-Scale Factor Analysis of High-Dimensional Brain Signals

    KAUST Repository

    Ting, Chee-Ming

    2017-05-18

    In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive spatio-temporal data defined over the complex networks into a finite set of regional clusters. To achieve further dimension reduction, we represent the signals in each cluster by a small number of latent factors. The correlation matrix for all nodes in the network are approximated by lower-dimensional sub-structures derived from the cluster-specific factors. To estimate regional connectivity between numerous nodes (within each cluster), we apply principal components analysis (PCA) to produce factors which are derived as the optimal reconstruction of the observed signals under the squared loss. Then, we estimate global connectivity (between clusters or sub-networks) based on the factors across regions using the RV-coefficient as the cross-dependence measure. This gives a reliable and computationally efficient multi-scale analysis of both regional and global dependencies of the large networks. The proposed novel approach is applied to estimate brain connectivity networks using functional magnetic resonance imaging (fMRI) data. Results on resting-state fMRI reveal interesting modular and hierarchical organization of human brain networks during rest.

  17. Multiscale modeling of a rectifying bipolar nanopore: explicit-water versus implicit-water simulations.

    Science.gov (United States)

    Ható, Zoltán; Valiskó, Mónika; Kristóf, Tamás; Gillespie, Dirk; Boda, Dezsö

    2017-07-21

    In a multiscale modeling approach, we present computer simulation results for a rectifying bipolar nanopore at two modeling levels. In an all-atom model, we use explicit water to simulate ion transport directly with the molecular dynamics technique. In a reduced model, we use implicit water and apply the Local Equilibrium Monte Carlo method together with the Nernst-Planck transport equation. This hybrid method makes the fast calculation of ion transport possible at the price of lost details. We show that the implicit-water model is an appropriate representation of the explicit-water model when we look at the system at the device (i.e., input vs. output) level. The two models produce qualitatively similar behavior of the electrical current for different voltages and model parameters. Looking at the details of concentration and potential profiles, we find profound differences between the two models. These differences, however, do not influence the basic behavior of the model as a device because they do not influence the z-dependence of the concentration profiles which are the main determinants of current. These results then address an old paradox: how do reduced models, whose assumptions should break down in a nanoscale device, predict experimental data? Our simulations show that reduced models can still capture the overall device physics correctly, even though they get some important aspects of the molecular-scale physics quite wrong; reduced models work because they include the physics that is necessary from the point of view of device function. Therefore, reduced models can suffice for general device understanding and device design, but more detailed models might be needed for molecular level understanding.

  18. A variational multiscale method for particle-cloud tracking in turbomachinery flows

    Science.gov (United States)

    Corsini, A.; Rispoli, F.; Sheard, A. G.; Takizawa, K.; Tezduyar, T. E.; Venturini, P.

    2014-11-01

    We present a computational method for simulation of particle-laden flows in turbomachinery. The method is based on a stabilized finite element fluid mechanics formulation and a finite element particle-cloud tracking method. We focus on induced-draft fans used in process industries to extract exhaust gases in the form of a two-phase fluid with a dispersed solid phase. The particle-laden flow causes material wear on the fan blades, degrading their aerodynamic performance, and therefore accurate simulation of the flow would be essential in reliable computational turbomachinery analysis and design. The turbulent-flow nature of the problem is dealt with a Reynolds-Averaged Navier-Stokes model and Streamline-Upwind/Petrov-Galerkin/Pressure-Stabilizing/Petrov-Galerkin stabilization, the particle-cloud trajectories are calculated based on the flow field and closure models for the turbulence-particle interaction, and one-way dependence is assumed between the flow field and particle dynamics. We propose a closure model utilizing the scale separation feature of the variational multiscale method, and compare that to the closure utilizing the eddy viscosity model. We present computations for axial- and centrifugal-fan configurations, and compare the computed data to those obtained from experiments, analytical approaches, and other computational methods.

  19. Investigations into radiation damages of reactor materials by computer simulation

    International Nuclear Information System (INIS)

    Bronnikov, V.A.

    2004-01-01

    Data on the state of works in European countries in the field of computerized simulation of radiation damages of reactor materials under the context of the international projects ITEM (European Database for Multiscale Modelling) and SIRENA (Simulation of Radiation Effects in Zr-Nb alloys) - computerized simulation of stress corrosion when contact of Zr-Nb alloys with iodine are presented. Computer codes for the simulation of radiation effects in reactor materials were developed. European Database for Multiscale Modelling (EDAM) was organized using the results of the investigations provided in the ITEM project [ru

  20. Epidermal Homeostasis and Radiation Responses in a Multiscale Tissue Modeling Framework

    Science.gov (United States)

    Hu, Shaowen; Cucinotta, Francis A.

    2013-01-01

    The surface of skin is lined with several thin layers of epithelial cells that are maintained throughout life time by a small population of stem cells. High dose radiation exposures could injure and deplete the underlying proliferative cells and induce cutaneous radiation syndrome. In this work we propose a multiscale computational model for skin epidermal dynamics that links phenomena occurring at the subcellular, cellular, and tissue levels of organization, to simulate the experimental data of the radiation response of swine epidermis, which is closely similar to human epidermis. Incorporating experimentally measured histological and cell kinetic parameters, we obtain results of population kinetics and proliferation indexes comparable to observations in unirradiated and acutely irradiated swine experiments. At the sub-cellular level, several recently published Wnt signaling controlled cell-cycle models are applied and the roles of key components and parameters are analyzed. Based on our simulation results, we demonstrate that a moderate increase of proliferation rate for the survival proliferative cells is sufficient to fully repopulate the area denuded by high dose radiation, as long as the integrity of underlying basement membrane is maintained. Our work highlights the importance of considering proliferation kinetics as well as the spatial organization of tissues when conducting in vivo investigations of radiation responses. This integrated model allow us to test the validity of several basic biological rules at the cellular level and sub-cellular mechanisms by qualitatively comparing simulation results with published research, and enhance our understanding of the pathophysiological effects of ionizing radiation on skin.

  1. Evaluation of kriging based surrogate models constructed from mesoscale computations of shock interaction with particles

    Energy Technology Data Exchange (ETDEWEB)

    Sen, Oishik, E-mail: oishik-sen@uiowa.edu [Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Gaul, Nicholas J., E-mail: nicholas-gaul@ramdosolutions.com [RAMDO Solutions, LLC, Iowa City, IA 52240 (United States); Choi, K.K., E-mail: kyung-choi@uiowa.edu [Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Jacobs, Gustaaf, E-mail: gjacobs@sdsu.edu [Aerospace Engineering, San Diego State University, San Diego, CA 92115 (United States); Udaykumar, H.S., E-mail: hs-kumar@uiowa.edu [Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States)

    2017-05-01

    Macro-scale computations of shocked particulate flows require closure laws that model the exchange of momentum/energy between the fluid and particle phases. Closure laws are constructed in this work in the form of surrogate models derived from highly resolved mesoscale computations of shock-particle interactions. The mesoscale computations are performed to calculate the drag force on a cluster of particles for different values of Mach Number and particle volume fraction. Two Kriging-based methods, viz. the Dynamic Kriging Method (DKG) and the Modified Bayesian Kriging Method (MBKG) are evaluated for their ability to construct surrogate models with sparse data; i.e. using the least number of mesoscale simulations. It is shown that if the input data is noise-free, the DKG method converges monotonically; convergence is less robust in the presence of noise. The MBKG method converges monotonically even with noisy input data and is therefore more suitable for surrogate model construction from numerical experiments. This work is the first step towards a full multiscale modeling of interaction of shocked particle laden flows.

  2. Modelling an industrial anaerobic granular reactor using a multi-scale approach.

    Science.gov (United States)

    Feldman, H; Flores-Alsina, X; Ramin, P; Kjellberg, K; Jeppsson, U; Batstone, D J; Gernaey, K V

    2017-12-01

    The objective of this paper is to show the results of an industrial project dealing with modelling of anaerobic digesters. A multi-scale mathematical approach is developed to describe reactor hydrodynamics, granule growth/distribution and microbial competition/inhibition for substrate/space within the biofilm. The main biochemical and physico-chemical processes in the model are based on the Anaerobic Digestion Model No 1 (ADM1) extended with the fate of phosphorus (P), sulfur (S) and ethanol (Et-OH). Wastewater dynamic conditions are reproduced and data frequency increased using the Benchmark Simulation Model No 2 (BSM2) influent generator. All models are tested using two plant data sets corresponding to different operational periods (#D1, #D2). Simulation results reveal that the proposed approach can satisfactorily describe the transformation of organics, nutrients and minerals, the production of methane, carbon dioxide and sulfide and the potential formation of precipitates within the bulk (average deviation between computer simulations and measurements for both #D1, #D2 is around 10%). Model predictions suggest a stratified structure within the granule which is the result of: 1) applied loading rates, 2) mass transfer limitations and 3) specific (bacterial) affinity for substrate. Hence, inerts (X I ) and methanogens (X ac ) are situated in the inner zone, and this fraction lowers as the radius increases favouring the presence of acidogens (X su ,X aa , X fa ) and acetogens (X c4 ,X pro ). Additional simulations show the effects on the overall process performance when operational (pH) and loading (S:COD) conditions are modified. Lastly, the effect of intra-granular precipitation on the overall organic/inorganic distribution is assessed at: 1) different times; and, 2) reactor heights. Finally, the possibilities and opportunities offered by the proposed approach for conducting engineering optimization projects are discussed. Copyright © 2017 Elsevier Ltd. All

  3. Hybrid stochastic simplifications for multiscale gene networks

    Directory of Open Access Journals (Sweden)

    Debussche Arnaud

    2009-09-01

    Full Text Available Abstract Background Stochastic simulation of gene networks by Markov processes has important applications in molecular biology. The complexity of exact simulation algorithms scales with the number of discrete jumps to be performed. Approximate schemes reduce the computational time by reducing the number of simulated discrete events. Also, answering important questions about the relation between network topology and intrinsic noise generation and propagation should be based on general mathematical results. These general results are difficult to obtain for exact models. Results We propose a unified framework for hybrid simplifications of Markov models of multiscale stochastic gene networks dynamics. We discuss several possible hybrid simplifications, and provide algorithms to obtain them from pure jump processes. In hybrid simplifications, some components are discrete and evolve by jumps, while other components are continuous. Hybrid simplifications are obtained by partial Kramers-Moyal expansion 123 which is equivalent to the application of the central limit theorem to a sub-model. By averaging and variable aggregation we drastically reduce simulation time and eliminate non-critical reactions. Hybrid and averaged simplifications can be used for more effective simulation algorithms and for obtaining general design principles relating noise to topology and time scales. The simplified models reproduce with good accuracy the stochastic properties of the gene networks, including waiting times in intermittence phenomena, fluctuation amplitudes and stationary distributions. The methods are illustrated on several gene network examples. Conclusion Hybrid simplifications can be used for onion-like (multi-layered approaches to multi-scale biochemical systems, in which various descriptions are used at various scales. Sets of discrete and continuous variables are treated with different methods and are coupled together in a physically justified approach.

  4. Addressing the multi-scale lapsus of landscape : multi-scale landscape process modelling to support sustainable land use : a case study for the Lower Guadalhorce valley South Spain

    NARCIS (Netherlands)

    Schoorl, J.M.

    2002-01-01

    "Addressing the Multi-scale Lapsus of Landscape" with the sub-title "Multi-scale landscape process modelling to support sustainable land use: A case study for the Lower Guadalhorce valley South Spain" focuses on the role of

  5. Multi-scale Mexican spotted owl (Strix occidentalis lucida) nest/roost habitat selection in Arizona and a comparison with single-scale modeling results

    Science.gov (United States)

    Brad C. Timm; Kevin McGarigal; Samuel A. Cushman; Joseph L. Ganey

    2016-01-01

    Efficacy of future habitat selection studies will benefit by taking a multi-scale approach. In addition to potentially providing increased explanatory power and predictive capacity, multi-scale habitat models enhance our understanding of the scales at which species respond to their environment, which is critical knowledge required to implement effective...

  6. A variational multiscale constitutive model for nanocrystalline materials

    KAUST Repository

    Gurses, Ercan

    2011-03-01

    This paper presents a variational multi-scale constitutive model in the finite deformation regime capable of capturing the mechanical behavior of nanocrystalline (nc) fcc metals. The nc-material is modeled as a two-phase material consisting of a grain interior phase and a grain boundary effected zone (GBAZ). A rate-independent isotropic porous plasticity model is employed to describe the GBAZ, whereas a crystal-plasticity model which accounts for the transition from partial dislocation to full dislocation mediated plasticity is employed for the grain interior. The constitutive models of both phases are formulated in a small strain framework and extended to finite deformation by use of logarithmic and exponential mappings. Assuming the rule of mixtures, the overall behavior of a given grain is obtained via volume averaging. The scale transition from a single grain to a polycrystal is achieved by Taylor-type homogenization where a log-normal grain size distribution is assumed. It is shown that the proposed model is able to capture the inverse HallPetch effect, i.e., loss of strength with grain size refinement. Finally, the predictive capability of the model is validated against experimental results on nanocrystalline copper and nickel. © 2010 Elsevier Ltd. All rights reserved.

  7. Modeling Urban Collaborative Growth Dynamics Using a Multiscale Simulation Model for the Wuhan Urban Agglomeration Area, China

    Directory of Open Access Journals (Sweden)

    Yan Yu

    2018-05-01

    Full Text Available Urban agglomeration has become the predominant form of urbanization in China. In this process, spatial interaction evidently played a significant role in promoting the collaborative development of these correlated cities. The traditional urban model’s focus on individual cities should be transformed to an urban system model. In this study, a multi-scale simulation model has been proposed to simulate the agglomeration development process of the Wuhan urban agglomeration area by embedding the multi-scale spatial interaction into the transition rule system of cellular automata (CA. A system dynamic model was used to predict the demand for new urban land at an aggregated urban agglomeration area scale. A data field approach was adopted to measuring the interaction of intercity at city scale. Neighborhood interaction was interpreted with a logistic regression method at the land parcel scale. Land use data from 1995, 2005, and 2015 were used to calibrate and evaluate the model. The simulation results show that there has been continuing urban growth in the Wuhan urban agglomeration area from 1995 to 2020. Although extension-sprawl was the predominant pattern of urban spatial expansion, the trend of extensive growth to intensive growth is clear during the entire period. The spatial interaction among these cities has been reinforced, which guided the collaborative development and formed the regional urban system network.

  8. Multi-scale modeling of inter-granular fracture in UO2

    Energy Technology Data Exchange (ETDEWEB)

    Chakraborty, Pritam [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zhang, Yongfeng [Idaho National Lab. (INL), Idaho Falls, ID (United States); Tonks, Michael R. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Biner, S. Bulent [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-03-01

    A hierarchical multi-scale approach is pursued in this work to investigate the influence of porosity, pore and grain size on the intergranular brittle fracture in UO2. In this approach, molecular dynamics simulations are performed to obtain the fracture properties for different grain boundary types. A phase-field model is then utilized to perform intergranular fracture simulations of representative microstructures with different porosities, pore and grain sizes. In these simulations the grain boundary fracture properties obtained from molecular dynamics simulations are used. The responses from the phase-field fracture simulations are then fitted with a stress-based brittle fracture model usable at the engineering scale. This approach encapsulates three different length and time scales, and allows the development of microstructurally informed engineering scale model from properties evaluated at the atomistic scale.

  9. MRI-Based Multiscale Model for Electromagnetic Analysis in the Human Head with Implanted DBS

    Directory of Open Access Journals (Sweden)

    Maria Ida Iacono

    2013-01-01

    Full Text Available Deep brain stimulation (DBS is an established procedure for the treatment of movement and affective disorders. Patients with DBS may benefit from magnetic resonance imaging (MRI to evaluate injuries or comorbidities. However, the MRI radio-frequency (RF energy may cause excessive tissue heating particularly near the electrode. This paper studies how the accuracy of numerical modeling of the RF field inside a DBS patient varies with spatial resolution and corresponding anatomical detail of the volume surrounding the electrodes. A multiscale model (MS was created by an atlas-based segmentation using a 1 mm3 head model (mRes refined in the basal ganglia by a 200 μm2 ex-vivo dataset. Four DBS electrodes targeting the left globus pallidus internus were modeled. Electromagnetic simulations at 128 MHz showed that the peak of the electric field of the MS doubled (18.7 kV/m versus 9.33 kV/m and shifted 6.4 mm compared to the mRes model. Additionally, the MS had a sixfold increase over the mRes model in peak-specific absorption rate (SAR of 43.9 kW/kg versus 7 kW/kg. The results suggest that submillimetric resolution and improved anatomical detail in the model may increase the accuracy of computed electric field and local SAR around the tip of the implant.

  10. Integrative computational models of cardiac arrhythmias -- simulating the structurally realistic heart

    Science.gov (United States)

    Trayanova, Natalia A; Tice, Brock M

    2009-01-01

    Simulation of cardiac electrical function, and specifically, simulation aimed at understanding the mechanisms of cardiac rhythm disorders, represents an example of a successful integrative multiscale modeling approach, uncovering emergent behavior at the successive scales in the hierarchy of structural complexity. The goal of this article is to present a review of the integrative multiscale models of realistic ventricular structure used in the quest to understand and treat ventricular arrhythmias. It concludes with the new advances in image-based modeling of the heart and the promise it holds for the development of individualized models of ventricular function in health and disease. PMID:20628585

  11. Multiscale modeling of radiation damage in Fe-based alloys in the fusion environment

    International Nuclear Information System (INIS)

    Wirth, B.D.; Odette, G.R.; Marian, J.; Ventelon, L.; Young-Vandersall, J.A.; Zepeda-Ruiz, L.A.

    2004-01-01

    Ferritic alloys represent a technologically important class of candidate materials for fusion first wall and blanket structures. A detailed understanding of the mechanisms of defect accumulation and microstructure evolution, and the corresponding effects on mechanical properties is required to predict their in-service structural performance limits. The physical processes involved in radiation damage, and its effects on mechanical properties, are inherently multiscale and hierarchical, spanning length and time scales from the atomic nucleus to meters and picosecond to decades. In this paper, we present a multiscale modeling methodology to describe radiation effects within the fusion energy environment. Selected results from atomic scale investigation are presented, focusing on (i) the mechanisms of self-interstitial dislocation loop formation with Burgers vector of a in iron relative to vanadium, (ii) helium transport and (iii) the interaction between helium and small self-interstitial clusters in iron, and (iv) dislocation-helium bubble interactions in fcc aluminum

  12. Multiscale Modeling of the Early CD8 T-Cell Immune Response in Lymph Nodes: An Integrative Study

    Directory of Open Access Journals (Sweden)

    Sotiris A. Prokopiou

    2014-09-01

    Full Text Available CD8 T-cells are critical  in controlling infection by intracellular  pathogens. Upon encountering antigen presenting cells, T-cell receptor activation promotes the differentiation of naïve CD8 T-cells into strongly proliferating  activated and effector stages. We propose a 2D-multiscale computational model to study the maturation of CD8 T-cells in a lymph node controlled by their molecular profile. A novel molecular pathway is presented and converted into an ordinary differential  equation model, coupled with a cellular Potts model to describe cell-cell interactions. Key molecular  players such as activated IL2 receptor and Tbet levels  control the differentiation  from naïve into activated and effector stages, respectively,  while caspases and Fas-Fas ligand interactions control cell apoptosis.  Coupling  this molecular model to the cellular scale successfully  reproduces  qualitatively the evolution of total CD8 T-cell counts observed in mice lymph node, between Day 3 and 5.5 post-infection. Furthermore, this model allows us to make testable predictions  of the evolution of the different CD8 T-cell stages.

  13. Multiscale entropy analysis of resting-state magnetoencephalogram with tensor factorisations in Alzheimer's disease

    DEFF Research Database (Denmark)

    Escudero, Javier; Evrim, Acar Ataman; Fernández, Alberto

    2015-01-01

    dynamics. We consider the "refined composite multiscale entropy" (rcMSE), which computes entropy "profiles" showing levels of physiological complexity over temporal scales for individual signals. We compute the rcMSE of resting-state magnetoencephalogram (MEG) recordings from 36 patients with Alzheimer...

  14. Multiscale modeling of the effect of carbon nanotube orientation on the shear deformation properties of reinforced polymer-based composites

    Energy Technology Data Exchange (ETDEWEB)

    Montazeri, A. [Institute for Nano-Science and Technology, Sharif University of Technology, Tehran (Iran, Islamic Republic of); Computational Physical Sciences Research Laboratory, School of Nano-Science, Institute for Research in Fundamental Sciences (IPM), Tehran (Iran, Islamic Republic of); Sadeghi, M. [Institute for Nano-Science and Technology, Sharif University of Technology, Tehran (Iran, Islamic Republic of); Naghdabadi, R., E-mail: naghdabd@sharif.ed [Institute for Nano-Science and Technology, Sharif University of Technology, Tehran (Iran, Islamic Republic of); Department of Mechanical Engineering, Sharif University of Technology, Tehran (Iran, Islamic Republic of); Rafii-Tabar, H. [Computational Physical Sciences Research Laboratory, School of Nano-Science, Institute for Research in Fundamental Sciences (IPM), Tehran (Iran, Islamic Republic of); Department of Medical Physics and Biomedical Engineering, and Research Centre for Medical Nanotechnology and Tissue Engineering, Shahid Beheshti University of Medical Sciences, Evin, Tehran (Iran, Islamic Republic of)

    2011-04-04

    A combination of molecular dynamics (MD), continuum elasticity and FEM is used to predict the effect of CNT orientation on the shear modulus of SWCNT-polymer nanocomposites. We first develop a transverse-isotropic elastic model of SWCNTs based on the continuum elasticity and MD to compute the transverse-isotropic elastic constants of SWCNTs. These constants are then used in an FEM-based simulation to investigate the effect of SWCNT alignment on the shear modulus of nanocomposites. Furthermore, shear stress distributions along the nanotube axis and over its cross-sectional area are investigated to study the effect of CNT orientation on the shear load transfer. - Highlights: A transverse-isotropic elastic model of SWCNTs is presented. A hierarchical MD/FEM multiscale model of SWCNT-polymer composites is developed. Behavior of these nanocomposites under shear deformation is studied. A symmetric shear stress distribution occurs only in SWCNTs with 45{sup o} orientation. The total shear load sustained is greatest in the case of 45{sup o} orientation.

  15. Multiscale modeling of the effect of carbon nanotube orientation on the shear deformation properties of reinforced polymer-based composites

    International Nuclear Information System (INIS)

    Montazeri, A.; Sadeghi, M.; Naghdabadi, R.; Rafii-Tabar, H.

    2011-01-01

    A combination of molecular dynamics (MD), continuum elasticity and FEM is used to predict the effect of CNT orientation on the shear modulus of SWCNT-polymer nanocomposites. We first develop a transverse-isotropic elastic model of SWCNTs based on the continuum elasticity and MD to compute the transverse-isotropic elastic constants of SWCNTs. These constants are then used in an FEM-based simulation to investigate the effect of SWCNT alignment on the shear modulus of nanocomposites. Furthermore, shear stress distributions along the nanotube axis and over its cross-sectional area are investigated to study the effect of CNT orientation on the shear load transfer. - Highlights: → A transverse-isotropic elastic model of SWCNTs is presented. → A hierarchical MD/FEM multiscale model of SWCNT-polymer composites is developed. → Behavior of these nanocomposites under shear deformation is studied. → A symmetric shear stress distribution occurs only in SWCNTs with 45 o orientation. → The total shear load sustained is greatest in the case of 45 o orientation.

  16. Mapping rice ecosystem dynamics and greenhouse gas emissions using multiscale imagery and biogeochemical models

    Science.gov (United States)

    Salas, W.; Torbick, N.

    2017-12-01

    Rice greenhouse gas (GHG) emissions in production hot spots have been mapped using multiscale satellite imagery and a processed-based biogeochemical model. The multiscale Synthetic Aperture Radar (SAR) and optical imagery were co-processed and fed into a machine leanring framework to map paddy attributes that are tuned using field observations and surveys. Geospatial maps of rice extent, crop calendar, hydroperiod, and cropping intensity were then used to parameterize the DeNitrification-DeComposition (DNDC) model to estimate emissions. Results, in the Red River Detla for example, show total methane emissions at 345.4 million kgCH4-C equivalent to 11.5 million tonnes CO2e (carbon dioxide equivalent). We further assessed the role of Alternative Wetting and Drying and the impact on GHG and yield across production hot spots with uncertainty estimates. The approach described in this research provides a framework for using SAR to derive maps of rice and landscape characteristics to drive process models like DNDC. These types of tools and approaches will support the next generation of Monitoring, Reporting, and Verification (MRV) to combat climate change and support ecosystem service markets.

  17. GEMMER: GEnome-wide tool for Multi-scale Modeling data Extraction and Representation for Saccharomyces cerevisiae.

    Science.gov (United States)

    Mondeel, Thierry D G A; Crémazy, Frédéric; Barberis, Matteo

    2018-02-01

    Multi-scale modeling of biological systems requires integration of various information about genes and proteins that are connected together in networks. Spatial, temporal and functional information is available; however, it is still a challenge to retrieve and explore this knowledge in an integrated, quick and user-friendly manner. We present GEMMER (GEnome-wide tool for Multi-scale Modelling data Extraction and Representation), a web-based data-integration tool that facilitates high quality visualization of physical, regulatory and genetic interactions between proteins/genes in Saccharomyces cerevisiae. GEMMER creates network visualizations that integrate information on function, temporal expression, localization and abundance from various existing databases. GEMMER supports modeling efforts by effortlessly gathering this information and providing convenient export options for images and their underlying data. GEMMER is freely available at http://gemmer.barberislab.com. Source code, written in Python, JavaScript library D3js, PHP and JSON, is freely available at https://github.com/barberislab/GEMMER. M.Barberis@uva.nl. Supplementary data are available at Bioinformatics online. © The Author(s) 2018. Published by Oxford University Press.

  18. Multiscale Modeling of Wear Degradation in Cylinder Liners

    KAUST Repository

    Moraes, Alvaro; Ruggeri, Fabrizio; Tempone, Raul; Vilanova, Pedro

    2014-01-01

    both to predict and to avoid them. To achieve this, a monitoring system of the wear level should be implemented to decrease the risk of failure. In this work, we take a first step into the development of a multiscale indirect inference methodology

  19. A constrained approach to multiscale stochastic simulation of chemically reacting systems

    KAUST Repository

    Cotter, Simon L.; Zygalakis, Konstantinos C.; Kevrekidis, Ioannis G.; Erban, Radek

    2011-01-01

    Stochastic simulation of coupled chemical reactions is often computationally intensive, especially if a chemical system contains reactions occurring on different time scales. In this paper, we introduce a multiscale methodology suitable to address

  20. Deductive multiscale simulation using order parameters

    Science.gov (United States)

    Ortoleva, Peter J.

    2017-05-16

    Illustrative embodiments of systems and methods for the deductive multiscale simulation of macromolecules are disclosed. In one illustrative embodiment, a deductive multiscale simulation method may include (i) constructing a set of order parameters that model one or more structural characteristics of a macromolecule, (ii) simulating an ensemble of atomistic configurations for the macromolecule using instantaneous values of the set of order parameters, (iii) simulating thermal-average forces and diffusivities for the ensemble of atomistic configurations, and (iv) evolving the set of order parameters via Langevin dynamics using the thermal-average forces and diffusivities.

  1. Coupling of ab initio density functional theory and molecular dynamics for the multiscale modeling of carbon nanotubes

    International Nuclear Information System (INIS)

    Ng, T Y; Yeak, S H; Liew, K M

    2008-01-01

    A multiscale technique is developed that couples empirical molecular dynamics (MD) and ab initio density functional theory (DFT). An overlap handshaking region between the empirical MD and ab initio DFT regions is formulated and the interaction forces between the carbon atoms are calculated based on the second-generation reactive empirical bond order potential, the long-range Lennard-Jones potential as well as the quantum-mechanical DFT derived forces. A density of point algorithm is also developed to track all interatomic distances in the system, and to activate and establish the DFT and handshaking regions. Through parallel computing, this multiscale method is used here to study the dynamic behavior of single-walled carbon nanotubes (SWCNTs) under asymmetrical axial compression. The detection of sideways buckling due to the asymmetrical axial compression is reported and discussed. It is noted from this study on SWCNTs that the MD results may be stiffer compared to those with electron density considerations, i.e. first-principle ab initio methods

  2. Metabolic dynamics in skeletal muscle during acute reduction in blood flow and oxygen supply to mitochondria: in-silico studies using a multi-scale, top-down integrated model.

    Science.gov (United States)

    Dash, Ranjan K; Li, Yanjun; Kim, Jaeyeon; Beard, Daniel A; Saidel, Gerald M; Cabrera, Marco E

    2008-09-09

    Control mechanisms of cellular metabolism and energetics in skeletal muscle that may become evident in response to physiological stresses such as reduction in blood flow and oxygen supply to mitochondria can be quantitatively understood using a multi-scale computational model. The analysis of dynamic responses from such a model can provide insights into mechanisms of metabolic regulation that may not be evident from experimental studies. For the purpose, a physiologically-based, multi-scale computational model of skeletal muscle cellular metabolism and energetics was developed to describe dynamic responses of key chemical species and reaction fluxes to muscle ischemia. The model, which incorporates key transport and metabolic processes and subcellular compartmentalization, is based on dynamic mass balances of 30 chemical species in both capillary blood and tissue cells (cytosol and mitochondria) domains. The reaction fluxes in cytosol and mitochondria are expressed in terms of a general phenomenological Michaelis-Menten equation involving the compartmentalized energy controller ratios ATP/ADP and NADH/NAD(+). The unknown transport and reaction parameters in the model are estimated simultaneously by minimizing the differences between available in vivo experimental data on muscle ischemia and corresponding model outputs in coupled with the resting linear flux balance constraints using a robust, nonlinear, constrained-based, reduced gradient optimization algorithm. With the optimal parameter values, the model is able to simulate dynamic responses to reduced blood flow and oxygen supply to mitochondria associated with muscle ischemia of several key metabolite concentrations and metabolic fluxes in the subcellular cytosolic and mitochondrial compartments, some that can be measured and others that can not be measured with the current experimental techniques. The model can be applied to test complex hypotheses involving dynamic regulation of cellular metabolism and

  3. Multiscale Rotation-Invariant Convolutional Neural Networks for Lung Texture Classification.

    Science.gov (United States)

    Wang, Qiangchang; Zheng, Yuanjie; Yang, Gongping; Jin, Weidong; Chen, Xinjian; Yin, Yilong

    2018-01-01

    We propose a new multiscale rotation-invariant convolutional neural network (MRCNN) model for classifying various lung tissue types on high-resolution computed tomography. MRCNN employs Gabor-local binary pattern that introduces a good property in image analysis-invariance to image scales and rotations. In addition, we offer an approach to deal with the problems caused by imbalanced number of samples between different classes in most of the existing works, accomplished by changing the overlapping size between the adjacent patches. Experimental results on a public interstitial lung disease database show a superior performance of the proposed method to state of the art.

  4. Computational fluid dynamics modelling in cardiovascular medicine.

    Science.gov (United States)

    Morris, Paul D; Narracott, Andrew; von Tengg-Kobligk, Hendrik; Silva Soto, Daniel Alejandro; Hsiao, Sarah; Lungu, Angela; Evans, Paul; Bressloff, Neil W; Lawford, Patricia V; Hose, D Rodney; Gunn, Julian P

    2016-01-01

    This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards 'digital patient' or 'virtual physiological human' representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges. Published by the BMJ Publishing Group Limited. For permission

  5. Multi-scale graph-cut algorithm for efficient water-fat separation.

    Science.gov (United States)

    Berglund, Johan; Skorpil, Mikael

    2017-09-01

    To improve the accuracy and robustness to noise in water-fat separation by unifying the multiscale and graph cut based approaches to B 0 -correction. A previously proposed water-fat separation algorithm that corrects for B 0 field inhomogeneity in 3D by a single quadratic pseudo-Boolean optimization (QPBO) graph cut was incorporated into a multi-scale framework, where field map solutions are propagated from coarse to fine scales for voxels that are not resolved by the graph cut. The accuracy of the single-scale and multi-scale QPBO algorithms was evaluated against benchmark reference datasets. The robustness to noise was evaluated by adding noise to the input data prior to water-fat separation. Both algorithms achieved the highest accuracy when compared with seven previously published methods, while computation times were acceptable for implementation in clinical routine. The multi-scale algorithm was more robust to noise than the single-scale algorithm, while causing only a small increase (+10%) of the reconstruction time. The proposed 3D multi-scale QPBO algorithm offers accurate water-fat separation, robustness to noise, and fast reconstruction. The software implementation is freely available to the research community. Magn Reson Med 78:941-949, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

  6. Multiscale modelling of solidification microstructures, including microsegregation and microporosity, in an Al-Si-Cu alloy

    International Nuclear Information System (INIS)

    Lee, P.D.; Chirazi, A.; Atwood, R.C.; Wang, W.

    2004-01-01

    Phase transition phenomena in metallic alloys involve complex physical processes occurring over a wide range of temporal, spatial and energy scales. Multiscale modelling is a powerful methodology for understanding these complex systems. In this paper, a multiscale model of grain and pore formation is presented during solidification. At the microscale, a combined stochastic-deterministic approach based on the cellular automata method is used to solve multicomponent diffusion in a three-phase system (liquid, solid and gas), simulating the nucleation and growth of both grains and pores. The impingement of the growing pores upon the developing solid is also solved to predict the tortuous shape of the porosity, a critical factor for fatigue properties. The micromodel is coupled with a finite element method (FEM) solution of the macroscale heat transfer and fluid flow in industrial castings through the temperature and pressure fields. The result model was used to investigate the influence of local solidification time, hydrogen content, local metallostatic pressure and alloy composition upon the predicted grain structure and pore morphology. Comparison of the model predictions to both laboratory and industrial scale castings are presented

  7. Multiscale Modeling of Fracture Processes in Cementitious Materials

    NARCIS (Netherlands)

    Qian, Z.

    2012-01-01

    Concrete is a composite construction material, which is composed primarily of coarse aggregates, sands and cement paste. The fracture processes in concrete are complicated, because of the multiscale and multiphase nature of the material. In the past decades, comprehensive effort has been put to

  8. The role of zonal flows in the saturation of multi-scale gyrokinetic turbulence

    Energy Technology Data Exchange (ETDEWEB)

    Staebler, G. M.; Candy, J. [General Atomics, San Diego, California 92186 (United States); Howard, N. T. [Oak Ridge Institute for Science Education (ORISE), Oak Ridge, Tennessee 37831 (United States); Holland, C. [University of California San Diego, San Diego, California 92093 (United States)

    2016-06-15

    The 2D spectrum of the saturated electric potential from gyrokinetic turbulence simulations that include both ion and electron scales (multi-scale) in axisymmetric tokamak geometry is analyzed. The paradigm that the turbulence is saturated when the zonal (axisymmetic) ExB flow shearing rate competes with linear growth is shown to not apply to the electron scale turbulence. Instead, it is the mixing rate by the zonal ExB velocity spectrum with the turbulent distribution function that competes with linear growth. A model of this mechanism is shown to be able to capture the suppression of electron-scale turbulence by ion-scale turbulence and the threshold for the increase in electron scale turbulence when the ion-scale turbulence is reduced. The model computes the strength of the zonal flow velocity and the saturated potential spectrum from the linear growth rate spectrum. The model for the saturated electric potential spectrum is applied to a quasilinear transport model and shown to accurately reproduce the electron and ion energy fluxes of the non-linear gyrokinetic multi-scale simulations. The zonal flow mixing saturation model is also shown to reproduce the non-linear upshift in the critical temperature gradient caused by zonal flows in ion-scale gyrokinetic simulations.

  9. Biology meets Physics: Reductionism and Multi-scale Modeling of Morphogenesis

    DEFF Research Database (Denmark)

    Green, Sara; Batterman, Robert

    2017-01-01

    A common reductionist assumption is that macro-scale behaviors can be described "bottom-up" if only sufficient details about lower-scale processes are available. The view that an "ideal" or "fundamental" physics would be sufficient to explain all macro-scale phenomena has been met with criticism ...... modeling in developmental biology. In such contexts, the relation between models at different scales and from different disciplines is neither reductive nor completely autonomous, but interdependent....... from philosophers of biology. Specifically, scholars have pointed to the impossibility of deducing biological explanations from physical ones, and to the irreducible nature of distinctively biological processes such as gene regulation and evolution. This paper takes a step back in asking whether bottom......-up modeling is feasible even when modeling simple physical systems across scales. By comparing examples of multi-scale modeling in physics and biology, we argue that the “tyranny of scales” problem present a challenge to reductive explanations in both physics and biology. The problem refers to the scale...

  10. Computational models of stellar collapse and core-collapse supernovae

    International Nuclear Information System (INIS)

    Ott, Christian D; O'Connor, Evan; Schnetter, Erik; Loeffler, Frank; Burrows, Adam; Livne, Eli

    2009-01-01

    Core-collapse supernovae are among Nature's most energetic events. They mark the end of massive star evolution and pollute the interstellar medium with the life-enabling ashes of thermonuclear burning. Despite their importance for the evolution of galaxies and life in the universe, the details of the core-collapse supernova explosion mechanism remain in the dark and pose a daunting computational challenge. We outline the multi-dimensional, multi-scale, and multi-physics nature of the core-collapse supernova problem and discuss computational strategies and requirements for its solution. Specifically, we highlight the axisymmetric (2D) radiation-MHD code VULCAN/2D and present results obtained from the first full-2D angle-dependent neutrino radiation-hydrodynamics simulations of the post-core-bounce supernova evolution. We then go on to discuss the new code Zelmani which is based on the open-source HPC Cactus framework and provides a scalable AMR approach for 3D fully general-relativistic modeling of stellar collapse, core-collapse supernovae and black hole formation on current and future massively-parallel HPC systems. We show Zelmani's scaling properties to more than 16,000 compute cores and discuss first 3D general-relativistic core-collapse results.

  11. Multiscale Lattice Boltzmann method for flow simulations in highly heterogenous porous media

    KAUST Repository

    Li, Jun

    2013-01-01

    A lattice Boltzmann method (LBM) for flow simulations in highly heterogeneous porous media at both pore and Darcy scales is proposed in the paper. In the pore scale simulations, flow of two phases (e.g., oil and gas) or two immiscible fluids (e.g., water and oil) are modeled using cohesive or repulsive forces, respectively. The relative permeability can be computed using pore-scale simulations and seamlessly applied for intermediate and Darcy-scale simulations. A multiscale LBM that can reduce the computational complexity of existing LBM and transfer the information between different scales is implemented. The results of coarse-grid, reduced-order, simulations agree very well with the averaged results obtained using fine grid.

  12. Multi-scale modelling of the hydro-mechanical behaviour of argillaceous rocks

    International Nuclear Information System (INIS)

    Van den Eijnden, Bram

    2015-01-01

    theoretical developments of this extension are implemented in the finite element code Lagamine (Liege) as an independent constitutive relation. For the modelling of localization of deformation, which in classical FE methods suffers from the well-known mesh dependency, the double-scale approach of hydro-mechanical coupling is combined with a local second gradient model to control the internal length scale of localized deformation. By accepting the periodic boundary conditions as a regularization of the microscale deformation, the use of the multi-scale model in combination with the local second gradient model can be used for modelling localization phenomena in HM-coupled settings with material softening. The modelling capacities of the approach are demonstrated by means of simulations of odometer tests and biaxial compression tests. The approach is demonstrated to be a powerful way to model anisotropy in the mechanical as well as the hydraulic behaviour of the material both in the initial material state and as an effect of hydro-mechanical alterations. For the application to the modelling of Callovo-Oxfordian clay-stone, microstructural REVs are calibrated to geometrical characteristics of the inclusion that form the microstructure under consideration and to macro-scale experimental results of the mechanical behaviour. The calibrated constitutive relation is used in the simulation of gallery excavation processes. These computations give a proof of concept of the double-scale assessment of the hydro-mechanical behaviour of the excavation damaged zones around galleries in the context of nuclear waste disposal. (author) [fr

  13. Multiscale Persistent Functions for Biomolecular Structure Characterization

    Energy Technology Data Exchange (ETDEWEB)

    Xia, Kelin [Nanyang Technological University (Singapore). Division of Mathematical Sciences, School of Physical, Mathematical Sciences and School of Biological Sciences; Li, Zhiming [Central China Normal University, Wuhan (China). Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics; Mu, Lin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computer Science and Mathematics Division

    2017-11-02

    Here in this paper, we introduce multiscale persistent functions for biomolecular structure characterization. The essential idea is to combine our multiscale rigidity functions (MRFs) with persistent homology analysis, so as to construct a series of multiscale persistent functions, particularly multiscale persistent entropies, for structure characterization. To clarify the fundamental idea of our method, the multiscale persistent entropy (MPE) model is discussed in great detail. Mathematically, unlike the previous persistent entropy (Chintakunta et al. in Pattern Recognit 48(2):391–401, 2015; Merelli et al. in Entropy 17(10):6872–6892, 2015; Rucco et al. in: Proceedings of ECCS 2014, Springer, pp 117–128, 2016), a special resolution parameter is incorporated into our model. Various scales can be achieved by tuning its value. Physically, our MPE can be used in conformational entropy evaluation. More specifically, it is found that our method incorporates in it a natural classification scheme. This is achieved through a density filtration of an MRF built from angular distributions. To further validate our model, a systematical comparison with the traditional entropy evaluation model is done. Additionally, it is found that our model is able to preserve the intrinsic topological features of biomolecular data much better than traditional approaches, particularly for resolutions in the intermediate range. Moreover, by comparing with traditional entropies from various grid sizes, bond angle-based methods and a persistent homology-based support vector machine method (Cang et al. in Mol Based Math Biol 3:140–162, 2015), we find that our MPE method gives the best results in terms of average true positive rate in a classic protein structure classification test. More interestingly, all-alpha and all-beta protein classes can be clearly separated from each other with zero error only in our model. Finally, a special protein structure index (PSI) is proposed, for the first

  14. Integrating Cellular Metabolism into a Multiscale Whole-Body Model

    Science.gov (United States)

    Krauss, Markus; Schaller, Stephan; Borchers, Steffen; Findeisen, Rolf; Lippert, Jörg; Kuepfer, Lars

    2012-01-01

    Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development. PMID:23133351

  15. Mathematical modeling and computational prediction of cancer drug resistance.

    Science.gov (United States)

    Sun, Xiaoqiang; Hu, Bin

    2017-06-23

    computational methods for studying drug resistance, including inferring drug-induced signaling networks, multiscale modeling, drug combinations and precision medicine. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  16. Collaborating for Multi-Scale Chemical Science

    Energy Technology Data Exchange (ETDEWEB)

    William H. Green

    2006-07-14

    Advanced model reduction methods were developed and integrated into the CMCS multiscale chemical science simulation software. The new technologies were used to simulate HCCI engines and burner flames with exceptional fidelity.

  17. Multi-Scale Validation of a Nanodiamond Drug Delivery System and Multi-Scale Engineering Education

    Science.gov (United States)

    Schwalbe, Michelle Kristin

    2010-01-01

    This dissertation has two primary concerns: (i) evaluating the uncertainty and prediction capabilities of a nanodiamond drug delivery model using Bayesian calibration and bias correction, and (ii) determining conceptual difficulties of multi-scale analysis from an engineering education perspective. A Bayesian uncertainty quantification scheme…

  18. Predicting the impact of combined therapies on myeloma cell growth using a hybrid multi-scale agent-based model.

    Science.gov (United States)

    Ji, Zhiwei; Su, Jing; Wu, Dan; Peng, Huiming; Zhao, Weiling; Nlong Zhao, Brian; Zhou, Xiaobo

    2017-01-31

    Multiple myeloma is a malignant still incurable plasma cell disorder. This is due to refractory disease relapse, immune impairment, and development of multi-drug resistance. The growth of malignant plasma cells is dependent on the bone marrow (BM) microenvironment and evasion of the host's anti-tumor immune response. Hence, we hypothesized that targeting tumor-stromal cell interaction and endogenous immune system in BM will potentially improve the response of multiple myeloma (MM). Therefore, we proposed a computational simulation of the myeloma development in the complicated microenvironment which includes immune cell components and bone marrow stromal cells and predicted the effects of combined treatment with multi-drugs on myeloma cell growth. We constructed a hybrid multi-scale agent-based model (HABM) that combines an ODE system and Agent-based model (ABM). The ODEs was used for modeling the dynamic changes of intracellular signal transductions and ABM for modeling the cell-cell interactions between stromal cells, tumor, and immune components in the BM. This model simulated myeloma growth in the bone marrow microenvironment and revealed the important role of immune system in this process. The predicted outcomes were consistent with the experimental observations from previous studies. Moreover, we applied this model to predict the treatment effects of three key therapeutic drugs used for MM, and found that the combination of these three drugs potentially suppress the growth of myeloma cells and reactivate the immune response. In summary, the proposed model may serve as a novel computational platform for simulating the formation of MM and evaluating the treatment response of MM to multiple drugs.

  19. Extending the Applicability of the Community Multiscale Air Quality Model to Hemispheric Scales: Motivation, Challenges, and Progress

    Science.gov (United States)

    The adaptation of the Community Multiscale Air Quality (CMAQ) modeling system to simulate O3, particulate matter, and related precursor distributions over the northern hemisphere is presented. Hemispheric simulations with CMAQ and the Weather Research and Forecasting (...

  20. MULTISCALE THERMOHYDROLOGIC MODEL

    International Nuclear Information System (INIS)

    T. Buscheck

    2005-01-01

    The intended purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. The goal of the MSTHM is to predict a reasonable range of possible thermal-hydrologic conditions within the emplacement drift. To be reasonable, this range includes the influence of waste-package-to-waste-package heat output variability relevant to the license application design, as well as the influence of uncertainty and variability in the geologic and hydrologic conditions relevant to predicting the thermal-hydrologic response in emplacement drifts. This goal is quite different from the goal of a model to predict a single expected thermal-hydrologic response. As a result, the development and validation of the MSTHM and the associated analyses using this model are focused on the goal of predicting a reasonable range of thermal-hydrologic conditions resulting from parametric uncertainty and waste-package-to-waste-package heat-output variability. Thermal-hydrologic conditions within emplacement drifts depend primarily on thermal-hydrologic conditions in the host rock at the drift wall and on the temperature difference between the drift wall and the drip-shield and waste-package surfaces. Thus, the ability to predict a reasonable range of relevant in-drift MSTHM output parameters (e.g., temperature and relative humidity) is based on valid predictions of thermal-hydrologic processes in the host rock, as well as valid predictions of heat-transfer processes between the drift wall and the drip-shield and waste-package surfaces. Because the invert contains crushed gravel derived from the host rock, the invert is, in effect, an extension of the host rock, with thermal and hydrologic properties that have been modified by virtue of the crushing (and the resulting

  1. MULTISCALE THERMOHYDROLOGIC MODEL

    Energy Technology Data Exchange (ETDEWEB)

    T. Buscheck

    2005-07-07

    The intended purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. The goal of the MSTHM is to predict a reasonable range of possible thermal-hydrologic conditions within the emplacement drift. To be reasonable, this range includes the influence of waste-package-to-waste-package heat output variability relevant to the license application design, as well as the influence of uncertainty and variability in the geologic and hydrologic conditions relevant to predicting the thermal-hydrologic response in emplacement drifts. This goal is quite different from the goal of a model to predict a single expected thermal-hydrologic response. As a result, the development and validation of the MSTHM and the associated analyses using this model are focused on the goal of predicting a reasonable range of thermal-hydrologic conditions resulting from parametric uncertainty and waste-package-to-waste-package heat-output variability. Thermal-hydrologic conditions within emplacement drifts depend primarily on thermal-hydrologic conditions in the host rock at the drift wall and on the temperature difference between the drift wall and the drip-shield and waste-package surfaces. Thus, the ability to predict a reasonable range of relevant in-drift MSTHM output parameters (e.g., temperature and relative humidity) is based on valid predictions of thermal-hydrologic processes in the host rock, as well as valid predictions of heat-transfer processes between the drift wall and the drip-shield and waste-package surfaces. Because the invert contains crushed gravel derived from the host rock, the invert is, in effect, an extension of the host rock, with thermal and hydrologic properties that have been modified by virtue of the crushing (and the resulting

  2. Key Factors Influencing the Energy Absorption of Dual-Phase Steels: Multiscale Material Model Approach and Microstructural Optimization

    Science.gov (United States)

    Belgasam, Tarek M.; Zbib, Hussein M.

    2018-06-01

    The increase in use of dual-phase (DP) steel grades by vehicle manufacturers to enhance crash resistance and reduce body car weight requires the development of a clear understanding of the effect of various microstructural parameters on the energy absorption in these materials. Accordingly, DP steelmakers are interested in predicting the effect of various microscopic factors as well as optimizing microstructural properties for application in crash-relevant components of vehicle bodies. This study presents a microstructure-based approach using a multiscale material and structure model. In this approach, Digimat and LS-DYNA software were coupled and employed to provide a full micro-macro multiscale material model, which is then used to simulate tensile tests. Microstructures with varied ferrite grain sizes, martensite volume fractions, and carbon content in DP steels were studied. The impact of these microstructural features at different strain rates on energy absorption characteristics of DP steels is investigated numerically using an elasto-viscoplastic constitutive model. The model is implemented in a multiscale finite-element framework. A comprehensive statistical parametric study using response surface methodology is performed to determine the optimum microstructural features for a required tensile toughness at different strain rates. The simulation results are validated using experimental data found in the literature. The developed methodology proved to be effective for investigating the influence and interaction of key microscopic properties on the energy absorption characteristics of DP steels. Furthermore, it is shown that this method can be used to identify optimum microstructural conditions at different strain-rate conditions.

  3. Toward the multiscale nature of stress corrosion cracking

    Directory of Open Access Journals (Sweden)

    Xiaolong Liu

    2018-02-01

    Full Text Available This article reviews the multiscale nature of stress corrosion cracking (SCC observed by high-resolution characterizations in austenite stainless steels and Ni-base superalloys in light water reactors (including boiling water reactors, pressurized water reactors, and supercritical water reactors with related opinions. A new statistical summary and comparison of observed degradation phenomena at different length scales is included. The intrinsic causes of this multiscale nature of SCC are discussed based on existing evidence and related opinions, ranging from materials theory to practical processing technologies. Questions of interest are then discussed to improve bottom-up understanding of the intrinsic causes. Last, a multiscale modeling and simulation methodology is proposed as a promising interdisciplinary solution to understand the intrinsic causes of the multiscale nature of SCC in light water reactors, based on a review of related supporting application evidence.

  4. Multiscale Modeling of Grain Boundary Segregation and Embrittlement in Tungsten for Mechanistic Design of Alloys for Coal Fired Plants

    Energy Technology Data Exchange (ETDEWEB)

    Luo, Jian; Tomar, Vikas; Zhou, Naixie; Lee, Hongsuk

    2013-06-30

    Based on a recent discovery of premelting-like grain boundary segregation in refractory metals occurring at high temperatures and/or high alloying levels, this project investigated grain boundary segregation and embrittlement in tungsten (W) based alloys. Specifically, new interfacial thermodynamic models have been developed and quantified to predict high-temperature grain boundary segregation in the W-Ni binary alloy and W-Ni-Fe, W-Ni-Ti, W-Ni-Co, W-Ni-Cr, W-Ni-Zr and W-Ni-Nb ternary alloys. The thermodynamic modeling results have been experimentally validated for selected systems. Furthermore, multiscale modeling has been conducted at continuum, atomistic and quantum-mechanical levels to link grain boundary segregation with embrittlement. In summary, this 3-year project has successfully developed a theoretical framework in combination with a multiscale modeling strategy for predicting grain boundary segregation and embrittlement in W based alloys.

  5. A multi-scale correlative investigation of ductile fracture

    International Nuclear Information System (INIS)

    Daly, M.; Burnett, T.L.; Pickering, E.J.; Tuck, O.C.G.; Léonard, F.; Kelley, R.; Withers, P.J.; Sherry, A.H.

    2017-01-01

    The use of novel multi-scale correlative methods, which involve the coordinated characterisation of matter across a range of length scales, are becoming of increasing value to materials scientists. Here, we describe for the first time how a multi-scale correlative approach can be used to investigate the nature of ductile fracture in metals. Specimens of a nuclear pressure vessel steel, SA508 Grade 3, are examined following ductile fracture using medium and high-resolution 3D X-ray computed tomography (CT) analyses, and a site-specific analysis using a dual beam plasma focused ion beam scanning electron microscope (PFIB-SEM). The methods are employed sequentially to characterise damage by void nucleation and growth in one volume of interest, allowing for the imaging of voids that ranged in size from less than 100 nm to over 100 μm. This enables the examination of voids initiated at carbide particles to be detected, as well as the large voids initiated at inclusions. We demonstrate that this multi-scale correlative approach is a powerful tool, which not only enhances our understanding of ductile failure through detailed characterisation of microstructure, but also provides quantitative information about the size, volume fractions and spatial distributions of voids that can be used to inform models of failure. It is found that the vast majority of large voids nucleated at MnS inclusions, and that the volume of a void varied according to the volume of its initiating inclusion raised to the power 3/2. The most severe voiding was concentrated within 500 μm of the fracture surface, but measurable damage was found to extend to a depth of at least 3 mm. Microvoids associated with carbides (carbide-initiated voids) were found to be concentrated around larger inclusion-initiated voids at depths of at least 400 μm. Methods for quantifying X-ray CT void data are discussed, and a procedure for using this data to calibrate parameters in the Gurson-Tvergaard Needleman (GTN

  6. Multi-Scale Pattern Recognition for Image Classification and Segmentation

    NARCIS (Netherlands)

    Li, Y.

    2013-01-01

    Scale is an important parameter of images. Different objects or image structures (e.g. edges and corners) can appear at different scales and each is meaningful only over a limited range of scales. Multi-scale analysis has been widely used in image processing and computer vision, serving as the basis

  7. Linear theory for filtering nonlinear multiscale systems with model error.

    Science.gov (United States)

    Berry, Tyrus; Harlim, John

    2014-07-08

    In this paper, we study filtering of multiscale dynamical systems with model error arising from limitations in resolving the smaller scale processes. In particular, the analysis assumes the availability of continuous-time noisy observations of all components of the slow variables. Mathematically, this paper presents new results on higher order asymptotic expansion of the first two moments of a conditional measure. In particular, we are interested in the application of filtering multiscale problems in which the conditional distribution is defined over the slow variables, given noisy observation of the slow variables alone. From the mathematical analysis, we learn that for a continuous time linear model with Gaussian noise, there exists a unique choice of parameters in a linear reduced model for the slow variables which gives the optimal filtering when only the slow variables are observed. Moreover, these parameters simultaneously give the optimal equilibrium statistical estimates of the underlying system, and as a consequence they can be estimated offline from the equilibrium statistics of the true signal. By examining a nonlinear test model, we show that the linear theory extends in this non-Gaussian, nonlinear configuration as long as we know the optimal stochastic parametrization and the correct observation model. However, when the stochastic parametrization model is inappropriate, parameters chosen for good filter performance may give poor equilibrium statistical estimates and vice versa; this finding is based on analytical and numerical results on our nonlinear test model and the two-layer Lorenz-96 model. Finally, even when the correct stochastic ansatz is given, it is imperative to estimate the parameters simultaneously and to account for the nonlinear feedback of the stochastic parameters into the reduced filter estimates. In numerical experiments on the two-layer Lorenz-96 model, we find that the parameters estimated online , as part of a filtering

  8. Multi-scale Modeling of the Impact Response of a Strain Rate Sensitive High-Manganese Austenitic Steel

    Directory of Open Access Journals (Sweden)

    Orkun eÖnal

    2014-09-01

    Full Text Available A multi-scale modeling approach was applied to predict the impact response of a strain rate sensitive high-manganese austenitic steel. The roles of texture, geometry and strain rate sensitivity were successfully taken into account all at once by coupling crystal plasticity and finite element (FE analysis. Specifically, crystal plasticity was utilized to obtain the multi-axial flow rule at different strain rates based on the experimental deformation response under uniaxial tensile loading. The equivalent stress – equivalent strain response was then incorporated into the FE model for the sake of a more representative hardening rule under impact loading. The current results demonstrate that reliable predictions can be obtained by proper coupling of crystal plasticity and FE analysis even if the experimental flow rule of the material is acquired under uniaxial loading and at moderate strain rates that are significantly slower than those attained during impact loading. Furthermore, the current findings also demonstrate the need for an experiment-based multi-scale modeling approach for the sake of reliable predictions of the impact response.

  9. Modelling an industrial anaerobic granular reactor using a multi-scale approach

    DEFF Research Database (Denmark)

    Feldman, Hannah; Flores Alsina, Xavier; Ramin, Pedram

    2017-01-01

    The objective of this paper is to show the results of an industrial project dealing with modelling of anaerobic digesters. A multi-scale mathematical approach is developed to describe reactor hydrodynamics, granule growth/distribution and microbial competition/inhibition for substrate/space within...... the biofilm. The main biochemical and physico-chemical processes in the model are based on the Anaerobic Digestion Model No 1 (ADM1) extended with the fate of phosphorus (P), sulfur (S) and ethanol (Et-OH). Wastewater dynamic conditions are reproduced and data frequency increased using the Benchmark...... simulations show the effects on the overall process performance when operational (pH) and loading (S:COD) conditions are modified. Lastly, the effect of intra-granular precipitation on the overall organic/inorganic distribution is assessed at: 1) different times; and, 2) reactor heights. Finally...

  10. Multiscale Retinex

    Directory of Open Access Journals (Sweden)

    Ana Belén Petro

    2014-04-01

    Full Text Available While the retinex theory aimed at explaining human color perception, its derivations have led to efficient algorithms enhancing local image contrast, thus permitting among other features, to "see in the shadows". Among these derived algorithms, Multiscale Retinex is probably the most successful center-surround image filter. In this paper, we offer an analysis and implementation of Multiscale Retinex. We point out and resolve some ambiguities of the method. In particular, we show that the important color correction final step of the method can be seriously improved. This analysis permits to come up with an automatic implementation of Multiscale Retinex which is as faithful as possible to the one described in the original paper. Overall, this implementation delivers excellent results and confirms the validity of Multiscale Retinex for image color restoration and contrast enhancement. Nevertheless, while the method parameters can be fixed, we show that a crucial choice must be left to the user, depending on the lightning condition of the image: the method must either be applied to each color independently if a color balance is required, or to the luminance only if the goal is to achieve local contrast enhancement. Thus, we propose two slightly different algorithms to deal with both cases.

  11. Coupled numerical approach combining finite volume and lattice Boltzmann methods for multi-scale multi-physicochemical processes

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Li; He, Ya-Ling [Key Laboratory of Thermo-Fluid Science and Engineering of MOE, School of Energy and Power Engineering, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China); Kang, Qinjun [Computational Earth Science Group (EES-16), Los Alamos National Laboratory, Los Alamos, NM (United States); Tao, Wen-Quan, E-mail: wqtao@mail.xjtu.edu.cn [Key Laboratory of Thermo-Fluid Science and Engineering of MOE, School of Energy and Power Engineering, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China)

    2013-12-15

    A coupled (hybrid) simulation strategy spatially combining the finite volume method (FVM) and the lattice Boltzmann method (LBM), called CFVLBM, is developed to simulate coupled multi-scale multi-physicochemical processes. In the CFVLBM, computational domain of multi-scale problems is divided into two sub-domains, i.e., an open, free fluid region and a region filled with porous materials. The FVM and LBM are used for these two regions, respectively, with information exchanged at the interface between the two sub-domains. A general reconstruction operator (RO) is proposed to derive the distribution functions in the LBM from the corresponding macro scalar, the governing equation of which obeys the convection–diffusion equation. The CFVLBM and the RO are validated in several typical physicochemical problems and then are applied to simulate complex multi-scale coupled fluid flow, heat transfer, mass transport, and chemical reaction in a wall-coated micro reactor. The maximum ratio of the grid size between the FVM and LBM regions is explored and discussed. -- Highlights: •A coupled simulation strategy for simulating multi-scale phenomena is developed. •Finite volume method and lattice Boltzmann method are coupled. •A reconstruction operator is derived to transfer information at the sub-domains interface. •Coupled multi-scale multiple physicochemical processes in micro reactor are simulated. •Techniques to save computational resources and improve the efficiency are discussed.

  12. Variational Multi-Scale method with spectral approximation of the sub-scales.

    KAUST Repository

    Dia, Ben Mansour; Chá con-Rebollo, Tomas

    2015-01-01

    A variational multi-scale method where the sub-grid scales are computed by spectral approximations is presented. It is based upon an extension of the spectral theorem to non necessarily self-adjoint elliptic operators that have an associated base

  13. Multiscale Modeling of Point and Line Defects in Cubic Lattices

    National Research Council Canada - National Science Library

    Chung, P. W; Clayton, J. D

    2007-01-01

    .... This multiscale theory explicitly captures heterogeneity in microscopic atomic motion in crystalline materials, attributed, for example, to the presence of various point and line lattice defects...

  14. Multi-Scale Modeling of Microstructural Evolution in Structural Metallic Systems

    Science.gov (United States)

    Zhao, Lei

    Metallic alloys are a widely used class of structural materials, and the mechanical properties of these alloys are strongly dependent on the microstructure. Therefore, the scientific design of metallic materials with superior mechanical properties requires the understanding of the microstructural evolution. Computational models and simulations offer a number of advantages over experimental techniques in the prediction of microstructural evolution, because they can allow studies of microstructural evolution in situ, i.e., while the material is mechanically loaded (meso-scale simulations), and bring atomic-level insights into the microstructure (atomistic simulations). In this thesis, we applied a multi-scale modeling approach to study the microstructural evolution in several metallic systems, including polycrystalline materials and metallic glasses (MGs). Specifically, for polycrystalline materials, we developed a coupled finite element model that combines phase field method and crystal plasticity theory to study the plasticity effect on grain boundary (GB) migration. Our model is not only coupled strongly (i.e., we include plastic driving force on GB migration directly) and concurrently (i.e., coupled equations are solved simultaneously), but also it qualitatively captures such phenomena as the dislocation absorption by mobile GBs. The developed model provides a tool to study the microstructural evolution in plastically deformed metals and alloys. For MGs, we used molecular dynamics (MD) simulations to investigate the nucleation kinetics in the primary crystallization in Al-Sm system. We calculated the time-temperature-transformation curves for low Sm concentrations, from which the strong suppressing effect of Sm solute on Al nucleation and its influencing mechanism are revealed. Also, through the comparative analysis of both Al attachment and Al diffusion in MGs, it has been found that the nucleation kinetics is controlled by interfacial attachment of Al, and that

  15. Information theory and stochastics for multiscale nonlinear systems

    CERN Document Server

    Majda, Andrew J; Grote, Marcus J

    2005-01-01

    This book introduces mathematicians to the fascinating emerging mathematical interplay between ideas from stochastics and information theory and important practical issues in studying complex multiscale nonlinear systems. It emphasizes the serendipity between modern applied mathematics and applications where rigorous analysis, the development of qualitative and/or asymptotic models, and numerical modeling all interact to explain complex phenomena. After a brief introduction to the emerging issues in multiscale modeling, the book has three main chapters. The first chapter is an introduction to information theory with novel applications to statistical mechanics, predictability, and Jupiter's Red Spot for geophysical flows. The second chapter discusses new mathematical issues regarding fluctuation-dissipation theorems for complex nonlinear systems including information flow, various approximations, and illustrates applications to various mathematical models. The third chapter discusses stochastic modeling of com...

  16. Multiscale Modeling with Carbon Nanotubes

    Energy Technology Data Exchange (ETDEWEB)

    Maiti, A

    2006-02-21

    Technologically important nanomaterials come in all shapes and sizes. They can range from small molecules to complex composites and mixtures. Depending upon the spatial dimensions of the system and properties under investigation computer modeling of such materials can range from equilibrium and nonequilibrium Quantum Mechanics, to force-field-based Molecular Mechanics and kinetic Monte Carlo, to Mesoscale simulation of evolving morphology, to Finite-Element computation of physical properties. This brief review illustrates some of the above modeling techniques through a number of recent applications with carbon nanotubes: nano electromechanical sensors (NEMS), chemical sensors, metal-nanotube contacts, and polymer-nanotube composites.

  17. Simulation of laminar and turbulent concentric pipe flows with the isogeometric variational multiscale method

    KAUST Repository

    Ghaffari Motlagh, Yousef; Ahn, Hyungtaek; Hughes, Thomas Jr R; Calo, Victor M.

    2013-01-01

    We present an application of the residual-based variational multiscale modeling methodology to the computation of laminar and turbulent concentric annular pipe flows. Isogeometric analysis is utilized for higher-order approximation of the solution using Non-Uniform Rational B-Splines (NURBS). The ability of NURBS to exactly represent curved geometries makes NURBS-based isogeometric analysis attractive for the application to the flow through annular channels. We demonstrate the applicability of the methodology to both laminar and turbulent flow regimes. © 2012 Elsevier Ltd.

  18. High-Efficiency Multiscale Modeling of Cell Deformations in Confined Microenvironments in Microcirculation and Microfluidic Devices

    Science.gov (United States)

    Lu, Huijie; Peng, Zhangli

    2017-11-01

    Our goal is to develop a high-efficiency multiscale modeling method to predict the stress and deformation of cells during the interactions with their microenvironments in microcirculation and microfluidic devices, including red blood cells (RBCs) and circulating tumor cells (CTCs). There are more than 1 billion people in the world suffering from RBC diseases, e.g. anemia, sickle cell diseases, and malaria. The mechanical properties of RBCs are changed in these diseases due to molecular structure alternations, which is not only important for understanding the disease pathology but also provides an opportunity for diagnostics. On the other hand, the mechanical properties of cancer cells are also altered compared to healthy cells. This can lead to acquired ability to cross the narrow capillary networks and endothelial gaps, which is crucial for metastasis, the leading cause of cancer mortality. Therefore, it is important to predict the deformation and stress of RBCs and CTCs in microcirculations. We are developing a high-efficiency multiscale model of cell-fluid interaction to study these two topics.

  19. Fast Decentralized Averaging via Multi-scale Gossip

    Science.gov (United States)

    Tsianos, Konstantinos I.; Rabbat, Michael G.

    We are interested in the problem of computing the average consensus in a distributed fashion on random geometric graphs. We describe a new algorithm called Multi-scale Gossip which employs a hierarchical decomposition of the graph to partition the computation into tractable sub-problems. Using only pairwise messages of fixed size that travel at most O(n^{1/3}) hops, our algorithm is robust and has communication cost of O(n loglogn logɛ - 1) transmissions, which is order-optimal up to the logarithmic factor in n. Simulated experiments verify the good expected performance on graphs of many thousands of nodes.

  20. Accelerating Electrostatic Surface Potential Calculation with Multiscale Approximation on Graphics Processing Units

    Science.gov (United States)

    Anandakrishnan, Ramu; Scogland, Tom R. W.; Fenley, Andrew T.; Gordon, John C.; Feng, Wu-chun; Onufriev, Alexey V.

    2010-01-01

    Tools that compute and visualize biomolecular electrostatic surface potential have been used extensively for studying biomolecular function. However, determining the surface potential for large biomolecules on a typical desktop computer can take days or longer using currently available tools and methods. Two commonly used techniques to speed up these types of electrostatic computations are approximations based on multi-scale coarse-graining and parallelization across multiple processors. This paper demonstrates that for the computation of electrostatic surface potential, these two techniques can be combined to deliver significantly greater speed-up than either one separately, something that is in general not always possible. Specifically, the electrostatic potential computation, using an analytical linearized Poisson Boltzmann (ALPB) method, is approximated using the hierarchical charge partitioning (HCP) multiscale method, and parallelized on an ATI Radeon 4870 graphical processing unit (GPU). The implementation delivers a combined 934-fold speed-up for a 476,040 atom viral capsid, compared to an equivalent non-parallel implementation on an Intel E6550 CPU without the approximation. This speed-up is significantly greater than the 42-fold speed-up for the HCP approximation alone or the 182-fold speed-up for the GPU alone. PMID:20452792

  1. Modeling Materials: Design for Planetary Entry, Electric Aircraft, and Beyond

    Science.gov (United States)

    Thompson, Alexander; Lawson, John W.

    2014-01-01

    NASA missions push the limits of what is possible. The development of high-performance materials must keep pace with the agency's demanding, cutting-edge applications. Researchers at NASA's Ames Research Center are performing multiscale computational modeling to accelerate development times and further the design of next-generation aerospace materials. Multiscale modeling combines several computationally intensive techniques ranging from the atomic level to the macroscale, passing output from one level as input to the next level. These methods are applicable to a wide variety of materials systems. For example: (a) Ultra-high-temperature ceramics for hypersonic aircraft-we utilized the full range of multiscale modeling to characterize thermal protection materials for faster, safer air- and spacecraft, (b) Planetary entry heat shields for space vehicles-we computed thermal and mechanical properties of ablative composites by combining several methods, from atomistic simulations to macroscale computations, (c) Advanced batteries for electric aircraft-we performed large-scale molecular dynamics simulations of advanced electrolytes for ultra-high-energy capacity batteries to enable long-distance electric aircraft service; and (d) Shape-memory alloys for high-efficiency aircraft-we used high-fidelity electronic structure calculations to determine phase diagrams in shape-memory transformations. Advances in high-performance computing have been critical to the development of multiscale materials modeling. We used nearly one million processor hours on NASA's Pleiades supercomputer to characterize electrolytes with a fidelity that would be otherwise impossible. For this and other projects, Pleiades enables us to push the physics and accuracy of our calculations to new levels.

  2. Reducing residual stresses and deformations in selective laser melting through multi-level multi-scale optimization of cellular scanning strategy

    DEFF Research Database (Denmark)

    Mohanty, Sankhya; Hattel, Jesper Henri

    2016-01-01

    . A multilevel optimization strategy is adopted using a customized genetic algorithm developed for optimizing cellular scanning strategy for selective laser melting, with an objective of reducing residual stresses and deformations. The resulting thermo-mechanically optimized cellular scanning strategies......, a calibrated, fast, multiscale thermal model coupled with a 3D finite element mechanical model is used to simulate residual stress formation and deformations during selective laser melting. The resulting reduction in thermal model computation time allows evolutionary algorithm-based optimization of the process...

  3. Multi-scale modeling for prediction of distributed cellular properties in response to substrate spatial gradients in a continuously run microreactor

    DEFF Research Database (Denmark)

    Lencastre Fernandes, Rita; Krühne, Ulrich; Nopens, Ingmar

    2012-01-01

    microbioreactor is simulated. A multiscale model consisting of the coupling of a population balance model, a kinetic model and a flow model was developed in order to predict simultaneously local concentrations of substrate (glucose), product (ethanol) and biomass, as well as the local cell size distributions....

  4. A general multiscale framework for the emergent effective elastodynamics of metamaterials

    Science.gov (United States)

    Sridhar, A.; Kouznetsova, V. G.; Geers, M. G. D.

    2018-02-01

    This paper presents a general multiscale framework towards the computation of the emergent effective elastodynamics of heterogeneous materials, to be applied for the analysis of acoustic metamaterials and phononic crystals. The generality of the framework is exemplified by two key characteristics. First, the underlying formalism relies on the Floquet-Bloch theorem to derive a robust definition of scales and scale separation. Second, unlike most homogenization approaches that rely on a classical volume average, a generalized homogenization operator is defined with respect to a family of particular projection functions. This yields a generalized macro-scale continuum, instead of the classical Cauchy continuum. This enables (in a micromorphic sense) to homogenize the rich dispersive behavior resulting from both Bragg scattering and local resonance. For an arbitrary unit cell, the homogenization projection functions are constructed using the Floquet-Bloch eigenvectors obtained in the desired frequency regime at select high symmetry points, which effectively resolves the emergent phenomena dominating that regime. Furthermore, a generalized Hill-Mandel condition is proposed that ensures power consistency between the homogenized and full-scale model. A high-order spatio-temporal gradient expansion is used to localize the multiscale problem leading to a series of recursive unit cell problems giving the appropriate micro-mechanical corrections. The developed multiscale method is validated against standard numerical Bloch analysis of the dispersion spectra of example unit cells encompassing multiple high-order branches generated by local resonance and/or Bragg scattering.

  5. Integrating cellular metabolism into a multiscale whole-body model.

    Directory of Open Access Journals (Sweden)

    Markus Krauss

    Full Text Available Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development.

  6. Cloud processing of gases and aerosols in the Community Multiscale Air Quality (CMAQ) model: Impacts of extended chemistry

    Science.gov (United States)

    Clouds and fogs can significantly impact the concentration and distribution of atmospheric gases and aerosols through chemistry, scavenging, and transport. This presentation summarizes the representation of cloud processes in the Community Multiscale Air Quality (CMAQ) modeling ...

  7. A Multiscale Time-Splitting Discrete Fracture Model of Nanoparticles Transport in Fractured Porous Media

    KAUST Repository

    El-Amin, Mohamed F.; Kou, Jisheng; Sun, Shuyu

    2017-01-01

    Recently, applications of nanoparticles have been considered in many branches of petroleum engineering, especially, enhanced oil recovery. The current paper is devoted to investigate the problem of nanoparticles transport in fractured porous media, numerically. We employed the discrete-fracture model (DFM) to represent the flow and transport in the fractured formations. The system of the governing equations consists of the mass conservation law, Darcy's law, nanoparticles concentration in water, deposited nanoparticles concentration on the pore-wall, and entrapped nanoparticles concentration in the pore-throat. The variation of porosity and permeability due to the nanoparticles deposition/entrapment on/in the pores is also considered. We employ the multiscale time-splitting strategy to control different time-step sizes for different physics, such as pressure and concentration. The cell-centered finite difference (CCFD) method is used for the spatial discretization. Numerical examples are provided to demonstrate the efficiency of the proposed multiscale time splitting approach.

  8. A Multiscale Time-Splitting Discrete Fracture Model of Nanoparticles Transport in Fractured Porous Media

    KAUST Repository

    El-Amin, Mohamed F.

    2017-06-06

    Recently, applications of nanoparticles have been considered in many branches of petroleum engineering, especially, enhanced oil recovery. The current paper is devoted to investigate the problem of nanoparticles transport in fractured porous media, numerically. We employed the discrete-fracture model (DFM) to represent the flow and transport in the fractured formations. The system of the governing equations consists of the mass conservation law, Darcy\\'s law, nanoparticles concentration in water, deposited nanoparticles concentration on the pore-wall, and entrapped nanoparticles concentration in the pore-throat. The variation of porosity and permeability due to the nanoparticles deposition/entrapment on/in the pores is also considered. We employ the multiscale time-splitting strategy to control different time-step sizes for different physics, such as pressure and concentration. The cell-centered finite difference (CCFD) method is used for the spatial discretization. Numerical examples are provided to demonstrate the efficiency of the proposed multiscale time splitting approach.

  9. Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®

    Energy Technology Data Exchange (ETDEWEB)

    Stander, Nielen [Livermore Software Technology Corporation, CA (United States); Basudhar, Anirban [Livermore Software Technology Corporation, CA (United States); Basu, Ushnish [Livermore Software Technology Corporation, CA (United States); Gandikota, Imtiaz [Livermore Software Technology Corporation, CA (United States); Savic, Vesna [General Motors, Flint, MI (United States); Sun, Xin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hu, XiaoHua [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Pourboghrat, Farhang [The Ohio State Univ., Columbus, OH (United States); Park, Taejoon [The Ohio State Univ., Columbus, OH (United States); Mapar, Aboozar [Michigan State Univ., East Lansing, MI (United States); Kumar, Sharvan [Brown Univ., Providence, RI (United States); Ghassemi-Armaki, Hassan [Brown Univ., Providence, RI (United States); Abu-Farha, Fadi [Clemson Univ., SC (United States)

    2015-06-15

    Ever-tightening regulations on fuel economy and carbon emissions demand continual innovation in finding ways for reducing vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials by adding material diversity, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing thickness while retaining sufficient strength and ductility required for durability and safety. Such a project was proposed and is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the Department of Energy. Under this program, new steel alloys (Third Generation Advanced High Strength Steel or 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. In this project the principal phases identified are (i) material identification, (ii) formability optimization and (iii) multi-disciplinary vehicle optimization. This paper serves as an introduction to the LS-OPT methodology and therefore mainly focuses on the first phase, namely an approach to integrate material identification using material models of different length scales. For this purpose, a multi-scale material identification strategy, consisting of a Crystal Plasticity (CP) material model and a Homogenized State Variable (SV) model, is discussed and demonstrated. The paper concludes with proposals for integrating the multi-scale methodology into the overall vehicle design.

  10. Multiscale Thermohydrologic Model Supporting the License Application for the Yucca Mountain Repository

    International Nuclear Information System (INIS)

    T.A. Buscheck; Y. Sun; Y. Hao

    2006-01-01

    The MultiScale ThermoHydrologic Model (MSTHM) predicts thermal-hydrologic (TH) conditions within emplacement tunnels (drifts) and in the adjoining host rock at Yucca Mountain, Nevada, which is the proposed site for a radioactive waste repository in the US. Because these predictions are used in the performance assessment of the Yucca Mountain repository, they must address the influence of variability and uncertainty of the engineered- and natural-system parameters that significantly influence those predictions. Parameter-sensitivity studies show that the MSTHM predictions adequately propagate the influence of parametric variability and uncertainty. Model-validation studies show that the influence of conceptual-model uncertainty on the MSTHM predictions is insignificant compared to that of parametric uncertainty, which is propagated through the MSTHM

  11. Integrated Multiscale Latent Variable Regression and Application to Distillation Columns

    Directory of Open Access Journals (Sweden)

    Muddu Madakyaru

    2013-01-01

    Full Text Available Proper control of distillation columns requires estimating some key variables that are challenging to measure online (such as compositions, which are usually estimated using inferential models. Commonly used inferential models include latent variable regression (LVR techniques, such as principal component regression (PCR, partial least squares (PLS, and regularized canonical correlation analysis (RCCA. Unfortunately, measured practical data are usually contaminated with errors, which degrade the prediction abilities of inferential models. Therefore, noisy measurements need to be filtered to enhance the prediction accuracy of these models. Multiscale filtering has been shown to be a powerful feature extraction tool. In this work, the advantages of multiscale filtering are utilized to enhance the prediction accuracy of LVR models by developing an integrated multiscale LVR (IMSLVR modeling algorithm that integrates modeling and feature extraction. The idea behind the IMSLVR modeling algorithm is to filter the process data at different decomposition levels, model the filtered data from each level, and then select the LVR model that optimizes a model selection criterion. The performance of the developed IMSLVR algorithm is illustrated using three examples, one using synthetic data, one using simulated distillation column data, and one using experimental packed bed distillation column data. All examples clearly demonstrate the effectiveness of the IMSLVR algorithm over the conventional methods.

  12. Multi-scale calculation based on dual domain material point method combined with molecular dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Dhakal, Tilak Raj [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-02-27

    computation. The numerical properties of the multiscale method are investigated as well as the results from this multi-scale calculation are compared of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the computation. The numerical properties of the multiscale method are investigated as well as the results from this multi-scale calculation are compared with direct MD simulation results to demonstrate the feasibility of the method. Also, the multi-scale method is applied for a two dimensional problem of jet formation around copper notch under a strong impact.

  13. Computational models of stellar collapse and core-collapse supernovae

    Energy Technology Data Exchange (ETDEWEB)

    Ott, Christian D; O' Connor, Evan [TAPIR, Mailcode 350-17, California Institute of Technology, Pasadena, CA (United States); Schnetter, Erik; Loeffler, Frank [Center for Computation and Technology, Louisiana State University, Baton Rouge, LA (United States); Burrows, Adam [Department of Astrophysical Sciences, Princeton University, Princeton, NJ (United States); Livne, Eli, E-mail: cott@tapir.caltech.ed [Racah Institute of Physics, Hebrew University, Jerusalem (Israel)

    2009-07-01

    Core-collapse supernovae are among Nature's most energetic events. They mark the end of massive star evolution and pollute the interstellar medium with the life-enabling ashes of thermonuclear burning. Despite their importance for the evolution of galaxies and life in the universe, the details of the core-collapse supernova explosion mechanism remain in the dark and pose a daunting computational challenge. We outline the multi-dimensional, multi-scale, and multi-physics nature of the core-collapse supernova problem and discuss computational strategies and requirements for its solution. Specifically, we highlight the axisymmetric (2D) radiation-MHD code VULCAN/2D and present results obtained from the first full-2D angle-dependent neutrino radiation-hydrodynamics simulations of the post-core-bounce supernova evolution. We then go on to discuss the new code Zelmani which is based on the open-source HPC Cactus framework and provides a scalable AMR approach for 3D fully general-relativistic modeling of stellar collapse, core-collapse supernovae and black hole formation on current and future massively-parallel HPC systems. We show Zelmani's scaling properties to more than 16,000 compute cores and discuss first 3D general-relativistic core-collapse results.

  14. A machine learning approach for efficient uncertainty quantification using multiscale methods

    Science.gov (United States)

    Chan, Shing; Elsheikh, Ahmed H.

    2018-02-01

    Several multiscale methods account for sub-grid scale features using coarse scale basis functions. For example, in the Multiscale Finite Volume method the coarse scale basis functions are obtained by solving a set of local problems over dual-grid cells. We introduce a data-driven approach for the estimation of these coarse scale basis functions. Specifically, we employ a neural network predictor fitted using a set of solution samples from which it learns to generate subsequent basis functions at a lower computational cost than solving the local problems. The computational advantage of this approach is realized for uncertainty quantification tasks where a large number of realizations has to be evaluated. We attribute the ability to learn these basis functions to the modularity of the local problems and the redundancy of the permeability patches between samples. The proposed method is evaluated on elliptic problems yielding very promising results.

  15. Multiscale simulation of molecular processes in cellular environments.

    Science.gov (United States)

    Chiricotto, Mara; Sterpone, Fabio; Derreumaux, Philippe; Melchionna, Simone

    2016-11-13

    We describe the recent advances in studying biological systems via multiscale simulations. Our scheme is based on a coarse-grained representation of the macromolecules and a mesoscopic description of the solvent. The dual technique handles particles, the aqueous solvent and their mutual exchange of forces resulting in a stable and accurate methodology allowing biosystems of unprecedented size to be simulated.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2016 The Author(s).

  16. Hybrid numerical methods for multiscale simulations of subsurface biogeochemical processes

    International Nuclear Information System (INIS)

    Scheibe, T D; Tartakovsky, A M; Tartakovsky, D M; Redden, G D; Meakin, P

    2007-01-01

    Many subsurface flow and transport problems of importance today involve coupled non-linear flow, transport, and reaction in media exhibiting complex heterogeneity. In particular, problems involving biological mediation of reactions fall into this class of problems. Recent experimental research has revealed important details about the physical, chemical, and biological mechanisms involved in these processes at a variety of scales ranging from molecular to laboratory scales. However, it has not been practical or possible to translate detailed knowledge at small scales into reliable predictions of field-scale phenomena important for environmental management applications. A large assortment of numerical simulation tools have been developed, each with its own characteristic scale. Important examples include 1. molecular simulations (e.g., molecular dynamics); 2. simulation of microbial processes at the cell level (e.g., cellular automata or particle individual-based models); 3. pore-scale simulations (e.g., lattice-Boltzmann, pore network models, and discrete particle methods such as smoothed particle hydrodynamics); and 4. macroscopic continuum-scale simulations (e.g., traditional partial differential equations solved by finite difference or finite element methods). While many problems can be effectively addressed by one of these models at a single scale, some problems may require explicit integration of models across multiple scales. We are developing a hybrid multi-scale subsurface reactive transport modeling framework that integrates models with diverse representations of physics, chemistry and biology at different scales (sub-pore, pore and continuum). The modeling framework is being designed to take advantage of advanced computational technologies including parallel code components using the Common Component Architecture, parallel solvers, gridding, data and workflow management, and visualization. This paper describes the specific methods/codes being used at each

  17. Transition between inverse and direct energy cascades in multiscale optical turbulence

    Science.gov (United States)

    Malkin, V. M.; Fisch, N. J.

    2018-03-01

    Multiscale turbulence naturally develops and plays an important role in many fluid, gas, and plasma phenomena. Statistical models of multiscale turbulence usually employ Kolmogorov hypotheses of spectral locality of interactions (meaning that interactions primarily occur between pulsations of comparable scales) and scale-invariance of turbulent pulsations. However, optical turbulence described by the nonlinear Schrodinger equation exhibits breaking of both the Kolmogorov locality and scale-invariance. A weaker form of spectral locality that holds for multi-scale optical turbulence enables a derivation of simplified evolution equations that reduce the problem to a single scale modeling. We present the derivation of these equations for Kerr media with random inhomogeneities. Then, we find the analytical solution that exhibits a transition between inverse and direct energy cascades in optical turbulence.

  18. Transition between inverse and direct energy cascades in multiscale optical turbulence.

    Science.gov (United States)

    Malkin, V M; Fisch, N J

    2018-03-01

    Multiscale turbulence naturally develops and plays an important role in many fluid, gas, and plasma phenomena. Statistical models of multiscale turbulence usually employ Kolmogorov hypotheses of spectral locality of interactions (meaning that interactions primarily occur between pulsations of comparable scales) and scale-invariance of turbulent pulsations. However, optical turbulence described by the nonlinear Schrodinger equation exhibits breaking of both the Kolmogorov locality and scale-invariance. A weaker form of spectral locality that holds for multi-scale optical turbulence enables a derivation of simplified evolution equations that reduce the problem to a single scale modeling. We present the derivation of these equations for Kerr media with random inhomogeneities. Then, we find the analytical solution that exhibits a transition between inverse and direct energy cascades in optical turbulence.

  19. Multiscale modeling of the influence of Fe content in a Al-Si-Cu alloy on the size distribution of intermetallic phases and micropores

    International Nuclear Information System (INIS)

    Wang Junsheng; Lee, Peter D.; Li Mei; Allison, John

    2010-01-01

    A multiscale model was developed to simulate the formation of Fe-rich intermetallics and pores in quaternary Al-Si-Cu-Fe alloys. At the microscale, the multicomponent diffusion equations were solved for multiphase (liquid-solid-gas) materials via a finite difference framework to predict microstructure formation. A fast and robust decentered plate algorithm was developed to simulate the strong anisotropy of the solid/liquid interfacial energy for the Fe-rich intermetallic phase. The growth of porosity was controlled by local pressure drop due to solidification and interactions with surrounding solid phases, in addition to hydrogen diffusion. The microscale model was implemented as a subroutine in a commercial finite element package, producing a coupled multiscale model. This allows the influence of varying casting conditions on the Fe-rich intermetallics, the pores, and their interactions to be predicted. Synchrotron x-ray tomography experiments were performed to validate the model by comparing the three-dimensional morphology and size distribution of Fe-rich intermetallics as a function of Fe content. Large platelike Fe-rich β intermetallics were successfully simulated by the multiscale model and their influence on pore size distribution in shape castings was predicted as a function of casting conditions.

  20. Development of porous structure simulator for multi-scale simulation of irregular porous catalysts

    International Nuclear Information System (INIS)

    Koyama, Michihisa; Suzuki, Ai; Sahnoun, Riadh; Tsuboi, Hideyuki; Hatakeyama, Nozomu; Endou, Akira; Takaba, Hiromitsu; Kubo, Momoji; Del Carpio, Carlos A.; Miyamoto, Akira

    2008-01-01

    Efficient development of highly functional porous materials, used as catalysts in the automobile industry, demands a meticulous knowledge of the nano-scale interface at the electronic and atomistic scale. However, it is often difficult to correlate the microscopic interfacial interactions with macroscopic characteristics of the materials; for instance, the interaction between a precious metal and its support oxide with long-term sintering properties of the catalyst. Multi-scale computational chemistry approaches can contribute to bridge the gap between micro- and macroscopic characteristics of these materials; however this type of multi-scale simulations has been difficult to apply especially to porous materials. To overcome this problem, we have developed a novel mesoscopic approach based on a porous structure simulator. This simulator can construct automatically irregular porous structures on a computer, enabling simulations with complex meso-scale structures. Moreover, in this work we have developed a new method to simulate long-term sintering properties of metal particles on porous catalysts. Finally, we have applied the method to the simulation of sintering properties of Pt on alumina support. This newly developed method has enabled us to propose a multi-scale simulation approach for porous catalysts