ANALYSIS OF MULTISCALE METHODS
Institute of Scientific and Technical Information of China (English)
Wei-nan E; Ping-bing Ming
2004-01-01
The heterogeneous multiscale method gives a general framework for the analysis of multiscale methods. In this paper, we demonstrate this by applying this framework to two canonical problems: The elliptic problem with multiscale coefficients and the quasicontinuum method.
Multiscale Signal Analysis and Modeling
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...
Multiscale analysis of neural spike trains.
Ramezan, Reza; Marriott, Paul; Chenouri, Shojaeddin
2014-01-30
This paper studies the multiscale analysis of neural spike trains, through both graphical and Poisson process approaches. We introduce the interspike interval plot, which simultaneously visualizes characteristics of neural spiking activity at different time scales. Using an inhomogeneous Poisson process framework, we discuss multiscale estimates of the intensity functions of spike trains. We also introduce the windowing effect for two multiscale methods. Using quasi-likelihood, we develop bootstrap confidence intervals for the multiscale intensity function. We provide a cross-validation scheme, to choose the tuning parameters, and study its unbiasedness. Studying the relationship between the spike rate and the stimulus signal, we observe that adjusting for the first spike latency is important in cross-validation. We show, through examples, that the correlation between spike trains and spike count variability can be multiscale phenomena. Furthermore, we address the modeling of the periodicity of the spike trains caused by a stimulus signal or by brain rhythms. Within the multiscale framework, we introduce intensity functions for spike trains with multiplicative and additive periodic components. Analyzing a dataset from the retinogeniculate synapse, we compare the fit of these models with the Bayesian adaptive regression splines method and discuss the limitations of the methodology. Computational efficiency, which is usually a challenge in the analysis of spike trains, is one of the highlights of these new models. In an example, we show that the reconstruction quality of a complex intensity function demonstrates the ability of the multiscale methodology to crack the neural code.
Numerical Analysis of Multiscale Computations
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.
Multiscale simulation of microbe structure and dynamics.
Joshi, Harshad; Singharoy, Abhishek; Sereda, Yuriy V; Cheluvaraja, Srinath C; Ortoleva, Peter J
2011-10-01
A multiscale mathematical and computational approach is developed that captures the hierarchical organization of a microbe. It is found that a natural perspective for understanding a microbe is in terms of a hierarchy of variables at various levels of resolution. This hierarchy starts with the N -atom description and terminates with order parameters characterizing a whole microbe. This conceptual framework is used to guide the analysis of the Liouville equation for the probability density of the positions and momenta of the N atoms constituting the microbe and its environment. Using multiscale mathematical techniques, we derive equations for the co-evolution of the order parameters and the probability density of the N-atom state. This approach yields a rigorous way to transfer information between variables on different space-time scales. It elucidates the interplay between equilibrium and far-from-equilibrium processes underlying microbial behavior. It also provides framework for using coarse-grained nanocharacterization data to guide microbial simulation. It enables a methodical search for free-energy minimizing structures, many of which are typically supported by the set of macromolecules and membranes constituting a given microbe. This suite of capabilities provides a natural framework for arriving at a fundamental understanding of microbial behavior, the analysis of nanocharacterization data, and the computer-aided design of nanostructures for biotechnical and medical purposes. Selected features of the methodology are demonstrated using our multiscale bionanosystem simulator DeductiveMultiscaleSimulator. Systems used to demonstrate the approach are structural transitions in the cowpea chlorotic mosaic virus, RNA of satellite tobacco mosaic virus, virus-like particles related to human papillomavirus, and iron-binding protein lactoferrin.
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.
Multivariate Generalized Multiscale Entropy Analysis
Directory of Open Access Journals (Sweden)
Anne Humeau-Heurtier
2016-11-01
Full Text Available Multiscale entropy (MSE was introduced in the 2000s to quantify systems’ complexity. MSE relies on (i a coarse-graining procedure to derive a set of time series representing the system dynamics on different time scales; (ii the computation of the sample entropy for each coarse-grained time series. A refined composite MSE (rcMSE—based on the same steps as MSE—also exists. Compared to MSE, rcMSE increases the accuracy of entropy estimation and reduces the probability of inducing undefined entropy for short time series. The multivariate versions of MSE (MMSE and rcMSE (MrcMSE have also been introduced. In the coarse-graining step used in MSE, rcMSE, MMSE, and MrcMSE, the mean value is used to derive representations of the original data at different resolutions. A generalization of MSE was recently published, using the computation of different moments in the coarse-graining procedure. However, so far, this generalization only exists for univariate signals. We therefore herein propose an extension of this generalized MSE to multivariate data. The multivariate generalized algorithms of MMSE and MrcMSE presented herein (MGMSE and MGrcMSE, respectively are first analyzed through the processing of synthetic signals. We reveal that MGrcMSE shows better performance than MGMSE for short multivariate data. We then study the performance of MGrcMSE on two sets of short multivariate electroencephalograms (EEG available in the public domain. We report that MGrcMSE may show better performance than MrcMSE in distinguishing different types of multivariate EEG data. MGrcMSE could therefore supplement MMSE or MrcMSE in the processing of multivariate datasets.
Multiscale statistical analysis of coronal solar activity
Gamborino, Diana; Martinell, Julio J
2016-01-01
Multi-filter images from the solar corona are used to obtain temperature maps which are analyzed using techniques based on proper orthogonal decomposition (POD) in order to extract dynamical and structural information at various scales. Exploring active regions before and after a solar flare and comparing them with quiet regions we show that the multiscale behavior presents distinct statistical properties for each case that can be used to characterize the level of activity in a region. Information about the nature of heat transport is also be extracted from the analysis.
Multiscale Analysis of Heterogeneous Media in the Peridynamic Formulation
2009-10-28
Bond Model 41 6.1 Existence and Uniqueness Results . . . . . . . . . . . . . . . . . . . . . . . . 43 6.2 Multiscale Analysis Using the Semigroups ... Semigroup theory provides a strong approximation for capturing the mirco-level fluctuations about the macroscopic displacement field. The multiscale...third model, the Semigroup theory of linear operators [12, 13] is utilized to identify both the macroscopic and microscopic dynamics of the composite
Numerical methods and analysis of multiscale problems
Madureira, Alexandre L
2017-01-01
This book is about numerical modeling of multiscale problems, and introduces several asymptotic analysis and numerical techniques which are necessary for a proper approximation of equations that depend on different physical scales. Aimed at advanced undergraduate and graduate students in mathematics, engineering and physics – or researchers seeking a no-nonsense approach –, it discusses examples in their simplest possible settings, removing mathematical hurdles that might hinder a clear understanding of the methods. The problems considered are given by singular perturbed reaction advection diffusion equations in one and two-dimensional domains, partial differential equations in domains with rough boundaries, and equations with oscillatory coefficients. This work shows how asymptotic analysis can be used to develop and analyze models and numerical methods that are robust and work well for a wide range of parameters.
Scheibe, Timothy D; Murphy, Ellyn M; Chen, Xingyuan; Rice, Amy K; Carroll, Kenneth C; Palmer, Bruce J; Tartakovsky, Alexandre M; Battiato, Ilenia; Wood, Brian D
2015-01-01
One of the most significant challenges faced by hydrogeologic modelers is the disparity between the spatial and temporal scales at which fundamental flow, transport, and reaction processes can best be understood and quantified (e.g., microscopic to pore scales and seconds to days) and at which practical model predictions are needed (e.g., plume to aquifer scales and years to centuries). While the multiscale nature of hydrogeologic problems is widely recognized, technological limitations in computation and characterization restrict most practical modeling efforts to fairly coarse representations of heterogeneous properties and processes. For some modern problems, the necessary level of simplification is such that model parameters may lose physical meaning and model predictive ability is questionable for any conditions other than those to which the model was calibrated. Recently, there has been broad interest across a wide range of scientific and engineering disciplines in simulation approaches that more rigorously account for the multiscale nature of systems of interest. In this article, we review a number of such approaches and propose a classification scheme for defining different types of multiscale simulation methods and those classes of problems to which they are most applicable. Our classification scheme is presented in terms of a flowchart (Multiscale Analysis Platform), and defines several different motifs of multiscale simulation. Within each motif, the member methods are reviewed and example applications are discussed. We focus attention on hybrid multiscale methods, in which two or more models with different physics described at fundamentally different scales are directly coupled within a single simulation. Very recently these methods have begun to be applied to groundwater flow and transport simulations, and we discuss these applications in the context of our classification scheme. As computational and characterization capabilities continue to improve
Development of multiscale analysis and some applications
Wang, Lipo
2014-11-01
For most complex systems the interaction of different scales is among the most interesting and challenging features. Typically different scale regimes have different physical properties. The commonly used analysis approaches such as structure function and Fourier analysis have their respective limitations, for instance the mixing of large and small scale information, i.e. the so-called infrared and ultraviolet effects. To make improvement in this regard, a new method, segment structure analysis (SSA), has been developed to study the multiscale statistics. Such method can detect the regime scaling based on the conditional extremal points, depicting the geometrical features directly in physical space. From standard test cases (e.g. fractal Brownian motion) to real turbulence data, results show that SSA can appropriately distinguish the different scale effects. A successful application is the scaling of the Lagrangian velocity structure function. This long-time controversial topic has been confirmed using the present method. In principle SSA can generally be applied to various problems.
Multiscale Methods for Nuclear Reactor Analysis
Collins, Benjamin S.
The ability to accurately predict local pin powers in nuclear reactors is necessary to understand the mechanisms that cause fuel pin failure during steady state and transient operation. In the research presented here, methods are developed to improve the local solution using high order methods with boundary conditions from a low order global solution. Several different core configurations were tested to determine the improvement in the local pin powers compared to the standard techniques, that use diffusion theory and pin power reconstruction (PPR). Two different multiscale methods were developed and analyzed; the post-refinement multiscale method and the embedded multiscale method. The post-refinement multiscale methods use the global solution to determine boundary conditions for the local solution. The local solution is solved using either a fixed boundary source or an albedo boundary condition; this solution is "post-refinement" and thus has no impact on the global solution. The embedded multiscale method allows the local solver to change the global solution to provide an improved global and local solution. The post-refinement multiscale method is assessed using three core designs. When the local solution has more energy groups, the fixed source method has some difficulties near the interface: however the albedo method works well for all cases. In order to remedy the issue with boundary condition errors for the fixed source method, a buffer region is used to act as a filter, which decreases the sensitivity of the solution to the boundary condition. Both the albedo and fixed source methods benefit from the use of a buffer region. Unlike the post-refinement method, the embedded multiscale method alters the global solution. The ability to change the global solution allows for refinement in areas where the errors in the few group nodal diffusion are typically large. The embedded method is shown to improve the global solution when it is applied to a MOX/LEU assembly
Discrete Multiscale Analysis: A Biatomic Lattice System
Contra, G A Cassatella; 10.1142/S1402925110000957
2010-01-01
We discuss a discrete approach to the multiscale reductive perturbative method and apply it to a biatomic chain with a nonlinear interaction between the atoms. This system is important to describe the time evolution of localized solitonic excitations. We require that also the reduced equation be discrete. To do so coherently we need to discretize the time variable to be able to get asymptotic discrete waves and carry out a discrete multiscale expansion around them. Our resulting nonlinear equation will be a kind of discrete Nonlinear Schr\\"odinger equation. If we make its continuum limit, we obtain the standard Nonlinear Schr\\"odinger differential equation.
Objective multiscale analysis of random heterogeneous materials
Lloberas Valls, O.; Everdij, F.P.X.; Rixen, D.J.; Simone, A.; Sluys, L.J.
2013-01-01
The multiscale framework presented in [1, 2] is assessed in this contribution for a study of random heterogeneous materials. Results are compared to direct numerical simulations (DNS) and the sensitivity to user-defined parameters such as the domain decomposition type and initial coarse scale resolu
Multiscale Analysis and Optimisation of Photosynthetic Solar Energy Systems
Ringsmuth, Andrew K
2014-01-01
This work asks how light harvesting in photosynthetic systems can be optimised for economically scalable, sustainable energy production. Hierarchy theory is introduced as a system-analysis and optimisation tool better able to handle multiscale, multiprocess complexities in photosynthetic energetics compared with standard linear-process analysis. Within this framework, new insights are given into relationships between composition, structure and energetics at the scale of the thylakoid membrane, and also into how components at different scales cooperate under functional objectives of the whole photosynthetic system. Combining these reductionistic and holistic analyses creates a platform for modelling multiscale-optimal, idealised photosynthetic systems in silico.
Multiscale multifractal time irreversibility analysis of stock markets
Jiang, Chenguang; Shang, Pengjian; Shi, Wenbin
2016-11-01
Time irreversibility is one of the most important properties of nonstationary time series. Complex time series often demonstrate even multiscale time irreversibility, such that not only the original but also coarse-grained time series are asymmetric over a wide range of scales. We study the multiscale time irreversibility of time series. In this paper, we develop a method called multiscale multifractal time irreversibility analysis (MMRA), which allows us to extend the description of time irreversibility to include the dependence on the segment size and statistical moments. We test the effectiveness of MMRA in detecting multifractality and time irreversibility of time series generated from delayed Henon map and binomial multifractal model. Then we employ our method to the time irreversibility analysis of stock markets in different regions. We find that the emerging market has higher multifractality degree and time irreversibility compared with developed markets. In this sense, the MMRA method may provide new angles in assessing the evolution stage of stock markets.
Multiscale feature analysis of salivary gland branching morphogenesis.
Directory of Open Access Journals (Sweden)
Cemal Cagatay Bilgin
Full Text Available Pattern formation in developing tissues involves dynamic spatio-temporal changes in cellular organization and subsequent evolution of functional adult structures. Branching morphogenesis is a developmental mechanism by which patterns are generated in many developing organs, which is controlled by underlying molecular pathways. Understanding the relationship between molecular signaling, cellular behavior and resulting morphological change requires quantification and categorization of the cellular behavior. In this study, tissue-level and cellular changes in developing salivary gland in response to disruption of ROCK-mediated signaling by are modeled by building cell-graphs to compute mathematical features capturing structural properties at multiple scales. These features were used to generate multiscale cell-graph signatures of untreated and ROCK signaling disrupted salivary gland organ explants. From confocal images of mouse submandibular salivary gland organ explants in which epithelial and mesenchymal nuclei were marked, a multiscale feature set capturing global structural properties, local structural properties, spectral, and morphological properties of the tissues was derived. Six feature selection algorithms and multiway modeling of the data was performed to identify distinct subsets of cell graph features that can uniquely classify and differentiate between different cell populations. Multiscale cell-graph analysis was most effective in classification of the tissue state. Cellular and tissue organization, as defined by a multiscale subset of cell-graph features, are both quantitatively distinct in epithelial and mesenchymal cell types both in the presence and absence of ROCK inhibitors. Whereas tensor analysis demonstrate that epithelial tissue was affected the most by inhibition of ROCK signaling, significant multiscale changes in mesenchymal tissue organization were identified with this analysis that were not identified in previous
Multiscale Analysis of Information Dynamics for Linear Multivariate Processes
Faes, Luca; Stramaglia, Sebastiano; Nollo, Giandomenico; Stramaglia, Sebastiano
2016-01-01
In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving average (MA) component, we describe how to represent the resulting VARMA process using state-space (SS) models and how to exploit the SS model parameters to compute analytical measures of information storage and information transfer for the original and rescaled processes. The framework is then used to quantify multiscale infor...
Multiscale analysis of structure development in expanded starch snacks
Sman, van der R.G.M.; Broeze, J.
2014-01-01
In this paper we perform a multiscale analysis of the food structuring process of the expansion of starchy snack foods like keropok, which obtains a solid foam structure. In particular, we want to investigate the validity of the hypothesis of Kokini and coworkers, that expansion is optimal at the mo
Entropic Approach to Multiscale Clustering Analysis
Directory of Open Access Journals (Sweden)
Antonio Insolia
2012-05-01
Full Text Available Recently, a novel method has been introduced to estimate the statistical significance of clustering in the direction distribution of objects. The method involves a multiscale procedure, based on the Kullback–Leibler divergence and the Gumbel statistics of extreme values, providing high discrimination power, even in presence of strong background isotropic contamination. It is shown that the method is: (i semi-analytical, drastically reducing computation time; (ii very sensitive to small, medium and large scale clustering; (iii not biased against the null hypothesis. Applications to the physics of ultra-high energy cosmic rays, as a cosmological probe, are presented and discussed.
Multiscale characterization and analysis of shapes
Prasad, Lakshman; Rao, Ramana
2002-01-01
An adaptive multiscale method approximates shapes with continuous or uniformly and densely sampled contours, with the purpose of sparsely and nonuniformly discretizing the boundaries of shapes at any prescribed resolution, while at the same time retaining the salient shape features at that resolution. In another aspect, a fundamental geometric filtering scheme using the Constrained Delaunay Triangulation (CDT) of polygonized shapes creates an efficient parsing of shapes into components that have semantic significance dependent only on the shapes' structure and not on their representations per se. A shape skeletonization process generalizes to sparsely discretized shapes, with the additional benefit of prunability to filter out irrelevant and morphologically insignificant features. The skeletal representation of characters of varying thickness and the elimination of insignificant and noisy spurs and branches from the skeleton greatly increases the robustness, reliability and recognition rates of character recognition algorithms.
Lifetime statistics of quantum chaos studied by a multiscale analysis
Di Falco, A.
2012-04-30
In a series of pump and probe experiments, we study the lifetime statistics of a quantum chaotic resonator when the number of open channels is greater than one. Our design embeds a stadium billiard into a two dimensional photonic crystal realized on a silicon-on-insulator substrate. We calculate resonances through a multiscale procedure that combines energy landscape analysis and wavelet transforms. Experimental data is found to follow the universal predictions arising from random matrix theory with an excellent level of agreement.
Complexity of carbon market from multi-scale entropy analysis
Fan, Xinghua; Li, Shasha; Tian, Lixin
2016-06-01
Complexity of carbon market is the consequence of economic dynamics and extreme social political events in global carbon markets. The multi-scale entropy can measure the long-term structures in the daily price return time series. By using multi-scale entropy analysis, we explore the complexity of carbon market and mean reversion trend of daily price return. The logarithmic difference of data Dec16 from August 6, 2010 to May 22, 2015 is selected as the sample. The entropy is higher in small time scale, while lower in large. The dependence of the entropy on the time scale reveals the mean reversion of carbon prices return in the long run. A relatively great fluctuation over some short time period indicates that the complexity of carbon market evolves consistently with economic development track and the events of international climate conferences.
Multi-scale statistical analysis of coronal solar activity
Gamborino, Diana; del-Castillo-Negrete, Diego; Martinell, Julio J.
2016-07-01
Multi-filter images from the solar corona are used to obtain temperature maps that are analyzed using techniques based on proper orthogonal decomposition (POD) in order to extract dynamical and structural information at various scales. Exploring active regions before and after a solar flare and comparing them with quiet regions, we show that the multi-scale behavior presents distinct statistical properties for each case that can be used to characterize the level of activity in a region. Information about the nature of heat transport is also to be extracted from the analysis.
Engineering Complex Systems: Multiscale Analysis and Evolutionary Engineering
Bar-Yam, Yaneer
We describe an analytic approach, multiscale analysis, that can demonstrate the fundamental limitations of decomposition based engineering for the development of highly complex systems. The interdependence of components and communication between design teams limits any planning based process. Recognizing this limitation, we found that a new strategy for constructing many highly complex systems should be modeled after biological evolution, or market economies, where multiple design efforts compete in parallel for adoption through testing in actual use. Evolution is the only process that is known to create highly complex systems.
Multiscale recurrence analysis of spatio-temporal data
Riedl, M.; Marwan, N.; Kurths, J.
2015-12-01
The description and analysis of spatio-temporal dynamics is a crucial task in many scientific disciplines. In this work, we propose a method which uses the mapogram as a similarity measure between spatially distributed data instances at different time points. The resulting similarity values of the pairwise comparison are used to construct a recurrence plot in order to benefit from established tools of recurrence quantification analysis and recurrence network analysis. In contrast to other recurrence tools for this purpose, the mapogram approach allows the specific focus on different spatial scales that can be used in a multi-scale analysis of spatio-temporal dynamics. We illustrate this approach by application on mixed dynamics, such as traveling parallel wave fronts with additive noise, as well as more complicate examples, pseudo-random numbers and coupled map lattices with a semi-logistic mapping rule. Especially the complicate examples show the usefulness of the multi-scale consideration in order to take spatial pattern of different scales and with different rhythms into account. So, this mapogram approach promises new insights in problems of climatology, ecology, or medicine.
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
Multiscale Analysis of Pebble Bed Reactors
Energy Technology Data Exchange (ETDEWEB)
Hans Gougar; Woo Yoon; Abderrafi Ougouag
2010-10-01
– The PEBBED code was developed at the Idaho National Laboratory for design and analysis of pebble-bed high temperature reactors. The diffusion-depletion-pebble-mixing algorithm of the original PEBBED code was enhanced through coupling with the THERMIX-KONVEK code for thermal fluid analysis and by the COMBINE code for online cross section generation. The COMBINE code solves the B-1 or B-3 approximations to the transport equation for neutron slowing down and resonance interactions in a homogeneous medium with simple corrections for shadowing and thermal self-shielding. The number densities of materials within specified regions of the core are averaged and transferred to COMBINE from PEBBED for updating during the burnup iteration. The simple treatment of self-shielding in previous versions of COMBINE led to inaccurate results for cross sections and unsatisfactory core performance calculations. A new version of COMBINE has been developed that treats all levels of heterogeneity using the 1D transport code ANISN. In a 3-stage calculation, slowing down is performed in 167 groups for each homogeneous subregion (kernel, particle layers, graphite shell, control rod absorber annulus, etc.) Particles in a local average pebble are homogenized using ANISN then passed to the next (pebble) stage. A 1D transport solution is again performed over the pebble geometry and the homogenized pebble cross sections are passed to a 1-d radial model of a wedge of the pebble bed core. This wedge may also include homogeneous reflector regions and a control rod region composed of annuli of different absorbing regions. Radial leakage effects are therefore captured with discrete ordinates transport while axial and azimuthal effects are captured with a transverse buckling term. In this paper, results of various PBR models will be compared with comparable models from literature. Performance of the code will be assessed.
Multiscale analysis of damage using dual and primal domain decomposition techniques
Lloberas-Valls, O.; Everdij, F.P.X.; Rixen, D.J.; Simone, A.; Sluys, L.J.
2014-01-01
In this contribution, dual and primal domain decomposition techniques are studied for the multiscale analysis of failure in quasi-brittle materials. The multiscale strategy essentially consists in decomposing the structure into a number of nonoverlapping domains and considering a refined spatial res
Multiscale analysis of the CMB temperature derivatives
Marcos-Caballero, A.; Martínez-González, E.; Vielva, P.
2017-02-01
We study the Planck CMB temperature at different scales through its derivatives up to second order, which allows one to characterize the local shape and isotropy of the field. The problem of having an incomplete sky in the calculation and statistical characterization of the derivatives is addressed in the paper. The analysis confirms the existence of a low variance in the CMB at large scales, which is also noticeable in the derivatives. Moreover, deviations from the standard model in the gradient, curvature and the eccentricity tensor are studied in terms of extreme values on the data. As it is expected, the Cold Spot is detected as one of the most prominent peaks in terms of curvature, but additionally, when the information of the temperature and its Laplacian are combined, another feature with similar probability at the scale of 10o is also observed. However, the p-value of these two deviations increase above the 6% when they are referred to the variance calculated from the theoretical fiducial model, indicating that these deviations can be associated to the low variance anomaly. Finally, an estimator of the directional anisotropy for spinorial quantities is introduced, which is applied to the spinors derived from the field derivatives. An anisotropic direction whose probability is <1% is detected in the eccentricity tensor.
Big data-enabled multiscale serviceability analysis for aging bridges☆
Directory of Open Access Journals (Sweden)
Yu Liang
2016-08-01
Full Text Available This work is dedicated to constructing a multi-scale structural health monitoring system to monitor and evaluate the serviceability of bridges based on the Hadoop Ecosystem (MS-SHM-Hadoop. By taking the advantages of the fault-tolerant distributed file system called the Hadoop Distributed File System (HDFS and high-performance parallel data processing engine called MapReduce programming paradigm, MS-SHM-Hadoop features include high scalability and robustness in data ingestion, fusion, processing, retrieval, and analytics. MS-SHM-Hadoop is a multi-scale reliability analysis framework, which ranges from nationwide bridge-surveys, global structural integrity analysis, and structural component reliability analysis. This Nationwide bridge survey uses deep-learning techniques to evaluate the bridge serviceability according to real-time sensory data or archived bridge-related data such as traffic status, weather conditions and bridge structural configuration. The global structural integrity analysis of a targeted bridge is made by processing and analyzing the measured vibration signals incurred by external loads such as wind and traffic flow. Component-wise reliability analysis is also enabled by the deep learning technique, where the input data is derived from the measured structural load effects, hyper-spectral images, and moisture measurement of the structural components. As one of its major contributions, this work employs a Bayesian network to formulate the integral serviceability of a bridge according to its components serviceability and inter-component correlations. Here the inter-component correlations are jointly specified using a statistics-oriented machine learning method (e.g., association rule learning or structural mechanics modeling and simulation.
Multiscale recurrence quantification analysis of order recurrence plots
Xu, Mengjia; Shang, Pengjian; Lin, Aijing
2017-03-01
In this paper, we propose a new method of multiscale recurrence quantification analysis (MSRQA) to analyze the structure of order recurrence plots. The MSRQA is based on order patterns over a range of time scales. Compared with conventional recurrence quantification analysis (RQA), the MSRQA can show richer and more recognizable information on the local characteristics of diverse systems which successfully describes their recurrence properties. Both synthetic series and stock market indexes exhibit their properties of recurrence at large time scales that quite differ from those at a single time scale. Some systems present more accurate recurrence patterns under large time scales. It demonstrates that the new approach is effective for distinguishing three similar stock market systems and showing some inherent differences.
Bednarcyk, Brett A.; Arnold, Steven M.
2012-01-01
A framework for the multiscale design and analysis of composite materials and structures is presented. The ImMAC software suite, developed at NASA Glenn Research Center, embeds efficient, nonlinear micromechanics capabilities within higher scale structural analysis methods such as finite element analysis. The result is an integrated, multiscale tool that relates global loading to the constituent scale, captures nonlinearities at this scale, and homogenizes local nonlinearities to predict their effects at the structural scale. Example applications of the multiscale framework are presented for the stochastic progressive failure of a SiC/Ti composite tensile specimen and the effects of microstructural variations on the nonlinear response of woven polymer matrix composites.
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.
Multiscale Asymptotic Analysis and Parallel Algorithm of Parabolic Equation in Composite Materials
Directory of Open Access Journals (Sweden)
Xin Wang
2014-01-01
Full Text Available An efficient parallel multiscale numerical algorithm is proposed for a parabolic equation with rapidly oscillating coefficients representing heat conduction in composite material with periodic configuration. Instead of following the classical multiscale asymptotic expansion method, the Fourier transform in time is first applied to obtain a set of complex-valued elliptic problems in frequency domain. The multiscale asymptotic analysis is presented and multiscale asymptotic solutions are obtained in frequency domain which can be solved in parallel essentially without data communications. The inverse Fourier transform will then recover the approximate solution in time domain. Convergence result is established. Finally, a novel parallel multiscale FEM algorithm is proposed and some numerical examples are reported.
Multi-Scale Analysis Based Curve Feature Extraction in Reverse Engineering
Institute of Scientific and Technical Information of China (English)
YANG Hongjuan; ZHOU Yiqi; CHEN Chengjun; ZHAO Zhengxu
2006-01-01
A sectional curve feature extraction algorithm based on multi-scale analysis is proposed for reverse engineering. The algorithm consists of two parts: feature segmentation and feature classification. In the first part, curvature scale space is applied to multi-scale analysis and original feature detection. To obtain the primary and secondary curve primitives, feature fusion is realized by multi-scale feature detection information transmission. In the second part: projection height function is presented based on the area of quadrilateral, which improved criterions of sectional curve feature classification. Results of synthetic curves and practical scanned sectional curves are given to illustrate the efficiency of the proposed algorithm on feature extraction. The consistence between feature extraction based on multi-scale curvature analysis and curve primitives is verified.
Ontology-based analysis of multi-scale modeling of geographical features
Institute of Scientific and Technical Information of China (English)
WANG; Yanhui; LI; Xiaojuan; GONG; Huili
2006-01-01
As multi-scale databases based on scale series of map data are built, conceptual models are needed to define proper multi-scale representation formulas and to extract model entities and the relationships among them. However, the results of multi-scale conceptual abstraction schema may differ, according to which cognition, abstraction and application views are utilized, which presents an obvious obstacle to the reuse and sharing of spatial data. To facilitate the design of unified, common and objective abstract schema views for multi-scale spatial databases, this paper proposes an ontology-based analysis method for the multi-scale modeling of geographical features. It includes a three-layer ontology model, which serves as the framework for common multi-scale abstraction schema; an explanation of formulary abstractions accompanied by definitions of entities and their relationships at the same scale, as well as different scales,which are meant to provide strong feasibility, expansibility and speciality functions; and a case in point involving multi-scale representations of road features, to verify the method's feasibility.
Multiscale Modeling Methods for Analysis of Failure Modes in Foldcore Sandwich Panels
Sturm, R.; Schatrow, P.; Klett, Y.
2015-12-01
The paper presents an homogenised core model suitable for use in the analysis of fuselage sandwich panels with folded composite cores under combined loading conditions. Within a multiscale numerical design process a failure criterion was derived for describing the macroscopic behaviour of folded cores under combined loading using a detailed foldcore micromodel. The multiscale modelling method was validated by simulation of combined compression/bending failure of foldcore sandwich panels.
Multiscale Analysis of the Predictability of Stock Returns
Directory of Open Access Journals (Sweden)
Paweł Fiedor
2015-06-01
Full Text Available Due to the strong complexity of financial markets, economics does not have a unified theory of price formation in financial markets. The most common assumption is the Efficient-Market Hypothesis, which has been attacked by a number of researchers, using different tools. There were varying degrees to which these tools complied with the formal definitions of efficiency and predictability. In our earlier work, we analysed the predictability of stock returns at two time scales using the entropy rate, which can be directly linked to the mathematical definition of predictability. Nonetheless, none of the above-mentioned studies allow any general understanding of how the financial markets work, beyond disproving the Efficient-Market Hypothesis. In our previous study, we proposed the Maximum Entropy Production Principle, which uses the entropy rate to create a general principle underlying the price formation processes. Both of these studies show that the predictability of price changes is higher at the transaction level intraday scale than the scale of daily returns, but ignore all scales in between. In this study we extend these ideas using the multiscale entropy analysis framework to enhance our understanding of the predictability of price formation processes at various time scales.
Design and Analysis of a Multiscale Active Queue Management Scheme
Institute of Scientific and Technical Information of China (English)
Qi-Jin Ji; Yong-Qiang Dong
2006-01-01
Since Internet is dominated by TCP-based applications, active queue management (AQM) is considered as an effective way for congestion control. However, most AQM schemes suffer obvious performance degradation with dynamic traffic. Extensive measurements found that Internet traffic is extremely bursty and possibly self-similar. We propose in this paper a new AQM scheme called multiscale controller (MSC) based on the understanding of traffic burstiness in multiple time scale. Different from most of other AQM schemes, MSC combines rate-based and queue-based control in two time scales. While the rate-based dropping on burst level (large time scales) determines the packet drop aggressiveness and is responsible for low and stable queuing delay, good robustness and responsiveness, the queue-based modulation of the packet drop probability on packet level (small time scales) will bring low loss and high throughput. Stability analysis is performed based on a fluid-flow model of the TCP/MSC congestion control system and simulation results show that MSC outperforms many of the current AQM schemes.
Magnetospheric Multiscale (MMS) Mission Commissioning Phase Orbit Determination Error Analysis
Chung, Lauren R.; Novak, Stefan; Long, Anne; Gramling, Cheryl
2009-01-01
The Magnetospheric MultiScale (MMS) mission commissioning phase starts in a 185 km altitude x 12 Earth radii (RE) injection orbit and lasts until the Phase 1 mission orbits and orientation to the Earth-Sun li ne are achieved. During a limited time period in the early part of co mmissioning, five maneuvers are performed to raise the perigee radius to 1.2 R E, with a maneuver every other apogee. The current baseline is for the Goddard Space Flight Center Flight Dynamics Facility to p rovide MMS orbit determination support during the early commissioning phase using all available two-way range and Doppler tracking from bo th the Deep Space Network and Space Network. This paper summarizes th e results from a linear covariance analysis to determine the type and amount of tracking data required to accurately estimate the spacecraf t state, plan each perigee raising maneuver, and support thruster cal ibration during this phase. The primary focus of this study is the na vigation accuracy required to plan the first and the final perigee ra ising maneuvers. Absolute and relative position and velocity error hi stories are generated for all cases and summarized in terms of the ma ximum root-sum-square consider and measurement noise error contributi ons over the definitive and predictive arcs and at discrete times inc luding the maneuver planning and execution times. Details of the meth odology, orbital characteristics, maneuver timeline, error models, and error sensitivities are provided.
Multi-scale analysis for random quantum systems with interaction
Chulaevsky, Victor
2014-01-01
The study of quantum disorder has generated considerable research activity in mathematics and physics over past 40 years. While single-particle models have been extensively studied at a rigorous mathematical level, little was known about systems of several interacting particles, let alone systems with positive spatial particle density. Creating a consistent theory of disorder in multi-particle quantum systems is an important and challenging problem that largely remains open. Multi-scale Analysis for Random Quantum Systems with Interaction presents the progress that had been recently achieved in this area. The main focus of the book is on a rigorous derivation of the multi-particle localization in a strong random external potential field. To make the presentation accessible to a wider audience, the authors restrict attention to a relatively simple tight-binding Anderson model on a cubic lattice Zd. This book includes the following cutting-edge features: * an introduction to the state-of-the-art single-...
Multiscale Detrended Cross-Correlation Analysis of STOCK Markets
Yin, Yi; Shang, Pengjian
2014-06-01
In this paper, we employ the detrended cross-correlation analysis (DCCA) to investigate the cross-correlations between different stock markets. We report the results of cross-correlated behaviors in US, Chinese and European stock markets in period 1997-2012 by using DCCA method. The DCCA shows the cross-correlated behaviors of intra-regional and inter-regional stock markets in the short and long term which display the similarities and differences of cross-correlated behaviors simply and roughly and the persistence of cross-correlated behaviors of fluctuations. Then, because of the limitation and inapplicability of DCCA method, we propose multiscale detrended cross-correlation analysis (MSDCCA) method to avoid "a priori" selecting the ranges of scales over which two coefficients of the classical DCCA method are identified, and employ MSDCCA to reanalyze these cross-correlations to exhibit some important details such as the existence and position of minimum, maximum and bimodal distribution which are lost if the scale structure is described by two coefficients only and essential differences and similarities in the scale structures of cross-correlation of intra-regional and inter-regional markets. More statistical characteristics of cross-correlation obtained by MSDCCA method help us to understand how two different stock markets influence each other and to analyze the influence from thus two inter-regional markets on the cross-correlation in detail, thus we get a richer and more detailed knowledge of the complex evolutions of dynamics of the cross-correlations between stock markets. The application of MSDCCA is important to promote our understanding of the internal mechanisms and structures of financial markets and helps to forecast the stock indices based on our current results demonstrated the cross-correlations between stock indices. We also discuss the MSDCCA methods of secant rolling window with different sizes and, lastly, provide some relevant implications and
Multi-scale analysis of lung computed tomography images
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.
Multi-scale symbolic time reverse analysis of gas-liquid two-phase flow structures
Wang, Hongmei; Zhai, Lusheng; Jin, Ningde; Wang, Youchen
Gas-liquid two-phase flows are widely encountered in production processes of petroleum and chemical industry. Understanding the dynamic characteristics of multi-scale gas-liquid two-phase flow structures is of great significance for the optimization of production process and the measurement of flow parameters. In this paper, we propose a method of multi-scale symbolic time reverse (MSTR) analysis for gas-liquid two-phase flows. First, through extracting four time reverse asymmetry measures (TRAMs), i.e. Euclidean distance, difference entropy, percentage of constant words and percentage of reversible words, the time reverse asymmetry (TRA) behaviors of typical nonlinear systems are investigated from the perspective of multi-scale analysis, and the results show that the TRAMs are sensitive to the changing of dynamic characteristics underlying the complex nonlinear systems. Then, the MSTR analysis is used to study the conductance signals from gas-liquid two-phase flows. It is found that the multi-scale TRA analysis can effectively reveal the multi-scale structure characteristics and nonlinear evolution properties of the flow structures.
Radiation induced genome instability: multiscale modelling and data analysis
Andreev, Sergey; Eidelman, Yuri
2012-07-01
Genome instability (GI) is thought to be an important step in cancer induction and progression. Radiation induced GI is usually defined as genome alterations in the progeny of irradiated cells. The aim of this report is to demonstrate an opportunity for integrative analysis of radiation induced GI on the basis of multiscale modelling. Integrative, systems level modelling is necessary to assess different pathways resulting in GI in which a variety of genetic and epigenetic processes are involved. The multilevel modelling includes the Monte Carlo based simulation of several key processes involved in GI: DNA double strand breaks (DSBs) generation in cells initially irradiated as well as in descendants of irradiated cells, damage transmission through mitosis. Taking the cell-cycle-dependent generation of DNA/chromosome breakage into account ensures an advantage in estimating the contribution of different DNA damage response pathways to GI, as to nonhomologous vs homologous recombination repair mechanisms, the role of DSBs at telomeres or interstitial chromosomal sites, etc. The preliminary estimates show that both telomeric and non-telomeric DSB interactions are involved in delayed effects of radiation although differentially for different cell types. The computational experiments provide the data on the wide spectrum of GI endpoints (dicentrics, micronuclei, nonclonal translocations, chromatid exchanges, chromosome fragments) similar to those obtained experimentally for various cell lines under various experimental conditions. The modelling based analysis of experimental data demonstrates that radiation induced GI may be viewed as processes of delayed DSB induction/interaction/transmission being a key for quantification of GI. On the other hand, this conclusion is not sufficient to understand GI as a whole because factors of DNA non-damaging origin can also induce GI. Additionally, new data on induced pluripotent stem cells reveal that GI is acquired in normal mature
Advances in multiscale theoretical analysis and imaging aspects of turbulence
Shockro, Jennifer
The work presented in this dissertation is focused on two aspects related to turbulent flow. The first of these is the one-dimensional theoretical analysis of the logarithmic spiral in terms of fractal dimension and spectrum. The second is on imaging methodologies and analysis of turbulent jet scalar interfaces in atmospheric conditions, with broad applicability to various studies where turbulence has a key role, such as urban contaminant dispersion or free space laser communications. The logarithmic spiral is of particular interest to studies of turbulence and natural phenomena as it appears frequently in nature with the "Golden Ratio" and is thought to play an important role in turbulent mixing. It is also an inherently anisotropic geometric structure and therefore provides information towards examining phenomena in which anisotropic properties might be expected to appear and is thought to be present as a structure within the fine scales of the turbulent hierarchy. In this work it is subjected to one-dimensional theoretical analysis, focusing on the development of a probability density function (pdf) for the spiral and the relation of the pdf to its fractal dimension. Results indicate that the logarithmic spiral does not have a constant fractal dimension and thus that it does not exhibit any form of self-similar statistical behavior, supporting previous theoretical suppositions about behavior at the fine scales within the turbulent hierarchy. A signal is developed from the pdf in order to evaluate its power spectrum. Results of this analysis provide information about the manner in which energy is carried at different scales of the spiral. To our knowledge, the logarithmic spiral in particular has not yet been examined in this fashion in literature. In order to further investigate this object, the multiscale minima meshless (M(3) ) method isextended and employed computationally to the two-dimensional logarithmic spiral as well as to experimental images of a
Higher-Dimensional Signal Processing via Multiscale Geometric Analysis
2010-02-10
1.1 Review of motivation Over the past twenty years multiscale methods like the discrete wavelet transform (DWT) have revolutionized signal processing...sparsity and structure boost the performance of wavelet -domain statistical models and enable simple yet powerful algorithms for estimation/ denoising ...for many state-of-the-art wavelet domain processing algorithms for applications including compression [23,24], denoising [25,26], and segmentation [27
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.
Multi-Scale Scratch Analysis in Qinghai-Tibet Plateau and its Geological Implications
Sun, Yanyun; Yang, Wencai; Yu, Changqing
2016-04-01
Multi-scale scratch analysis on a regional gravity field is a new data processing system for depicting three-dimensional density structures and tectonic features. It comprises four modules including the spectral analysis of potential fields, multi-scale wavelet analysis, density distribution inversion, and scratch analysis. The multi-scale scratch analysis method was applied to regional gravity data to extract information about the deformation belts in the Qinghai-Tibet Plateau, which can help reveal variations of the deformation belts and plane distribution features from the upper crust to the lower crust, provide evidence for the study of three-dimensional crustal structures, and define distribution of deformation belts and mass movement. Results show the variation of deformation belts from the upper crust to the lower crust. The deformation belts vary from dense and thin in the upper crust to coarse and thick in the lower crust, demonstrating that vertical distribution of deformation belts resembles a tree with a coarse and thick trunk in the lower part and dense and thin branches at the top. The dense and thin deformation areas in the upper crust correspond to crustal shortening areas, while the thick and continuous deformation belts in the lower crust indicate the structural framework of the plateau. Additionally, the lower crustal deformation belts recognized by the multi-scale scratch analysis coincide approximately with the crustal deformation belts recognized using single-scale scratch analysis. However, deformation belts recognized by the latter are somewhat rough while multi-scale scratch analysis can provide more detailed and accurate results.
Multi-scale analysis of soil erosion dynamics in Kwazulu-natal, South Africa
Sonneveld, M.P.W.; Everson, T.M.; Veldkamp, A.
2005-01-01
For a case study area in the Okhombe catchment in the province of KwaZulu-Natal, South Africa, a multi-scale analysis of soil erosion dynamics was performed. At sub-catchment level, the dynamics of erosional features were investigated by means of aerial photographs. At site level, the changes in soi
Data-Adaptive Wavelets and Multi-Scale Singular Spectrum Analysis
Yiou, P; Ghil, M
1998-01-01
Using multi-scale ideas from wavelet analysis, we extend singular-spectrum analysis (SSA) to the study of nonstationary time series of length $N$ whose intermittency can give rise to the divergence of their variance. SSA relies on the construction of the lag-covariance matrix C on M lagged copies of the time series over a fixed window width W to detect the regular part of the variability in that window in terms of the minimal number of oscillatory components; here W = M Dt, with Dt the time step. The proposed multi-scale SSA is a local SSA analysis within a moving window of width M 3/4 W 3/4 N. Multi-scale SSA varies W, while keeping a fixed W/M ratio, and uses the eigenvectors of the corresponding lag-covariance matrix C_M as a data-adaptive wavelets; successive eigenvectors of C_M correspond approximately to successive derivatives of the first mother wavelet in standard wavelet analysis. Multi-scale SSA thus solves objectively the delicate problem of optimizing the analyzing wavelet in the time-frequency do...
Auer, Manfred; Peng, Hanchuan; Singh, Ambuj
2007-01-01
The 2006 International Workshop on Multiscale Biological Imaging, Data Mining and Informatics was held at Santa Barbara, on Sept 7–8, 2006. Based on the presentations at the workshop, we selected and compiled this collection of research articles related to novel algorithms and enabling techniques for bio- and biomedical image analysis, mining, visualization, and biology applications.
Analysis of the Spatial Distribution of Galaxies by Multiscale Methods
Directory of Open Access Journals (Sweden)
E. Saar
2005-09-01
Full Text Available Galaxies are arranged in interconnected walls and filaments forming a cosmic web encompassing huge, nearly empty, regions between the structures. Many statistical methods have been proposed in the past in order to describe the galaxy distribution and discriminate the different cosmological models. We present in this paper multiscale geometric transforms sensitive to clusters, sheets, and walls: the 3D isotropic undecimated wavelet transform, the 3D ridgelet transform, and the 3D beamlet transform. We show that statistical properties of transform coefficients measure in a coherent and statistically reliable way, the degree of clustering, filamentarity, sheetedness, and voidedness of a data set.
Strain analysis of nanowire interfaces in multiscale composites
Malakooti, Mohammad H.; Zhou, Zhi; Spears, John H.; Shankwitz, Timothy J.; Sodano, Henry A.
2016-04-01
Recently, the reinforcement-matrix interface of fiber reinforced polymers has been modified through grafting nanostructures - particularly carbon nanotubes and ZnO nanowires - on to the fiber surface. This type of interface engineering has made a great impact on the development of multiscale composites that have high stiffness, interfacial strength, toughness, and vibrational damping - qualities that are mutually exclusive to a degree in most raw materials. Although the efficacy of such nanostructured interfaces has been established, the reinforcement mechanisms of these multiscale composites have not been explored. Here, strain transfer across a nanowire interphase is studied in order to gain a heightened understanding of the working principles of physical interface modification and the formation of a functional gradient. This problem is studied using a functionally graded piezoelectric interface composed of vertically aligned lead zirconate titanate nanowires, as their piezoelectric properties can be utilized to precisely control the strain on one side of the interface. The displacement and strain across the nanowire interface is captured using digital image correlation. It is demonstrated that the material gradient created through nanowires cause a smooth strain transfer from reinforcement phase into matrix phase that eliminates the stress concentration between these phases, which have highly mismatched elasticity.
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.
Quantitative Multiscale Analysis using Different Wavelets in 1D Voice Signal and 2D Image
Shakhakarmi, Niraj
2012-01-01
Mutiscale analysis represents multiresolution scrutiny of a signal to improve its signal quality. Multiresolution analysis of 1D voice signal and 2D image is conducted using DCT, FFT and different wavelets such as Haar, Deubachies, Morlet, Cauchy, Shannon, Biorthogonal, Symmlet and Coiflet deploying the cascaded filter banks based decomposition and reconstruction. The outstanding quantitative analysis of the specified wavelets is done to investigate the signal quality, mean square error, entropy and peak-to-peak SNR at multiscale stage-4 for both 1D voice signal and 2D image. In addition, the 2D image compression performance is significantly found 93.00% in DB-4, 93.68% in bior-4.4, 93.18% in Sym-4 and 92.20% in Coif-2 during the multiscale analysis.
Traffic time series analysis by using multiscale time irreversibility and entropy
Wang, Xuejiao; Shang, Pengjian; Fang, Jintang
2014-09-01
Traffic systems, especially urban traffic systems, are regulated by different kinds of interacting mechanisms which operate across multiple spatial and temporal scales. Traditional approaches fail to account for the multiple time scales inherent in time series, such as empirical probability distribution function and detrended fluctuation analysis, which have lead to different results. The role of multiscale analytical method in traffic time series is a frontier area of investigation. In this paper, our main purpose is to introduce a new method—multiscale time irreversibility, which is helpful to extract information from traffic time series we studied. In addition, to analyse the complexity of traffic volume time series of Beijing Ring 2, 3, 4 roads between workdays and weekends, which are from August 18, 2012 to October 26, 2012, we also compare the results by this new method and multiscale entropy method we have known well. The results show that the higher asymmetry index we get, the higher traffic congestion level will be, and accord with those which are obtained by multiscale entropy.
Traffic time series analysis by using multiscale time irreversibility and entropy.
Wang, Xuejiao; Shang, Pengjian; Fang, Jintang
2014-09-01
Traffic systems, especially urban traffic systems, are regulated by different kinds of interacting mechanisms which operate across multiple spatial and temporal scales. Traditional approaches fail to account for the multiple time scales inherent in time series, such as empirical probability distribution function and detrended fluctuation analysis, which have lead to different results. The role of multiscale analytical method in traffic time series is a frontier area of investigation. In this paper, our main purpose is to introduce a new method-multiscale time irreversibility, which is helpful to extract information from traffic time series we studied. In addition, to analyse the complexity of traffic volume time series of Beijing Ring 2, 3, 4 roads between workdays and weekends, which are from August 18, 2012 to October 26, 2012, we also compare the results by this new method and multiscale entropy method we have known well. The results show that the higher asymmetry index we get, the higher traffic congestion level will be, and accord with those which are obtained by multiscale entropy.
Framework for adaptive multiscale analysis of nonhomogeneous point processes.
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.
Multi-Scale Analysis of Lagrangian Properties of Turbulence
Wilczek, Michael; Lalescu, Cristian
2016-11-01
Turbulence is a multi-scale problem in space and time with a broad range of strongly interacting degrees of freedom. Lagrangian tracer particles advected with the flow sample this spatio-temporal complexity. This naturally leads to the question of how Lagrangian properties are affected by the scales of turbulence. We attempt to answer this question numerically and theoretically adopting a coarse-graining approach. In an extensive DNS (direct numerical simulation) study, we track tracer particles advected by spatially coarse-grained velocity fields. This allows to distinguish the impact of large-scale sweeping effects and small-scale intermittency on Lagrangian aspects of turbulence. In this presentation we will present results on Lagrangian particle dispersion and velocity fluctuations for various coarse-graining scales. The results will furthermore be discussed in the context of Eulerian-Lagrangian bridging relations.
Multiscale Modeling for the Analysis for Grain-Scale Fracture Within Aluminum Microstructures
Glaessgen, Edward H.; Phillips, Dawn R.; Yamakov, Vesselin; Saether, Erik
2005-01-01
Multiscale modeling methods for the analysis of metallic microstructures are discussed. Both molecular dynamics and the finite element method are used to analyze crack propagation and stress distribution in a nanoscale aluminum bicrystal model subjected to hydrostatic loading. Quantitative similarity is observed between the results from the two very different analysis methods. A bilinear traction-displacement relationship that may be embedded into cohesive zone finite elements is extracted from the nanoscale molecular dynamics results.
Multivariate Multi-Scale Permutation Entropy for Complexity Analysis of Alzheimer’s Disease EEG
Directory of Open Access Journals (Sweden)
Isabella Palamara
2012-07-01
Full Text Available An original multivariate multi-scale methodology for assessing the complexity of physiological signals is proposed. The technique is able to incorporate the simultaneous analysis of multi-channel data as a unique block within a multi-scale framework. The basic complexity measure is done by using Permutation Entropy, a methodology for time series processing based on ordinal analysis. Permutation Entropy is conceptually simple, structurally robust to noise and artifacts, computationally very fast, which is relevant for designing portable diagnostics. Since time series derived from biological systems show structures on multiple spatial-temporal scales, the proposed technique can be useful for other types of biomedical signal analysis. In this work, the possibility of distinguish among the brain states related to Alzheimer’s disease patients and Mild Cognitive Impaired subjects from normal healthy elderly is checked on a real, although quite limited, experimental database.
Pak, Theodore R; Kasarskis, Andrew
2015-12-01
Recent reviews have examined the extent to which routine next-generation sequencing (NGS) on clinical specimens will improve the capabilities of clinical microbiology laboratories in the short term, but do not explore integrating NGS with clinical data from electronic medical records (EMRs), immune profiling data, and other rich datasets to create multiscale predictive models. This review introduces a range of "omics" and patient data sources relevant to managing infections and proposes 3 potentially disruptive applications for these data in the clinical workflow. The combined threats of healthcare-associated infections and multidrug-resistant organisms may be addressed by multiscale analysis of NGS and EMR data that is ideally updated and refined over time within each healthcare organization. Such data and analysis should form the cornerstone of future learning health systems for infectious disease.
Multiscale analysis of heart rate, blood pressure and respiration time series
Angelini, L; Marinazzo, D; Nitti, L; Pellicoro, M; Pinna, G D; Stramaglia, S; Tupputi, S A
2005-01-01
We present the multiscale entropy analysis of short term physiological time series of simultaneously acquired samples of heart rate, blood pressure and lung volume, from healthy subjects and from subjects with Chronic Heart Failure. Evaluating the complexity of signals at the multiple time scales inherent in physiologic dynamics, we find that healthy subjects show more complex time series at large time scales; on the other hand, at fast time scales, which are more influenced by respiration, the pathologic dynamics of blood pressure is the most random. These results robustly separate healthy and pathologic groups. We also propose a multiscale approach to evaluate interactions between time series, by performing a multivariate autoregressive modelling of the coarse grained time series: this analysis provides several new quantitative indicators which are statistically correlated with the pathology.
Low-carbon building assessment and multi-scale input-output analysis
Chen, G. Q.; Chen, H.; Chen, Z. M.; Zhang, Bo; Shao, L.; Guo, S.; Zhou, S. Y.; Jiang, M. M.
2011-01-01
Presented as a low-carbon building evaluation framework in this paper are detailed carbon emission account procedures for the life cycle of buildings in terms of nine stages as building construction, fitment, outdoor facility construction, transportation, operation, waste treatment, property management, demolition, and disposal for buildings, supported by integrated carbon intensity databases based on multi-scale input-output analysis, essential for low-carbon planning, procurement and supply chain design, and logistics management.
Multiscale Analysis of Head Impacts in Contact Sports
Guttag, Mark; Sett, Subham; Franck, Jennifer; McNamara, Kyle; Bar-Kochba, Eyal; Crisco, Joseph; Blume, Janet; Franck, Christian
2012-02-01
Traumatic brain injury (TBI) is one of the world's major causes of death and disability. To aid companies in designing safer and improved protective gear and to aid the medical community in producing improved quantitative TBI diagnosis and assessment tools, a multiscale finite element model of the human brain, head and neck is being developed. Recorded impact data from football and hockey helmets instrumented with accelerometers are compared to simulated impact data in the laboratory. Using data from these carefully constructed laboratory experiments, we can quantify impact location, magnitude, and linear and angular accelerations of the head. The resultant forces and accelerations are applied to a fully meshed head-form created from MRI data by Simpleware. With appropriate material properties for each region of the head-form, the Abaqus finite element model can determine the stresses, strains, and deformations in the brain. Simultaneously, an in-vitro cellular TBI criterion is being developed to be incorporated into Abaqus models for the brain. The cell-based injury criterion functions the same way that damage criteria for metals and other materials are used to predict failure in structural materials.
A Spectral Multiscale Method for Wave Propagation Analysis: Atomistic-Continuum Coupled Simulation
Patra, Amit K; Ganguli, Ranjan
2014-01-01
In this paper, we present a new multiscale method which is capable of coupling atomistic and continuum domains for high frequency wave propagation analysis. The problem of non-physical wave reflection, which occurs due to the change in system description across the interface between two scales, can be satisfactorily overcome by the proposed method. We propose an efficient spectral domain decomposition of the total fine scale displacement along with a potent macroscale equation in the Laplace domain to eliminate the spurious interfacial reflection. We use Laplace transform based spectral finite element method to model the macroscale, which provides the optimum approximations for required dynamic responses of the outer atoms of the simulated microscale region very accurately. This new method shows excellent agreement between the proposed multiscale model and the full molecular dynamics (MD) results. Numerical experiments of wave propagation in a 1D harmonic lattice, a 1D lattice with Lennard-Jones potential, a ...
Band, Leah R; Fozard, John A; Godin, Christophe; Jensen, Oliver E; Pridmore, Tony; Bennett, Malcolm J; King, John R
2012-10-01
Over recent decades, we have gained detailed knowledge of many processes involved in root growth and development. However, with this knowledge come increasing complexity and an increasing need for mechanistic modeling to understand how those individual processes interact. One major challenge is in relating genotypes to phenotypes, requiring us to move beyond the network and cellular scales, to use multiscale modeling to predict emergent dynamics at the tissue and organ levels. In this review, we highlight recent developments in multiscale modeling, illustrating how these are generating new mechanistic insights into the regulation of root growth and development. We consider how these models are motivating new biological data analysis and explore directions for future research. This modeling progress will be crucial as we move from a qualitative to an increasingly quantitative understanding of root biology, generating predictive tools that accelerate the development of improved crop varieties.
Consistent approach to edge detection using multiscale fuzzy modeling analysis in the human retina
Directory of Open Access Journals (Sweden)
Mehdi Salimian
2012-06-01
Full Text Available Today, many widely used image processing algorithms based on human visual system have been developed. In this paper a smart edge detection based on modeling the performance of simple and complex cells and also modeling and multi-scale image processing in the primary visual cortex is presented. A way to adjust the parameters of Gabor filters (mathematical models of simple cells And the proposed non-linear threshold response are presented in order to Modeling of simple and complex cells. Also, due to multi-scale modeling analysis conducted in the human retina, in the proposed algorithm, all edges of the small and large structures with high precision are detected and localized. Comparing the results of the proposed method for a reliable database with conventional methods shows the higher Performance (about 4-13% and reliability of the proposed method in the detection and localization of edge.
Lin, Aijing; Shang, Pengjian
2016-04-01
Considering the diverse application of multifractal techniques in natural scientific disciplines, this work underscores the versatility of multiscale multifractal detrended fluctuation analysis (MMA) method to investigate artificial and real-world data sets. The modified MMA method based on cumulative distribution function is proposed with the objective of quantifying the scaling exponent and multifractality of nonstationary time series. It is demonstrated that our approach can provide a more stable and faithful description of multifractal properties in comprehensive range rather than fixing the window length and slide length. Our analyzes based on CDF-MMA method reveal significant differences in the multifractal characteristics in the temporal dynamics between US and Chinese stock markets, suggesting that these two stock markets might be regulated by very different mechanism. The CDF-MMA method is important for evidencing the stable and fine structure of multiscale and multifractal scaling behaviors and can be useful to deepen and broaden our understanding of scaling exponents and multifractal characteristics.
Nanosystem Self-Assembly Pathways Discovered via All-Atom Multiscale Analysis
Pankavich, Stephen
2014-01-01
We consider the self-assembly of composite structures from a group of nanocomponents, each consisting of particles within an $N$-atom system. Self-assembly pathways and rates for nanocomposites are derived via a multiscale analysis of the classical Liouville equation. From a reduced statistical framework, rigorous stochastic equations for population levels of beginning, intermediate, and final aggregates are also derived. It is shown that the definition of an assembly type is a self-consistency criterion that must strike a balance between precision and the need for population levels to be slowly varying relative to the time scale of atomic motion. The deductive multiscale approach is complemented by a qualitative notion of multicomponent association and the ensemble of exact atomic-level configurations consistent with them. In processes such as viral self-assembly from proteins and RNA or DNA, there are many possible intermediates, so that it is usually difficult to predict the most efficient assembly pathway...
Multiscale dynamic analysis of blast furnace system based on intensive signal processing.
Chu, Yanxu; Gao, Chuanhou; Liu, Xiangguan
2010-09-01
In this paper, the Hilbert-Huang transform method and time delay embedding method are applied to multiscale dynamic analysis on the time series of silicon content in hot metal collected from a medium-sized blast furnace with the inner volume of 2500 m3. The results provide clear evidence of multiscale features in blast furnace ironmaking process. Ten intrinsic mode functions (IMFs) are decomposed from the silicon content time series; the presence of noninteger fractal dimension, positive finite Kolmogorov entropy, and positive finite maximum Lyapunov exponent are found in some IMF components. In addition, the coupling of subscale structures of blast furnace system is studied using the dimension of interaction dynamics and a robust algorithm for detecting interdependence. It is found that IMF(3) is the main driver in the coupling system IMF(2) and IMF(3) while for the coupling system IMF(3) and IMF(4) neither subsystem can act as the driver. All these provide a guideline for studying blast furnace ironmaking process with multiscale theory and methods, and may open way for more candidate tools to model and control blast furnace system in the future.
Azami, Hamed; Escudero, Javier
2017-01-01
Multiscale entropy (MSE) is an appealing tool to characterize the complexity of time series over multiple temporal scales. Recent developments in the field have tried to extend the MSE technique in different ways. Building on these trends, we propose the so-called refined composite multivariate multiscale fuzzy entropy (RCmvMFE) whose coarse-graining step uses variance (RCmvMFEσ2) or mean (RCmvMFEμ). We investigate the behavior of these multivariate methods on multichannel white Gaussian and 1/ f noise signals, and two publicly available biomedical recordings. Our simulations demonstrate that RCmvMFEσ2 and RCmvMFEμ lead to more stable results and are less sensitive to the signals' length in comparison with the other existing multivariate multiscale entropy-based methods. The classification results also show that using both the variance and mean in the coarse-graining step offers complexity profiles with complementary information for biomedical signal analysis. We also made freely available all the Matlab codes used in this paper.
Jolivet, S.; Mezghani, S.; El Mansori, M.
2016-09-01
The replication of topography has been generally restricted to optimizing material processing technologies in terms of statistical and single-scale features such as roughness. By contrast, manufactured surface topography is highly complex, irregular, and multiscale. In this work, we have demonstrated the use of multiscale analysis on replicates of surface finish to assess the precise control of the finished replica. Five commercial resins used for surface replication were compared. The topography of five standard surfaces representative of common finishing processes were acquired both directly and by a replication technique. Then, they were characterized using the ISO 25178 standard and multiscale decomposition based on a continuous wavelet transform, to compare the roughness transfer quality at different scales. Additionally, atomic force microscope force modulation mode was used in order to compare the resins’ stiffness properties. The results showed that less stiff resins are able to replicate the surface finish along a larger wavelength band. The method was then tested for non-destructive quality control of automotive gear tooth surfaces.
Mood states modulate complexity in heartbeat dynamics: A multiscale entropy analysis
Valenza, G.; Nardelli, M.; Bertschy, G.; Lanata, A.; Scilingo, E. P.
2014-07-01
This paper demonstrates that heartbeat complex dynamics is modulated by different pathological mental states. Multiscale entropy analysis was performed on R-R interval series gathered from the electrocardiogram of eight bipolar patients who exhibited mood states among depression, hypomania, and euthymia, i.e., good affective balance. Three different methodologies for the choice of the sample entropy radius value were also compared. We show that the complexity level can be used as a marker of mental states being able to discriminate among the three pathological mood states, suggesting to use heartbeat complexity as a more objective clinical biomarker for mental disorders.
Data-adaptive wavelets and multi-scale singular-spectrum analysis
Yiou, Pascal; Sornette, Didier; Ghil, Michael
2000-08-01
Using multi-scale ideas from wavelet analysis, we extend singular-spectrum analysis (SSA) to the study of nonstationary time series, including the case where intermittency gives rise to the divergence of their variance. The wavelet transform resembles a local Fourier transform within a finite moving window whose width W, proportional to the major period of interest, is varied to explore a broad range of such periods. SSA, on the other hand, relies on the construction of the lag-correlation matrix C on M lagged copies of the time series over a fixed window width W to detect the regular part of the variability in that window in terms of the minimal number of oscillatory components; here W= MΔ t with Δ t as the time step. The proposed multi-scale SSA is a local SSA analysis within a moving window of width M≤ W≤ N, where N is the length of the time series. Multi-scale SSA varies W, while keeping a fixed W/ M ratio, and uses the eigenvectors of the corresponding lag-correlation matrix C(M) as data-adaptive wavelets; successive eigenvectors of C(M) correspond approximately to successive derivatives of the first mother wavelet in standard wavelet analysis. Multi-scale SSA thus solves objectively the delicate problem of optimizing the analyzing wavelet in the time-frequency domain by a suitable localization of the signal’s correlation matrix. We present several examples of application to synthetic signals with fractal or power-law behavior which mimic selected features of certain climatic or geophysical time series. The method is applied next to the monthly values of the Southern Oscillation Index (SOI) for 1933-1996; the SOI time series is widely believed to capture major features of the El Niño/Southern Oscillation (ENSO) in the Tropical Pacific. Our methodology highlights an abrupt periodicity shift in the SOI near 1960. This abrupt shift between 5 and 3 years supports the Devil’s staircase scenario for the ENSO phenomenon (preliminary results of this study
Global Appearance Applied to Visual Map Building and Path Estimation Using Multiscale Analysis
Directory of Open Access Journals (Sweden)
Francisco Amorós
2014-01-01
Full Text Available In this work we present a topological map building and localization system for mobile robots based on global appearance of visual information. We include a comparison and analysis of global-appearance techniques applied to wide-angle scenes in retrieval tasks. Next, we define multiscale analysis, which permits improving the association between images and extracting topological distances. Then, a topological map-building algorithm is proposed. At first, the algorithm has information only of some isolated positions of the navigation area in the form of nodes. Each node is composed of a collection of images that covers the complete field of view from a certain position. The algorithm solves the node retrieval and estimates their spatial arrangement. With these aims, it uses the visual information captured along some routes that cover the navigation area. As a result, the algorithm builds a graph that reflects the distribution and adjacency relations between nodes (map. After the map building, we also propose a route path estimation system. This algorithm takes advantage of the multiscale analysis. The accuracy in the pose estimation is not reduced to the nodes locations but also to intermediate positions between them. The algorithms have been tested using two different databases captured in real indoor environments under dynamic conditions.
Multiscale analysis of restoration priorities for marine shoreline planning.
Diefenderfer, Heida L; Sobocinski, Kathryn L; Thom, Ronald M; May, Christopher W; Borde, Amy B; Southard, Susan L; Vavrinec, John; Sather, Nichole K
2009-10-01
Planners are being called on to prioritize marine shorelines for conservation status and restoration action. This study documents an approach to determining the management strategy most likely to succeed based on current conditions at local and landscape scales. The conceptual framework based in restoration ecology pairs appropriate restoration strategies with sites based on the likelihood of producing long-term resilience given the condition of ecosystem structures and processes at three scales: the shorezone unit (site), the drift cell reach (nearshore marine landscape), and the watershed (terrestrial landscape). The analysis is structured by a conceptual ecosystem model that identifies anthropogenic impacts on targeted ecosystem functions. A scoring system, weighted by geomorphic class, is applied to available spatial data for indicators of stress and function using geographic information systems. This planning tool augments other approaches to prioritizing restoration, including historical conditions and change analysis and ecosystem valuation.
A Multi-scale Approach to Urban Thermal Analysis
Gluch, Renne; Quattrochi, Dale A.
2005-01-01
An environmental consequence of urbanization is the urban heat island effect, a situation where urban areas are warmer than surrounding rural areas. The urban heat island phenomenon results from the replacement of natural landscapes with impervious surfaces such as concrete and asphalt and is linked to adverse economic and environmental impacts. In order to better understand the urban microclimate, a greater understanding of the urban thermal pattern (UTP), including an analysis of the thermal properties of individual land covers, is needed. This study examines the UTP by means of thermal land cover response for the Salt Lake City, Utah, study area at two scales: 1) the community level, and 2) the regional or valleywide level. Airborne ATLAS (Advanced Thermal Land Applications Sensor) data, a high spatial resolution (10-meter) dataset appropriate for an environment containing a concentration of diverse land covers, are used for both land cover and thermal analysis at the community level. The ATLAS data consist of 15 channels covering the visible, near-IR, mid-IR and thermal-IR wavelengths. At the regional level Landsat TM data are used for land cover analysis while the ATLAS channel 13 data are used for the thermal analysis. Results show that a heat island is evident at both the community and the valleywide level where there is an abundance of impervious surfaces. ATLAS data perform well in community level studies in terms of land cover and thermal exchanges, but other, more coarse-resolution data sets are more appropriate for large-area thermal studies. Thermal response per land cover is consistent at both levels, which suggests potential for urban climate modeling at multiple scales.
Multiscale analysis of river networks using the R package linbin
Welty, Ethan Z.; Torgersen, Christian E.; Brenkman, Samuel J.; Duda, Jeffrey J.; Armstrong, Jonathan B.
2015-01-01
Analytical tools are needed in riverine science and management to bridge the gap between GIS and statistical packages that were not designed for the directional and dendritic structure of streams. We introduce linbin, an R package developed for the analysis of riverscapes at multiple scales. With this software, riverine data on aquatic habitat and species distribution can be scaled and plotted automatically with respect to their position in the stream network or—in the case of temporal data—their position in time. The linbin package aggregates data into bins of different sizes as specified by the user. We provide case studies illustrating the use of the software for (1) exploring patterns at different scales by aggregating variables at a range of bin sizes, (2) comparing repeat observations by aggregating surveys into bins of common coverage, and (3) tailoring analysis to data with custom bin designs. Furthermore, we demonstrate the utility of linbin for summarizing patterns throughout an entire stream network, and we analyze the diel and seasonal movements of tagged fish past a stationary receiver to illustrate how linbin can be used with temporal data. In short, linbin enables more rapid analysis of complex data sets by fisheries managers and stream ecologists and can reveal underlying spatial and temporal patterns of fish distribution and habitat throughout a riverscape.
Multi-scale model analysis and hindcast of the 2013 Colorado Flood
Gochis, David; Yu, Wei; Sampson, Kevin; Dugger, Aubrey; McCreight, James; Zhang, Yongxin; Ikeda, Kyoko
2015-04-01
While the generation of most flood and flash flood events is fundamentally linked to the occurrence of heavy rainfall, the physical mechanisms responsible for translating rainfall into floods are complex and manifold. These runoff generation processes evolve over many spatial and temporal scales during the course of flooding events. As such robust flood and flash flood prediction systems need to account for multitude of terrestrial processes occurring over a wide range of space and time scales. One such extreme multiscale flood event was the 2013 Colorado Flood in which over 400 mm of rainfall fell along the Rock Mountain mountain front region over the course of a few days. The flooding impacts from this heavy rainfall event included not only high, fast flows in steep mountain streams but also included large areas of inundation on the adjacent plains and numerous soil saturation excess impacts such as hillslope failures and groundwater intrusions into domestic structures. A multi-scale and multi-process evaluation of this flood event is performed using the community WRF-Hydro modeling system. We incorporate several operational quantitative precipitation estimate and quantitative precipitation forecast products in the analysis and document the skill of multiple configurations of WRF-Hydro physics options across a range of contributing area length scales. Emphasis is placed on assessing how well the different model configurations capture the multi-scale streamflow response from small headwater catchments out to the entire South Platte River basin whose total contributing area exceeds 25,000 sq km. In addition to streamflow we also present evaluations of event simulations and hindcasts of soil saturation fraction, groundwater levels and inundated areas as a means of assessing different runoff generation mechanisms. Finally, results from a U.S. national-scale, fully-coupled hydrometeorological hindcast of the 2013 Colorado flood event using the combined WRF atmospheric
Varghese, Julian
This research work has contributed in various ways to help develop a better understanding of textile composites and materials with complex microstructures in general. An instrumental part of this work was the development of an object-oriented framework that made it convenient to perform multiscale/multiphysics analyses of advanced materials with complex microstructures such as textile composites. In addition to the studies conducted in this work, this framework lays the groundwork for continued research of these materials. This framework enabled a detailed multiscale stress analysis of a woven DCB specimen that revealed the effect of the complex microstructure on the stress and strain energy release rate distribution along the crack front. In addition to implementing an oxidation model, the framework was also used to implement strategies that expedited the simulation of oxidation in textile composites so that it would take only a few hours. The simulation showed that the tow architecture played a significant role in the oxidation behavior in textile composites. Finally, a coupled diffusion/oxidation and damage progression analysis was implemented that was used to study the mechanical behavior of textile composites under mechanical loading as well as oxidation. A parametric study was performed to determine the effect of material properties and the number of plies in the laminate on its mechanical behavior. The analyses indicated a significant effect of the tow architecture and other parameters on the damage progression in the laminates.
Multivariate Image Analysis in Gaussian Multi-Scale Space for Defect Detection
Institute of Scientific and Technical Information of China (English)
Dong-tai Liang; Wei-yan Deng; Xuan-yin Wang; Yang Zhang
2009-01-01
Inspired by the coarse-to-fine visual perception process of human vision system, a new approach based on Gaussian multi-scale space for defect detection of industrial products was proposed. By selecting different scale parameters of the Gaussian kernel, the multi-scale representation of the original image data could be obtained and used to constitute the multi-variate image, in which each channel could represent a perceptual observation of the original image from different scales. The Multivariate Image Analysis (MIA) techniques were used to extract defect features information. The MIA combined Principal Component Analysis (PCA) to obtain the principal component scores of the multivariate test image. The Q-statistic image, derived from the residuals after the extraction of the first principal component score and noise, could be used to efficiently reveal the surface defects with an appropriate threshold value decided by training images. Experimental results show that the proposed method performs better than the gray histogram-based method. It has less sensitivity to the inhomogeneous of illumination, and has more robustness and reliability of defect detection with lower pseudo reject rate.
Multiscale analysis of heart beat interval increment series and its clinical significance
Institute of Scientific and Technical Information of China (English)
HUANG XiaoLin; NING XinBao; WANG XinLong
2009-01-01
Analysis of multiscale entropy (MSE) and multiscale standard deviation (MSD) are performed for both the heart rate interval series and the interval increment series. For the interval series, it is found that, it is impractical to discriminate the diseases of atrial fibrillation (AF) and congestive heart failure (CHF) unambiguously from the healthy. A clear discrimination from the healthy, both young and old, however, can be made in the MSE analysis of the increment series where we find that both CHF and AF sufferers have significantly low MSE values in the whole range of time scales investigated, which reveals that there are common dynamic characteristics underlying these two different diseases. In addition, we propose the sample entropy (SE) corresponding to time scale factor 4 of increment series as a diag-nosis index of both AF and CHF, and the reference threshold is recommended. Further indication that this index can help discriminate sensitively the mild heart failure (cardiac function classes 1 and 2) from the healthy gives a clue to early clinic diagnosis of CHF.
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
The multi-scale characteristics of wave significant height (Hs) in eastern China seas were revealed by multi-scale wavelet analysis. In order to understand the relation between wave and wind, the TOPEX/Poseidon measurements of Hs and wind speed were analyzed. The result showed that Hs and wind speed change in multi-scale at one-, two-month, half-, one- and two-year cycles. But in a larger time scale, the variations in Hs and wind speed are different. Hs has a five-year cycle similar to the cycle of ENSO variation, while the wind speed has no such cycle. In the time domain, the correlation between Hs and ENSO is unclear.
Multiscale analysis of nonlinear systems using computational homology
Energy Technology Data Exchange (ETDEWEB)
Konstantin Mischaikow, Rutgers University/Georgia Institute of Technology, Michael Schatz, Georgia Institute of Technology, William Kalies, Florida Atlantic University, Thomas Wanner,George Mason University
2010-05-19
This is a collaborative project between the principal investigators. However, as is to be expected, different PIs have greater focus on different aspects of the project. This report lists these major directions of research which were pursued during the funding period: (1) Computational Homology in Fluids - For the computational homology effort in thermal convection, the focus of the work during the first two years of the funding period included: (1) A clear demonstration that homology can sensitively detect the presence or absence of an important flow symmetry, (2) An investigation of homology as a probe for flow dynamics, and (3) The construction of a new convection apparatus for probing the effects of large-aspect-ratio. (2) Computational Homology in Cardiac Dynamics - We have initiated an effort to test the use of homology in characterizing data from both laboratory experiments and numerical simulations of arrhythmia in the heart. Recently, the use of high speed, high sensitivity digital imaging in conjunction with voltage sensitive fluorescent dyes has enabled researchers to visualize electrical activity on the surface of cardiac tissue, both in vitro and in vivo. (3) Magnetohydrodynamics - A new research direction is to use computational homology to analyze results of large scale simulations of 2D turbulence in the presence of magnetic fields. Such simulations are relevant to the dynamics of black hole accretion disks. The complex flow patterns from simulations exhibit strong qualitative changes as a function of magnetic field strength. Efforts to characterize the pattern changes using Fourier methods and wavelet analysis have been unsuccessful. (4) Granular Flow - two experts in the area of granular media are studying 2D model experiments of earthquake dynamics where the stress fields can be measured; these stress fields from complex patterns of 'force chains' that may be amenable to analysis using computational homology. (5) Microstructure
Multiscale analysis of nonlinear systems using computational homology
Energy Technology Data Exchange (ETDEWEB)
Konstantin Mischaikow; Michael Schatz; William Kalies; Thomas Wanner
2010-05-24
This is a collaborative project between the principal investigators. However, as is to be expected, different PIs have greater focus on different aspects of the project. This report lists these major directions of research which were pursued during the funding period: (1) Computational Homology in Fluids - For the computational homology effort in thermal convection, the focus of the work during the first two years of the funding period included: (1) A clear demonstration that homology can sensitively detect the presence or absence of an important flow symmetry, (2) An investigation of homology as a probe for flow dynamics, and (3) The construction of a new convection apparatus for probing the effects of large-aspect-ratio. (2) Computational Homology in Cardiac Dynamics - We have initiated an effort to test the use of homology in characterizing data from both laboratory experiments and numerical simulations of arrhythmia in the heart. Recently, the use of high speed, high sensitivity digital imaging in conjunction with voltage sensitive fluorescent dyes has enabled researchers to visualize electrical activity on the surface of cardiac tissue, both in vitro and in vivo. (3) Magnetohydrodynamics - A new research direction is to use computational homology to analyze results of large scale simulations of 2D turbulence in the presence of magnetic fields. Such simulations are relevant to the dynamics of black hole accretion disks. The complex flow patterns from simulations exhibit strong qualitative changes as a function of magnetic field strength. Efforts to characterize the pattern changes using Fourier methods and wavelet analysis have been unsuccessful. (4) Granular Flow - two experts in the area of granular media are studying 2D model experiments of earthquake dynamics where the stress fields can be measured; these stress fields from complex patterns of 'force chains' that may be amenable to analysis using computational homology. (5) Microstructure
Network analysis reveals multiscale controls on streamwater chemistry
McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.
2014-01-01
By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.
Multiscale Morphological Filtering for Analysis of Noisy and Complex Images
Kher, A.; Mitra, S.
1993-01-01
Images acquired with passive sensing techniques suffer from illumination variations and poor local contrasts that create major difficulties in interpretation and identification tasks. On the other hand, images acquired with active sensing techniques based on monochromatic illumination are degraded with speckle noise. Mathematical morphology offers elegant techniques to handle a wide range of image degradation problems. Unlike linear filters, morphological filters do not blur the edges and hence maintain higher image resolution. Their rich mathematical framework facilitates the design and analysis of these filters as well as their hardware implementation. Morphological filters are easier to implement and are more cost effective and efficient than several conventional linear filters. Morphological filters to remove speckle noise while maintaining high resolution and preserving thin image regions that are particularly vulnerable to speckle noise were developed and applied to SAR imagery. These filters used combination of linear (one-dimensional) structuring elements in different (typically four) orientations. Although this approach preserves more details than the simple morphological filters using two-dimensional structuring elements, the limited orientations of one-dimensional elements approximate the fine details of the region boundaries. A more robust filter designed recently overcomes the limitation of the fixed orientations. This filter uses a combination of concave and convex structuring elements. Morphological operators are also useful in extracting features from visible and infrared imagery. A multiresolution image pyramid obtained with successive filtering and a subsampling process aids in the removal of the illumination variations and enhances local contrasts. A morphology-based interpolation scheme was also introduced to reduce intensity discontinuities created in any morphological filtering task. The generality of morphological filtering techniques in
Simulation of multi-scale heterogeneity of porous media and parameter sensitivity analysis
Institute of Scientific and Technical Information of China (English)
ZHANG; Yong; (张; 勇); G.E.; Fogg
2003-01-01
Because of the inherent multi-scale heterogeneity of porous media and the limitation of single-subject observed data, we propose to combine deterministic and stochastic techniques to simulate heterogeneity. We select a coastal plain sediment system as an example to demonstrate and verify this approach. Firstly, we apply transition probability matrix to determine and delineate the nonstationary unconformity, and combine hydro-stratigraphy analyses to establish the field/large-scale, deterministic stratigraphy model. Secondly, we apply fence diagrams and CPT data to infer the horizontal mean length of hydrofacies, and then build Markov chain models for each depositional system and simulate the local/intermediate-scale, stochastic hydrofacies model. Finally, we combine the stratigraphy and hydrofacies models to get a multi-scale heterogeneous model embedded with quantitative and qualitative observed data, with both deterministic and stochastic characteristics. In order to study the influence of uncertainty in model parameters on solute transport, we build multiple realizations of two types of heterogeneous model and use them to simulate groundwater flow and solute transport. The parameter sensitivity analysis shows the 1st and 2nd spatial moments of the contaminant plume increase with the lateral average length of hydrofacies.
Krzysztof, Kecik; Borowiec, Marek; Rafał, Rusinek
2016-01-01
Correctness verification of the stability lobe diagrams of milling process determined by commercial software CutPro 9 is the aim of this work. The analysis is performed for nickel superalloy Inconel 718 which is widely used in aviation industry. A methodology of stability analysis which bases on advanced nonlinear methods such as recurrence plot, recurrence quantifications analysis and composite multiscale entropy analysis are applied to the experimental data. Additionally, a new criterion for the determination of the unstable areas is proposed.
Multi-scale dynamical analysis (MSDA) of sea level records versus PDO, AMO, and NAO indexes
Scafetta, Nicola
2013-01-01
Herein I propose a multi-scale dynamical analysis to facilitate the physical interpretation of tide gauge records. The technique uses graphical diagrams. It is applied to six secular-long tide gauge records representative of the world oceans: Sydney, Pacific coast of Australia; Fremantle, Indian Ocean coast of Australia; New York City, Atlantic coast of USA; Honolulu, U.S. state of Hawaii; San Diego, U.S. state of California; and Venice, Mediterranean Sea, Italy. For comparison, an equivalent analysis is applied to the Pacific Decadal Oscillation (PDO) index and to the Atlantic Multidecadal Oscillation (AMO) index. Finally, a global reconstruction of sea level and a reconstruction of the North Atlantic Oscillation (NAO) index are analyzed and compared: both sequences cover about three centuries from 1700 to 2000. The proposed methodology quickly highlights oscillations and teleconnections among the records at the decadal and multidecadal scales. At the secular time scales tide gauge records present relatively...
Lian, Enyang; Ren, Yingyu; Han, Yunfeng; Liu, Weixin; Jin, Ningde; Zhao, Junying
2016-11-01
The multi-scale analysis is an important method for detecting nonlinear systems. In this study, we carry out experiments and measure the fluctuation signals from a rotating electric field conductance sensor with eight electrodes. We first use a recurrence plot to recognise flow patterns in vertical upward gas-liquid two-phase pipe flow from measured signals. Then we apply a multi-scale morphological analysis based on the first-order difference scatter plot to investigate the signals captured from the vertical upward gas-liquid two-phase flow loop test. We find that the invariant scaling exponent extracted from the multi-scale first-order difference scatter plot with the bisector of the second-fourth quadrant as the reference line is sensitive to the inhomogeneous distribution characteristics of the flow structure, and the variation trend of the exponent is helpful to understand the process of breakup and coalescence of the gas phase. In addition, we explore the dynamic mechanism influencing the inhomogeneous distribution of the gas phase in terms of adaptive optimal kernel time-frequency representation. The research indicates that the system energy is a factor influencing the distribution of the gas phase and the multi-scale morphological analysis based on the first-order difference scatter plot is an effective method for indicating the inhomogeneous distribution of the gas phase in gas-liquid two-phase flow.
Directory of Open Access Journals (Sweden)
T. Lahousse
2011-10-01
Full Text Available We developed a multi-scale OBIA (object-based image analysis landslide detection technique to map shallow landslides in the Baichi watershed, Taiwan, after the 2004 Typhoon Aere event. Our semi-automated detection method selected multiple scales through landslide size statistics analysis for successive classification rounds. The detection performance achieved a modified success rate (MSR of 86.5% with the training dataset and 86% with the validation dataset. This performance level was due to the multi-scale aspect of our methodology, as the MSR for single scale classification was substantially lower, even after spectral difference segmentation, with a maximum of 74%. Our multi-scale technique was capable of detecting landslides of varying sizes, including very small landslides, up to 95 m^{2}. The method presented certain limitations: the thresholds we established for classification were specific to the study area, to the landslide type in the study area, and to the spectral characteristics of the satellite image. Because updating site-specific and image-specific classification thresholds is easy with OBIA software, our multi-scale technique is expected to be useful for mapping shallow landslides at watershed level.
Three-band decomposition analysis in multiscale FSI models of abdominal aortic aneurysms
Nestola, Maria G. C.; Gizzi, Alessio; Cherubini, Christian; Filippi, Simonetta
2016-07-01
Computational modeling plays an important role in biology and medicine to assess the effects of hemodynamic alterations in the onset and development of vascular pathologies. Synthetic analytic indices are of primary importance for a reliable and effective a priori identification of the risk. In this scenario, we propose a multiscale fluid-structure interaction (FSI) modeling approach of hemodynamic flows, extending the recently introduced three-band decomposition (TBD) analysis for moving domains. A quantitative comparison is performed with respect to the most common hemodynamic risk indicators in a systematic manner. We demonstrate the reliability of the TBD methodology also for deformable domains by assuming a hyperelastic formulation of the arterial wall and a Newtonian approximation of the blood flow. Numerical simulations are performed for physiologic and pathologic axially symmetric geometry models with particular attention to abdominal aortic aneurysms (AAAs). Risk assessment, limitations and perspectives are finally discussed.
Multiscale Static Analysis of Notched and Unnotched Laminates Using the Generalized Method of Cells
Naghipour Ghezeljeh, Paria; Arnold, Steven M.; Pineda, Evan J.; Stier, Bertram; Hansen, Lucas; Bednarcyk, Brett A.; Waas, Anthony M.
2016-01-01
The generalized method of cells (GMC) is demonstrated to be a viable micromechanics tool for predicting the deformation and failure response of laminated composites, with and without notches, subjected to tensile and compressive static loading. Given the axial [0], transverse [90], and shear [+45/-45] response of a carbon/epoxy (IM7/977-3) system, the unnotched and notched behavior of three multidirectional layups (Layup 1: [0,45,90,-45](sub 2S), Layup 2: [0,60,0](sub 3S), and Layup 3: [30,60,90,-30, -60](sub 2S)) are predicted under both tensile and compressive static loading. Matrix nonlinearity is modeled in two ways. The first assumes all nonlinearity is due to anisotropic progressive damage of the matrix only, which is modeled, using the multiaxial mixed-mode continuum damage model (MMCDM) within GMC. The second utilizes matrix plasticity coupled with brittle final failure based on the maximum principle strain criteria to account for matrix nonlinearity and failure within the Finite Element Analysis--Micromechanics Analysis Code (FEAMAC) software multiscale framework. Both MMCDM and plasticity models incorporate brittle strain- and stress-based failure criteria for the fiber. Upon satisfaction of these criteria, the fiber properties are immediately reduced to a nominal value. The constitutive response for each constituent (fiber and matrix) is characterized using a combination of vendor data and the axial, transverse, and shear responses of unnotched laminates. Then, the capability of the multiscale methodology is assessed by performing blind predictions of the mentioned notched and unnotched composite laminates response under tensile and compressive loading. Tabulated data along with the detailed results (i.e., stress-strain curves as well as damage evolution states at various ratios of strain to failure) for all laminates are presented.
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...
Bednarcyk, Brett A.; Arnold, Steven M.
2007-01-01
A framework is presented that enables coupled multiscale analysis of composite structures. The recently developed, free, Finite Element Analysis-Micromechanics Analysis Code (FEAMAC) software couples the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) with ABAQUS to perform micromechanics based FEA such that the nonlinear composite material response at each integration point is modeled at each increment by MAC/GMC. As a result, the stochastic nature of fiber breakage in composites can be simulated through incorporation of an appropriate damage and failure model that operates within MAC/GMC on the level of the fiber. Results are presented for the progressive failure analysis of a titanium matrix composite tensile specimen that illustrate the power and utility of the framework and address the techniques needed to model the statistical nature of the problem properly. In particular, it is shown that incorporating fiber strength randomness on multiple scales improves the quality of the simulation by enabling failure at locations other than those associated with structural level stress risers.
Multiscale analysis of biological data by scale-dependent lyapunov exponent.
Gao, Jianbo; Hu, Jing; Tung, Wen-Wen; Blasch, Erik
2011-01-01
Physiological signals often are highly non-stationary (i.e., mean and variance change with time) and multiscaled (i.e., dependent on the spatial or temporal interval lengths). They may exhibit different behaviors, such as non-linearity, sensitive dependence on small disturbances, long memory, and extreme variations. Such data have been accumulating in all areas of health sciences and rapid analysis can serve quality testing, physician assessment, and patient diagnosis. To support patient care, it is very desirable to characterize the different signal behaviors on a wide range of scales simultaneously. The Scale-Dependent Lyapunov Exponent (SDLE) is capable of such a fundamental task. In particular, SDLE can readily characterize all known types of signal data, including deterministic chaos, noisy chaos, random 1/f(α) processes, stochastic limit cycles, among others. SDLE also has some unique capabilities that are not shared by other methods, such as detecting fractal structures from non-stationary data and detecting intermittent chaos. In this article, we describe SDLE in such a way that it can be readily understood and implemented by non-mathematically oriented researchers, develop a SDLE-based consistent, unifying theory for the multiscale analysis, and demonstrate the power of SDLE on analysis of heart-rate variability (HRV) data to detect congestive heart failure and analysis of electroencephalography (EEG) data to detect seizures.
Multiscale multifractal multiproperty analysis of financial time series based on Rényi entropy
Yujun, Yang; Jianping, Li; Yimei, Yang
This paper introduces a multiscale multifractal multiproperty analysis based on Rényi entropy (3MPAR) method to analyze short-range and long-range characteristics of financial time series, and then applies this method to the five time series of five properties in four stock indices. Combining the two analysis techniques of Rényi entropy and multifractal detrended fluctuation analysis (MFDFA), the 3MPAR method focuses on the curves of Rényi entropy and generalized Hurst exponent of five properties of four stock time series, which allows us to study more universal and subtle fluctuation characteristics of financial time series. By analyzing the curves of the Rényi entropy and the profiles of the logarithm distribution of MFDFA of five properties of four stock indices, the 3MPAR method shows some fluctuation characteristics of the financial time series and the stock markets. Then, it also shows a richer information of the financial time series by comparing the profile of five properties of four stock indices. In this paper, we not only focus on the multifractality of time series but also the fluctuation characteristics of the financial time series and subtle differences in the time series of different properties. We find that financial time series is far more complex than reported in some research works using one property of time series.
Large deviations estimates for the multiscale analysis of heart rate variability
Loiseau, Patrick; Médigue, Claire; Gonçalves, Paulo; Attia, Najmeddine; Seuret, Stéphane; Cottin, François; Chemla, Denis; Sorine, Michel; Barral, Julien
2012-11-01
In the realm of multiscale signal analysis, multifractal analysis provides a natural and rich framework to measure the roughness of a time series. As such, it has drawn special attention of both mathematicians and practitioners, and led them to characterize relevant physiological factors impacting the heart rate variability. Notwithstanding these considerable progresses, multifractal analysis almost exclusively developed around the concept of Legendre singularity spectrum, for which efficient and elaborate estimators exist, but which are structurally blind to subtle features like non-concavity or, to a certain extent, non scaling of the distributions. Large deviations theory allows bypassing these limitations but it is only very recently that performing estimators were proposed to reliably compute the corresponding large deviations singularity spectrum. In this article, we illustrate the relevance of this approach, on both theoretical objects and on human heart rate signals from the Physionet public database. As conjectured, we verify that large deviations principles reveal significant information that otherwise remains hidden with classical approaches, and which can be reminiscent of some physiological characteristics. In particular we quantify the presence/absence of scale invariance of RR signals.
Institute of Scientific and Technical Information of China (English)
JIANG Nan; ZHANG Jin
2005-01-01
@@ Multi-scale decomposition by wavelet transform has been performed to velocity time sequences obtained by fine measurements of turbulent boundary layer flow. A conditional sampling technique for detecting multi-scale coherent eddy structures in turbulent field is proposed by using multi-scale instantaneous intensity factor and flatness factor of wavelet coefficients. Although the number of coherent eddy structures in the turbulent boundary layer is very small, their energy percentage with respect to the turbulence kinetic energy is high. Especially in buffer layer, the energy percentages of coherent structures are significantly higher than those in the logarithmic layer, indicating that the buffer layer is the most active region in the turbulent boundary layer. These multi-scale coherent eddy structures share some common dynamical characteristics and are responsible for the anomalous scaling law in the turbulent boundary layer.
Saether, Erik; Hochhalter, Jacob D.; Glaessgen, Edward H.; Mishin, Yuri
2014-01-01
A multiscale modeling methodology is developed for structurally-graded material microstructures. Molecular dynamic (MD) simulations are performed at the nanoscale to determine fundamental failure mechanisms and quantify material constitutive parameters. These parameters are used to calibrate material processes at the mesoscale using discrete dislocation dynamics (DD). Different grain boundary interactions with dislocations are analyzed using DD to predict grain-size dependent stress-strain behavior. These relationships are mapped into crystal plasticity (CP) parameters to develop a computationally efficient finite element-based DD/CP model for continuum-level simulations and complete the multiscale analysis by predicting the behavior of macroscopic physical specimens. The present analysis is focused on simulating the behavior of a graded microstructure in which grain sizes are on the order of nanometers in the exterior region and transition to larger, multi-micron size in the interior domain. This microstructural configuration has been shown to offer improved mechanical properties over homogeneous coarse-grained materials by increasing yield stress while maintaining ductility. Various mesoscopic polycrystal models of structurally-graded microstructures are generated, analyzed and used as a benchmark for comparison between multiscale DD/CP model and DD predictions. A final series of simulations utilize the DD/CP analysis method exclusively to study macroscopic models that cannot be analyzed by MD or DD methods alone due to the model size.
Multi-scale analysis and characterization of the ITER pre-compression rings
Foussat, A.; Park, B.; Rajainmaki, H.
2014-01-01
The toroidal field (TF) system of ITER Tokamak composed of 18 "D" shaped Toroidal Field (TF) coils during an operating scenario experiences out-of-plane forces caused by the interaction between the 68kA operating TF current and the poloidal magnetic fields. In order to keep the induced static and cyclic stress range in the intercoil shear keys between coils cases within the ITER allowable limits [1], centripetal preload is introduced by means of S2 fiber-glass/epoxy composite pre-compression rings (PCRs). Those PCRs consist in two sets of three rings, each 5 m in diameter and 337 × 288 mm in cross-section, and are installed at the top and bottom regions to apply a total resultant preload of 70 MN per TF coil equivalent to about 400 MPa hoop stress. Recent developments of composites in the aerospace industry have accelerated the use of advanced composites as primary structural materials. The PCRs represent one of the most challenging composite applications of large dimensions and highly stressed structures operating at 4 K over a long term life. Efficient design of those pre-compression composite structures requires a detailed understanding of both the failure behavior of the structure and the fracture behavior of the material. Due to the inherent difficulties to carry out real scale testing campaign, there is a need to develop simulation tools to predict the multiple complex failure mechanisms in pre-compression rings. A framework contract was placed by ITER Organization with SENER Ingenieria y Sistemas SA to develop multi-scale models representative of the composite structure of the Pre-compression rings based on experimental material data. The predictive modeling based on ABAQUS FEM provides the opportunity both to understand better how PCR composites behave in operating conditions and to support the development of materials by the supplier with enhanced performance to withstand the machine design lifetime of 30,000 cycles. The multi-scale stress analysis has
Directory of Open Access Journals (Sweden)
Johan Debayle
2011-05-01
Full Text Available An image analysis method has been developed in order to compute the velocity field of a granular medium (sand grains, mean diameter 600 μm submitted to different kinds of mechanical stresses. The differential method based on optical flow conservation consists in describing a dense motion field with vectors associated to each pixel. A multiscale, coarse-to-fine, analytical approach through tailor sized windows yields the best compromise between accuracy and robustness of the results, while enabling an acceptable computation time. The corresponding algorithmis presented and its validation discussed through different tests. The results of the validation tests of the proposed approach show that the method is satisfactory when attributing specific values to parameters in association with the size of the image analysis window. An application in the case of vibrated sand has been studied. An instrumented laboratory device provides sinusoidal vibrations and enables external optical observations of sand motion in 3D transparent boxes. At 50 Hz, by increasing the relative acceleration G, the onset and development of two convective rolls can be observed. An ultra fast camera records the grain avalanches, and several pairs of images are analysed by the proposed method. The vertical velocity profiles are deduced and allow to precisely quantify the dimensions of the fluidized region as a function of G.
Directory of Open Access Journals (Sweden)
Wen-Yao Pan
2015-01-01
Full Text Available Obstructive sleep apnea (OSA is an independent cardiovascular risk factor to which autonomic nervous dysfunction has been reported to be an important contributor. Ninety subjects recruited from the sleep center of a single medical center were divided into four groups: normal snoring subjects without OSA (apnea hypopnea index, AHI < 5, n = 11, mild OSA (5 ≤ AHI < 15, n = 10, moderate OSA (15 ≤ AHI < 30, n = 24, and severe OSA (AHI ≥ 30, n = 45. Demographic (i.e., age, gender, anthropometric (i.e., body mass index, neck circumference, and polysomnographic (PSG data were recorded and compared among the different groups. For each subject, R-R intervals (RRI from 10 segments of 10-minute electrocardiogram recordings during non-rapid eye movement sleep at stage N2 were acquired and analyzed for heart rate variability (HRV and sample entropy using multiscale entropy index (MEI that was divided into small scale (MEISS, scale 1–5 and large scale (MEILS, scale 6–10. Our results not only demonstrated that MEISS could successfully distinguish normal snoring subjects and those with mild OSA from those with moderate and severe disease, but also revealed good correlation between MEISS and AHI with Spearman correlation analysis (r = −0.684, p < 0.001. Therefore, using the two parameters of EEG and ECG, MEISS may serve as a simple preliminary screening tool for assessing the severity of OSA before proceeding to PSG analysis.
Multiscale integral analysis of a HT leakage in a fusion nuclear power plant
Velarde, M.; Fradera, J.; Perlado, J. M.; Zamora, I.; Martínez-Saban, E.; Colomer, C.; Briani, P.
2016-05-01
The present work presents an example of the application of an integral methodology based on a multiscale analysis that covers the whole tritium cycle within a nuclear fusion power plant, from a micro scale, analyzing key components where tritium is leaked through permeation, to a macro scale, considering its atmospheric transport. A leakage from the Nuclear Power Plants, (NPP) primary to the secondary side of a heat exchanger (HEX) is considered for the present example. Both primary and secondary loop coolants are assumed to be He. Leakage is placed inside the HEX, leaking tritium in elementary tritium (HT) form to the secondary loop where it permeates through the piping structural material to the exterior. The Heating Ventilation and Air Conditioning (HVAC) system removes the leaked tritium towards the NPP exhaust. The HEX is modelled with system codes and coupled to Computational Fluid Dynamic (CFD) to account for tritium dispersion inside the nuclear power plants buildings and in site environment. Finally, tritium dispersion is calculated with an atmospheric transport code and a dosimetry analysis is carried out. Results show how the implemented methodology is capable of assessing the impact of tritium from the microscale to the atmospheric scale including the dosimetric aspect.
Region of interest extraction based on multiscale visual saliency analysis for remote sensing images
Zhang, Yinggang; Zhang, Libao; Yu, Xianchuan
2015-01-01
Region of interest (ROI) extraction is an important component of remote sensing image processing. However, traditional ROI extraction methods are usually prior knowledge-based and depend on classification, segmentation, and a global searching solution, which are time-consuming and computationally complex. We propose a more efficient ROI extraction model for remote sensing images based on multiscale visual saliency analysis (MVS), implemented in the CIE L*a*b* color space, which is similar to visual perception of the human eye. We first extract the intensity, orientation, and color feature of the image using different methods: the visual attention mechanism is used to eliminate the intensity feature using a difference of Gaussian template; the integer wavelet transform is used to extract the orientation feature; and color information content analysis is used to obtain the color feature. Then, a new feature-competition method is proposed that addresses the different contributions of each feature map to calculate the weight of each feature image for combining them into the final saliency map. Qualitative and quantitative experimental results of the MVS model as compared with those of other models show that it is more effective and provides more accurate ROI extraction results with fewer holes inside the ROI.
Rong, Libin; Perelson, Alan S
2013-09-01
Chronic hepatitis C virus (HCV) infection remains a world-wide public health problem. Therapy with interferon and ribavirin leads to viral elimination in less than 50% of treated patients. New treatment options aiming at a higher cure rate are focused on direct-acting antiviral agents (DAAs), which directly interfere with different steps in the HCV life cycle. In this paper, we describe and analyze a recently developed multiscale model that predicts HCV dynamics under therapy with DAAs. The model includes both intracellular viral RNA replication and extracellular viral infection. We calculate the steady states of the model and perform a detailed stability analysis. With certain assumptions we obtain analytical approximations of the viral load decline after treatment initiation. One approximation agrees well with the prediction of the model, and can conveniently be used to fit patient data and estimate parameter values. We also discuss other possible ways to incorporate intracellular viral dynamics into the multiscale model.
A Systemic Analysis of Multiscale Deep Convective Variability over the Tropical Pacific.
Tung, Wen-Wen; Moncrieff, Mitchell W.; Gao, Jian-Bo
2004-07-01
The multiscale tropical deep convective variability over the Pacific Ocean is examined with the 4-month high-resolution deep convection index (ITBB) derived from satellite imagery. With a systemic view, the complex phenomenon is described with succinct parameters known as generalized dimensions associated with the correlation structures embedded in the observed time series, with higher-order dimensions emphasizing extreme convective events. It is suggested that convective activities of lifetimes ranging from 1 h to 21 days have interdependence across scales that can be described by a series of power laws; hence, a spectrum of generalized dimensions, that is, the ITBB time series is multifractal. The spatiotemporal features of the ITBB time series is preliminarily examined by changing the spatial domain from 0.1° × 0.1° to 25° × 25°. The multifractal features are weakened with increasing strength of spatial averaging but cannot be eliminated. Furthermore, the ITBB data has the property of long-range dependency, implying that its autocorrelation function decays with a power law in contrast to the zero or exponentially decaying autocorrelation functions for white and commonly used red noise processes generated from autoregressive models. Physically, this means that intensified convection tends to be followed by another intensified event, and vice versa for weakened events or droughts. Such tendency is stronger with larger domain averaging, probably due to more complete inclusion of larger-scale variability that has more definite trends, such as the supercloud clusters associated with the Madden Julian oscillation (MJO). The evolution of cloud clusters within an MJO event is studied by following the MJO system across the analysis domain for 21 days. Convective activities along the front, center, and rear parts of the MJO event continuously intensify while approaching the date line, indicating multifractal features in the range of 1 h to about 5 10 days
Use of multiscale zirconium alloy deformation models in nuclear fuel behavior analysis
Energy Technology Data Exchange (ETDEWEB)
Montgomery, Robert; Tomé, Carlos; Liu, Wenfeng; Alankar, Alankar; Subramanian, Gopinath; Stanek, Christopher
2017-01-01
Accurate prediction of cladding mechanical behavior is a key aspect of modeling nuclear fuel behavior, especially for conditions of pellet-cladding interaction (PCI), reactivity-initiated accidents (RIA), and loss of coolant accidents (LOCA). Current approaches to fuel performance modeling rely on empirical models for cladding creep, growth and plastic deformation, which are limited to the materials and conditions for which the models were developed. CASL has endeavored to improve upon this approach by incorporating a microstructurally-based, atomistically-informed, zirconium alloy mechanical deformation analysis capability into the BISON-CASL engineering scale fuel performance code. Specifically, the viscoplastic self-consistent (VPSC) polycrystal plasticity modeling approach, developed by Lebensohn and Tome´ [2], has been coupled with BISON-CASL to represent the mechanistic material processes controlling the deformation behavior of the cladding. A critical component of VPSC is the representation of the crystallographic orientation of the grains within the matrix material and the ability to account for the role of texture on deformation. The multiscale modeling of cladding deformation mechanisms allowed by VPSC far exceed the functionality of typical semi-empirical constitutive models employed in nuclear fuel behavior codes to model irradiation growth and creep, thermal creep, or plasticity. This paper describes the implementation of an interface between VPSC and BISON-CASL and provides initial results utilizing the coupled functionality.
Gierałtowski, J.; Żebrowski, J. J.; Baranowski, R.
2012-02-01
Human heart rate variability, in the form of time series of intervals between heart beats, shows complex, fractal properties. Recently, it was demonstrated many times that the fractal properties vary from point to point along the series, leading to multifractality. In this paper, we concentrate not only on the fact that the human heart rate has multifractal properties but also that these properties depend on the time scale in which the multifractality is measured. This time scale is related to the frequency band of the signal. We find that human heart rate variability appears to be far more complex than hitherto reported in the studies using a fixed time scale. We introduce a method called multiscale multifractal analysis (MMA), which allows us to extend the description of heart rate variability to include the dependence on the magnitude of the variability and time scale (or frequency band). MMA is relatively immune to additive noise and nonstationarity, including the nonstationarity due to inclusions into the time series of events of a different dynamics (e.g., arrhythmic events in sinus rhythm). The MMA method may provide new ways of measuring the nonlinearity of a signal, and it may help to develop new methods of medical diagnostics.
Multi-scale analysis of optic chiasmal compression by finite element modelling.
Wang, Xiaofei; Neely, Andrew J; McIlwaine, Gawn G; Lueck, Christian J
2014-07-18
The precise mechanism of bitemporal hemianopia (a type of partial visual field defect) is still not clear. Previous work has investigated this problem by studying the biomechanics of chiasmal compression caused by a pituitary tumour growing up from below the optic chiasm. A multi-scale analysis was performed using finite element models to examine both the macro-scale behaviour of the chiasm and the micro-scale interactions of the nerve fibres within it using representative volume elements. Possible effects of large deflection and non-linear material properties were incorporated. Strain distributions in the optic chiasm and optic nerve fibres were obtained from these models. The results of the chiasmal model agreed well with the limited experimental results available, indicating that the finite element modelling can be a useful tool for analysing chiasmal compression. Simulation results showed that the strain distribution in nasal (crossed) nerve fibres was much more nonuniform and locally higher than in temporal (uncrossed) nerve fibres. This strain difference between nasal and temporal nerve fibres may account for the phenomenon of bitemporal hemianopia.
Multi-scale Analysis of MEMS Sensors Subject to Drop Impacts
Directory of Open Access Journals (Sweden)
Sarah Zerbini
2007-09-01
Full Text Available The effect of accidental drops on MEMS sensors are examined within the frame-work of a multi-scale finite element approach. With specific reference to a polysilicon MEMSaccelerometer supported by a naked die, the analysis is decoupled into macro-scale (at dielength-scale and meso-scale (at MEMS length-scale simulations, accounting for the verysmall inertial contribution of the sensor to the overall dynamics of the device. Macro-scaleanalyses are adopted to get insights into the link between shock waves caused by the impactagainst a target surface and propagating inside the die, and the displacement/acceleration his-tories at the MEMS anchor points. Meso-scale analyses are adopted to detect the most stresseddetails of the sensor and to assess whether the impact can lead to possible localized failures.Numerical results show that the acceleration at sensor anchors cannot be considered an ob-jective indicator for drop severity. Instead, accurate analyses at sensor level are necessary toestablish how MEMS can fail because of drops.
Bhattacharjee, Satyaki; Matouš, Karel
2016-05-01
A new manifold-based reduced order model for nonlinear problems in multiscale modeling of heterogeneous hyperelastic materials is presented. The model relies on a global geometric framework for nonlinear dimensionality reduction (Isomap), and the macroscopic loading parameters are linked to the reduced space using a Neural Network. The proposed model provides both homogenization and localization of the multiscale solution in the context of computational homogenization. To construct the manifold, we perform a number of large three-dimensional simulations of a statistically representative unit cell using a parallel finite strain finite element solver. The manifold-based reduced order model is verified using common principles from the machine-learning community. Both homogenization and localization of the multiscale solution are demonstrated on a large three-dimensional example and the local microscopic fields as well as the homogenized macroscopic potential are obtained with acceptable engineering accuracy.
Stability analysis of titanium alloy milling by multiscale entropy and Hurst exponent
Rusinek, Rafał; Borowiec, Marek
2015-10-01
This paper discusses the problem of stability in a milling process for titanium super-alloy Ti6242. The phenomenon of chatter vibration is analysed by the multiscale entropy method and Hurst exponent. Although this problem is often considered based on stability lobe diagrams, theoretical findings do not always agree with experimental results. First, a stability lobe diagram is created based on parameters determined by impact testing. Next, cutting forces are measured in an experiment where the axial cutting depth is gradually increased. Finally, the obtained experimental signals are investigated with respect to stability using the multiscale entropy method and Hurst exponent.
A multiscale analysis of drought and pluvial mechanisms for the Southeastern United States
Kam, Jonghun; Sheffield, Justin; Wood, Eric F.
2014-06-01
The Southeast (SE) U.S. has experienced several severe droughts over the past 30 years, with the most recent drought during 2006-2008 causing agricultural impacts of $1 billion. However, the mechanisms that lead to droughts over the region and their persistence have been poorly understood due to the region's humid coastal environment and its complex climate. In this study, we carry out a multiscale analysis of drought mechanisms for the SE U.S. over 1979-2008 using the North American Regional Reanalysis (NARR) to identify conditions associated with drought and contrast with those associated with pluvials. These conditions include land surface drought propagation, land-atmosphere feedbacks, regional moisture sources, persistent atmospheric patterns, and larger-scale oceanic conditions. Typical conditions for SE U.S. droughts (pluvials) are identified as follows: (1) weaker (stronger) southerly meridional fluxes and weaker (stronger) westerly zonal fluxes, (2) strong moisture flux divergence (convergence) by transient eddies, and (3) strong (weak) coupling between the land surface and atmosphere. The NARR demonstrates that historic SE droughts are mainly derived from a combination of a strong North Atlantic subtropical high (NASH) and Icelandic Low (IL) during summer and winter, respectively, which peak 1 month earlier than the onset of the drought. The land surface plays a moderate role in drought occurrence over the SE via recycling of precipitation, and the oceans show an asymmetric influence on droughts and pluvials depending on the season. This study suggests that the NASH and IL can be used as a predictor for SE droughts at 1 month lead despite the overall that it represents an atmospheric forcing.
Jiang, Shan; Wang, Fang; Shen, Luming; Liao, Guiping; Wang, Lin
2017-03-01
Spectrum technology has been widely used in crop non-destructive testing diagnosis for crop information acquisition. Since spectrum covers a wide range of bands, it is of critical importance to extract the sensitive bands. In this paper, we propose a methodology to extract the sensitive spectrum bands of rapeseed using multiscale multifractal detrended fluctuation analysis. Our obtained sensitive bands are relatively robust in the range of 534 nm-574 nm. Further, by using the multifractal parameter (Hurst exponent) of the extracted sensitive bands, we propose a prediction model to forecast the Soil and plant analyzer development values ((SPAD), often used as a parameter to indicate the chlorophyll content) and an identification model to distinguish the different planting patterns. Three vegetation indices (VIs) based on previous work are used for comparison. Three evaluation indicators, namely, the root mean square error, the correlation coefficient, and the relative error employed in the SPAD values prediction model all demonstrate that our Hurst exponent has the best performance. Four rapeseed compound planting factors, namely, seeding method, planting density, fertilizer type, and weed control method are considered in the identification model. The Youden indices calculated by the random decision forest method and the K-nearest neighbor method show that our Hurst exponent is superior to other three Vis, and their combination for the factor of seeding method. In addition, there is no significant difference among the five features for other three planting factors. This interesting finding suggests that the transplanting and the direct seeding would make a big difference in the growth of rapeseed.
Multi-scale Tomographic Analysis of Ductile Fracture in Ultrahigh Strength Steels
Chan, Stephanie Christine
Three-dimensional tomographic characterization and analysis tools were developed to address microstructural evolution governing toughness, shear instability resistance, and fatigue strength in high-performance steels for naval applications. A multi-scale approach aims to capture this on the sub-micron and millimeter length scales by employing a suite of sectioning, imaging, and analyzing techniques. On the sub-micron scale, serial sectioning by focused ion beam (FIB) milling and scanning electron microscopy (SEM) resolved secondary grain-refining dispersions, microvoids, and primary particles in a modified-4330 steel shear band. On the micron scale, crack tips in modified-4330 and BlastAlloy160 steels were serial sectioned by metallographic polishing and optical microscopy to offer a three-dimensional picture of the void nucleation, growth, and coalescence stages involved in ductile fracture. Quantitative comparisons of the process zone, crack advance, zig-zag wavelength, crack opening displacement, void number density, void growth ratios, critical strain, and inclusion statistics illustrate the superior toughness of BlastAlloy160 over modified-4330 steel. Synchrotron X-ray computed microtomography of BlastAlloy160 crack tips validated serial sectioning methods by showing good corroboration in quantitative parameters. Lastly, three-dimensional reconstructions of fatigue nucleants in the form of non-metallic inclusion clusters and a sharp FIB-milled groove offer insight into early fatigue failure and fatigue crack microstructure interaction. The qualitative and quantitative information collected from the plethora of data will provide ample input and experimental basis for simulations and models of ductile fracture, toughness, and fatigue damage. Predictive modeling of failure is further possible because of three-dimensional characterization.
Use of multiscale zirconium alloy deformation models in nuclear fuel behavior analysis
Montgomery, Robert; Tomé, Carlos; Liu, Wenfeng; Alankar, Alankar; Subramanian, Gopinath; Stanek, Christopher
2017-01-01
Accurate prediction of cladding mechanical behavior is a key aspect of modeling nuclear fuel behavior, especially for conditions of pellet-cladding interaction (PCI), reactivity-initiated accidents (RIA), and loss of coolant accidents (LOCA). Current approaches to fuel performance modeling rely on empirical constitutive models for cladding creep, growth and plastic deformation, which are limited to the materials and conditions for which the models were developed. To improve upon this approach, a microstructurally-based zirconium alloy mechanical deformation analysis capability is being developed within the United States Department of Energy Consortium for Advanced Simulation of Light Water Reactors (CASL). Specifically, the viscoplastic self-consistent (VPSC) polycrystal plasticity modeling approach, developed by Lebensohn and Tomé [1], has been coupled with the BISON engineering scale fuel performance code to represent the mechanistic material processes controlling the deformation behavior of light water reactor (LWR) cladding. A critical component of VPSC is the representation of the crystallographic nature (defect and dislocation movement) and orientation of the grains within the matrix material and the ability to account for the role of texture on deformation. A future goal is for VPSC to obtain information on reaction rate kinetics from atomistic calculations to inform the defect and dislocation behavior models described in VPSC. The multiscale modeling of cladding deformation mechanisms allowed by VPSC far exceed the functionality of typical semi-empirical constitutive models employed in nuclear fuel behavior codes to model irradiation growth and creep, thermal creep, or plasticity. This paper describes the implementation of an interface between VPSC and BISON and provides initial results utilizing the coupled functionality.
Effects of salt on the expansion of starchy snacks: a multiscale analysis
Sman, van der R.G.M.; Broeze, J.
2014-01-01
We investigate the effect of salt on the expansion of starchy snacks during frying by means of a multiscale simulation model. This model has been developed earlier for starchy snacks without salt. The simulation results are analysed by means of the supplemented state diagram. We have found that the
A Mathematical Analysis of Atomistic-to-Continuum (AtC) Multiscale Coupling Methods
Energy Technology Data Exchange (ETDEWEB)
Gunzburger, Max
2013-11-13
We have worked on several projects aimed at improving the efficiency and understanding of multiscale methods, especially those applicable to problems involving atomistic-to-continuum coupling. Activities include blending methods for AtC coupling and efficient quasi-continuum methods for problems with long-range interactions.
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...
Hu, Meng; Liang, Hualou
2013-04-01
Generalized flash suppression (GFS), in which a salient visual stimulus can be rendered invisible despite continuous retinal input, provides a rare opportunity to directly study the neural mechanism of visual perception. Previous work based on linear methods, such as spectral analysis, on local field potential (LFP) during GFS has shown that the LFP power at distinctive frequency bands are differentially modulated by perceptual suppression. Yet, the linear method alone may be insufficient for the full assessment of neural dynamic due to the fundamentally nonlinear nature of neural signals. In this study, we set forth to analyze the LFP data collected from multiple visual areas in V1, V2 and V4 of macaque monkeys while performing the GFS task using a nonlinear method - adaptive multi-scale entropy (AME) - to reveal the neural dynamic of perceptual suppression. In addition, we propose a new cross-entropy measure at multiple scales, namely adaptive multi-scale cross-entropy (AMCE), to assess the nonlinear functional connectivity between two cortical areas. We show that: (1) multi-scale entropy exhibits percept-related changes in all three areas, with higher entropy observed during perceptual suppression; (2) the magnitude of the perception-related entropy changes increases systematically over successive hierarchical stages (i.e. from lower areas V1 to V2, up to higher area V4); and (3) cross-entropy between any two cortical areas reveals higher degree of asynchrony or dissimilarity during perceptual suppression, indicating a decreased functional connectivity between cortical areas. These results, taken together, suggest that perceptual suppression is related to a reduced functional connectivity and increased uncertainty of neural responses, and the modulation of perceptual suppression is more effective at higher visual cortical areas. AME is demonstrated to be a useful technique in revealing the underlying dynamic of nonlinear/nonstationary neural signal.
Multiscale Modeling of the Impact of Textile Fabrics Based on Hybrid Element Analysis
2010-05-19
Leighton RB, Sands M. The Feynman lectures on physics , definitive edition, vol. 1. Addison-Wesley Publishing Company; 2006. ISBN 0- 8053-9046-4. [21...model with distance away from the impact zone based on the multiscale nature of the fabric architecture and the physics of the impact event. Solid...nature of the fabric architecture and the physics of the impact event. Solid elements are used to discretize the yarns around the impact region
Institute of Scientific and Technical Information of China (English)
Xavier Blanc; Claude Le Bris; Prédéric Legol
2007-01-01
In order to describe a solid which deforms smoothly in some region,but non smoothly in some other region,many multiscale methods have been recently proposed that aim at coupling an atonfistic model (discrete mechanics)with a macroscopic model(continuum mechanics).We provide here a theoretical basis for such a coupling in a one-dimensional setting,in the case of convex energy.
Directory of Open Access Journals (Sweden)
Chia-Hsuan Lee
2015-11-01
Full Text Available The goal of this study was to investigate the parameters affecting exergame performance using multi-scale entropy analysis, with the aim of informing the design of exergames for personalized balance training. Test subjects’ center of pressure (COP displacement data were recorded during exergame play to examine their balance ability at varying difficulty levels of a balance-based exergame; the results of a multi-scale entropy-based analysis were then compared to traditional COP indicators. For games involving static posture frames, variation in posture frame travel time was found to significantly affect the complexity of both the anterior-posterior (MSE-AP and medio-lateral (MSE-ML components of balancing movements. However, in games involving dynamic posture frames, only MSE-AP was found to be sensitive to the variation of parameters, namely foot-lifting speed. Findings were comparable to the COP data published by Sun et al., indicating that the use of complexity data is a feasible means of distinguishing between different parameter sets and of understanding how human design considerations must be taken into account in exergame development. Not only can this method be used as another assessment index in the future, it can also be used in the optimization of parameters within the virtual environments of exergames.
Silva, Luiz Eduardo Virgilio; Lataro, Renata Maria; Castania, Jaci Airton; da Silva, Carlos Alberto Aguiar; Valencia, Jose Fernando; Murta, Luiz Otavio; Salgado, Helio Cesar; Fazan, Rubens; Porta, Alberto
2016-07-01
The analysis of heart rate variability (HRV) by nonlinear methods has been gaining increasing interest due to their ability to quantify the complexity of cardiovascular regulation. In this study, multiscale entropy (MSE) and refined MSE (RMSE) were applied to track the complexity of HRV as a function of time scale in three pathological conscious animal models: rats with heart failure (HF), spontaneously hypertensive rats (SHR), and rats with sinoaortic denervation (SAD). Results showed that HF did not change HRV complexity, although there was a tendency to decrease the entropy in HF animals. On the other hand, SHR group was characterized by reduced complexity at long time scales, whereas SAD animals exhibited a smaller short- and long-term irregularity. We propose that short time scales (1 to 4), accounting for fast oscillations, are more related to vagal and respiratory control, whereas long time scales (5 to 20), accounting for slow oscillations, are more related to sympathetic control. The increased sympathetic modulation is probably the main reason for the lower entropy observed at high scales for both SHR and SAD groups, acting as a negative factor for the cardiovascular complexity. This study highlights the contribution of the multiscale complexity analysis of HRV for understanding the physiological mechanisms involved in cardiovascular regulation.
Analysis of High Order Difference Methods for Multiscale Complex Compressible Flows
Sjoegreen, Bjoern; Yee, H. C.; Tang, Harry (Technical Monitor)
2002-01-01
Accurate numerical simulations of complex multiscale compressible viscous flows, especially high speed turbulence combustion and acoustics, demand high order schemes with adaptive numerical dissipation controls. Standard high resolution shock-capturing methods are too dissipative to capture the small scales and/or long-time wave propagations without extreme grid refinements and small time steps. An integrated approach for the control of numerical dissipation in high order schemes with incremental studies was initiated. Here we further refine the analysis on, and improve the understanding of the adaptive numerical dissipation control strategy. Basically, the development of these schemes focuses on high order nondissipative schemes and takes advantage of the progress that has been made for the last 30 years in numerical methods for conservation laws, such as techniques for imposing boundary conditions, techniques for stability at shock waves, and techniques for stable and accurate long-time integration. We concentrate on high order centered spatial discretizations and a fourth-order Runge-Kutta temporal discretizations as the base scheme. Near the bound-aries, the base scheme has stable boundary difference operators. To further enhance stability, the split form of the inviscid flux derivatives is frequently used for smooth flow problems. To enhance nonlinear stability, linear high order numerical dissipations are employed away from discontinuities, and nonlinear filters are employed after each time step in order to suppress spurious oscillations near discontinuities to minimize the smearing of turbulent fluctuations. Although these schemes are built from many components, each of which is well-known, it is not entirely obvious how the different components be best connected. For example, the nonlinear filter could instead have been built into the spatial discretization, so that it would have been activated at each stage in the Runge-Kutta time stepping. We could think
Wang, Y. D.; Liu, K. Y.; Yang, Y. S.; Ren, Y. Q.; Hu, T.; Deng, B.; Xiao, T. Q.
2016-04-01
Three dimensional (3D) characterization of shales has recently attracted wide attentions in relation to the growing importance of shale oil and gas. Obtaining a complete 3D compositional distribution of shale has proven to be challenging due to its multi-scale characteristics. A combined multi-energy X-ray micro-CT technique and data-constrained modelling (DCM) approach has been used to quantitatively investigate the multi-scale mineral and porosity distributions of a heterogeneous shale from the Junger Basin, northwestern China by sub-sampling. The 3D sub-resolution structures of minerals and pores in the samples are quantitatively obtained as the partial volume fraction distributions, with colours representing compositions. The shale sub-samples from two areas have different physical structures for minerals and pores, with the dominant minerals being feldspar and dolomite, respectively. Significant heterogeneities have been observed in the analysis. The sub-voxel sized pores form large interconnected clusters with fractal structures. The fractal dimensions of the largest clusters for both sub-samples were quantitatively calculated and found to be 2.34 and 2.86, respectively. The results are relevant in quantitative modelling of gas transport in shale reservoirs.
Unsupervised DInSAR processing chain for multi-scale displacement analysis
Casu, Francesco; Manunta, Michele
2016-04-01
Earth Observation techniques can be very helpful for the estimation of several sources of ground deformation due to their characteristics of large spatial coverage, high resolution and cost effectiveness. In this scenario, Differential Synthetic Aperture Radar Interferometry (DInSAR) is one of the most effective methodologies for its capability to generate spatially dense deformation maps at both global and local spatial scale, with centimeter to millimeter accuracy. DInSAR exploits the phase difference (interferogram) between SAR image pairs relevant to acquisitions gathered at different times, but with the same illumination geometry and from sufficiently close flight tracks, whose separation is typically referred to as baseline. Among several, the SBAS algorithm is one of the most used DInSAR approaches and it is aimed at generating displacement time series at a multi-scale level by exploiting a set of small baseline interferograms. SBAS, and generally DInSAR, has taken benefit from the large availability of spaceborne SAR data collected along years by several satellite systems, with particular regard to the European ERS and ENVISAT sensors, which have acquired SAR images worldwide during approximately 20 years. Moreover, since 2014 the new generation of Copernicus Sentinel satellites has started to acquire data with a short revisit time (12 days) and a global coverage policy, thus flooding the scientific EO community with an unprecedent amount of data. To efficiently manage such amount of data, proper processing facilities (as those coming from the emerging Cloud Computing technologies) have to be used, as well as novel algorithms aimed at their efficient exploitation have to be developed. In this work we present a set of results achieved by exploiting a recently proposed implementation of the SBAS algorithm, namely Parallel-SBAS (P-SBAS), which allows us to effectively process, in an unsupervised way and in a limited time frame, a huge number of SAR images
An integrated multi-scale risk analysis procedure for pluvial flooding
Tader, Andreas; Mergili, Martin; Jäger, Stefan; Glade, Thomas; Neuhold, Clemens; Stiefelmeyer, Heinz
2016-04-01
Mitigation of or adaptation to the negative impacts of natural processes on society requires a better understanding of the spatio-temporal distribution not only of the processes themselves, but also of the elements at risk. Information on their values, exposures and vulnerabilities towards the expected impact magnitudes/intensities of the relevant processes is needed. GIS-supported methods are particularly useful for integrated spatio-temporal analyses of natural processes and their potential consequences. Hereby, pluvial floods are of particular concern for many parts of Austria. The overall aim of the present study is to calculate the hazards emanating from pluvial floods, to determine the exposure of given elements at risk, to determine their vulnerabilities towards given pluvial flood hazards and to analyze potential consequences in terms of monetary losses. The whole approach builds on data available on a national scale. We introduce an integrated, multi-scale risk analysis procedure with regard to pluvial flooding. Focusing on the risk to buildings, we firstly exemplify this procedure with a well-documented event in the city of Graz (Austria), in order to highlight the associated potentials and limitations. Secondly, we attempt to predict the possible consequences of pluvial flooding triggered by rainfall events with recurrence intervals of 30, 100 and 300 years. (i) We compute spatially distributed inundation depths using the software FloodArea. Infiltration capacity and surface roughness are estimated from the land cover units given by the official cadastre. Various assumptions are tested with regard to the inflow to the urban sewer system. (ii) Based on the inundation depths and the official building register, we employ a set of rules and functions to deduce the exposure, vulnerability and risk for each building. A risk indicator for each building, expressed as the expected damage associated to a given event, is derived by combining the building value and
Energy Technology Data Exchange (ETDEWEB)
Antrett, Philipp [RWTH Aachen Univ. (Germany). Energy and Mineral Resources Group
2013-06-01
Outstanding Ph.D. thesis nominated for a Springer Theses Prize by the RWTH Aachen University, Germany. Uses various approaches and covers a broad range of disciplines. Integrated study, carried out on multiple scales with state of the art technical equipment, that only few laboratories can offer worldwide. ''The thesis of Philipp Antrett is focused on reservoir properties, petrography, lithofacies and sedimentology, core analysis and nanoporosity studies. It will be of major interest for colleagues involved in the exploration and production of tight gas reservoirs in Northern Europe and elsewhere.'' - Francois Roure, August 2012 This thesis describes a multidisciplinary, multiscale approach to the analysis of tight gas reservoirs. It focused initially on the facies architecture of a Permian tight gas field in the Southern Permian Basin (SPB), East Frisia, northern Germany. To improve field development, 3D seismic data, wireline and core data were compared to a reservoir analogue in the Panamint Valley, California, United States. In addition to the large scale approach, a work flow that investigates microporosity by combining Scanning Electron Microscopy-Broad Ion Beam (SEM-BIB) and optical microscopy was developed. For a better understanding of the depositional environment and reservoir rock distribution in the SPB, a sedimentary facies analysis of four cores from the tight gas field in East Frisia was compared to a second study area in northern central Germany. This study demonstrates that tight gas exploration and production requires multidisciplinary, multiscale approaches beyond standard seismic interpretation work flows to better understand the temporal and spatial evolution of these complex reservoirs.
Multiscale in situ analysis of the role of dyskerin in lung cancer cells.
Fernandez-Garcia, Ignacio; Marcos, Tamara; Muñoz-Barrutia, Arrate; Serrano, Diego; Pio, Ruben; Montuenga, Luis M; Ortiz-de-Solorzano, Carlos
2013-02-01
Dyskerin is one of the three subunits of the telomerase ribonucleoprotein (RNP) complex. Very little is known about the role of dyskerin in the biology of the telomeres in cancer cells. In this study, we use a quantitative, multiscale 3D image-based in situ method and several molecular techniques to show that dyskerin is overexpressed in lung cancer cell lines. Furthermore, we show that dyskerin expression correlates with telomere length both at the cell population level--cells with higher dyskerin expression have short telomeres--and at the single cell level--the shortest telomeres of the cell are spatially associated with areas of concentration of dyskerin proteins. Using this in vitro model, we also show that exogenous increase in dyskerin expression confers resistance to telomere shortening caused by a telomerase inactivating drug. Finally, we show that resistance is achieved by the recovery of telomerase activity associated with dyskerin. In summary, using a novel multiscale image-based in situ method, we show that, in lung cancer cell lines, dyskerin responds to continuous telomere attrition by increasing the telomerase RNP activity, which in turn provides resistance to telomere shortening.
Raghib, M; Levin, S A; Kevrekidis, I G
2010-06-01
We propose a (time) multiscale method for the coarse-grained analysis of collective motion and decision-making in self-propelled particle models of swarms comprising a mixture of 'naïve' and 'informed' individuals. The method is based on projecting the particle configuration onto a single 'meta-particle' that consists of the elongation of the flock together with the mean group velocity and position. We find that the collective states can be associated with the transient and asymptotic transport properties of the random walk followed by the meta-particle, which we assume follows a continuous time random walk (CTRW). These properties can be accurately predicted at the macroscopic level by an advection-diffusion equation with memory (ADEM) whose parameters are obtained from a mean group velocity time series obtained from a single simulation run of the individual-based model.
Topology in galaxy distributions: method for a multi-scale analysis. A use of the wavelet transform.
Escalera, E.; MacGillivray, H. T.
1995-06-01
We report the 2D analysis of distributions of galaxies in a search for structures on all scales, from groups up to superclusters (including the identification of voids), based on the use of the wavelet transform. The wavelet method is an objective, multi-scale technique which gives the position, dimension and probability for each individual feature (both structures and voids) detected. We are currently performing the analysis on data from the COSMOS/UKST Southern Sky Galaxy Catalogue. The subsample used in our investigation contains some 2.5x10^6^ galaxies in an area of ~140x45 degrees around the South Galactic Pole. This is the first search for multi-scale objects on such an extended database, allowing us to cover many related topics in present-day Cosmology: realisation of superclusters as large-scale entities in their own right (as opposed to being considered merely as regions of enhanced cluster numbers); improvement in the definition of clusters of galaxies with a new approach to their general behaviour (distribution, typical sizes, state of evolution, etc.); and the objective characterisation of voids, which is exclusive to the wavelet method. In the present paper, we demonstrate the power of the technique by applying it to a selected field covering approximately 3000deg^2^ in the Grus-Sculptor region. In this area, we find 7 large scale structures (of more than 5 degrees in extent) and 26 structures of smaller scales (cluster-sized down to 1 degree, or group-sized down to 0.5 degrees). Sixteen of these small scale aggregates are connected with the large scale structures while ten appear isolated in the field. All these features are significant, having high confidence levels for detection. Voids are also detected in this area, likewise with high significance levels.
Giampietro, Mario; Sorman, Alevgül H
2013-01-01
The vast majority of the countries of the world are now facing an imminent energy crisis, particularly the USA, China, India, Japan and EU countries, but also developing countries having to boost their economic growth precisely when more powerful economies will prevent them from using the limited supply of fossil energy. Despite this crisis, current protocols of energy accounting have been developed for dealing with fossil energy exclusively and are therefore not useful for the analysis of alternative energy sources. The first part of the book illustrates the weakness of existing analyses of energy problems: the science of energy was born and developed neglecting the issue of scale. The authors argue that it is necessary to adopt more complex protocols of accounting and analysis in order to generate robust energy scenarios and effective assessments of the quality of alternative energy sources. The second part of the book introduces the concept of energetic metabolism of modern societies and uses empirical res...
3D多尺度几何分析研究进展%Advances in Three-Dimensional Multiscale Geometrical Analysis
Institute of Scientific and Technical Information of China (English)
宋传鸣; 赵长伟; 刘丹; 王相海
2015-01-01
Three-Dimensional (3D) multiscale geometrical analysis is the technological fundamental for the processing of digital visual media, such as images, videos, and geometrical models. Its objective is to efficiently represent the point singularity, curve singularity, as well as surface singularity presented in those visual media. This study first reviews the research advances in two-dimensional (2D) multiscale geometrical analysis. It then elaborates on the development of 3D multiscale geometrical analysis for video according to the capability evolution in capturing singularity and nonlinear approximation efficiency improvement of various transforms. State-of-the-Art 3D multiscale geometrical analysis is classified into three categories: the extended multiscale geometrical analysis from 2D basis functions, the multiscale geometrical analysis based on 3D basis function, and the multiscale geometrical analysis based on spatiotemporal non-local correlation. The basic ideas of typical transforms are thoroughly discussed subsequently, and so are their nonlinear approximation efficiency, computational complexity, advantages, and disadvantages. Meanwhile, this study also presents a general review on the development of the 3D multiscale geometrical analysis for geometrical models. Based on the study above, the development trend of the 3D multiscale geometrical analysis is forecast in the near future.%3D多尺度几何分析是图像、视频和几何模型等数字可视媒体处理的技术基础,其目的在于高效地表示这些媒体中存在的点、线、面奇异.为此,依据不同变换捕获奇异的能力演进及其非线性逼近效率的提高,从 2D 图像多尺度几何分析的研究进展切入,着重阐述视频3D多尺度几何分析的发展,并将其归纳为3类:由2D基函数直接扩展的3D多尺度几何分析、基于3D基函数的3D多尺度几何分析和基于时空非局部相关性的3D多尺度几何分析,深入探讨了各种典型变换
Energy Technology Data Exchange (ETDEWEB)
Speck, D E
2008-04-28
The Multiscale Epidemiologic/Economic Simulation and Analysis (MESA) Decision Support System (DSS) is the product of investments that began in FY05 by the Department of Homeland Security (DHS) Science and Technology Directorate and continue today with joint funding by both DHS and the US Department of Agriculture (USDA). The DSS consists of a coupled epidemiologic/economic model, a standalone graphical user interface (GUI) that supports both model setup and post-analysis, and a Scenario Bank archive to store all content related to foreign animal disease (FAD) studies. The MESA epi model is an object-oriented, agent-based, stochastic, spatio-temporal simulator that parametrically models FAD outbreaks and response strategies from initial disease introduction to conclusion over local, regional, and national scales. Through its output database, the epi model couples to an economic model that calculates farm-level impacts from animal infections, responsive control strategies and loss of trade. The MESA architecture contains a variety of internal models that implement the major components of the epi simulation, including disease introduction, intra-herd spread, inter-herd spread (direct and indirect), detection, and various control strategies (movement restrictions, culling, vaccination) in a highly configurable and extensible fashion. MESA development was originally focused to support investigations into the economic and agricultural industry impacts associated with Foot-and-Mouth Disease (FMD outbreaks). However, it has been adapted to other FADs such has Highly Pathogenic Avian Influenza (HPAI), Classical Swine Fever (CSF) and Exotic Newcastle Disease (END). The MESA model is highly parameterized and employs an extensible architecture that permits straightforward addition of new component models (e.g., alternative disease spread approaches) when necessary. Since its inception, MESA has been developed with a requirement to enable simulation of the very large scale
Adjoint Based A Posteriori Analysis of Multiscale Mortar Discretizations with Multinumerics
Tavener, Simon
2013-01-01
In this paper we derive a posteriori error estimates for linear functionals of the solution to an elliptic problem discretized using a multiscale nonoverlapping domain decomposition method. The error estimates are based on the solution of an appropriately defined adjoint problem. We present a general framework that allows us to consider both primal and mixed formulations of the forward and adjoint problems within each subdomain. The primal subdomains are discretized using either an interior penalty discontinuous Galerkin method or a continuous Galerkin method with weakly imposed Dirichlet conditions. The mixed subdomains are discretized using Raviart- Thomas mixed finite elements. The a posteriori error estimate also accounts for the errors due to adjoint-inconsistent subdomain discretizations. The coupling between the subdomain discretizations is achieved via a mortar space. We show that the numerical discretization error can be broken down into subdomain and mortar components which may be used to drive adaptive refinement.Copyright © by SIAM.
A multiscale physical model for the transient analysis of PEM water electrolyzer anodes.
Oliveira, Luiz Fernando L; Laref, Slimane; Mayousse, Eric; Jallut, Christian; Franco, Alejandro A
2012-08-07
Polymer electrolyte membrane water electrolyzers (PEMWEs) are electrochemical devices that can be used for the production of hydrogen. In a PEMWE the anode is the most complex electrode to study due to the high overpotential of the oxygen evolution reaction (OER), not widely understood. A physical bottom-up multi-scale transient model describing the operation of a PEMWE anode is proposed here. This model includes a detailed description of the elementary OER kinetics in the anode, a description of the non-equilibrium behavior of the nanoscale catalyst-electrolyte interface, and a microstructural-resolved description of the transport of charges and O(2) at the micro and mesoscales along the whole anode. The impact of different catalyst materials on the performance of the PEMWE anode, and a study of sensitivity to the operation conditions are evaluated from numerical simulations and the results are discussed in comparison with experimental data.
Multi-scale analysis of the European airspace using network community detection.
Directory of Open Access Journals (Sweden)
Gérald Gurtner
Full Text Available We show that the European airspace can be represented as a multi-scale traffic network whose nodes are airports, sectors, or navigation points and links are defined and weighted according to the traffic of flights between the nodes. By using a unique database of the air traffic in the European airspace, we investigate the architecture of these networks with a special emphasis on their community structure. We propose that unsupervised network community detection algorithms can be used to monitor the current use of the airspace and improve it by guiding the design of new ones. Specifically, we compare the performance of several community detection algorithms, both with fixed and variable resolution, and also by using a null model which takes into account the spatial distance between nodes, and we discuss their ability to find communities that could be used to define new control units of the airspace.
Multi-scale analysis of the European airspace using network community detection
Gurtner, Gérald; Cipolla, Marco; Lillo, Fabrizio; Mantegna, Rosario Nunzio; Miccichè, Salvatore; Pozzi, Simone
2013-01-01
We show that the European airspace can be represented as a multi-scale traffic network whose nodes are airports, sectors, or navigation points and links are defined and weighted according to the traffic of flights between the nodes. By using a unique database of the air traffic in the European airspace, we investigate the architecture of these networks with a special emphasis on their community structure. We propose that unsupervised network community detection algorithms can be used to monitor the current use of the airspaces and improve it by guiding the design of new ones. Specifically, we compare the performance of three community detection algorithms, also by using a null model which takes into account the spatial distance between nodes, and we discuss their ability to find communities that could be used to define new control units of the airspace.
Wavelet spectrum analysis on energy transfer of multi-scale structures in wall turbulence
Institute of Scientific and Technical Information of China (English)
Zhen-yan XIA; Yan TIAN; Nan JIANG
2009-01-01
The streamwise velocity components at different vertical heights in wall turbulence were measured. Wavelet transform was used to study the turbulent energy spectra, indicating that the global spectrum results from the weighted average of Fourier spectrum based on wavelet scales. Wavelet transform with more vanishing moments can express the declining of turbulent spectrum. The local wavelet spectrum shows that the physical phenomena such as deformation or breakup of eddies are related to the vertical position in the boundary layer, and the energy-containing eddies exist in a multi-scale form. Moreover, the size of these eddies increases with the measured points moving out of the wall. In the buffer region, the small scale energy-containing eddies with higher frequency are excited. In the outer region, the maximal energy is concentrated in the low-frequency large-scale eddies, and the frequency domain of energy-containing eddies becomes narrower.
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.
Novel Materials & Multi-scale Analysis of the Superconducting State in Iron Based Superconductors
Sefat, Athena S.
2015-03-01
The understanding of the fundamental nature of a material's superconducting state is of crucial importance, if superconductors are to fulfill their promise for widespread use in energy-related needs. Our research applies multi-scale characterization techniques to study and probe the nuclear, electronic, and magnetic details of single crystals. The importance of such broad investigative work is demonstrated in our recent publication on praseodymium-doped BaFe2As2 for which non-uniform local distortions through isolated Pr atoms do not provide percolation path superconductivity. For CaFe2As2, it is found that large Fermi-surface reconstruction in the non-magnetic phase causes a non-superconducting ground state, while different crystalline domains with varying lattice parameters are identified. For Cu-doped BaFe2As2 it is found that orthorhombic distortion below Ts leads to magnetically ordered state of FeAs planes, hence no superconductivity. Studies of this nature can yield groundbreaking results by demonstrating that many parameters can compete in a bulk material and even be spatially and electronically non-homogenous on nanometers. This work was primarily supported by the U. S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Science and Engineering Division.
MRI-Based Multiscale Model for Electromagnetic Analysis in the Human Head with Implanted DBS
Iacono, Maria Ida; Makris, Nikos; Mainardi, Luca; Angelone, Leonardo M.; Bonmassar, Giorgio
2013-01-01
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. PMID:23956789
Time-Varying, Multi-Scale Adaptive System Reliability Analysis of Lifeline Infrastructure Networks
Energy Technology Data Exchange (ETDEWEB)
Gearhart, Jared Lee [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kurtz, Nolan Scot [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2014-09-01
The majority of current societal and economic needs world-wide are met by the existing networked, civil infrastructure. Because the cost of managing such infrastructure is high and increases with time, risk-informed decision making is essential for those with management responsibilities for these systems. To address such concerns, a methodology that accounts for new information, deterioration, component models, component importance, group importance, network reliability, hierarchical structure organization, and efficiency concerns has been developed. This methodology analyzes the use of new information through the lens of adaptive Importance Sampling for structural reliability problems. Deterioration, multi-scale bridge models, and time-variant component importance are investigated for a specific network. Furthermore, both bridge and pipeline networks are studied for group and component importance, as well as for hierarchical structures in the context of specific networks. Efficiency is the primary driver throughout this study. With this risk-informed approach, those responsible for management can address deteriorating infrastructure networks in an organized manner.
Multi-Scale Visualization Analysis of Bus Flow Average Travel Speed in Qingdao
Yong, HAN; Man, GAO; Xiao-Lei, ZHANG; Jie, LI; Ge, CHEN
2016-11-01
Public transportation is a kind of complex spatiotemporal behaviour. The traffic congestion and environmental pollution caused by the increase in private cars is becoming more and more serious in our city. Spatiotemporal data visualization is an effective tool for studying traffic, transforming non-visual data into recognizable images, which can reveal where/when congestion is formed, developed and disappeared in space and time simultaneously. This paper develops a multi-scale visualization of average travel speed derived from floating bus data, to enable congestion on urban bus networks to be shown and analyzed. The techniques of R language, Echarts, WebGL are used to draw statistical pictures and 3D wall map, which show the congestion in Qingdao from the view of space and time. The results are as follows:(1) There is a more severely delay in Shibei and Shinan areas than Licun and Laoshan areas; (2) The high congestion usually occurs on Hong Kong Middle Road, Shandong Road, Nanjing Road, Liaoyang West Road and Taiping Road;(3) There is a similar law from Monday to Sunday that the congestion is severer in the morning and evening rush hours than other hours; (4) On Monday morning the severity of congestion is higher than on Friday morning, and on Friday evening the severity is higher than on Monday evening. The research results will help to improve the public transportation of Qingdao.
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.
Multi-scale and multi-fractal analysis of pressure fluctuation in slurry bubble column bed reactor
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
The Daubechies second order wavelet was applied to decompose pressure fluctuation signals with the gas flux varying from 0.18 to 0.90 m3/h and the solid mass fraction from 0 to 20% and scales 1-9 detail signals and the 9th scale approximation signals. The pressure signals were studied by multi-scale and R/S analysis method. Hurst analysis method was applied to analyze multi-fractal characteristics of different scale signals. The results show that the characteristics of mono-fractal under scale 1 and scale 2, and bi-fractal under scale 3-9 are effective in deducing the hydrodynamics in slurry bubbling flow system. The measured pressure signals are decomposed to micro-scale signals, meso-scale signals and macro-scale signals. Micro-scale and macro-scale signals are of mono-fractal characteristics, and meso-scale signals are of bi-fractal characteristics. By analyzing energy distribution of different scale signals, it is shown that pressure fluctuations mainly reflects meso-scale interaction between the particles and the bubble.
Li, Rui; Wang, Jun
2016-01-01
A financial price model is developed based on the voter interacting system in this work. The Lempel-Ziv complexity is introduced to analyze the complex behaviors of the stock market. Some stock market stylized facts including fat tails, absence of autocorrelation and volatility clustering are investigated for the proposed price model firstly. Then the complexity of fluctuation behaviors of the real stock markets and the proposed price model are mainly explored by Lempel-Ziv complexity (LZC) analysis and multi-scale weighted-permutation entropy (MWPE) analysis. A series of LZC analyses of the returns and the absolute returns of daily closing prices and moving average prices are performed. Moreover, the complexity of the returns, the absolute returns and their corresponding intrinsic mode functions (IMFs) derived from the empirical mode decomposition (EMD) with MWPE is also investigated. The numerical empirical study shows similar statistical and complex behaviors between the proposed price model and the real stock markets, which exhibits that the proposed model is feasible to some extent.
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
Bush Encroachment Mapping for Africa - Multi-Scale Analysis with Remote Sensing and GIS
Graw, V. A. M.; Oldenburg, C.; Dubovyk, O.
2015-12-01
Bush encroachment describes a global problem which is especially facing the savanna ecosystem in Africa. Livestock is directly affected by decreasing grasslands and inedible invasive species which defines the process of bush encroachment. For many small scale farmers in developing countries livestock represents a type of insurance in times of crop failure or drought. Among that bush encroachment is also a problem for crop production. Studies on the mapping of bush encroachment so far focus on small scales using high-resolution data and rarely provide information beyond the national level. Therefore a process chain was developed using a multi-scale approach to detect bush encroachment for whole Africa. The bush encroachment map is calibrated with ground truth data provided by experts in Southern, Eastern and Western Africa. By up-scaling location specific information on different levels of remote sensing imagery - 30m with Landsat images and 250m with MODIS data - a map is created showing potential and actual areas of bush encroachment on the African continent and thereby provides an innovative approach to map bush encroachment on the regional scale. A classification approach links location data based on GPS information from experts to the respective pixel in the remote sensing imagery. Supervised classification is used while actual bush encroachment information represents the training samples for the up-scaling. The classification technique is based on Random Forests and regression trees, a machine learning classification approach. Working on multiple scales and with the help of field data an innovative approach can be presented showing areas affected by bush encroachment on the African continent. This information can help to prevent further grassland decrease and identify those regions where land management strategies are of high importance to sustain livestock keeping and thereby also secure livelihoods in rural areas.
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.
Zhang, Xiancheng; Noda, Shigeho; Himeno, Ryutaro; Liu, Hao
2017-02-01
We present a novel methodology and strategy to predict pressures and flow rates in the global cardiovascular network in different postures varying from supine to upright. A closed-loop, multiscale mathematical model of the entire cardiovascular system (CVS) is developed through an integration of one-dimensional (1D) modeling of the large systemic arteries and veins, and zero-dimensional (0D) lumped-parameter modeling of the heart, the cardiac-pulmonary circulation, the cardiac and venous valves, as well as the microcirculation. A versatile junction model is proposed and incorporated into the 1D model to cope with splitting and/or merging flows across a multibranched junction, which is validated to be capable of estimating both subcritical and supercritical flows while ensuring the mass conservation and total pressure continuity. To model gravitational effects on global hemodynamics during postural change, a robust venous valve model is further established for the 1D venous flows and distributed throughout the entire venous network with consideration of its anatomically realistic numbers and locations. The present integrated model is proven to enable reasonable prediction of pressure and flow rate waveforms associated with cardiopulmonary circulation, systemic circulation in arteries and veins, as well as microcirculation within normal physiological ranges, particularly in mean venous pressures, which well match the in vivo measurements. Applications of the cardiovascular model at different postures demonstrate that gravity exerts remarkable influence on arterial and venous pressures, venous returns and cardiac outputs whereas venous pressures below the heart level show a specific correlation between central venous and hydrostatic pressures in right atrium and veins.
Multiscale Analysis for Field-Effect Penetration through Two-Dimensional Materials.
Tian, Tian; Rice, Peter; Santos, Elton J G; Shih, Chih-Jen
2016-08-10
Gate-tunable two-dimensional (2D) materials-based quantum capacitors (QCs) and van der Waals heterostructures involve tuning transport or optoelectronic characteristics by the field effect. Recent studies have attributed the observed gate-tunable characteristics to the change of the Fermi level in the first 2D layer adjacent to the dielectrics, whereas the penetration of the field effect through the one-molecule-thick material is often ignored or oversimplified. Here, we present a multiscale theoretical approach that combines first-principles electronic structure calculations and the Poisson-Boltzmann equation methods to model penetration of the field effect through graphene in a metal-oxide-graphene-semiconductor (MOGS) QC, including quantifying the degree of "transparency" for graphene two-dimensional electron gas (2DEG) to an electric displacement field. We find that the space charge density in the semiconductor layer can be modulated by gating in a nonlinear manner, forming an accumulation or inversion layer at the semiconductor/graphene interface. The degree of transparency is determined by the combined effect of graphene quantum capacitance and the semiconductor capacitance, which allows us to predict the ranking for a variety of monolayer 2D materials according to their transparency to an electric displacement field as follows: graphene > silicene > germanene > WS2 > WTe2 > WSe2 > MoS2 > phosphorene > MoSe2 > MoTe2, when the majority carrier is electron. Our findings reveal a general picture of operation modes and design rules for the 2D-materials-based QCs.
Microstructural analysis of TRISO particles using multi-scale X-ray computed tomography
Lowe, T.; Bradley, R. S.; Yue, S.; Barii, K.; Gelb, J.; Rohbeck, N.; Turner, J.; Withers, P. J.
2015-06-01
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.
Gago, Jorge; Martínez-Núñez, Lourdes; Landín, Mariana; Flexas, Jaume; Gallego, Pedro P.
2014-01-01
Background Plant acclimation is a highly complex process, which cannot be fully understood by analysis at any one specific level (i.e. subcellular, cellular or whole plant scale). Various soft-computing techniques, such as neural networks or fuzzy logic, were designed to analyze complex multivariate data sets and might be used to model large such multiscale data sets in plant biology. Methodology and Principal Findings In this study we assessed the effectiveness of applying neuro-fuzzy logic to modeling the effects of light intensities and sucrose content/concentration in the in vitro culture of kiwifruit on plant acclimation, by modeling multivariate data from 14 parameters at different biological scales of organization. The model provides insights through application of 14 sets of straightforward rules and indicates that plants with lower stomatal aperture areas and higher photoinhibition and photoprotective status score best for acclimation. The model suggests the best condition for obtaining higher quality acclimatized plantlets is the combination of 2.3% sucrose and photonflux of 122–130 µmol m−2 s−1. Conclusions Our results demonstrate that artificial intelligence models are not only successful in identifying complex non-linear interactions among variables, by integrating large-scale data sets from different levels of biological organization in a holistic plant systems-biology approach, but can also be used successfully for inferring new results without further experimental work. PMID:24465829
A Multi-scale Approach for CO2 Accounting and Risk Analysis in CO2 Enhanced Oil Recovery Sites
Dai, Z.; Viswanathan, H. S.; Middleton, R. S.; Pan, F.; Ampomah, W.; Yang, C.; Jia, W.; Lee, S. Y.; McPherson, B. J. O. L.; Grigg, R.; White, M. D.
2015-12-01
Using carbon dioxide in enhanced oil recovery (CO2-EOR) is a promising technology for emissions management because CO2-EOR can dramatically reduce carbon sequestration costs in the absence of greenhouse gas emissions policies that include incentives for carbon capture and storage. This study develops a multi-scale approach to perform CO2 accounting and risk analysis for understanding CO2 storage potential within an EOR environment at the Farnsworth Unit of the Anadarko Basin in northern Texas. A set of geostatistical-based Monte Carlo simulations of CO2-oil-water flow and transport in the Marrow formation are conducted for global sensitivity and statistical analysis of the major risk metrics: CO2 injection rate, CO2 first breakthrough time, CO2 production rate, cumulative net CO2 storage, cumulative oil and CH4 production, and water injection and production rates. A global sensitivity analysis indicates that reservoir permeability, porosity, and thickness are the major intrinsic reservoir parameters that control net CO2 injection/storage and oil/CH4 recovery rates. The well spacing (the distance between the injection and production wells) and the sequence of alternating CO2 and water injection are the major operational parameters for designing an effective five-spot CO2-EOR pattern. The response surface analysis shows that net CO2 injection rate increases with the increasing reservoir thickness, permeability, and porosity. The oil/CH4 production rates are positively correlated to reservoir permeability, porosity and thickness, but negatively correlated to the initial water saturation. The mean and confidence intervals are estimated for quantifying the uncertainty ranges of the risk metrics. The results from this study provide useful insights for understanding the CO2 storage potential and the corresponding risks of commercial-scale CO2-EOR fields.
Energy Technology Data Exchange (ETDEWEB)
Wagner, Gregory John (Sandia National Laboratories, Livermore, CA); Collis, Samuel Scott; Templeton, Jeremy Alan (Sandia National Laboratories, Livermore, CA); Lehoucq, Richard B.; Parks, Michael L.; Jones, Reese E. (Sandia National Laboratories, Livermore, CA); Silling, Stewart Andrew; Scovazzi, Guglielmo; Bochev, Pavel B.
2007-10-01
This report is a collection of documents written as part of the Laboratory Directed Research and Development (LDRD) project A Mathematical Framework for Multiscale Science and Engineering: The Variational Multiscale Method and Interscale Transfer Operators. We present developments in two categories of multiscale mathematics and analysis. The first, continuum-to-continuum (CtC) multiscale, includes problems that allow application of the same continuum model at all scales with the primary barrier to simulation being computing resources. The second, atomistic-to-continuum (AtC) multiscale, represents applications where detailed physics at the atomistic or molecular level must be simulated to resolve the small scales, but the effect on and coupling to the continuum level is frequently unclear.
Multiscale remote sensing analysis to monitor riparian and upland semiarid vegetation
Nguyen, Uyen
The health of natural vegetation communities is of concern due to observed changes in the climatic-hydrological regime and land cover changes particularly in arid and semiarid regions. Monitoring vegetation at multi temporal and spatial scales can be the most informative approach for detecting change and inferring causal agents of change and remediation strategies. Riparian communities are tightly linked to annual stream hydrology, ground water elevations and sediment transport. These processes are subject to varying magnitudes of disturbance overtime and are candidates for multi-scale monitoring. My first research objective focused on the response of vegetation in the Upper San Pedro River, Arizona, to reduced base flows and climate change. I addressed the correlation between riparian vegetation and hydro-climate variables during the last three decades in one of the remaining undammed rivers in the southwestern U.S. Its riparian forest is threatened by the diminishing base flows, attributed by different studies either to increases in evapotranspiration (ET) due to conversion of grasslands to mesquite shrublands in the adjacent uplands, or to increased regional groundwater pumping to serve growing populations in surrounding urban areas and or to some interactions of those causes. Landsat 5 imagery was acquired for pre- monsoon period, when riparian trees had leafed out but before the arrival of summer monsoon rains in July. The result has showed Normalized Difference Vegetation Index (NDVI) values from both Landsat and Moderate Resolution Imaging Spectrometer (MODIS) had significant decreases which positively correlated to river flows, which decreased over the study period, and negatively correlated with air temperatures, which have increased by about 1.4°C from 1904 to the present. The predictions from other studies that decreased river flows could negatively impact the riparian forest were supported by this study. The pre-monsoon Normalized Different Vegetation
Diffusion-driven multiscale analysis on manifolds and graphs: top-down and bottom-up constructions
Szlam, Arthur D.; Maggioni, Mauro; Coifman, Ronald R.; Bremer, James C., Jr.
2005-08-01
Classically, analysis on manifolds and graphs has been based on the study of the eigenfunctions of the Laplacian and its generalizations. These objects from differential geometry and analysis on manifolds have proven useful in applications to partial differential equations, and their discrete counterparts have been applied to optimization problems, learning, clustering, routing and many other algorithms.1-7 The eigenfunctions of the Laplacian are in general global: their support often coincides with the whole manifold, and they are affected by global properties of the manifold (for example certain global topological invariants). Recently a framework for building natural multiresolution structures on manifolds and graphs was introduced, that greatly generalizes, among other things, the construction of wavelets and wavelet packets in Euclidean spaces.8,9 This allows the study of the manifold and of functions on it at different scales, which are naturally induced by the geometry of the manifold. This construction proceeds bottom-up, from the finest scale to the coarsest scale, using powers of a diffusion operator as dilations and a numerical rank constraint to critically sample the multiresolution subspaces. In this paper we introduce a novel multiscale construction, based on a top-down recursive partitioning induced by the eigenfunctions of the Laplacian. This yields associated local cosine packets on manifolds, generalizing local cosines in Euclidean spaces.10 We discuss some of the connections with the construction of diffusion wavelets. These constructions have direct applications to the approximation, denoising, compression and learning of functions on a manifold and are promising in view of applications to problems in manifold approximation, learning, dimensionality reduction.
Energy Technology Data Exchange (ETDEWEB)
Dombroski, M; Melius, C; Edmunds, T; Banks, L E; Bates, T; Wheeler, R
2008-09-24
This study uses the Multi-scale Epidemiologic Simulation and Analysis (MESA) system developed for foreign animal diseases to assess consequences of nationwide human infectious disease outbreaks. A literature review identified the state of the art in both small-scale regional models and large-scale nationwide models and characterized key aspects of a nationwide epidemiological model. The MESA system offers computational advantages over existing epidemiological models and enables a broader array of stochastic analyses of model runs to be conducted because of those computational advantages. However, it has only been demonstrated on foreign animal diseases. This paper applied the MESA modeling methodology to human epidemiology. The methodology divided 2000 US Census data at the census tract level into school-bound children, work-bound workers, elderly, and stay at home individuals. The model simulated mixing among these groups by incorporating schools, workplaces, households, and long-distance travel via airports. A baseline scenario with fixed input parameters was run for a nationwide influenza outbreak using relatively simple social distancing countermeasures. Analysis from the baseline scenario showed one of three possible results: (1) the outbreak burned itself out before it had a chance to spread regionally, (2) the outbreak spread regionally and lasted a relatively long time, although constrained geography enabled it to eventually be contained without affecting a disproportionately large number of people, or (3) the outbreak spread through air travel and lasted a long time with unconstrained geography, becoming a nationwide pandemic. These results are consistent with empirical influenza outbreak data. The results showed that simply scaling up a regional small-scale model is unlikely to account for all the complex variables and their interactions involved in a nationwide outbreak. There are several limitations of the methodology that should be explored in future
2014-09-30
1 Multiscale Data Assimilation Dr. Pierre F.J. Lermusiaux Department of Mechanical Engineering, Center for Ocean Science and Engineering...concerned with next-generation multiscale data assimilation , with a focus on shelfbreak regions, including non-hydrostatic effects. Our long-term...goals are to: - Develop and utilize GMM-DO data assimilation schemes for rigorous multiscale inferences, where observations provide information on
Fenderson, Lindsey E; Kovach, Adrienne I; Litvaitis, John A; O'Brien, Kathleen M; Boland, Kelly M; Jakubas, Walter J
2014-05-01
Landscape features of anthropogenic or natural origin can influence organisms' dispersal patterns and the connectivity of populations. Understanding these relationships is of broad interest in ecology and evolutionary biology and provides key insights for habitat conservation planning at the landscape scale. This knowledge is germane to restoration efforts for the New England cottontail (Sylvilagus transitionalis), an early successional habitat specialist of conservation concern. We evaluated local population structure and measures of genetic diversity of a geographically isolated population of cottontails in the northeastern United States. We also conducted a multiscale landscape genetic analysis, in which we assessed genetic discontinuities relative to the landscape and developed several resistance models to test hypotheses about landscape features that promote or inhibit cottontail dispersal within and across the local populations. Bayesian clustering identified four genetically distinct populations, with very little migration among them, and additional substructure within one of those populations. These populations had private alleles, low genetic diversity, critically low effective population sizes (3.2-36.7), and evidence of recent genetic bottlenecks. Major highways and a river were found to limit cottontail dispersal and to separate populations. The habitat along roadsides, railroad beds, and utility corridors, on the other hand, was found to facilitate cottontail movement among patches. The relative importance of dispersal barriers and facilitators on gene flow varied among populations in relation to landscape composition, demonstrating the complexity and context dependency of factors influencing gene flow and highlighting the importance of replication and scale in landscape genetic studies. Our findings provide information for the design of restoration landscapes for the New England cottontail and also highlight the dual influence of roads, as both
Cruz, Roberto de la; Guerrero, Pilar; Spill, Fabian; Alarcón, Tomás
2016-10-21
We propose a modelling framework to analyse the stochastic behaviour of heterogeneous, multi-scale cellular populations. We illustrate our methodology with a particular example in which we study a population with an oxygen-regulated proliferation rate. Our formulation is based on an age-dependent stochastic process. Cells within the population are characterised by their age (i.e. time elapsed since they were born). The age-dependent (oxygen-regulated) birth rate is given by a stochastic model of oxygen-dependent cell cycle progression. Once the birth rate is determined, we formulate an age-dependent birth-and-death process, which dictates the time evolution of the cell population. The population is under a feedback loop which controls its steady state size (carrying capacity): cells consume oxygen which in turn fuels cell proliferation. We show that our stochastic model of cell cycle progression allows for heterogeneity within the cell population induced by stochastic effects. Such heterogeneous behaviour is reflected in variations in the proliferation rate. Within this set-up, we have established three main results. First, we have shown that the age to the G1/S transition, which essentially determines the birth rate, exhibits a remarkably simple scaling behaviour. Besides the fact that this simple behaviour emerges from a rather complex model, this allows for a huge simplification of our numerical methodology. A further result is the observation that heterogeneous populations undergo an internal process of quasi-neutral competition. Finally, we investigated the effects of cell-cycle-phase dependent therapies (such as radiation therapy) on heterogeneous populations. In particular, we have studied the case in which the population contains a quiescent sub-population. Our mean-field analysis and numerical simulations confirm that, if the survival fraction of the therapy is too high, rescue of the quiescent population occurs. This gives rise to emergence of resistance
Directory of Open Access Journals (Sweden)
Francisco de Assis Salviano de Sousa
2009-03-01
Full Text Available The variations of the rainfall in a region of the Mundaú river watershed, at state of Alagoas, Brazil, had been studied using the rainfall anomaly index (RAI and the Wavelet Analysis. This method involves transformation of a one-dimensional series in a time space and frequency, allowing determining the dominant scales of variability and its secular variations. The results had shown that the precipitation variability in the two regions is defined by located secular multi-scales in certain intervals of time. However, on inter-annual variability to the ENSO cycle and the decadal variability of the scales had influenced in the local pluviometric variability.
DEFF Research Database (Denmark)
Cash, Philip; Hicks, Ben; Culley, Steve
2015-01-01
This paper contributes to improving our understanding of design activity. Specifically the paper uses Activity Theory to enable a multi-scale analysis of the activity of three engineering designers over a period of one month. Correspondingly, this paper represents the first work that explicitly...... the wider implications of the proposed framework and its findings for both design research and practice. Central to these implications is the articulation of design as a complex fabric of interwoven processes. © 2015 Elsevier Ltd. All rights reserved....
Image analysis methods based on hierarchies of graphs and multi-scale mathematical morphology
Nacken, P.F.M.
1994-01-01
This thesis is about image analysis methods based on hierarchical graph represen-tations. A hierarchical graph representation of an image is an ordered set of graphs that represent the image on different levels of abstraction. The vertices of the graph represent image structures (lines, areas). Its
Nonlocal multi-scale traffic flow models: analysis beyond vector spaces
Directory of Open Access Journals (Sweden)
Peter E. Kloeden
2016-08-01
Full Text Available Abstract Realistic models of traffic flow are nonlinear and involve nonlocal effects in balance laws. Flow characteristics of different types of vehicles, such as cars and trucks, need to be described differently. Two alternatives are used here, $$L^p$$ L p -valued Lebesgue measurable density functions and signed Radon measures. The resulting solution spaces are metric spaces that do not have a linear structure, so the usual convenient methods of functional analysis are no longer applicable. Instead ideas from mutational analysis will be used, in particular the method of Euler compactness will be applied to establish the well-posedness of the nonlocal balance laws. This involves the concatenation of solutions of piecewise linear systems on successive time subintervals obtained by freezing the nonlinear nonlocal coefficients to their values at the start of each subinterval. Various compactness criteria lead to a convergent subsequence. Careful estimates of the linear systems are needed to implement this program.
Energy Technology Data Exchange (ETDEWEB)
Steed, Chad A [ORNL; Beaver, Justin M [ORNL; BogenII, Paul L. [Google Inc.; Drouhard, Margaret MEG G [ORNL; Pyle, Joshua M [ORNL
2015-01-01
In this paper, we introduce a new visual analytics system, called Matisse, that allows exploration of global trends in textual information streams with specific application to social media platforms. Despite the potential for real-time situational awareness using these services, interactive analysis of such semi-structured textual information is a challenge due to the high-throughput and high-velocity properties. Matisse addresses these challenges through the following contributions: (1) robust stream data management, (2) automated sen- timent/emotion analytics, (3) inferential temporal, geospatial, and term-frequency visualizations, and (4) a flexible drill-down interaction scheme that progresses from macroscale to microscale views. In addition to describing these contributions, our work-in-progress paper concludes with a practical case study focused on the analysis of Twitter 1% sample stream information captured during the week of the Boston Marathon bombings.
Analysis and Visualization of Multi-Scale Astrophysical Simulations using Python and NumPy
Energy Technology Data Exchange (ETDEWEB)
Turk, M.; /KIPAC, Menlo Park
2008-09-30
The study the origins of cosmic structure requires large-scale computer simulations beginning with well-constrained, observationally-determined, initial conditions. We use Adaptive Mesh Refinement to conduct multi-resolution simulations spanning twelve orders of magnitude in spatial dimensions and over twenty orders of magnitude in density. These simulations must be analyzed and visualized in a manner that is fast, accurate, and reproducible. I present 'yt,' a cross-platform analysis toolkit written in Python. 'yt' consists of a data-management layer for transporting and tracking simulation outputs, a plotting layer, a parallel analysis layer for handling mesh-based and particle-based data, as well as several interfaces. I demonstrate how the origins of cosmic structure--from the scale of clusters of galaxies down to the formation of individual stars--can be analyzed and visualized using a NumPy-based toolkit. Additionally, I discuss efforts to port this analysis code to other adaptive mesh refinement data formats, enabling direct comparison of data between research groups using different methods to simulate the same objects.
Visualization and Analysis of Multi-scale Land Surface Products via Giovanni Portals
Shen, Suhung; Kempler, Steven J.; Gerasimov, Irina V.
2013-01-01
Large volumes of MODIS land data products at multiple spatial resolutions have been integrated into the Giovanni online analysis system to support studies on land cover and land use changes,focused on the Northern Eurasia and Monsoon Asia regions through the LCLUC program. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data.Customized Giovanni Web portals (Giovanni-NEESPI andGiovanni-MAIRS) have been created to integrate land, atmospheric,cryospheric, and societal products, enabling researchers to do quick exploration and basic analyses of land surface changes, and their relationships to climate, at global and regional scales. This presentation shows a sample Giovanni portal page, lists selected data products in the system, and illustrates potential analyses with imagesand time-series at global and regional scales, focusing on climatology and anomaly analysis. More information is available at the GES DISCMAIRS data support project portal: http:disc.sci.gsfc.nasa.govmairs.
Multiscale Monitoring and Analysis of the Impacts of Rural Land Use Changes on Downstream Flooding
Geris, J.; Ewen, J.; O'Donnell, G.; O'Connell, P. E.
2010-12-01
Recent dramatic flood events in several parts of the world have reignited the debate on the role played by rural land use/management changes (RLUMC). Whereas the effects of RLUMC on runoff generation and flood risk at small scales are often clear, it is difficult to determine how these effects travel through the river network to affect flooding at larger scales downstream. The headwaters of the River Hodder catchment (260 km2) in Northwest England, United Kingdom, have recently undergone widespread RLUMC, including changes in stocking density, blocking of moorland drainage ditches, and woodland planting. An unusually dense nested monitoring network has been set-up so that the effects of RLUMC can be studied at increasing scales, from the process scale (~1 ha) to the meso scale (~100 km2). The stream gauges are nested up to 5 deep. In total there are 27 stream gauges, 7 rain gauges, and 1 weather station. The main effort in analysis has focussed on detecting signals from stocking density changes, by studying pre-change and post-change runoff and river network flows at increasing scales. The field data set available for the analysis is comprehensive but is relatively short (approximately 1 year pre-change and 1 year post-change). Given the natural variability of rainfall and hydrological response, working with such short records is an important challenge, especially as there is an almost universal lack of comprehensive, nested, long-term historical data sets worldwide that could be used to investigate the effects of RLUMC on flooding. An analysis of a commonly used statistical data analysis method (based on data based mechanistic modelling) showed that, for such short records, any change effects from RLUMC are apparently masked by natural variability. In addition, the effects of some types of RLUMC, including changes in stocking density, need several years to be fully established. Analysis methods have therefore been sought that are sensitive to changes in the
Analysis of Multi-scale Characteristics of China's Stock MarketβCoefficient%中国股市β系数的多尺度特性分析
Institute of Scientific and Technical Information of China (English)
王红卫
2014-01-01
This paper presents β coefficient estimation method based on wavelet variance and wavelet covariance, and estimates the risk coefficient on different scales through multi-scale decomposition of wavelet variance and wavelet covariance, then uses this method to carry on multi-scale analysis for China securities A-share market branch industry and the investment portfolios coefficient. The empirical results show that China's stock markethas the characteristics of complex multi-scale fluctuations, stock market riskson different time scales exhibits different risk. The risk of short-term investments mainlyin the high-frequency fluctuations, investors should consider a low scalesβcoefficient, while long-term investment risk mainly forlow-frequency fluctuations, investors should consider a large scalesβcoefficient.%本文提出一种基于小波方差和小波协方差的β系数估计方法，并通过小波方差和小波协方差的多尺度分解估计出不同尺度上的风险系数，用该方法对中国证券A股市场分行业及投资组合的β系数进行了多尺度估计分析。实证结果表明，我国股市具有复杂的多尺度波动的特征，不同时间尺度上证券市场所表现出的风险不一样，短期投资的风险主要表现在高频波动，投资者应当考虑低尺度下的β系数，而长期投资风险主要表现为低频波动，应当考虑大尺度下的β系数。
New methodologies for multi-scale time-variant reliability analysis of complex lifeline networks
Kurtz, Nolan Scot
The cost of maintaining existing civil infrastructure is enormous. Since the livelihood of the public depends on such infrastructure, its state must be managed appropriately using quantitative approaches. Practitioners must consider not only which components are most fragile to hazard, e.g. seismicity, storm surge, hurricane winds, etc., but also how they participate on a network level using network analysis. Focusing on particularly damaged components does not necessarily increase network functionality, which is most important to the people that depend on such infrastructure. Several network analyses, e.g. S-RDA, LP-bounds, and crude-MCS, and performance metrics, e.g. disconnection bounds and component importance, are available for such purposes. Since these networks are existing, the time state is also important. If networks are close to chloride sources, deterioration may be a major issue. Information from field inspections may also have large impacts on quantitative models. To address such issues, hazard risk analysis methodologies for deteriorating networks subjected to seismicity, i.e. earthquakes, have been created from analytics. A bridge component model has been constructed for these methodologies. The bridge fragilities, which were constructed from data, required a deeper level of analysis as these were relevant for specific structures. Furthermore, chloride-induced deterioration network effects were investigated. Depending on how mathematical models incorporate new information, many approaches are available, such as Bayesian model updating. To make such procedures more flexible, an adaptive importance sampling scheme was created for structural reliability problems. Additionally, such a method handles many kinds of system and component problems with singular or multiple important regions of the limit state function. These and previously developed analysis methodologies were found to be strongly sensitive to the network size. Special network topologies may
Evaluation of the landscape surrounding northern bobwhite nest sites: A multiscale analysis
White, C.G.; Schweitzer, Sara H.; Moore, C.T.; Parnell, I.B.; Lewis-Weis, L.A.
2005-01-01
Implementation of the Conservation Reserve Program (CRP) altered the interspersion and abundance of patches of different land-cover types in landscapes of the southeastern United States. Because northern bobwhites (Colinus virginianus) are experiencing significant population declines throughout most of their range, including the Southeast, it is critical to understand the impacts of landscape-scale changes in habitat on their reproductive rates. Our objective was to identify components of landscape structure important in predicting nest site selection by bobwhites at different spatial scales in the Upper Coastal Plain of Georgia. We used a Geographic Information System (GIS) and spatial analysis software to calculate metrics of landscape structure near bobwhite nest sites. Logistic regression was used to model the relationship of nest sites to structure within the surrounding landscape at 4 spatial scales. We found that patch density and open-canopy planted pine were consistently important predictor variables at multiple scales, and other variables were important at various scales. The density of different patch types could be increased by thinning rows of pines in large monotypic stands of closed-canopy planted pine stands. Thinning and creating openings in CRP pine plantations should provide increased nesting opportunities for bobwhites. We interpret the support for other variables in our analysis as an indication that various patch configuration lead to different combinations of landscape structure that provide an acceptable range of habitat conditions for bobwhites.
Multi-scale AM-FM motion analysis of ultrasound videos of carotid artery plaques
Murillo, Sergio; Murray, Victor; Loizou, C. P.; Pattichis, C. S.; Pattichis, Marios; Barriga, E. Simon
2012-03-01
An estimated 82 million American adults have one or more type of cardiovascular diseases (CVD). CVD is the leading cause of death (1 of every 3 deaths) in the United States. When considered separately from other CVDs, stroke ranks third among all causes of death behind diseases of the heart and cancer. Stroke accounts for 1 out of every 18 deaths and is the leading cause of serious long-term disability in the United States. Motion estimation of ultrasound videos (US) of carotid artery (CA) plaques provides important information regarding plaque deformation that should be considered for distinguishing between symptomatic and asymptomatic plaques. In this paper, we present the development of verifiable methods for the estimation of plaque motion. Our methodology is tested on a set of 34 (5 symptomatic and 29 asymptomatic) ultrasound videos of carotid artery plaques. Plaque and wall motion analysis provides information about plaque instability and is used in an attempt to differentiate between symptomatic and asymptomatic cases. The final goal for motion estimation and analysis is to identify pathological conditions that can be detected from motion changes due to changes in tissue stiffness.
2009-01-01
A conceptual framework is presented for multiscale field/network/agent-based modeling to support human and ecological health risk assessments. This framework is based on the representation of environmental dynamics in terms of interacting networks, agents that move across different networks, fields representing spatiotemporal distributions of physical properties, rules governing constraints and interactions, and actors that make decisions affecting the state of the system. Different determini...
Directory of Open Access Journals (Sweden)
Yu-Ching Shih
2014-04-01
Full Text Available Micro-cantilever sensors are widely used to detect biomolecules, chemical gases, and ionic species. However, the theoretical descriptions and predictive modeling of these devices are not well developed, and lag behind advances in fabrication and applications. In this paper, we present a novel multiscale simulation framework for nanomechanical sensors. This framework, combining density functional theory (DFT calculations and finite element method (FEM analysis, is capable of analyzing molecular adsorption-induced deformation and stress fields in the sensors from the molecular scale to the device scale. Adsorption of alkanethiolate self-assembled monolayer (SAM on the Au(111 surface of the micro-cantilever sensor is studied in detail to demonstrate the applicability of this framework. DFT calculations are employed to investigate the molecular adsorption-induced surface stress upon the gold surface. The 3D shell elements with initial stresses obtained from the DFT calculations serve as SAM domains in the adsorption layer, while FEM is employed to analyze the deformation and stress of the sensor devices. We find that the micro-cantilever tip deflection has a linear relationship with the coverage of the SAM domains. With full coverage, the tip deflection decreases as the molecular chain length increases. The multiscale simulation framework provides a quantitative analysis of the displacement and stress fields, and can be used to predict the response of nanomechanical sensors subjected to complex molecular adsorption.
Beguet, Benoit; Guyon, Dominique; Boukir, Samia; Chehata, Nesrine
2014-10-01
The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure
Intercomparison of the community multiscale air quality model and CALGRID using process analysis.
O'Neill, Susan M; Lamb, Brian K
2005-08-01
This study was designed to examine the similarities and differences between two advanced photochemical air quality modeling systems: EPA Models-3/CMAQ and CALGRID/CALMET. Both modeling systems were applied to an ozone episode that occurred along the I-5 urban corridor in western Washington and Oregon during July 11-14, 1996. Both models employed the same modeling domain and used the same detailed gridded emission inventory. The CMAQ model was run using both the CB-IV and RADM2 chemical mechanisms, while CALGRID was used with the SAPRC-97 chemical mechanism. Outputfrom the Mesoscale Meteorological Model (MM5) employed with observational nudging was used in both models. The two modeling systems, representing three chemical mechanisms and two sets of meteorological inputs, were evaluated in terms of statistical performance measures for both 1- and 8-h average observed ozone concentrations. The results showed that the different versions of the systems were more similar than different, and all versions performed well in the Portland region and downwind of Seattle but performed poorly in the more rural region north of Seattle. Improving the meteorological input into the CALGRID/CALMET system with planetary boundary layer (PBL) parameters from the Models-3/CMAQ meteorology preprocessor (MCIP) improved the performance of the CALGRID/CALMET system. The 8-h ensemble case was often the best performer of all the cases indicating that the models perform better over longer analysis periods. The 1-h ensemble case, derived from all runs, was not necessarily an improvement over the five individual cases, but the standard deviation about the mean provided a measure of overall modeling uncertainty. Process analysis was applied to examine the contribution of the individual processes to the species conservation equation. The process analysis results indicated that the two modeling systems arrive at similar solutions by very different means. Transport rates are faster and exhibit
Multi-scale analysis of a household level agent-based model of landcover change.
Evans, Tom P; Kelley, Hugh
2004-08-01
Scale issues have significant implications for the analysis of social and biophysical processes in complex systems. These same scale implications are likewise considerations for the design and application of models of landcover change. Scale issues have wide-ranging effects from the representativeness of data used to validate models to aggregation errors introduced in the model structure. This paper presents an analysis of how scale issues affect an agent-based model (ABM) of landcover change developed for a research area in the Midwest, USA. The research presented here explores how scale factors affect the design and application of agent-based landcover change models. The ABM is composed of a series of heterogeneous agents who make landuse decisions on a portfolio of cells in a raster-based programming environment. The model is calibrated using measures of fit derived from both spatial composition and spatial pattern metrics from multi-temporal landcover data interpreted from historical aerial photography. A model calibration process is used to find a best-fit set of parameter weights assigned to agents' preferences for different landuses (agriculture, pasture, timber production, and non-harvested forest). Previous research using this model has shown how a heterogeneous set of agents with differing preferences for a portfolio of landuses produces the best fit to landcover changes observed in the study area. The scale dependence of the model is explored by varying the resolution of the input data used to calibrate the model (observed landcover), ancillary datasets that affect land suitability (topography), and the resolution of the model landscape on which agents make decisions. To explore the impact of these scale relationships the model is run with input datasets constructed at the following spatial resolutions: 60, 90, 120, 150, 240, 300 and 480 m. The results show that the distribution of landuse-preference weights differs as a function of scale. In addition
de Aranzabal, Itziar; Schmitz, María F; Pineda, Francisco D
2009-11-01
Tourism and landscape are interdependent concepts. Nature- and culture-based tourism are now quite well developed activities and can constitute an excellent way of exploiting the natural resources of certain areas, and should therefore be considered as key objectives in landscape planning and management in a growing number of countries. All of this calls for careful evaluation of the effects of tourism on the territory. This article focuses on an integrated spatial method for landscape analysis aimed at quantifying the relationship between preferences of visitors and landscape features. The spatial expression of the model relating types of leisure and recreational preferences to the potential capacity of the landscape to meet them involves a set of maps showing degrees of potential visitor satisfaction. The method constitutes a useful tool for the design of tourism planning and management strategies, with landscape conservation as a reference.
Analysis of multi-scale systemic risk in Brazil's financial market
Directory of Open Access Journals (Sweden)
Adriana Bruscato Bortoluzzo
2014-06-01
Full Text Available This work analyzes whether the relationship between risk and returns predicted by the Capital Asset Pricing Model (CAPM is valid in the Brazilian stock market. The analysis is based on discrete wavelet decomposition on different time scales. This technique allows to analyze the relationship between different time horizons, since the short-term ones (2 to 4 days up to the long-term ones (64 to 128 days. The results indicate that there is a negative or null relationship between systemic risk and returns for Brazil from 2004 to 2007. As the average excess return of a market portfolio in relation to a risk-free asset during that period was positive, it would be expected this relationship to be positive. That is, higher systematic risk should result in higher excess returns, which did not occur. Therefore, during that period, appropriate compensation for systemic risk was not observed in the Brazilian market. The scales that proved to be most significant to the risk-return relation were the first three, which corresponded to short-term time horizons. When treating differently, year-by-year, and consequently separating positive and negative premiums, some relevance is found, during some years, in the risk/return relation predicted by the CAPM. However, this pattern did not persist throughout the years. Therefore, there is not any evidence strong enough confirming that the asset pricing follows the model.
Drought analysis using multi-scale standardized precipitation index in the Han River Basin, China
Institute of Scientific and Technical Information of China (English)
Yue-ping XU; Sheng-ji LIN; Yan HUANG; Qin-qing ZHANG; Qi-hua RAN
2011-01-01
Regional drought analysis provides useful information for sustainable water resources management. In this paper, a standardized precipitation index (SPI) at multiple time scales was used to investigate the spatial patterns and trends of drought in the Han River Basin, one of the largest tributaries of Yangtze River, China. It was found that, in terms of drought severity, the upper basin of the Hart River is the least, while the growing trend is the most conspicuous; a less conspicuous growing trend can be observed in the middle basin; and there is an insignificant decreasing trend in the lower basin. Meanwhile, the impact of drought on the Middle Route of the South-to-North Water Transfer Project was investigated, and it is suggested that water intake must be reduced in times of drought, particularly when successive or simultaneous droughts in the upper and middle basins of the Han River Basin occur. The results can provide substantial information for future water allocation schemes of the South-to-North Water Transfer Project.
Korres, W.; Reichenau, T. G.; Schneider, K.
2012-12-01
Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture, influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Numerous studies have shown that in addition to natural factors (rainfall, soil, topography etc.) agricultural management is one of the key drivers for spatio-temporal patterns of soil moisture in agricultural landscapes. Interactions between plant growth, soil hydrology and soil nitrogen transformation processes are modeled by using a dynamically coupled modeling approach. The process-based ecohydrological model components of the integrated decision support system DANUBIA are used to identify the important processes and feedbacks determining soil moisture patterns in agroecosystems. Integrative validation of plant growth and surface soil moisture dynamics serves as a basis for a spatially distributed modeling analysis of surface soil moisture patterns in the northern part of the Rur catchment (1100 sq km), Western Germany. An extensive three year dataset (2007-2009) of surface soil moisture-, plant- (LAI, organ specific biomass and N) and soil- (texture, N, C) measurements was collected. Plant measurements were carried out biweekly for winter wheat, maize, and sugar beet during the growing season. Soil moisture was measured with three FDR soil moisture stations. Meteorological data was measured with an eddy flux station. The results of the model validation showed a very good agreement between the modeled plant parameters (biomass, green LAI) and the measured parameters with values between 0.84 and 0.98 (Willmotts index of agreement). The modeled surface soil moisture (0 - 20 cm) showed also a very favorable agreement with the measurements for winter wheat and sugar beet with an RMSE between 1.68 and 3.45 Vol.-%. For maize, the RMSE was less favorable particularly in the 1.5 months prior to harvest. The modeled soil
An integrative multi-scale analysis of the dynamic DNA methylation landscape in aging.
Directory of Open Access Journals (Sweden)
Tian Yuan
2015-02-01
Full Text Available Recent studies have demonstrated that the DNA methylome changes with age. This epigenetic drift may have deep implications for cellular differentiation and disease development. However, it remains unclear how much of this drift is functional or caused by underlying changes in cell subtype composition. Moreover, no study has yet comprehensively explored epigenetic drift at different genomic length scales and in relation to regulatory elements. Here we conduct an in-depth analysis of epigenetic drift in blood tissue. We demonstrate that most of the age-associated drift is independent of the increase in the granulocyte to lymphocyte ratio that accompanies aging and that enrichment of age-hypermethylated CpG islands increases upon adjustment for cellular composition. We further find that drift has only a minimal impact on in-cis gene expression, acting primarily to stabilize pre-existing baseline expression levels. By studying epigenetic drift at different genomic length scales, we demonstrate the existence of mega-base scale age-associated hypomethylated blocks, covering approximately 14% of the human genome, and which exhibit preferential hypomethylation in age-matched cancer tissue. Importantly, we demonstrate the feasibility of integrating Illumina 450k DNA methylation with ENCODE data to identify transcription factors with key roles in cellular development and aging. Specifically, we identify REST and regulatory factors of the histone methyltransferase MLL complex, whose function may be disrupted in aging. In summary, most of the epigenetic drift seen in blood is independent of changes in blood cell type composition, and exhibits patterns at different genomic length scales reminiscent of those seen in cancer. Integration of Illumina 450k with appropriate ENCODE data may represent a fruitful approach to identify transcription factors with key roles in aging and disease.
Energy Technology Data Exchange (ETDEWEB)
Li, Dengwang [Shandong Normal University, Jinan, Shandong Province (China); Wang, Qinfen [Shandong Normal University, Jinan, Shandong (China); Li, H; Chen, J [Shandong Cancer Hospital and Institute, Jinan, Shandong (China)
2014-06-01
Purpose: The purpose of this research is studying tumor heterogeneity of the primary and lymphoma by using multi-scale texture analysis with PET-CT images, where the tumor heterogeneity is expressed by texture features. Methods: Datasets were collected from 12 lung cancer patients, and both of primary and lymphoma tumors were detected with all these patients. All patients underwent whole-body 18F-FDG PET/CT scan before treatment.The regions of interest (ROI) of primary and lymphoma tumor were contoured by experienced clinical doctors. Then the ROI of primary and lymphoma tumor is extracted automatically by using Matlab software. According to the geometry size of contour structure, the images of tumor are decomposed by multi-scale method.Wavelet transform was performed on ROI structures within images by L layers sampling, and then wavelet sub-bands which have the same size of the original image are obtained. The number of sub-bands is 3L+1.The gray level co-occurrence matrix (GLCM) is calculated within different sub-bands, thenenergy, inertia, correlation and gray in-homogeneity were extracted from GLCM.Finally, heterogeneity statistical analysis was studied for primary and lymphoma tumor using the texture features. Results: Energy, inertia, correlation and gray in-homogeneity are calculated with our experiments for heterogeneity statistical analysis.Energy for primary and lymphomatumor is equal with the same patient, while gray in-homogeneity and inertia of primaryare 2.59595±0.00855, 0.6439±0.0007 respectively. Gray in-homogeneity and inertia of lymphoma are 2.60115±0.00635, 0.64435±0.00055 respectively. The experiments showed that the volume of lymphoma is smaller than primary tumor, but thegray in-homogeneity and inertia were higher than primary tumor with the same patient, and the correlation with lymphoma tumors is zero, while the correlation with primary tumor isslightly strong. Conclusion: This studying showed that there were effective heterogeneity
Homogenization-based multi-scale damage theory
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
The research of modern mechanics reveals that the damage and failure of structures should be considered on different scales. The present paper is dedicated to establishing the multi-scale damage theory for the nonlinear structural analysis. Starting from the asymptotic expansion based homogenization theory, the multi-scale energy integration is proposed to bridge the gap between the micro and macro scales. By recalling the Helmholtz free energy based damage definition, the damage variable is represented by the multi-scale energy integration. Hence the damage evolution could be numerically simulated on the basis of the unit cell analysis rather than the experimental data identification. Finally the framework of the multi-scale damage theory is established by transforming the multi-scale damage evolution into the conventional continuum damage mechanics. The agree- ment between the simulated results and the benchmark results indicates the validity and effectiveness of the proposed theory.
Deisboeck, Thomas S; Wang, Zhihui; Macklin, Paul; Cristini, Vittorio
2011-08-15
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 insights in 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.
Multiscale Gentlest Ascent Dynamics
Zhou, Xiang
2016-01-01
The gentlest ascent dynamics (E and Zhou in {\\it Nonlinearity} vol 24, p1831, 2011) locally converges to a nearby saddle point with one dimensional unstable manifold. Here we present a multiscale gentlest ascent dynamics for stochastic slow-fast systems in order to compute saddle point associated with the effective dynamics of the slow variable. Such saddle points, as the candidates of transition states, are important in non-equilibrium transitions for the coarse-grained slow variables; they are also helpful to explore free energy surface. We derive the expressions of the gentlest ascent dynamics for the averaged system, and propose the multiscale numerical methods to efficiently solve the multiscale gentlest ascent dynamics for search of saddle point. The examples of stochastic ordinary and partial differential equations are presented to illustrate the performance of this multiscale gentlest ascent dynamics.
Directory of Open Access Journals (Sweden)
Jiann-Shing Shieh
2012-11-01
Full Text Available Falls are unpredictable accidents and resulting injuries can be serious to the elderly. A preventative solution can be the use of vibration stimulus of white noise to improve the sense of balance. In this work, a pair of vibration shoes were developed and controlled by a touch-type switch which can generate mechanical vibration noise to stimulate the patient’s feet while wearing the shoes. In order to evaluate the balance stability and treatment effect of vibrating insoles in these shoes, multivariate multiscale entropy (MMSE algorithm is applied to calculate the relative complexity index of reconstructed center of pressure (COP signals in antero-posterior and medio-lateral directions by the multivariate empirical mode decomposition (MEMD. The results show that the balance stability of 61.5% elderly subjects is improved after wearing the developed shoes, which is more than 30.8% using multiscale entropy. In conclusion, MEMD-enhanced MMSE is able to distinguish the smaller differences between before and after the use of vibration shoes in both two directions, which is more powerful than the empirical mode decomposition (EMD-enhanced MSE in each individual direction.
Differential geometry based multiscale models.
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
Directory of Open Access Journals (Sweden)
Sandra R. Baptista
2008-12-01
Full Text Available Within the contexts of globalization and the Atlantic Forest ecoregion, I present a multiscale analysis of anthropogenic landscape dynamics in the Florianópolis city-region, Santa Catarina, southern Brazil. Drawing on field research conducted between 2000 and 2004 and a review of the literature, I examined Brazilian demographic and agricultural census data for the period of 1970 to 1995-1996. I hypothesized that economic restructuring, new institutional arrangements, and the valuation of environmental amenities and ecosystem services have contributed to forest recovery trends and thus a forest transition in the city-region. My results indicate that along with rapid urbanization, in-migration, socioeconomic polarization, and segregation, the city-region has experienced the contraction of private agricultural land area, expansion of protected areas, recovery of forests, and conversion of coastal plain ecosystems to built environments. Future analyses of forest transition dynamics should consider the spatial configurations of socioeconomic inequality in city-regions.
Multiscale flat norm signatures for shapes and images
Energy Technology Data Exchange (ETDEWEB)
Sandine, Gary [Los Alamos National Laboratory; Morgan, Simon P [Los Alamos National Laboratory; Vixie, Kevin R [WASHINGTON STATE UNIV.; Clawson, Keth [WASHINGTON STATE UNIV.; Asaki, Thomas J [WASHINGTON STATE UNIV.; Price, Brandon [WALLA WALLA UNIV.
2009-01-01
In this paper we begin to explore the application of the multiscale flat norm introduced in Morgan and Vixie to shape and image analysis. In particular, we look at the use of the multiscale flat norm signature for the identification of shapes. After briefly reviewing the multiscale flat norm, the L{sup 1}TV functional and the relation between these two, we introduce multiscale signatures that naturally follow from the multiscale flat norm and its components. A numerical method based on the min-cut, max-flow graph-cut is briefly recalled. We suggest using L{sup 2} minimization, rather than the usual Crofton's formula based approximation, for choosing the required weights. The resulting weights have the dual benefits of being analytically computable and of giving more accurate approximations to the anisotropic TV energy. Finally, we demonstrate the usefulness of the signatures on simple shape classification tasks.
Multicomponent and multiscale systems theory, methods, and applications in engineering
Geiser, Juergen
2016-01-01
This book examines the latest research results from combined multi-component and multi-scale explorations. It provides theory, considers underlying numerical methods, and presents brilliant computational experimentation. Engineering computations featured in this monograph further offer particular interest to many researchers, engineers, and computational scientists working in frontier modeling and applications of multicomponent and multiscale problems. Professor Geiser gives specific attention to the aspects of decomposing and splitting delicate structures and controlling decomposition and the rationale behind many important applications of multi-component and multi-scale analysis. Multicomponent and Multiscale Systems: Theory, Methods, and Applications in Engineering also considers the question of why iterative methods can be powerful and more appropriate for well-balanced multiscale and multicomponent coupled nonlinear problems. The book is ideal for engineers and scientists working in theoretical and a...
Multiscale Computing with the Multiscale Modeling Library and Runtime Environment
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 pre
Distributed infrastructure for multiscale computing
Zasada, S.J.; Mamonski, M.; Groen, D.; Borgdorff, J.; Saverchenko, I.; Piontek, T.; Kurowski, K.; Coveney, P.V.; Boukerche, A.; Cahill, V.; El-Saddik, A.; Theodoropoulos, G.; Walshe, R.
2012-01-01
Today scientists and engineers are commonly faced with the challenge of modelling, predicting and controlling multiscale systems which cross scientific disciplines and where several processes acting at different scales coexist and interact. Such multidisciplinary multiscale models, when simulated in
de la Cruz, Roberto; Spill, Fabian; Alarcón, Tomás
2016-01-01
We propose a modelling framework to analyse the stochastic behaviour of heterogeneous, multi-scale cellular populations. We illustrate our methodology with a particular example in which we study a population with an oxygen-regulated proliferation rate. Our formulation is based on an age-dependent stochastic process. Cells within the population are characterised by their age. The age-dependent (oxygen-regulated) birth rate is given by a stochastic model of oxygen-dependent cell cycle progression. We then formulate an age-dependent birth-and-death process, which dictates the time evolution of the cell population. The population is under a feedback loop which controls its steady state size: cells consume oxygen which in turns fuels cell proliferation. We show that our stochastic model of cell cycle progression allows for heterogeneity within the cell population induced by stochastic effects. Such heterogeneous behaviour is reflected in variations in the proliferation rate. Within this set-up, we have established...
Pineda, Evan J.; Bednarcyk, Brett A.; Arnold, Steven M.
2014-01-01
It is often advantageous to account for the microstructure of the material directly using multiscale modeling. For computational tractability, an idealized repeating unit cell (RUC) is used to capture all of the pertinent features of the microstructure. Typically, the RUC is dimensionless and depends only on the relative volume fractions of the different phases in the material. This works well for non-linear and inelastic behavior exhibiting a positive-definite constitutive response. Although, once the material exhibits strain softening, or localization, a mesh objective failure theories, such as smeared fracture theories, nodal and element enrichment theories (XFEM), cohesive elements or virtual crack closure technique (VCCT), can be utilized at the microscale, but the dimensions of the RUC must then be defined. One major challenge in multiscale progressive damage modeling is relating the characteristic lengths across the scales in order to preserve the energy that is dissipated via localization at the microscale. If there is no effort to relate the size of the macroscale element to the microscale RUC, then the energy that is dissipated will remain mesh dependent at the macroscale, even if it is regularized at the microscale. Here, a technique for mapping characteristic lengths across the scales is proposed. The RUC will be modeled using the generalized method of cells (GMC) micromechanics theory, and local failure in the matrix constituent subcells will be modeled using the crack band theory. The subcell characteristic lengths used in the crack band calculations will be mapped to the macroscale finite element in order to regularize the local energy in a manner consistent with the global length scale. Examples will be provided with and without the regularization, and they will be compared to a baseline case where the size and shape of the element and RUC are coincident (ensuring energy is preserved across the scales).
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
art of local models with the flexibility and accuracy of the nonlocal peridynamic model. In the mixed locality method this coupling occurs across scales, so that the nonlocal model can be used to communicate material heterogeneity at scales inappropriate to local partial differential equation models. Additionally, the computational burden of the weak form of the peridynamic model is reduced dramatically by only requiring that the model be solved on local patches of the simulation domain which may be computed in parallel, taking advantage of the heterogeneous nature of next generation computing platforms. Addition- ally, we present a novel Galerkin framework, the 'Ambulant Galerkin Method', which represents a first step towards a unified mathematical analysis of local and nonlocal multiscale finite element methods, and whose future extension will allow the analysis of multiscale finite element methods that mix models across scales under certain assumptions of the consistency of those models.
Multi-scale salient feature extraction on mesh models
Yang, Yongliang
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.
Multiscale Simulations Using Particles
DEFF Research Database (Denmark)
Walther, Jens Honore
vortex methods for problems in continuum fluid dynamics, dissipative particle dynamics for flow at the meso scale, and atomistic molecular dynamics simulations of nanofluidic systems. We employ multiscale techniques to breach the atomistic and continuum scales to study fundamental problems in fluid...
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...
Multi-scale Analysis of Chaotic Characteristics in a Gas-Solid Fluidized Bed%气固流化床中非线性特性的多尺度分析
Institute of Scientific and Technical Information of China (English)
甄玲; 王晓萍; 陈伯川; 黄海; 黄春艳
2002-01-01
Deterministic chaos theory offers useful quantitative tools to characterize the non-linear dynamic behavior of a fluidized bed and the developed complexity theory presents a new approach to evaluate finite sequences.In this paper, the non-linear, hydrodynamic behavior of the pressure fluctuation signals in a reactor was discussed by chaos parameters and complexity measures. Coherent results were achieved by our multi-scale analysis, which further exposed the behavior in a gas-solid two-phase system.
Multi-scale radiomic analysis of sub-cortical regions in MRI related to autism, gender and age
Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew
2017-01-01
We propose using multi-scale image textures to investigate links between neuroanatomical regions and clinical variables in MRI. Texture features are derived at multiple scales of resolution based on the Laplacian-of-Gaussian (LoG) filter. Three quantifier functions (Average, Standard Deviation and Entropy) are used to summarize texture statistics within standard, automatically segmented neuroanatomical regions. Significance tests are performed to identify regional texture differences between ASD vs. TDC and male vs. female groups, as well as correlations with age (corrected p Autism spectrum disorder (ASD, 65 female and 474 male) subjects. Statistically significant texture differences between ASD vs. TDC groups are identified asymmetrically in the right hippocampus, left choroid-plexus and corpus callosum (CC), and symmetrically in the cerebellar white matter. Sex-related texture differences in TDC subjects are found in primarily in the left amygdala, left cerebellar white matter, and brain stem. Correlations between age and texture in TDC subjects are found in the thalamus-proper, caudate and pallidum, most exhibiting bilateral symmetry. PMID:28361913
Directory of Open Access Journals (Sweden)
Quan Liu
2015-01-01
Full Text Available In order to build a reliable index to monitor the depth of anesthesia (DOA, many algorithms have been proposed in recent years, one of which is sample entropy (SampEn, a commonly used and important tool to measure the regularity of data series. However, SampEn only estimates the complexity of signals on one time scale. In this study, a new approach is introduced using multiscale entropy (MSE considering the structure information over different time scales. The entropy values over different time scales calculated through MSE are applied as the input data to train an artificial neural network (ANN model using bispectral index (BIS or expert assessment of conscious level (EACL as the target. To test the performance of the new index’s sensitivity to artifacts, we compared the results before and after filtration by multivariate empirical mode decomposition (MEMD. The new approach via ANN is utilized in real EEG signals collected from 26 patients before and after filtering by MEMD, respectively; the results show that is a higher correlation between index from the proposed approach and the gold standard compared with SampEn. Moreover, the proposed approach is more structurally robust to noise and artifacts which indicates that it can be used for monitoring the DOA more accurately.
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
The empirical mode decomposition method is used for analyzing the paleoclimate proxy δ18O from Greenland GISP2 ice core.The results show that millennium climate change trends in Greenland record the Medieval Warm Period (MWP) from 860AD-1350AD lasting for about 490 years,and the Little Ice Age (LIA) from 1350AD-1920AD lasting about 570 years.During these events,sub cooling-warming variations occurred.Its multi-scale oscillations changed with quasi-period of 3-year,6.5-year,12-year,24-year,49-year,96-year,213-year and 468-year,and are not only affected by ENSO but also by solar activity.The oscillation of intrinsic mode function IMF7,IMF8 and their tendency obviously appear in 1350AD which is considered as the key stage of transformation between MWP and LIA.The results give more detailed changes and their stages of millennium climate change in high latitude areas of the Northern Hemisphere.
Institute of Scientific and Technical Information of China (English)
HAN Jian; JIANG Nan
2008-01-01
Experimental measurement of hypersonic boundary layer stability and transition on a sharp cone with a half angle of 5° is carried out at free-coming stream Mach number 6 in a hypersonic wind tunnel.Mean and fluctuation surface-thermal-flux characteristics of the hypersonic boundary layer flow are measured by Pt-thin-film thermocouple temperature sensors installed at 28 stations on the cone surface along longitudinal direction.At hypersonic speeds,the dominant flow instabilities demonstrate that the growth rate of the second mode tends to exceed that of the low-frequency mode.Wavelet-based cross-spectrum technique is introduced to obtain the multi-scale cross-spectral characteristics of the fluctuating signals in the frequency range of the second mode.Nonlinear interactions both of the second mode disturbance and the first mode disturbance axe demonstrated to be dominant instabilities in the initial stage of laminar-turbulence transition for hypersonic shear flow.
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
Towards distributed multiscale computing for the VPH
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 o
Generalized multiscale finite element methods: Oversampling strategies
Efendiev, Yalchin R.
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
Directory of Open Access Journals (Sweden)
Jaime Resano-Mayor
Full Text Available Inter-individual diet variation within populations is likely to have important ecological and evolutionary implications. The diet-fitness relationships at the individual level and the emerging population processes are, however, poorly understood for most avian predators inhabiting complex terrestrial ecosystems. In this study, we use an isotopic approach to assess the trophic ecology of nestlings in a long-lived raptor, the Bonelli's eagle Aquila fasciata, and investigate whether nestling dietary breath and main prey consumption can affect the species' reproductive performance at two spatial scales: territories within populations and populations over a large geographic area. At the territory level, those breeding pairs whose nestlings consumed similar diets to the overall population (i.e. moderate consumption of preferred prey, but complemented by alternative prey categories or those disproportionally consuming preferred prey were more likely to fledge two chicks. An increase in the diet diversity, however, related negatively with productivity. The age and replacements of breeding pair members had also an influence on productivity, with more fledglings associated to adult pairs with few replacements, as expected in long-lived species. At the population level, mean productivity was higher in those population-years with lower dietary breadth and higher diet similarity among territories, which was related to an overall higher consumption of preferred prey. Thus, we revealed a correspondence in diet-fitness relationships at two spatial scales: territories and populations. We suggest that stable isotope analyses may be a powerful tool to monitor the diet of terrestrial avian predators on large spatio-temporal scales, which could serve to detect potential changes in the availability of those prey on which predators depend for breeding. We encourage ecologists and evolutionary and conservation biologists concerned with the multi-scale fitness
Multi-Scale Validation of a Nanodiamond Drug Delivery System and Multi-Scale Engineering Education
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…
Lencastre Fernandes, Rita; Carlquist, Magnus; Lundin, Luisa; Heins, Anna-Lena; Dutta, Abhishek; Sørensen, Søren J; Jensen, Anker D; Nopens, Ingmar; Lantz, Anna Eliasson; Gernaey, Krist V
2013-03-01
Despite traditionally regarded as identical, cells in a microbial cultivation present a distribution of phenotypic traits, forming a heterogeneous cell population. Moreover, the degree of heterogeneity is notably enhanced by changes in micro-environmental conditions. A major development in experimental single-cell studies has taken place in the last decades. It has however not been fully accompanied by similar contributions within data analysis and mathematical modeling. Indeed, literature reporting, for example, quantitative analyses of experimental single-cell observations and validation of model predictions for cell property distributions against experimental data is scarce. This study focuses on the experimental and mathematical description of the dynamics of cell size and cell cycle position distributions, of a population of Saccharomyces cerevisiae, in response to the substrate consumption observed during batch cultivation. The good agreement between the proposed multi-scale model (a population balance model [PBM] coupled to an unstructured model) and experimental data (both the overall physiology and cell size and cell cycle distributions) indicates that a mechanistic model is a suitable tool for describing the microbial population dynamics in a bioreactor. This study therefore contributes towards the understanding of the development of heterogeneous populations during microbial cultivations. More generally, it consists of a step towards a paradigm change in the study and description of cell cultivations, where average cell behaviors observed experimentally now are interpreted as a potential joint result of various co-existing single-cell behaviors, rather than a unique response common to all cells in the cultivation.
Using Multiscale Product for ECG Characterization
Directory of Open Access Journals (Sweden)
Rym Besrour
2009-01-01
Full Text Available This paper introduces a new method for R wave's locations using the multiscale wavelet analysis, that is based on Mallat's and Hwang's approach for singularity detection via local maxima of the wavelet coefficients signals. Using a first derivative Gaussian function as prototype wavelet, we apply the pointwise product of the wavelet coefficients (PWCs over some successive scales, in order to enhance the peak amplitude of the modulus maxima line and to reduce noise. The R wave corresponds to two modulus maximum lines with opposite signs (min-max of multi-scale product. The proposed algorithm does not include regularity analysis but only amplitude-based criteria. We evaluated the algorithm on two manually annotated databases, such as MIT-BIH Arrhythmia and QT.
Maxwell, R. M.; Bearup, L. A.; Penn, C. A.; Jefferson, J.; Engdahl, N. B.
2014-12-01
Changing climate, including warmer temperatures and drought conditions, has intensified mountain pine beetle infestation in the Rocky Mountains of North America, resulting in tree death over the last decade that is unprecedented in recorded history. The subsequent perturbation to tree-scale water budget processes such as interception, transpiration, and evaporation often combine non-uniformly and produce variable catchment-scale responses. Potentially offsetting perturbations such as decreased transpiration with tree death and increased exposure and evaporation with needle fall can produce changes in peak streamflow and water yield that are undetectable above typical interannual variability. These combined perturbations, however, may change streamflow generating processes and water sources that impact water quality in important mountain headwater streams. To determine the potential impact of widespread land cover change on catchment contributions to streamflow, this study combines a chemical and isotopic separation analysis using paired watersheds and pre-infestation controls with a multi-scale modeling approach (from hillslope to headwaters systems) that determines changes in water stores and fluxes between canopy, land-surface, groundwater and streamflow. Field observations and chemical hydrograph separation analysis suggest that groundwater contributions to streamflow increase with recent insect infestation, as transpiration ceases to remove water from the subsurface but potentially increased ground evaporation removes water from the land and subsurface with relative uniformity. Comparing these field observations to hillslope models provides additional spatial and temporal controls on inherently challenging field heterogeneities as well as a way of testing the influence of natural properties such as precipitation and topography on perturbations to streamflow partitioning from insect infestation. At larger scales, watershed models demonstrate how other factors
Finite Dimensional Approximations for Continuum Multiscale Problems
Energy Technology Data Exchange (ETDEWEB)
Berlyand, Leonid [Pennsylvania State Univ., University Park, PA (United States)
2017-01-24
The completed research project concerns the development of novel computational techniques for modeling nonlinear multiscale physical and biological phenomena. Specifically, it addresses the theoretical development and applications of the homogenization theory (coarse graining) approach to calculation of the effective properties of highly heterogenous biological and bio-inspired materials with many spatial scales and nonlinear behavior. This theory studies properties of strongly heterogeneous media in problems arising in materials science, geoscience, biology, etc. Modeling of such media raises fundamental mathematical questions, primarily in partial differential equations (PDEs) and calculus of variations, the subject of the PI’s research. The focus of completed research was on mathematical models of biological and bio-inspired materials with the common theme of multiscale analysis and coarse grain computational techniques. Biological and bio-inspired materials offer the unique ability to create environmentally clean functional materials used for energy conversion and storage. These materials are intrinsically complex, with hierarchical organization occurring on many nested length and time scales. The potential to rationally design and tailor the properties of these materials for broad energy applications has been hampered by the lack of computational techniques, which are able to bridge from the molecular to the macroscopic scale. The project addressed the challenge of computational treatments of such complex materials by the development of a synergistic approach that combines innovative multiscale modeling/analysis techniques with high performance computing.
2012-01-01
eddy simulation (LES) of wind-driven shear flow with Langmuir circulation (LC). Isogeometric analysis refers to our use of NURBS (Non-Uniform...analysis for large-eddy simulation (LES) of wind-driven shear flow with Langmuir circulation (LC). Isogeometric analysis refers to our use of NURBS ...equations with an extra vortex force term accounting for wave-current interaction giving rise to LC. The RBVMS method with quadratic NURBS is shown to
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
MULTISCALE PHENOMENA IN MATERIALS
Energy Technology Data Exchange (ETDEWEB)
A. BISHOP
2000-09-01
This project developed and supported a technology base in nonequilibrium phenomena underpinning fundamental issues in condensed matter and materials science, and applied this technology to selected problems. In this way the increasingly sophisticated synthesis and characterization available for classes of complex electronic and structural materials provided a testbed for nonlinear science, while nonlinear and nonequilibrium techniques helped advance our understanding of the scientific principles underlying the control of material microstructure, their evolution, fundamental to macroscopic functionalities. The project focused on overlapping areas of emerging thrusts and programs in the Los Alamos materials community for which nonlinear and nonequilibrium approaches will have decisive roles and where productive teamwork among elements of modeling, simulations, synthesis, characterization and applications could be anticipated--particularly multiscale and nonequilibrium phenomena, and complex matter in and between fields of soft, hard and biomimetic materials. Principal topics were: (i) Complex organic and inorganic electronic materials, including hard, soft and biomimetic materials, self-assembly processes and photophysics; (ii) Microstructure and evolution in multiscale and hierarchical materials, including dynamic fracture and friction, dislocation and large-scale deformation, metastability, and inhomogeneity; and (iii) Equilibrium and nonequilibrium phases and phase transformations, emphasizing competing interactions, frustration, landscapes, glassy and stochastic dynamics, and energy focusing.
Multiscale Cloud System Modeling
Tao, Wei-Kuo; Moncrieff, Mitchell W.
2009-01-01
The central theme of this paper is to describe how cloud system resolving models (CRMs) of grid spacing approximately 1 km have been applied to various important problems in atmospheric science across a wide range of spatial and temporal scales and how these applications relate to other modeling approaches. A long-standing problem concerns the representation of organized precipitating convective cloud systems in weather and climate models. Since CRMs resolve the mesoscale to large scales of motion (i.e., 10 km to global) they explicitly address the cloud system problem. By explicitly representing organized convection, CRMs bypass restrictive assumptions associated with convective parameterization such as the scale gap between cumulus and large-scale motion. Dynamical models provide insight into the physical mechanisms involved with scale interaction and convective organization. Multiscale CRMs simulate convective cloud systems in computational domains up to global and have been applied in place of contemporary convective parameterizations in global models. Multiscale CRMs pose a new challenge for model validation, which is met in an integrated approach involving CRMs, operational prediction systems, observational measurements, and dynamical models in a new international project: the Year of Tropical Convection, which has an emphasis on organized tropical convection and its global effects.
Multiscale macromolecular simulation: role of evolving ensembles.
Singharoy, A; Joshi, H; Ortoleva, P J
2012-10-22
Multiscale analysis provides an algorithm for the efficient simulation of macromolecular assemblies. This algorithm involves the coevolution of a quasiequilibrium probability density of atomic configurations and the Langevin dynamics of spatial coarse-grained variables denoted order parameters (OPs) characterizing nanoscale system features. In practice, implementation of the probability density involves the generation of constant OP ensembles of atomic configurations. Such ensembles are used to construct thermal forces and diffusion factors that mediate the stochastic OP dynamics. Generation of all-atom ensembles at every Langevin time step is computationally expensive. Here, multiscale computation for macromolecular systems is made more efficient by a method that self-consistently folds in ensembles of all-atom configurations constructed in an earlier step, history, of the Langevin evolution. This procedure accounts for the temporal evolution of these ensembles, accurately providing thermal forces and diffusions. It is shown that efficiency and accuracy of the OP-based simulations is increased via the integration of this historical information. Accuracy improves with the square root of the number of historical timesteps included in the calculation. As a result, CPU usage can be decreased by a factor of 3-8 without loss of accuracy. The algorithm is implemented into our existing force-field based multiscale simulation platform and demonstrated via the structural dynamics of viral capsomers.
Multiscale modeling of proteins.
Tozzini, Valentina
2010-02-16
The activity within a living cell is based on a complex network of interactions among biomolecules, exchanging information and energy through biochemical processes. These events occur on different scales, from the nano- to the macroscale, spanning about 10 orders of magnitude in the space domain and 15 orders of magnitude in the time domain. Consequently, many different modeling techniques, each proper for a particular time or space scale, are commonly used. In addition, a single process often spans more than a single time or space scale. Thus, the necessity arises for combining the modeling techniques in multiscale approaches. In this Account, I first review the different modeling methods for bio-systems, from quantum mechanics to the coarse-grained and continuum-like descriptions, passing through the atomistic force field simulations. Special attention is devoted to their combination in different possible multiscale approaches and to the questions and problems related to their coherent matching in the space and time domains. These aspects are often considered secondary, but in fact, they have primary relevance when the aim is the coherent and complete description of bioprocesses. Subsequently, applications are illustrated by means of two paradigmatic examples: (i) the green fluorescent protein (GFP) family and (ii) the proteins involved in the human immunodeficiency virus (HIV) replication cycle. The GFPs are currently one of the most frequently used markers for monitoring protein trafficking within living cells; nanobiotechnology and cell biology strongly rely on their use in fluorescence microscopy techniques. A detailed knowledge of the actions of the virus-specific enzymes of HIV (specifically HIV protease and integrase) is necessary to study novel therapeutic strategies against this disease. Thus, the insight accumulated over years of intense study is an excellent framework for this Account. The foremost relevance of these two biomolecular systems was
Betzel, Richard F
2016-01-01
The network architecture of the human brain has become a feature of increasing interest to the neuroscientific community, largely because of its potential to illuminate human cognition, its variation over development and aging, and its alteration in disease or injury. Traditional tools and approaches to study this architecture have largely focused on single scales -- of topology, time, and space. Expanding beyond this narrow view, we focus this review on pertinent questions and novel methodological advances for the multi-scale brain. We separate our exposition into content related to multi-scale topological structure, multi-scale temporal structure, and multi-scale spatial structure. In each case, we recount empirical evidence for such structures, survey network-based methodological approaches to reveal these structures, and outline current frontiers and open questions. Although predominantly peppered with examples from human neuroimaging, we hope that this account will offer an accessible guide to any neuros...
Multiscale spacetimes from first principles
Calcagni, Gianluca
2016-01-01
We formulate a theorem for the general profile of the Hausdorff and the spectral dimension of multiscale geometries, assuming a smooth and slow change of spacetime dimensionality at large scales. Agreement with various scenarios of quantum gravity is found. In particular, we derive uniquely the multiscale measure with log oscillations of theories of multifractional geometry. Predictivity of this class of models and falsifiability of their abundant phenomenology are thus established.
Multi-Scale Salient Features for Analyzing 3D Shapes
Institute of Scientific and Technical Information of China (English)
Yong-Liang Yang; Chao-Hui Shen
2012-01-01
Extracting feature regions on mesh models is crucial for shape analysis and understanding.It can be widely used for various 3D content-based applications in graphics and geometry field.In this paper,we present a new algorithm of extracting multi-scale salient features on meshes.This 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 kind of 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.
The Magnetospheric Multiscale Constellation
Tooley, C. R.; Black, R. K.; Robertson, B. P.; Stone, J. M.; Pope, S. E.; Davis, G. T.
2016-03-01
The Magnetospheric Multiscale (MMS) mission is the fourth mission of the Solar Terrestrial Probe (STP) program of the National Aeronautics and Space Administration (NASA). The MMS mission was launched on March 12, 2015. The MMS mission consists of four identically instrumented spin-stabilized observatories which are flown in formation to perform the first definitive study of magnetic reconnection in space. The MMS mission was presented with numerous technical challenges, including the simultaneous construction and launch of four identical large spacecraft with 100 instruments total, stringent electromagnetic cleanliness requirements, closed-loop precision maneuvering and pointing of spinning flexible spacecraft, on-board GPS based orbit determination far above the GPS constellation, and a flight dynamics design that enables formation flying with separation distances as small as 10 km. This paper describes the overall mission design and presents an overview of the design, testing, and early on-orbit operation of the spacecraft systems and instrument suite.
The Magentospheric Multiscale Constellation
Tooley, C. R.; Black, R. K.; Robertson, B. P.; Stone, J. M.; Pope, S. E.; Davis, G. T.
2015-01-01
The Magnetospheric Multiscale (MMS) mission is the fourth mission of the Solar Terrestrial Probe (STP) program of the National Aeronautics and Space Administration (NASA). The MMS mission was launched on March 12, 2015. The MMS mission consists of four identically instrumented spin-stabilized observatories which are flown in formation to perform the first definitive study of magnetic reconnection in space. The MMS mission was presented with numerous technical challenges, including the simultaneous construction and launch of four identical large spacecraft with 100 instruments total, stringent electromagnetic cleanliness requirements, closed-loop precision maneuvering and pointing of spinning flexible spacecraft, on-board GPS based orbit determination far above the GPS constellation, and a flight dynamics design that enables formation flying with separation distances as small as 10 km. This paper describes the overall mission design and presents an overview of the design, testing, and early on-orbit operation of the spacecraft systems and instrument suite.
Sensing and Multiscale Structure
Fletcher, John F A
2012-01-01
We introduce a method of estimating parameters associated with a fractal random scattering medium, which utilizes the multiscale properties of the scattered field. The example of ray-density fluctuations beyond a phase screen with fractal slope is considered. An exact solution to the forward problem, in the case of the Brownian fractal, leads to an expression for the volatility of the slope. This expression is invariant under a change of probability measure, a fact which gives rise to the corresponding result for a (stationary) Ornstein-Uhlenbeck slope. We demonstrate that our analytical results are consistent with numerical simulations. Finally, an application to the determination of sea ice thickness via sonar is discussed.
MULTISCALE THERMOHYDROLOGIC MODEL
Energy Technology Data Exchange (ETDEWEB)
T.A. Buscheck
2001-12-21
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&O 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.
y～n Curve Model of Multi-scale Analysis to DNA Microarray Data%基因芯片数据多尺度分析的y～n曲线模型
Institute of Scientific and Technical Information of China (English)
罗万春; 易东; 李辉智; 龚利红
2011-01-01
针对离散的基因芯片表达数据难以进行系统分析的问题,提出基因芯片数据的y～n曲线模型,将级基因芯片数据转化为唯一的一列信号,从而可以对其进行多尺度分析.对人类胎儿脑发育过程中大脑皮质基因表达基于y～n曲线模型进行小波多尺度降噪,结果证明,y～n曲线的降噪效果比用基因芯片原始数据更好.%The model of y～n curve is set up to solve the problem that discrete gene chip data are difficult to be systematically analyzed, which makes the data be changed into a row of sole signal, and can be studied by multi-scale analysis. Results of denoising the cerebral cortex gene expression of developing human brain based on wavelet multi-scale analysis show that the denoised effect of y～n curve is better than that of raw data.
Gravemeier, Volker; Kronbichler, Martin; Gee, Michael W.; Wall, Wolfgang A.
2011-02-01
This article studies three aspects of the recently proposed algebraic variational multiscale-multigrid method for large-eddy simulation of turbulent flow. First, the method is integrated into a second-order-accurate generalized-α time-stepping scheme. Second, a Fourier analysis of a simplified model problem is performed to assess the impact of scale separation on the overall performance of the method. The analysis reveals that scale separation implemented by projective operators provides modeling effects very close to an ideal small-scale subgrid viscosity, that is, it preserves low frequencies, in contrast to non-projective scale separations. Third, the algebraic variational multiscale-multigrid method is applied to turbulent flow past a square-section cylinder. The computational results obtained with the method reveal, on the one hand, the good accuracy achievable for this challenging test case already at a rather coarse discretization and, on the other hand, the superior computing efficiency, e.g., compared to a traditional dynamic Smagorinsky modeling approach.
Directory of Open Access Journals (Sweden)
Ming-Shu Chen
2014-01-01
Full Text Available Falls are unpredictable accidents, and the resulting injuries can be serious in the elderly, particularly those with chronic diseases. Regular exercise is recommended to prevent and treat hypertension and other chronic diseases by reducing clinical blood pressure. The “complexity index” (CI, based on multiscale entropy (MSE algorithm, has been applied in recent studies to show a person’s adaptability to intrinsic and external perturbations and widely used measure of postural sway or stability. The multivariate multiscale entropy (MMSE was advanced algorithm used to calculate the complexity index (CI values of the center of pressure (COP data. In this study, we applied the MSE & MMSE to analyze gait function of 24 elderly, chronically ill patients (44% female; 56% male; mean age, 67.56±10.70 years with either cardiovascular disease, diabetes mellitus, or osteoporosis. After a 12-week training program, postural stability measurements showed significant improvements. Our results showed beneficial effects of resistance training, which can be used to improve postural stability in the elderly and indicated that MMSE algorithms to calculate CI of the COP data were superior to the multiscale entropy (MSE algorithm to identify the sense of balance in the elderly.
Bertrand, Lionel; Géraud, Yves; Le Garzic, Edouard; Place, Joachim; Diraison, Marc; Walter, Bastien; Haffen, Sébastien
2015-09-01
The in-depth investigation of fractured reservoirs is mainly limited to geophysical data that is in 3D and mostly on the scale of hundred meters to several kilometers or boreholes data that is in 1D and at meter to lower scale. The study of outcropping analogues of buried reservoirs is therefore a key tool for the characterization of the fault and fracture network at the reservoir scale. Tamariu granite has been the subject of this study with the aim to analyse faults and fractures from seismic to borehole scale. With the combination of satellite picture at different resolution and field study, we perform a statistical analysis focused of the length and orientation from infra centimeter crack to hundred kilometer length fault. On the whole range of scale studied, i.e. on 7 orders of magnitude, we have defined a length distribution following a power-law with an exponent a = -2. On the contrary to the length that can be modelled with a unique law, the orientation data shows a variation depending on the scale of observation: as the fault and fracture sets are suitable from the regional faults to the centimeter crack, the proportion of the sets varies at each scale of observation.
Complexity multiscale asynchrony measure and behavior for interacting financial dynamics
Yang, Ge; Wang, Jun; Niu, Hongli
2016-08-01
A stochastic financial price process is proposed and investigated by the finite-range multitype contact dynamical system, in an attempt to study the nonlinear behaviors of real asset markets. The viruses spreading process in a finite-range multitype system is used to imitate the interacting behaviors of diverse investment attitudes in a financial market, and the empirical research on descriptive statistics and autocorrelation behaviors of return time series is performed for different values of propagation rates. Then the multiscale entropy analysis is adopted to study several different shuffled return series, including the original return series, the corresponding reversal series, the random shuffled series, the volatility shuffled series and the Zipf-type shuffled series. Furthermore, we propose and compare the multiscale cross-sample entropy and its modification algorithm called composite multiscale cross-sample entropy. We apply them to study the asynchrony of pairs of time series under different time scales.
Coherent multiscale image processing using dual-tree quaternion wavelets.
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.
Dyess, Jonathan
This dissertation is a multi-scale structural and kinematic analysis of the Shagawa Lake shear zone in northeastern Minnesota (USA). The Neoarchean Shagawa Lake shear zone is an ~70 km long ~7 km wide subvertical package of L-S tectonites located within the Wawa Subprovince of the Archean Superior Province. In this dissertation, I (1) discuss a new method for mapping regional tectonic fabrics using high-resolution LiDAR altimetry data; (2) examine the geometric relationships between metamorphic foliation, elongation lineation, vorticity, and non-coaxial shear direction within individual L-S tectonites; and (3) incorporate LiDAR, field, and microstructural data sets into a comprehensive structural and kinematic analysis of the Western Shagawa Lake shear zone. Lastly, I discuss implications for assembly of the southern Superior Province. In Chapter one I examine an Archean granite-greenstone terrane in NE Minnesota to illustrate the application of high-resolution LiDAR altimetry to mapping regional tectonic fabrics in forested, glaciated areas. I describe the recognition of lineaments and distinguishing between tectonic and glacial lineament fabrics. I use a 1-m posted LiDAR derived bare-earth digital elevation model (DEM) to construct multiple shaded-relief images for lineament mapping with sun elevation of 45˚ and varying sun azimuth in 45˚ intervals. Two suites of lineaments are apparent. Suite A has a unimodal orientation, mean trend of 035, and consists of short (> 2 km long) lineaments within sediment deposits and bedrock. Suite B lineaments, which are longer (1-30 km) than those of suite A, have a quasi-bimodal orientation distribution, with maximum trends of 065 and 090. Only one lineament suite is visible in areas where suites A and B are parallel. I interpret suite A as a surficial geomorphologic fabric related to recent glaciation, and suite B as a proxy for the regional tectonic fabric. In Chapter two I present a detailed kinematic study of seven
Multiscale modeling in nanomaterials science
Energy Technology Data Exchange (ETDEWEB)
Karakasidis, T.E. [Department of Civil Engineering, University of Thessaly, Pedion Areos, GR-38834 Volos (Greece)], E-mail: thkarak@uth.gr; Charitidis, C.A. [National Technical University of Athens, School of Chemical Engineering, 9 Heroon, Polytechniou st., Zografos, GR-157 80 Athens (Greece)
2007-09-15
Nanoscience is an area with increasing interest both in the physicochemical phenomena involved and the potential applications such as silicon carbide films, carbon nanotubes, quantum dots, MEMS etc. These materials exhibit very interesting properties (electronic, optical, mechanical) at various length/time scales necessitating better insight. Modern fabrication techniques, such as CVD, also require better understanding in a wide range of length/time scales, in order to achieve better process control. Multiscale modeling is a new, fast developing and challenging scientific field with contributions from many scientific disciplines in an effort to assure materials simulation across length/time scales. In this paper we present a brief review of recent advances in multiscale materials modeling. First, a classification of existing simulation methods based on time and length scales is presented along with basic principles of the multiscale approach. More specifically, we focus on electronic structure calculations, classical atomistic simulation with molecular dynamics or monte carlo methods at the nano/micro scale, Kinetic Monte Carlo for larger system/time scales and finite elements for very large scales. Then, we present the hierarchical and the hybrid strategies of multiscale modeling to couple these methods. Finally, we deal with selected applications concerning thin film CVD deposition and mechanical behavior of carbon nanotubes and we conclude presenting an overview of future trends of multiscale modeling.
The Magnetospheric Multiscale Magnetometers
Russell, C. T.; Anderson, B. J.; Baumjohann, W.; Bromund, K. R.; Dearborn, D.; Fischer, D.; Le, G.; Leinweber, H. K.; Leneman, D.; Magnes, W.; Means, J. D.; Moldwin, M. B.; Nakamura, R.; Pierce, D.; Plaschke, F.; Rowe, K. M.; Slavin, J. A.; Strangeway, R. J.; Torbert, R.; Hagen, C.; Jernej, I.; Valavanoglou, A.; Richter, I.
2016-03-01
The success of the Magnetospheric Multiscale mission depends on the accurate measurement of the magnetic field on all four spacecraft. To ensure this success, two independently designed and built fluxgate magnetometers were developed, avoiding single-point failures. The magnetometers were dubbed the digital fluxgate (DFG), which uses an ASIC implementation and was supplied by the Space Research Institute of the Austrian Academy of Sciences and the analogue magnetometer (AFG) with a more traditional circuit board design supplied by the University of California, Los Angeles. A stringent magnetic cleanliness program was executed under the supervision of the Johns Hopkins University's Applied Physics Laboratory. To achieve mission objectives, the calibration determined on the ground will be refined in space to ensure all eight magnetometers are precisely inter-calibrated. Near real-time data plays a key role in the transmission of high-resolution observations stored on board so rapid processing of the low-resolution data is required. This article describes these instruments, the magnetic cleanliness program, and the instrument pre-launch calibrations, the planned in-flight calibration program, and the information flow that provides the data on the rapid time scale needed for mission success.
Multi-Scale Pattern Recognition for Image Classification and Segmentation
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 basi
Institute of Scientific and Technical Information of China (English)
潘建荣; 杨正挺; 王湛; 董现
2016-01-01
考虑参数相关性，应用结构多尺度模型，对外加强环式钢管混凝土柱-钢梁节点进行了不确定性结构灵敏度分析，并进行多尺度半刚性组合平面框架体系模型在典型地震波下的弹塑性时程分析．分析表明，采用的多尺度界面连接方法，对于单一材料截面和组合材料截面是同样有效的；获得该组合节点转动的弯矩-转角曲线模型；在进行该组合框架体系地震时程分析时，框架顶层位移的平均相对偏差达到14.6%,，表明考虑节点半刚性是必要的．本文所提方法弥补了实体单元模型与杆系模型的不足，计算精确、有效，且可以关注局部区域．%By considering the correlations between parameters and adopting a multi-scale model,the probabilistic structure sensitivity analysis of the joint of steel beam-concrete filled steel tubular(CFST)column with stiffening ring is carried out,and an elastic-plastic time-history analysis is performed on the multi-scale semi-rigid composite frame under typical seismic waves.The results show that the multi-scale method is effective for both single and composite material sections;the moment-rotation angle model is obtained;the average relative error of the top floor displace-ment is 14.6%, according to the time-history analysis of the composite frame,indicating that the semi-rigidity of the joint should not be ignored.The proposed method in this paper can fix the deficiency of solid element model and beam element model,calculate accurately and efficiently,and focus on the local details.
Multiscale coupling:challenges and opportunities
Institute of Scientific and Technical Information of China (English)
HE Guowei; XIA Mengfen; KE Fuju; BAI Yilong
2004-01-01
Multiscale coupling is ubiquitous in nature and attracts broad interests of scientists from mathematicians, physicists, machinists, chemists to biologists. However, much less attention has been paid to its intrinsic implication. In this paper, multiscale coupling is introduced by studying two typical examples in classic mechanics: fluid turbulence and solid failure. The nature of multiscale coupling in the two examples lies in their physical diversities and strong coupling over wide-range scales. The theories of dynamical system and statistical mechanics provide fundamental methods for the multiscale coupling problems. The diverse multiscale couplings call for unified approaches and might expedite new concepts, theories and disciplines.
PDF-based heterogeneous multiscale filtration model.
Gong, Jian; Rutland, Christopher J
2015-04-21
Motivated by modeling of gasoline particulate filters (GPFs), a probability density function (PDF) based heterogeneous multiscale filtration (HMF) model is developed to calculate filtration efficiency of clean particulate filters. A new methodology based on statistical theory and classic filtration theory is developed in the HMF model. Based on the analysis of experimental porosimetry data, a pore size probability density function is introduced to represent heterogeneity and multiscale characteristics of the porous wall. The filtration efficiency of a filter can be calculated as the sum of the contributions of individual collectors. The resulting HMF model overcomes the limitations of classic mean filtration models which rely on tuning of the mean collector size. Sensitivity analysis shows that the HMF model recovers the classical mean model when the pore size variance is very small. The HMF model is validated by fundamental filtration experimental data from different scales of filter samples. The model shows a good agreement with experimental data at various operating conditions. The effects of the microstructure of filters on filtration efficiency as well as the most penetrating particle size are correctly predicted by the model.
Biomedical Engineering Bionanosystems Research at Louisiana Tech University
Energy Technology Data Exchange (ETDEWEB)
Palmer, James; Lvov, Yuri; Hegab, Hisham; Snow, Dale; Wilson, Chester; McDonald, John; Walker, Lynn; Pratt, Jon; Davis, Despina; Agarwal, Mangilal; DeCoster, Mark; Feng, June; Que, Long; O' Neal, Chad; Guilbeau, Eric; Zivanovic, Sandra; Dobbins, Tabbetha; Gold, Scott; Mainardi, Daniela; Gowda, Shathabish; Napper, Stan
2010-03-25
The nature of this project is to equip and support research in nanoengineered systems for biomedical, bioenvironmental, and bioenergy applications. Funds provided by the Department of Energy (DoE) under this Congressional Directive were used to support two ongoing research projects at Louisiana Tech University in biomedical, bioenvironmental, and bioenergy applications. Two major projects (Enzyme Immobilization for Large Scale Reactors to Reduce Cellulosic Ethanol Costs, and Nanocatalysts for Coal and Biomass Conversion to Diesel Fuel) and to fund three to five additional seed projects were funded using the project budget. The project funds also allowed the purchase and repair of sophisticated research equipment that will support continued research in these areas for many years to come. Project funds also supported faculty, graduate students, and undergraduate students, contributing to the development of a technically sophisticated work force in the region and the State. Descriptions of the technical accomplishments for each funded project are provided. Biofuels are an important part of the solution for sustainable transportation fuel and energy production for the future. Unfortunately, the country's appetite for fuel cannot be satisfied with traditional sugar crops such as sugar cane or corn. Emerging technologies are allowing cellulosic biomass (wood, grass, stalks, etc.) to also be converted into ethanol. Cellulosic ethanol does not compete with food production and it has the potential to decrease greenhouse gas (GHG) emissions by 86% versus current fossil fuels (current techniques for corn ethanol only reduce greenhouse gases by 19%). Because of these advantages, the federal government has made cellulosic ethanol a high priority. The Energy Independence and Security Act of 2007 (EISA) requires a minimum production of at least 16 billion gallons of cellulosic ethanol by 2022. Indeed, the Obama administration has signaled an ambitious commitment of achieving 2 billion gallons of cellulosic ethanol by 2013. Louisiana is well positioned to become a national contributor in cellulosic ethanol, with an excellent growing season, a strong pulp/paper industry, and one of the nation's first cellulosic ethanol demonstration plants. Dr. Palmer in Chemical Engineering at Louisiana Tech University is collaborating with Drs. Lvov and Snow in Chemistry and Dr. Hegab in Mechanical Engineering to capitalize on these advantages by applying nanotechnology to improve the cellulosic ethanol processes. In many of these processes, expensive enzymes are used to convert the cellulose to sugars. The nanotechnology processes developed at Louisiana Tech University can immobilize these enzymes and therefore significantly reduce the overall costs of the process. Estimates of savings range from approximately $32 million at each cellulosic ethanol plant, to $7.5 billion total if the 16 billion gallons of cellulosic ethanol is achieved. This process has the advantage of being easy to apply in a large-scale commercial environment and can immobilize a wide variety or mixture of enzymes for production. Two primary objectives with any immobilization technique are to demonstrate reusability and catalytic activity (both reuse of the immobilized enzyme and reuse of the polymer substrate). The scale-up of the layering-by-layering process has been a focus this past year as some interesting challenges in the surface chemistry have become evident. Catalytic activity of cellulase is highly dependent upon how the feed material is pretreated to enhance digestion. Therefore, efforts this year have been performed this year to characterize our process on a few of the more prevalent pretreatment methods.
Reduced basis heterogeneous multiscale methods
Abdulle, Assyr
2015-01-01
Numerical methods for partial differential equations with multiple scales that combine numerical homogenization methods with reduced order modeling techniques are discussed. These numerical methods can be applied to a variety of problems including multiscale nonlinear elliptic and parabolic problems or Stokes flow in heterogenenous media.
Multiscale Image Based Flow Visualization
Telea, Alexandru; Strzodka, Robert
2006-01-01
We present MIBFV, a method to produce real-time, multiscale animations of flow datasets. MIBFV extends the attractive features of the Image-Based Flow Visualization (IBFV) method, i.e. dense flow domain coverage with flow-aligned noise, real-time animation, implementation simplicity, and few (or no)
Generalized multiscale finite element methods for problems in perforated heterogeneous domains
Chung, Eric T.
2015-06-08
Complex processes in perforated domains occur in many real-world applications. These problems are typically characterized by physical processes in domains with multiple scales. Moreover, these problems are intrinsically multiscale and their discretizations can yield very large linear or nonlinear systems. In this paper, we investigate multiscale approaches that attempt to solve such problems on a coarse grid by constructing multiscale basis functions in each coarse grid, where the coarse grid can contain many perforations. In particular, we are interested in cases when there is no scale separation and the perforations can have different sizes. In this regard, we mention some earlier pioneering works, where the authors develop multiscale finite element methods. In our paper, we follow Generalized Multiscale Finite Element Method (GMsFEM) and develop a multiscale procedure where we identify multiscale basis functions in each coarse block using snapshot space and local spectral problems. We show that with a few basis functions in each coarse block, one can approximate the solution, where each coarse block can contain many small inclusions. We apply our general concept to (1) Laplace equation in perforated domains; (2) elasticity equation in perforated domains; and (3) Stokes equations in perforated domains. Numerical results are presented for these problems using two types of heterogeneous perforated domains. The analysis of the proposed methods will be presented elsewhere. © 2015 Taylor & Francis
Multiscale modeling methods in biomechanics.
Bhattacharya, Pinaki; Viceconti, Marco
2017-01-19
More and more frequently, computational biomechanics deals with problems where the portion of physical reality to be modeled spans over such a large range of spatial and temporal dimensions, that it is impossible to represent it as a single space-time continuum. We are forced to consider multiple space-time continua, each representing the phenomenon of interest at a characteristic space-time scale. Multiscale models describe a complex process across multiple scales, and account for how quantities transform as we move from one scale to another. This review offers a set of definitions for this emerging field, and provides a brief summary of the most recent developments on multiscale modeling in biomechanics. Of all possible perspectives, we chose that of the modeling intent, which vastly affect the nature and the structure of each research activity. To the purpose we organized all papers reviewed in three categories: 'causal confirmation,' where multiscale models are used as materializations of the causation theories; 'predictive accuracy,' where multiscale modeling is aimed to improve the predictive accuracy; and 'determination of effect,' where multiscale modeling is used to model how a change at one scale manifests in an effect at another radically different space-time scale. Consistent with how the volume of computational biomechanics research is distributed across application targets, we extensively reviewed papers targeting the musculoskeletal and the cardiovascular systems, and covered only a few exemplary papers targeting other organ systems. The review shows a research subdomain still in its infancy, where causal confirmation papers remain the most common. For further resources related to this article, please visit the WIREs website.
Analysis of Sleep EEG by Using Multi-Scale Entropy%睡眠EEG的多尺度信息熵分析
Institute of Scientific and Technical Information of China (English)
宦飞; 王志中; 郑崇勋
2001-01-01
Based on application of continuous wavelet transform, a new method for analyzing sleep EEG is presented.The wavelet transform coefficients of the EEG signals are computed by using Morlet's wavelet. The information content carried by the wavelet coefficients on any scale is measured with entropy. Analyzing sleep EEG, it may be observed that the change in the multi-scale entropy of the EEG signals in light sleep stage is different from that in deep sleep stage, and the change in the multiscale entropy of the EEG signals in REM sleep stage is similar to that in deep sleep. By this method, we can distinguish thecharacteristics of the EEG in light sleep stage and that in the REM sleep stage.%本文提出一种基于连续小波变换的睡眠EEG分析方法。该方法使用Morlet小波计算EEG信息的小波变换系数，通过计算EEG信号在多个尺度上小波系数的熵分析睡眠EEG。结果表明：浅睡阶段EEG信号的多尺度熵的变化模式与深睡阶段的多尺度熵的变化模式不同，REM睡眠期间EEG信号的多尺度熵的变化与深睡阶段类似，使用多尺度熵可以区分REM睡眠和浅睡时EEG之间的差别。
Ding, Jiao; Jiang, Yuan; Liu, Qi; Hou, Zhaojiang; Liao, Jianyu; Fu, Lan; Peng, Qiuzhi
2016-05-01
Understanding the relationships between land use patterns and water quality in low-order streams is useful for effective landscape planning to protect downstream water quality. A clear understanding of these relationships remains elusive due to the heterogeneity of land use patterns and scale effects. To better assess land use influences, we developed empirical models relating land use patterns to the water quality of low-order streams at different geomorphic regions across multi-scales in the Dongjiang River basin using multivariate statistical analyses. The land use pattern was quantified in terms of the composition, configuration and hydrological distance of land use types at the reach buffer, riparian corridor and catchment scales. Water was sampled under summer base flow at 56 low-order catchments, which were classified into two homogenous geomorphic groups. The results indicated that the water quality of low-order streams was most strongly affected by the configuration metrics of land use. Poorer water quality was associated with higher patch densities of cropland, orchards and grassland in the mountain catchments, whereas it was associated with a higher value for the largest patch index of urban land use in the plain catchments. The overall water quality variation was explained better by catchment scale than by riparian- or reach-scale land use, whereas the spatial scale over which land use influenced water quality also varied across specific water parameters and the geomorphic basis. Our study suggests that watershed management should adopt better landscape planning and multi-scale measures to improve water quality.
Randomized Oversampling for Generalized Multiscale Finite Element Methods
Calo, Victor M.
2016-03-23
In this paper, we develop efficient multiscale methods for flows in heterogeneous media. We use the generalized multiscale finite element (GMsFEM) framework. GMsFEM approximates the solution space locally using a few multiscale basis functions. This approximation selects an appropriate snapshot space and a local spectral decomposition, e.g., the use of oversampled regions, in order to achieve an efficient model reduction. However, the successful construction of snapshot spaces may be costly if too many local problems need to be solved in order to obtain these spaces. We use a moderate quantity of local solutions (or snapshot vectors) with random boundary conditions on oversampled regions with zero forcing to deliver an efficient methodology. Motivated by the randomized algorithm presented in [P. G. Martinsson, V. Rokhlin, and M. Tygert, A Randomized Algorithm for the approximation of Matrices, YALEU/DCS/TR-1361, Yale University, 2006], we consider a snapshot space which consists of harmonic extensions of random boundary conditions defined in a domain larger than the target region. Furthermore, we perform an eigenvalue decomposition in this small space. We study the application of randomized sampling for GMsFEM in conjunction with adaptivity, where local multiscale spaces are adaptively enriched. Convergence analysis is provided. We present representative numerical results to validate the method proposed.
Multiscale effect of hierarchical self-assembled nanostructures on superhydrophobic surface.
Passoni, Luca; Bonvini, Giacomo; Luzio, Alessandro; Facibeni, Anna; Bottani, Carlo E; Di Fonzo, Fabio
2014-11-18
In this work, we describe self-assembled surfaces with a peculiar multiscale organization, from the nanoscale to the microscale, exhibiting the Cassie-Baxter wetting regime with extremely low water adhesion: floating drops regime with roll-off angles surface cleanliness play a crucial role. Moreover, the multiscale analysis performed in this work contributes to the understanding of the basic mechanisms behind extreme wetting behaviors.
Multiscale vision model for event detection and reconstruction in two-photon imaging data
DEFF Research Database (Denmark)
Brazhe, Alexey; Mathiesen, Claus; Lind, Barbara;
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....
Multiscale Modelling and Inverse Problems
Nolen, J; Stuart, A M
2010-01-01
The need to blend observational data and mathematical models arises in many applications and leads naturally to inverse problems. Parameters appearing in the model, such as constitutive tensors, initial conditions, boundary conditions, and forcing can be estimated on the basis of observed data. The resulting inverse problems are often ill-posed and some form of regularization is required. These notes discuss parameter estimation in situations where the unknown parameters vary across multiple scales. We illustrate the main ideas using a simple model for groundwater flow. We will highlight various approaches to regularization for inverse problems, including Tikhonov and Bayesian methods. We illustrate three ideas that arise when considering inverse problems in the multiscale context. The first idea is that the choice of space or set in which to seek the solution to the inverse problem is intimately related to whether a homogenized or full multiscale solution is required. This is a choice of regularization. The ...
Multi-scale MSDT inversion based on LAI spatial knowledge
Institute of Scientific and Technical Information of China (English)
ZHU XiaoHua; FENG XiaoMing; ZHAO YingShi
2012-01-01
Quantitative remote sensing inversion is ill-posed.The Moderate Resolution Imaging Spectroradiometer at 250 m resolution (MODIS_250m) contains two bands.To deal with this ill-posed inversion of MODIS_250m data,we propose a framework,the Multi-scale,Multi-stage,Sample-direction Dependent,Target-decisions (Multi-scale MSDT) inversion method,based on spatial knowledge.First,MODIS images (1 km,500 m,250 m) are used to extract multi-scale spatial knowledge.The inversion accuracy of MODIS_1km data is improved by reducing the impact of spatial heterogeneity.Then,coarse-scale inversion is taken as prior knowledge for the fine scale,again by inversion.The prior knowledge is updated after each inversion step.At each scale,MODIS_1km to MODIS_250m,the inversion is directed by the Uncertainty and Sensitivity Matrix (USM),and the most uncertain parameters are inversed by the most sensitive data.All remote sensing data are involved in the inversion,during which multi-scale spatial knowledge is introduced,to reduce the impact of spatial heterogeneity.The USM analysis is used to implement a reasonable allocation of limited remote sensing data in the model space.In the entire multi-scale inversion process,field data,spatial knowledge and multi-scale remote sensing data are all involved.As the multi-scale,multi-stage inversion is gradually refined,initial expectations of parameters become more reasonable and their uncertainty range is effectively reduced,so that the inversion becomes increasingly targeted.Finally,the method is tested by retrieving the Leaf Area Index (LAI) of the crop canopy in the Heihe River Basin.The results show that the proposed method is reliable.
Canonical transfer and multiscale energetics for primitive and quasi-geostrophic atmospheres
Liang, X San
2016-01-01
The past years have seen the success of a novel multiscale energetic formalism in a variety of ocean and engineering fluid applications. In a self-contained way, this study introduces it to the atmospheric dynamical diagnostics, with important theoretical updates. Multiscale energy equations are derived using a new analysis apparatus, namely, multiscale window transform, with respect to both the primitive equation and quasi-geostrophic models. A reconstruction of the "atomic" energy fluxes on the multiple scale windows allows for a natural and unique separation of the in-scale transports and cross-scale transfers from the intertwined nonlinear processes. The resulting energy transfers bear a Lie bracket form, reminiscent of the Poisson bracket in Hamiltonian mechanics, we hence would call them "canonical". A canonical transfer process is a mere redistribution of energy among scale windows, without generating or destroying energy as a whole. By classification, a multiscale energetic cycle comprises of availabl...
Multi-scale random sets: from morphology to effective properties and to fracture statistics
Energy Technology Data Exchange (ETDEWEB)
Jeulin, Dominique, E-mail: dominique.jeulin@mines-paristech.fr [Centre de Morphologie Mathematique, Mathematiques et Systemes, Mines ParisTech 35 rue Saint-Honore, F77300 Fontainebleau (France)
2011-09-15
Complex microstructures in materials often involve multi-scale heterogeneous textures, modelled by random sets derived from Mathematical Morphology. Starting from 2D or 3D images, a complete morphological characterization by image analysis is performed, and used for the identification of a model of random structure. From morphological models, simulations of realistic microstructures are introduced in a numerical solver to compute appropriate fields (electric, elastic stress or strain, ...) and to estimate the effective properties by numerical homogenization, accounting for scale dependent statistical fluctuations of the fields. Our approach is illustrated by various examples of multi-scale models: Boolean random sets based on Cox point processes and various random grains (spheres, cylinders), showing a very low percolation threshold, and therefore a high conductivity or high elastic moduli for a low volume fraction of a second phase. Multiscale Cox point processes are also a source of instructive models of fracture statistics, such as multiscale weakest link models.
Multiscale expansions in discrete world
Indian Academy of Sciences (India)
Ömer Ünsal; Filiz Taşcan; Mehmet Naci Özer
2014-07-01
In this paper, we show the attainability of KdV equation from some types of nonlinear Schrödinger equation by using multiscale expansions discretely. The power of this manageable method is confirmed by applying it to two selected nonlinear Schrödinger evolution equations. This approach can also be applied to other nonlinear discrete evolution equations. All the computations have been made with Maple computer packet program.
Regueiro, R. A.; Yu, S.
2010-12-01
The paper models grain-scale micro-cracking in shale at grain-matrix interfaces, assuming constituents are composed of quart silt grains and compacted clay matrix for a typical shale. The influence of grain-matrix-grain interaction on micro-crack patterns is investigated. Elasto-plastic pressure-sensitive cohesive-surface models are inserted at grain-matrix interfaces and intra-clay-matrix finite element facets, while a bulk elasto-plasticity model with bifurcation is employed for the clay matrix to compare to the intra-clay-matrix cohesive-surface model. Numerical examples are presented under two-dimensional plane strain condition at small strains. A procedure is proposed to upscale grain-scale micro-cracking to predict macro-fracture nucleation and propagation in shale and other bound particulate materials. It is shown that using cohesive surface elements (CSEs) at all finite element facets in the clay matrix mesh to simulate micro-cracking in the clay matrix leads to mesh-dependent results. Using CSEs at grain-clay-matrix interfaces is physical and not mesh dependent. We also considered using bulk pressure-sensitive elasto-plasticity with bifurcation condition within the clay matrix to attempt to predict onset of localization around grains in the simulations. It was encouraging to see that for both the single grain and multiple grain simulations, the finite element region in the clay matrix meshes where bifurcation was first detected around the grains was nearly the same. This gives us confidence that once a proper post-bifurcation constitutive model is implemented within an embedded discontinuity formulation, micro-cracking nucleation and propagation at the grain-scale in shale can be properly simulated, which will provide the basis for up-scaling to macro-cracks within a multiscale method for fracture in shale. Other items to address in future research are: (i) include transverse isotropy (elastic and plastic) for the bulk clay matrix elasto-plasticity model
Multiscale modeling and synaptic plasticity.
Bhalla, Upinder S
2014-01-01
Synaptic plasticity is a major convergence point for theory and computation, and the process of plasticity engages physiology, cell, and molecular biology. In its many manifestations, plasticity is at the hub of basic neuroscience questions about memory and development, as well as more medically themed questions of neural damage and recovery. As an important cellular locus of memory, synaptic plasticity has received a huge amount of experimental and theoretical attention. If computational models have tended to pick specific aspects of plasticity, such as STDP, and reduce them to an equation, some experimental studies are equally guilty of oversimplification each time they identify a new molecule and declare it to be the last word in plasticity and learning. Multiscale modeling begins with the acknowledgment that synaptic function spans many levels of signaling, and these are so tightly coupled that we risk losing essential features of plasticity if we focus exclusively on any one level. Despite the technical challenges and gaps in data for model specification, an increasing number of multiscale modeling studies have taken on key questions in plasticity. These have provided new insights, but importantly, they have opened new avenues for questioning. This review discusses a wide range of multiscale models in plasticity, including their technical landscape and their implications.
Mathematical and Numerical Analyses of Peridynamics for Multiscale Materials Modeling
Energy Technology Data Exchange (ETDEWEB)
Du, Qiang [Pennsylvania State Univ., State College, PA (United States)
2014-11-12
The rational design of materials, the development of accurate and efficient material simulation algorithms, and the determination of the response of materials to environments and loads occurring in practice all require an understanding of mechanics at disparate spatial and temporal scales. The project addresses mathematical and numerical analyses for material problems for which relevant scales range from those usually treated by molecular dynamics all the way up to those most often treated by classical elasticity. The prevalent approach towards developing a multiscale material model couples two or more well known models, e.g., molecular dynamics and classical elasticity, each of which is useful at a different scale, creating a multiscale multi-model. However, the challenges behind such a coupling are formidable and largely arise because the atomistic and continuum models employ nonlocal and local models of force, respectively. The project focuses on a multiscale analysis of the peridynamics materials model. Peridynamics can be used as a transition between molecular dynamics and classical elasticity so that the difficulties encountered when directly coupling those two models are mitigated. In addition, in some situations, peridynamics can be used all by itself as a material model that accurately and efficiently captures the behavior of materials over a wide range of spatial and temporal scales. Peridynamics is well suited to these purposes because it employs a nonlocal model of force, analogous to that of molecular dynamics; furthermore, at sufficiently large length scales and assuming smooth deformation, peridynamics can be approximated by classical elasticity. The project will extend the emerging mathematical and numerical analysis of peridynamics. One goal is to develop a peridynamics-enabled multiscale multi-model that potentially provides a new and more extensive mathematical basis for coupling classical elasticity and molecular dynamics, thus enabling next
Institute of Scientific and Technical Information of China (English)
Zhou Hongjian; Huang Shuling; Wang Yuanyuan; Wang Jing'ai; Jia Huicong
2006-01-01
Increasing populations are causing an increase in food demands, and the area of cultivated land expands every year. Inappropriate land transition from ecology to production results in the constant decline of the ecological security level and influences the regional sustainable development. Adjusting unreasonable land use mode and reconstructing natural land cover are important ways to maintain and improve the ecological environment. Also reclaiming farmland as areas for forests and grasslands (FRFG) is another way. Successful implementation of FRFG in China is the result of comprehensive effect of the multi-scales driving forces.This paper analyses the driving forces of FRFG in China on a national (country) -regional (province) - local(county) - household (farmer) level scale, and the results are: driving forces at the national scale include ecological and food security and the western development of China;at the regional scale, ecological and economic benefits become the main factors to influence the dimension of FRFG under the same policy. The driving forces can be divided into 6 types: industrial structure adjustment,water source protection, flood prevention, the Three-Gorge Project protection, reduction of the amount of sediment flowing into the Yellow River and wind erosion desertification prevention. The driving forces at the local scale can be divided into 12 types with developing leading industries, increasing farmers'income and improving agricultural production conditions as the main types; at the household scale, the national policy meeting farmers' demands and the optimization of individual interests are all driving forces.
Coupling of Peridynamics and Finite Element Formulation for Multiscale Simulations
2012-10-16
comparison of stresses and strains by finite element analysis (FEA) and peridynamic solutions is performed for a ductile material. A multiscale...problems. One common benchmark problem characterized by the mixed mode fracture is the test of a double-edge-notched concrete specimen conducted by Nooru...Mohamed et al. [19]. The test of Nooru-Mohamed was adopted by De Borst [20] in the discussion of computational modeling of concrete fracture. For
Zouaghi, A; Velay, V.; Soveja, A; Pottier, T; Cheikh, M.; Rézaï-Aria, F
2016-01-01
International audience; The cyclic mechanical behavior, the wear and fatigue resistances and damage developments of working surface of tool steels are dependent on microstructural features. A multi-scale approach combining experimental testing, numerical treatments and simulations is developed to model the surface behavior of X38CrMoV5-1 martensitic tool steels. The multi-scale modeling is coupled with finite element calculations. The elasto-viscoplastic constitutive equations used are based ...
The Adaptive Multi-scale Simulation Infrastructure
Energy Technology Data Exchange (ETDEWEB)
Tobin, William R. [Rensselaer Polytechnic Inst., Troy, NY (United States)
2015-09-01
The Adaptive Multi-scale Simulation Infrastructure (AMSI) is a set of libraries and tools developed to support the development, implementation, and execution of general multimodel simulations. Using a minimal set of simulation meta-data AMSI allows for minimally intrusive work to adapt existent single-scale simulations for use in multi-scale simulations. Support for dynamic runtime operations such as single- and multi-scale adaptive properties is a key focus of AMSI. Particular focus has been spent on the development on scale-sensitive load balancing operations to allow single-scale simulations incorporated into a multi-scale simulation using AMSI to use standard load-balancing operations without affecting the integrity of the overall multi-scale simulation.
DMS: A Package for Multiscale Molecular Dynamics
Somogyi, Endre; Ortoleva, Peter J
2013-01-01
Advances in multiscale theory and computation provide a novel paradigm for simulating many-classical particle systems. The Deductive Multiscale Simulator (DMS) is a multiscale molecular dynamics (MD) program built on two of these advances, i.e., multiscale Langevin (ML) and multiscale factorization (MF). Both capture the coevolution of the the coarse-grained (CG) state and the microstate. This provides these methods with great efficiency over conventional MD. Neither involve the introduction of phenomenological governing equations for the CG state with attendant uncertainty in both their form of the governing equations and the data needed to calibrate them. The design and implementation of DMS as an open source computational platform is presented here. DMS is written in Python, uses Gromacs to achieve the microphase, and then advances the microstate via a CG-guided evolution. DMS uses MDAnalysis, a Python library for analyzing MD trajectories, to perform computations required to construct CG-related variables...
Many-Task Computing Tools for Multiscale Modeling
Katz, Daniel S.; Ripeanu, Matei; Wilde, Michael
2011-01-01
This paper discusses the use of many-task computing tools for multiscale modeling. It defines multiscale modeling and places different examples of it on a coupling spectrum, discusses the Swift parallel scripting language, describes three multiscale modeling applications that could use Swift, and then talks about how the Swift model is being extended to cover more of the multiscale modeling coupling spectrum.
Numerical Analysis on Multi-scale Structure of Asphalt Concrete Pavement%沥青路面多尺度结构的荷载响应分析
Institute of Scientific and Technical Information of China (English)
陈俊; 黄晓明
2012-01-01
In order to explore the stress and strain relation in the pavement layers under traffic load from a meso-structural perspective, the single-scale discrete element model of asphalt pavement structure was built using discrete element method (DEM). The stress and strain at the bottom of the asphalt concrete layer under vertical load were calculated. The validation of discrete element model of asphalt pavement structure was conducted by the comparison of discrete element prediction with the results from the classical program. The distribution and volumetric fraction of coarse aggregate, asphalt mastic and air voids were taken into consideration at the bottom of the asphalt layer in the validated discrete element model to build the multi-scale structure of asphalt concrete pavement. The tensile stress and strain in asphalt mastics and interface between aggregate and mastic were obtained and compared with the results from the single-scale model. Results show that the stress and strain in multi-scale structure is heterogeneous distribution. The tensile stress at the interface between aggregate and mastic is much higher than that in mastic. The ratio of stress at interfaces to the stress in mastics increases as the mastic stiffness decreases. The pavement design based on single-scale model may underestimate the tensile stress at interface between aggregate and mastic and overestimate the tensile stress in mastic.%为了从材料细观结构角度研究沥青路面结构的荷载响应,采用离散元方法,建立了柔性基层沥青路面典型结构模型,并进行了竖向荷载作用下沥青混凝土层应力和应变的计算,通过与经典路面响应程序计算结果的比较,验证了路面结构离散元模型和离散元计算方法的正确性.以验证过的路面结构模型为基础,采用较小的细观尺度描述了沥青混凝土结构层底部位置处粗集料、沥青砂浆和空隙的分布和体积大小,从而建立了路面结构的多尺度模
Multiscale empirical interpolation for solving nonlinear PDEs
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.
Multiscale Dynamics of Solar Magnetic Structures
Uritsky, Vadim M.; Davila, Joseph M.
2012-01-01
Multiscale topological complexity of the solar magnetic field is among the primary factors controlling energy release in the corona, including associated processes in the photospheric and chromospheric boundaries.We present a new approach for analyzing multiscale behavior of the photospheric magnetic flux underlying these dynamics as depicted by a sequence of high-resolution solar magnetograms. The approach involves two basic processing steps: (1) identification of timing and location of magnetic flux origin and demise events (as defined by DeForest et al.) by tracking spatiotemporal evolution of unipolar and bipolar photospheric regions, and (2) analysis of collective behavior of the detected magnetic events using a generalized version of the Grassberger-Procaccia correlation integral algorithm. The scale-free nature of the developed algorithms makes it possible to characterize the dynamics of the photospheric network across a wide range of distances and relaxation times. Three types of photospheric conditions are considered to test the method: a quiet photosphere, a solar active region (NOAA 10365) in a quiescent non-flaring state, and the same active region during a period of M-class flares. The results obtained show (1) the presence of a topologically complex asymmetrically fragmented magnetic network in the quiet photosphere driven by meso- and supergranulation, (2) the formation of non-potential magnetic structures with complex polarity separation lines inside the active region, and (3) statistical signatures of canceling bipolar magnetic structures coinciding with flaring activity in the active region. Each of these effects can represent an unstable magnetic configuration acting as an energy source for coronal dissipation and heating.
Multiscale Segmentation of Polarimetric SAR Image Based on Srm Superpixels
Lang, F.; Yang, J.; Wu, L.; Li, D.
2016-06-01
Multi-scale segmentation of remote sensing image is more systematic and more convenient for the object-oriented image analysis compared to single-scale segmentation. However, the existing pixel-based polarimetric SAR (PolSAR) image multi-scale segmentation algorithms are usually inefficient and impractical. In this paper, we proposed a superpixel-based binary partition tree (BPT) segmentation algorithm by combining the generalized statistical region merging (GSRM) algorithm and the BPT algorithm. First, superpixels are obtained by setting a maximum region number threshold to GSRM. Then, the region merging process of the BPT algorithm is implemented based on superpixels but not pixels. The proposed algorithm inherits the advantages of both GSRM and BPT. The operation efficiency is obviously improved compared to the pixel-based BPT segmentation. Experiments using the Lband ESAR image over the Oberpfaffenhofen test site proved the effectiveness of the proposed method.
Scafetta, Nicola
2013-01-01
Herein we adopt a multi-scale dynamical spectral analysis technique to compare and study the dynamical evolution of the harmonic components of the overlapping ACRIMSAT/ACRIM3, SOHO/VIRGO and SORCE/TIM total solar irradiance (TSI) records during 2003.15 to 2013.16 in solar cycles 23 and 24. The three TSI time series present highly correlated patterns. Significant power spectral peaks are common to these records and are observed at the following periods: 0.070 year, 0.097 year, 0.20 year, 0.25 year, 0.30-0.34 year, 0.39 year. Less certain spectral peaks occur at about 0.55 year, 0.60-0.65 year and 0.7-0.9 year. Four main frequency periods at 24.8 days (0.068 year), 27.3 days (0.075 year), at 34-35 days (0.093-0.096 year) and 36-38 days (0.099-0.104 year) characterize the solar rotation cycle. The amplitude of these oscillations, in particular of those with periods larger than 0.5 year, appears to be modulated by the 11-year solar cycle. Similar harmonics have been found in other solar indices. The observed peri...
Multi-scale interactions in Dictyostelium discoideum aggregation
Dixon, James A.; Kelty-Stephen, Damian G.
2012-12-01
Cellular aggregation is essential for a wide range of phenomena in developmental biology, and a crucial event in the life-cycle of Dictyostelium discoideum. The current manuscript presents an analysis of multi-scale interactions involved in D. discoideum aggregation and non-aggregation events. The multi-scale fractal dimensions of a sequence of microscope images were used to estimate changing structure at different spatial scales. Three regions showing aggregation and three showing non-aggregation were considered. The results showed that both aggregation and non-aggregation regions were strongly multi-fractal. Analyses of the over-time relationships among nine scales of the generalized dimension, D(q), were conducted using vector autoregression and vector error-correction models. Both types of regions showed evidence that across-scale interactions serve to maintain the equilibrium of the system. Aggregation and non-aggregation regions also showed different patterns of effects of individual scales on other scales. Specifically, aggregation regions showed greater effects of both the smallest and largest scales on the smaller scale structures. The results suggest that multi-scale interactions are responsible for maintaining and altering the cellular structures during aggregation.
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.
Multiscale geometric modeling of macromolecules II: Lagrangian representation.
Feng, Xin; Xia, Kelin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei
2013-09-15
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-electron microscopy, 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, whereas our coarse resolution representations highlight the compatibility of protein-ligand bindings and possibility of protein-protein interactions.
A Multiscale Enrichment Procedure for Nonlinear Monotone Operators
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.
Generalized multiscale finite element method for elasticity equations
Chung, Eric T.
2014-10-05
In this paper, we discuss the application of generalized multiscale finite element method (GMsFEM) to elasticity equation in heterogeneous media. We consider steady state elasticity equations though some of our applications are motivated by elastic wave propagation in subsurface where the subsurface properties can be highly heterogeneous and have high contrast. We present the construction of main ingredients for GMsFEM such as the snapshot space and offline spaces. The latter is constructed using local spectral decomposition in the snapshot space. The spectral decomposition is based on the analysis which is provided in the paper. We consider both continuous Galerkin and discontinuous Galerkin coupling of basis functions. Both approaches have their cons and pros. Continuous Galerkin methods allow avoiding penalty parameters though they involve partition of unity functions which can alter the properties of multiscale basis functions. On the other hand, discontinuous Galerkin techniques allow gluing multiscale basis functions without any modifications. Because basis functions are constructed independently from each other, this approach provides an advantage. We discuss the use of oversampling techniques that use snapshots in larger regions to construct the offline space. We provide numerical results to show that one can accurately approximate the solution using reduced number of degrees of freedom.
Moist multi-scale models for the hurricane embryo
Energy Technology Data Exchange (ETDEWEB)
Majda, Andrew J. [New York University; Xing, Yulong [ORNL; Mohammadian, Majid [University of Ottawa, Canada
2010-01-01
Determining the finite-amplitude preconditioned states in the hurricane embryo, which lead to tropical cyclogenesis, is a central issue in contemporary meteorology. In the embryo there is competition between different preconditioning mechanisms involving hydrodynamics and moist thermodynamics, which can lead to cyclogenesis. Here systematic asymptotic methods from applied mathematics are utilized to develop new simplified moist multi-scale models starting from the moist anelastic equations. Three interesting multi-scale models emerge in the analysis. The balanced mesoscale vortex (BMV) dynamics and the microscale balanced hot tower (BHT) dynamics involve simplified balanced equations without gravity waves for vertical vorticity amplification due to moist heat sources and incorporate nonlinear advective fluxes across scales. The BMV model is the central one for tropical cyclogenesis in the embryo. The moist mesoscale wave (MMW) dynamics involves simplified equations for mesoscale moisture fluctuations, as well as linear hydrostatic waves driven by heat sources from moisture and eddy flux divergences. A simplified cloud physics model for deep convection is introduced here and used to study moist axisymmetric plumes in the BHT model. A simple application in periodic geometry involving the effects of mesoscale vertical shear and moist microscale hot towers on vortex amplification is developed here to illustrate features of the coupled multi-scale models. These results illustrate the use of these models in isolating key mechanisms in the embryo in a simplified content.
Mixed Generalized Multiscale Finite Element Methods and Applications
Chung, Eric T.
2015-03-03
In this paper, we present a mixed generalized multiscale finite element method (GMsFEM) for solving flow in heterogeneous media. Our approach constructs multiscale basis functions following a GMsFEM framework and couples these basis functions using a mixed finite element method, which allows us to obtain a mass conservative velocity field. To construct multiscale basis functions for each coarse edge, we design a snapshot space that consists of fine-scale velocity fields supported in a union of two coarse regions that share the common interface. The snapshot vectors have zero Neumann boundary conditions on the outer boundaries, and we prescribe their values on the common interface. We describe several spectral decompositions in the snapshot space motivated by the analysis. In the paper, we also study oversampling approaches that enhance the accuracy of mixed GMsFEM. A main idea of oversampling techniques is to introduce a small dimensional snapshot space. We present numerical results for two-phase flow and transport, without updating basis functions in time. Our numerical results show that one can achieve good accuracy with a few basis functions per coarse edge if one selects appropriate offline spaces. © 2015 Society for Industrial and Applied Mathematics.
Reduced Noise Effect in Nonlinear Model Estimation Using Multiscale Representation
Directory of Open Access Journals (Sweden)
Mohamed N. Nounou
2010-01-01
Full Text Available Nonlinear process models are widely used in various applications. In the absence of fundamental models, it is usually relied on empirical models, which are estimated from measurements of the process variables. Unfortunately, measured data are usually corrupted with measurement noise that degrades the accuracy of the estimated models. Multiscale wavelet-based representation of data has been shown to be a powerful data analysis and feature extraction tool. In this paper, these characteristics of multiscale representation are utilized to improve the estimation accuracy of the linear-in-the-parameters nonlinear model by developing a multiscale nonlinear (MSNL modeling algorithm. The main idea in this MSNL modeling algorithm is to decompose the data at multiple scales, construct multiple nonlinear models at multiple scales, and then select among all scales the model which best describes the process. The main advantage of the developed algorithm is that it integrates modeling and feature extraction to improve the robustness of the estimated model to the presence of measurement noise in the data. This advantage of MSNL modeling is demonstrated using a nonlinear reactor model.
Generalization of mixed multiscale finite element methods with applications
Energy Technology Data Exchange (ETDEWEB)
Lee, C S [Texas A & M Univ., College Station, TX (United States)
2016-08-01
Many science and engineering problems exhibit scale disparity and high contrast. The small scale features cannot be omitted in the physical models because they can affect the macroscopic behavior of the problems. However, resolving all the scales in these problems can be prohibitively expensive. As a consequence, some types of model reduction techniques are required to design efficient solution algorithms. For practical purpose, we are interested in mixed finite element problems as they produce solutions with certain conservative properties. Existing multiscale methods for such problems include the mixed multiscale finite element methods. We show that for complicated problems, the mixed multiscale finite element methods may not be able to produce reliable approximations. This motivates the need of enrichment for coarse spaces. Two enrichment approaches are proposed, one is based on generalized multiscale finte element metthods (GMsFEM), while the other is based on spectral element-based algebraic multigrid (rAMGe). The former one, which is called mixed GMsFEM, is developed for both Darcy’s flow and linear elasticity. Application of the algorithm in two-phase flow simulations are demonstrated. For linear elasticity, the algorithm is subtly modified due to the symmetry requirement of the stress tensor. The latter enrichment approach is based on rAMGe. The algorithm differs from GMsFEM in that both of the velocity and pressure spaces are coarsened. Due the multigrid nature of the algorithm, recursive application is available, which results in an efficient multilevel construction of the coarse spaces. Stability, convergence analysis, and exhaustive numerical experiments are carried out to validate the proposed enrichment approaches. iii
Final Technical Report "Multiscale Simulation Algorithms for Biochemical Systems"
Energy Technology Data Exchange (ETDEWEB)
Petzold, Linda R.
2012-10-25
Biochemical systems are inherently multiscale and stochastic. In microscopic systems formed by living cells, the small numbers of reactant molecules can result in dynamical behavior that is discrete and stochastic rather than continuous and deterministic. An analysis tool that respects these dynamical characteristics is the stochastic simulation algorithm (SSA, Gillespie, 1976), a numerical simulation procedure that is essentially exact for chemical systems that are spatially homogeneous or well stirred. Despite recent improvements, as a procedure that simulates every reaction event, the SSA is necessarily inefficient for most realistic problems. There are two main reasons for this, both arising from the multiscale nature of the underlying problem: (1) stiffness, i.e. the presence of multiple timescales, the fastest of which are stable; and (2) the need to include in the simulation both species that are present in relatively small quantities and should be modeled by a discrete stochastic process, and species that are present in larger quantities and are more efficiently modeled by a deterministic differential equation (or at some scale in between). This project has focused on the development of fast and adaptive algorithms, and the fun- damental theory upon which they must be based, for the multiscale simulation of biochemical systems. Areas addressed by this project include: (1) Theoretical and practical foundations for ac- celerated discrete stochastic simulation (tau-leaping); (2) Dealing with stiffness (fast reactions) in an efficient and well-justified manner in discrete stochastic simulation; (3) Development of adaptive multiscale algorithms for spatially homogeneous discrete stochastic simulation; (4) Development of high-performance SSA algorithms.
Hybrid multiscale simulation of a mixing-controlled reaction
Energy Technology Data Exchange (ETDEWEB)
Scheibe, Timothy D.; Schuchardt, Karen L.; Agarwal, Khushbu; Chase, Jared M.; Yang, Xiaofan; Palmer, Bruce J.; Tartakovsky, Alexandre M.; Elsethagen, Todd O.; Redden, George D.
2015-09-01
Continuum-scale models have been used to study subsurface flow, transport, and reactions for many years but lack the capability to resolve fine-grained processes. Recently, pore-scale models, which operate at scales of individual soil grains, have been developed to more accurately model and study pore-scale phenomena, such as mineral precipitation and dissolution reactions, microbially-mediated surface reactions, and other complex processes. However, these highly-resolved models are prohibitively expensive for modeling domains of sizes relevant to practical problems. To broaden the utility of pore-scale models for larger domains, we developed a hybrid multiscale model that initially simulates the full domain at the continuum scale and applies a pore-scale model only to areas of high reactivity. Since the location and number of pore-scale model regions in the model varies as the reactions proceed, an adaptive script defines the number and location of pore regions within each continuum iteration and initializes pore-scale simulations from macroscale information. Another script communicates information from the pore-scale simulation results back to the continuum scale. These components provide loose coupling between the pore- and continuum-scale codes into a single hybrid multiscale model implemented within the SWIFT workflow environment. In this paper, we consider an irreversible homogenous bimolecular reaction (two solutes reacting to form a third solute) in a 2D test problem. This paper is focused on the approach used for multiscale coupling between pore- and continuum-scale models, application to a realistic test problem, and implications of the results for predictive simulation of mixing-controlled reactions in porous media. Our results and analysis demonstrate that loose coupling provides a feasible, efficient and scalable approach for multiscale subsurface simulations.
Institute of Scientific and Technical Information of China (English)
支联合; 支羽光; 谭永杰
2011-01-01
Objective To discuss the impact of aliasing frequency on the performance of multiscale feature extraction (MFE) for fMRI data analysis. Methods Under the conditions of removing and not removing aliasing frequencies. MFE was employed to analyze the simulated and the auditory fMRI data. In addition, the results revealed by MFE were compared with those of the general linear model (GLM) implemented with SPM8 software. Results Whether removing aliasing frequencies or not, MFE showed the same specificity as that of GLM. However, in terms of the sensitivity, the performance of MFE without removing aliasing frequencies was better than that of MFE when removing aliasing frequencies, and the latter was better than that of GLM. Conclusion In case of correlation analysis employed, aliasing frequencies do not influence the specificity of MFE, while removing these frequencies will decrease its sensitivity.%目的 探讨混频对多尺度特征提取(MFE)方法分析fMRI数据的影响.方法 分别在去除和不去除混频条件下用MFE分析模拟数据及听觉fMRI试验数据,并与由SPM8软件运行的广义线性模型(GLM)方法的结果进行比较.结果 MFE在去除和不去除混频两种条件下的特异度均与GLM相同,但MFE不去除混频时的灵敏度优于去除混频时的灵敏度,后者又优于GLM.结论 在使用相关分析检测激活的条件下,混频不影响MFE的特异度,但去除混频降低其灵敏度.
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.
Multiscale Modeling of Hall Thrusters Project
National Aeronautics and Space Administration — New multiscale modeling capability for analyzing advanced Hall thrusters is proposed. This technology offers NASA the ability to reduce development effort of new...
Multiscale Model Approach for Magnetization Dynamics Simulations
De Lucia, Andrea; Tretiakov, Oleg A; Kläui, Mathias
2016-01-01
Simulations of magnetization dynamics in a multiscale environment enable rapid evaluation of the Landau-Lifshitz-Gilbert equation in a mesoscopic sample with nanoscopic accuracy in areas where such accuracy is required. We have developed a multiscale magnetization dynamics simulation approach that can be applied to large systems with spin structures that vary locally on small length scales. To implement this, the conventional micromagnetic simulation framework has been expanded to include a multiscale solving routine. The software selectively simulates different regions of a ferromagnetic sample according to the spin structures located within in order to employ a suitable discretization and use either a micromagnetic or an atomistic model. To demonstrate the validity of the multiscale approach, we simulate the spin wave transmission across the regions simulated with the two different models and different discretizations. We find that the interface between the regions is fully transparent for spin waves with f...
Multiscale modelling in immunology: a review.
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.
Multiscale soil-landscape process modeling
Schoorl, J.M.; Veldkamp, A.
2006-01-01
The general objective of this chapter is to illustrate the role of soils and geomorphological processes in the multiscale soil-lanscape context. Included in this context is the fourth dimension (temporal dimension) and the human role (fifth dimension)
Multiscale geometric modeling of macromolecules I: Cartesian representation.
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
On the optimal choice of wavelet function for multiscale honed surface characterization
Energy Technology Data Exchange (ETDEWEB)
Mezghani, S; Mansori, M El [Arts and Metiers ParisTech, LMPF, rue St Dominique - BP 508, 51006 Chalons-en-Champagne (France); Sabri, L [RENAULT S.A.S., Direction de la Mecanique/Direction de l' Ingenierie Process, Rueil Malmaison, Paris (France); Zahouani, H, E-mail: sabeur.mezghani@ensam.eu [Ecole Centrale de Lyon, LTDS UMR CNRS 5513, 36 avenue Guy de Collongue, 69131 Ecully Cedex (France)
2011-08-19
Multiscale surface topography characterization is mostly suited than standard approaches because it is more adapted to the multi-stage process generation. Wavelet transform represents a power tool to perform the multiscale decomposition of the surface topography in a wide range of wavelength. However, characterization results depend closely on the topography data acquisition instrument (resolution, height accuracy, sensitivity...) and also on the wavelet analysis method (discrete or continuous transform). In particular, the choice of wavelet function can have significant effect on the analysis results. In this paper, we present experimental work on a number of popular wavelets functions with the aim of finding wavelets that exhibit optimal description of honed surface features when continuous wavelet transform is used. We demonstrate that the regularity property of wavelet function has a significant influence on the characterization performances. This comparative study shows also that the Morlet wavelet is the more adapted wavelet basis function for multiscale characterization of honed surfaces using continuous wavelet transform.
Multiscale Modeling of Damage Processes in fcc Aluminum: From Atoms to Grains
Glaessgen, E. H.; Saether, E.; Yamakov, V.
2008-01-01
Molecular dynamics (MD) methods are opening new opportunities for simulating the fundamental processes of material behavior at the atomistic level. However, current analysis is limited to small domains and increasing the size of the MD domain quickly presents intractable computational demands. A preferred approach to surmount this computational limitation has been to combine continuum mechanics-based modeling procedures, such as the finite element method (FEM), with MD analyses thereby reducing the region of atomic scale refinement. Such multiscale modeling strategies can be divided into two broad classifications: concurrent multiscale methods that directly incorporate an atomistic domain within a continuum domain and sequential multiscale methods that extract an averaged response from the atomistic simulation for later use as a constitutive model in a continuum analysis.
Multiscale modelling of DNA mechanics
Dršata, Tomáš; Lankaš, Filip
2015-08-01
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.
Multiscale Theory of Dislocation Climb.
Geslin, Pierre-Antoine; Appolaire, Benoît; Finel, Alphonse
2015-12-31
Dislocation climb is a ubiquitous mechanism playing a major role in the plastic deformation of crystals at high temperature. We propose a multiscale approach to model quantitatively this mechanism at mesoscopic length and time scales. First, we analyze climb at a nanoscopic scale and derive an analytical expression of the climb rate of a jogged dislocation. Next, we deduce from this expression the activation energy of the process, bringing valuable insights to experimental studies. Finally, we show how to rigorously upscale the climb rate to a mesoscopic phase-field model of dislocation climb. This upscaling procedure opens the way to large scale simulations where climb processes are quantitatively reproduced even though the mesoscopic length scale of the simulation is orders of magnitude larger than the atomic one.
Multiscale modeling of pedestrian dynamics
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.
Carbon nanotube integrated multifunctional multiscale composites
Energy Technology Data Exchange (ETDEWEB)
Qiu Jingjing; Zhang, Chuck; Wang, Ben; Liang, Richard [High-Performance Materials Institute, Department of Industrial and Manufacturing Engineering, Florida A and M University-Florida State University College of Engineering, 2525 Pottsdamer Street, Tallahassee, FL 32310-6046 (United States)
2007-07-11
Carbon nanotubes (CNTs) demonstrate extraordinary properties and show great promise in enhancing out-of-plane properties of traditional polymer composites and enabling functionality, but current manufacturing challenges hinder the realization of their potential. This paper presents a method to fabricate multifunctional multiscale composites through an effective infiltration-based vacuum-assisted resin transfer moulding (VARTM) process. Multi-walled carbon nanotubes (MWNTs) were infused through and between glass-fibre tows along the through-thickness direction. Both pristine and functionalized MWNTs were used in fabricating multiscale glass-fibre-reinforced epoxy composites. It was demonstrated that the mechanical properties of multiscale composites were remarkably enhanced, especially in the functionalized MWNT multiscale composites. With only 1 wt% loading of functionalized MWNTs, tensile strength was increased by 14% and Young's modulus by 20%, in comparison with conventional fibre-reinforced composites. Moreover, the shear strength and short-beam modulus were increased by 5% and 8%, respectively, indicating the improved inter-laminar properties. The strain-stress tests also suggested noticeable enhancement in toughness. Scanning electron microscopy (SEM) characterization confirmed an enhanced interfacial bonding when functionalized MWNTs were integrated into epoxy/glass-fibre composites. The coefficient thermal expansion (CTE) of functionalized nanocomposites indicated a reduction of 25.2% compared with epoxy/glass-fibre composites. The desired improvement of electrical conductivities was also achieved. The multiscale composites indicated a way to leverage the benefits of CNTs and opened up new opportunities for high-performance multifunctional multiscale composites.
Carbon nanotube integrated multifunctional multiscale composites
Qiu, Jingjing; Zhang, Chuck; Wang, Ben; Liang, Richard
2007-07-01
Carbon nanotubes (CNTs) demonstrate extraordinary properties and show great promise in enhancing out-of-plane properties of traditional polymer composites and enabling functionality, but current manufacturing challenges hinder the realization of their potential. This paper presents a method to fabricate multifunctional multiscale composites through an effective infiltration-based vacuum-assisted resin transfer moulding (VARTM) process. Multi-walled carbon nanotubes (MWNTs) were infused through and between glass-fibre tows along the through-thickness direction. Both pristine and functionalized MWNTs were used in fabricating multiscale glass-fibre-reinforced epoxy composites. It was demonstrated that the mechanical properties of multiscale composites were remarkably enhanced, especially in the functionalized MWNT multiscale composites. With only 1 wt% loading of functionalized MWNTs, tensile strength was increased by 14% and Young's modulus by 20%, in comparison with conventional fibre-reinforced composites. Moreover, the shear strength and short-beam modulus were increased by 5% and 8%, respectively, indicating the improved inter-laminar properties. The strain-stress tests also suggested noticeable enhancement in toughness. Scanning electron microscopy (SEM) characterization confirmed an enhanced interfacial bonding when functionalized MWNTs were integrated into epoxy/glass-fibre composites. The coefficient thermal expansion (CTE) of functionalized nanocomposites indicated a reduction of 25.2% compared with epoxy/glass-fibre composites. The desired improvement of electrical conductivities was also achieved. The multiscale composites indicated a way to leverage the benefits of CNTs and opened up new opportunities for high-performance multifunctional multiscale composites.
Multiscale coupling of molecular dynamics and peridynamics
Tong, Qi; Li, Shaofan
2016-10-01
We propose a multiscale computational model to couple molecular dynamics and peridynamics. The multiscale coupling model is based on a previously developed multiscale micromorphic molecular dynamics (MMMD) theory, which has three dynamics equations at three different scales, namely, microscale, mesoscale, and macroscale. In the proposed multiscale coupling approach, we divide the simulation domain into atomistic region and macroscale region. Molecular dynamics is used to simulate atom motions in atomistic region, and peridynamics is used to simulate macroscale material point motions in macroscale region, and both methods are nonlocal particle methods. A transition zone is introduced as a messenger to pass the information between the two regions or scales. We employ the "supercell" developed in the MMMD theory as the transition element, which is named as the adaptive multiscale element due to its ability of passing information from different scales, because the adaptive multiscale element can realize both top-down and bottom-up communications. We introduce the Cauchy-Born rule based stress evaluation into state-based peridynamics formulation to formulate atomistic-enriched constitutive relations. To mitigate the issue of wave reflection on the interface, a filter is constructed by switching on and off the MMMD dynamic equations at different scales. Benchmark tests of one-dimensional (1-D) and two-dimensional (2-D) wave propagations from atomistic region to macro region are presented. The mechanical wave can transit through the interface smoothly without spurious wave deflections, and the filtering process is proven to be efficient.
Magnetotellurics as a multiscale geophysical exploration method
Carbonari, Rolando; D'Auria, Luca; Di Maio, Rosa; Petrillo, Zaccaria
2016-04-01
Magnetotellurics (MT) is a geophysical method based on the use of natural electromagnetic signals to define subsurface electrical resistivity structure through electromagnetic induction. MT waves are generated in the Earth's atmosphere and magnetosphere by a range of physical processes, such as magnetic storms, micropulsations, lightning activity. Since the underground MT wave propagation is of diffusive type, the longer is the wavelength (i.e. the lower the wave frequency) the deeper will be the propagation depth. Considering the frequency band commonly used in MT prospecting (10-4 Hz to 104 Hz), the investigation depth ranges from few hundred meters to hundreds of kilometers. This means that magnetotellurics is inherently a multiscale method and, thus, appropriate for applications at different scale ranging from aquifer system characterization to petroleum and geothermal research. In this perspective, the application of the Wavelet transform to the MT data analysis could represent an excellent tool to emphasize characteristics of the MT signal at different scales. In this note, the potentiality of such an approach is studied. In particular, we show that the use of a Discrete Wavelet (DW) decomposition of measured MT time-series data allows to retrieve robust information about the subsoil resistivity over a wide range of spatial (depth) scales, spanning up to 5 orders of magnitude. Furthermore, the application of DWs to MT data analysis has proven to be a flexible tool for advanced data processing (e.g. non-linear filtering, denoising and clustering).
Holographic Dynamics from Multiscale Entanglement Renormalization Ansatz
Chua, Victor; Tiwari, Apoorv; Ryu, Shinsei
2016-01-01
The Multiscale Entanglement Renormalization Ansatz (MERA) is a tensor network based variational ansatz that is capable of capturing many of the key physical properties of strongly correlated ground states such as criticality and topological order. MERA also shares many deep relationships with the AdS/CFT (gauge-gravity) correspondence by realizing a UV complete holographic duality within the tensor networks framework. Motivated by this, we have re-purposed the MERA tensor network as an analysis tool to study the real-time evolution of the 1D transverse Ising model in its low energy excited state sector. We performed this analysis by allowing the ancilla qubits of the MERA tensor network to acquire quantum fluctuations, which yields a unitary transform between the physical (boundary) and ancilla qubit (bulk) Hilbert spaces. This then defines a reversible quantum circuit which is used as a `holographic transform' to study excited states and their real-time dynamics from the point of the bulk ancillae. In the ga...
Institute of Scientific and Technical Information of China (English)
施健; 刘兴高
2005-01-01
Prediction of melt index (MI), the most important parameter in determining the product's grade and quality control of polypropylene produced in practical industrial processes, is studied. A novel soft-sensor model with principal component analysis (PCA), radial basis function (RBF) networks, and multi-scale analysis (MSA) is proposed to infer the MI of manufactured products from real process variables, where PCA is carried out to select the most relevant process features and to eliminate the correlations of the input variables, MSA is introduced to acquire much more information and to reduce the uncertainty of the system, and RBF networks are used to characterize the nonlinearity of the process. The research results show that the proposed method provides promising prediction reliability and accuracy, and supposed to have extensive application prospects in propylene polymerization processes.
Multiscale Model Reduction with Generalized Multiscale Finite Element Methods in Geomathematics
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.
Multi-Scale SSA or Data-Adaptive Wavelets
Yiou, P.; Sornette, D.; Sornette, D.; Sornette, D.; Ghil, M.; Ghil, M.
2001-05-01
Using multi-scale ideas from wavelet analysis, the singular-spectrum analysis (SSA) is extended to the study of nonstationary time series, including the case where their variance diverges. The wavelet transform is similar to a local Fourier transform within a finite moving window whose width W, proportional to the major period of interest, is varied to explore a broad range of such periods. SSA, on the other hand, relies on the construction of the lag-correlation matrix C on M lagged copies of the time series over a fixed window width W proportional to M to detect the regular part of the variability in that window in terms of the minimal number of oscillatory components. The proposed multi-scale SSA is a local SSA analysis within a moving window of width Mwavelets; successive eigenvectors of C(M) correspond approximately to successive derivatives of the first mother wavelet in standard wavelet analysis. Multi-scale SSA thus solves objectively the delicate problem of optimizing the analyzing wavelet in the time-frequency domain, by a suitable localization of the signal's correlation matrix. We present several examples of application to synthetic signals with fractal or power-law behavior which mimic selected features of certain climatic or geophysical time series. The method is applied to the monthly values of the Southern Oscillation index (SOI) which captures major features of the El Niño/Southern Oscillation in the Tropical Pacific. Our methodology highlights an abrupt periodicity shift in the SOI near 1960. This abrupt shift between 5 and 3 years supports the Devil's staircase scenario for the El Niño/Southern Oscillation phenomenon.
Evaluation of Multi-Scale Full Waveform Inversion with Marine Vertical Cable Data
Institute of Scientific and Technical Information of China (English)
Aifei Bian; Zhihui Zou; Hua-Wei Zhou; Jin Zhang
2015-01-01
Seismic illumination plays an important role in subsurface imaging. A better image can be expected either through optimizing acquisition geometry or introducing more advanced seismic mi-gration and/or tomographic inversion methods involving illumination compensation. Vertical cable survey is a potential replacement of traditional marine seismic survey for its flexibility and data quality. Conventional vertical cable data processing requires separation of primaries and multiples before mi-gration. We proposed to use multi-scale full waveform inversion (FWI) to improve illumination cover-age of vertical cable survey. A deep water velocity model is built to test the capability of multi-scale FWI in detecting low velocity anomalies below seabed. Synthetic results show that multi-scale FWI is an effective model building tool in deep-water exploration. Geometry optimization through target ori-ented illumination analysis and multi-scale FWI may help to mitigate the risks of vertical cable survey. The combination of multi-scale FWI, low-frequency data and multi-vertical-cable acquisition system may provide both high resolution and high fidelity subsurface models.
Lu, Zhao; Sun, Jing; Butts, Kenneth
2014-05-01
Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.
Universal hierarchical symmetry for turbulence and general multi-scale fluctuation systems
Institute of Scientific and Technical Information of China (English)
Zhen-Su She; Zhi-Xiong Zhang
2009-01-01
Scaling is an important measure of multi-scale fluctuation systems. Turbulence as the most remarkable multi-scale system possesses scaling over a wide range of scales. She-Leveque (SL) hierarchical symmetry, since its publication in 1994, has received wide attention. A num-ber of experimental, numerical and theoretical work have been devoted to its verification, extension, and modification. Application to the understanding of magnetohydrodynamic turbulence, motions of cosmic baryon fluids, cosmological supersonic turbulence, natural image, spiral turbulent patterns, DNA anomalous composition, human heart vari-ability are just a few among the most successful examples. A number of modified scaling laws have been derived in the framework of the hierarchical symmetry, and the SL model parameters are found to reveal both the organizational order of the whole system and the properties of the most signif-icant fluctuation structures. A partial set of work related to these studies are reviewed. Particular emphasis is placed on the nature of the hierarchical symmetry. It is suggested that the SL hierarchical symmetry is a new form of the self-orga-nization principle for multi-scale fluctuation systems, and can be employed as a standard analysis tool in the general multi-scale methodology. It is further suggested that the SL hierarchical symmetry implies the existence of a turbulence ensemble. It is speculated that the search for defining the turbulence ensemble might open a new way for deriving sta-tistical closure equations for turbulence and other multi-scale fluctuation systems.
Wide Range Multiscale Entropy Changes through Development
Directory of Open Access Journals (Sweden)
Nicola R. Polizzotto
2015-12-01
Full Text Available How variability in the brain’s neurophysiologic signals evolves during development is important for a global, system-level understanding of brain maturation and its disturbance in neurodevelopmental disorders. In the current study, we use multiscale entropy (MSE, a measure that has been related to signal complexity, to investigate how this variability evolves during development across a broad range of temporal scales. We computed MSE, standard deviation (STD and standard spectral analyses on resting EEG from 188 healthy individuals aged 8–22 years old. We found age-related increases in entropy at lower scales (<~20 ms and decreases in entropy at higher scales (~60–80 ms. Decreases in the overall signal STD were anticorrelated with entropy, especially in the lower scales, where regression analyses showed substantial covariation of observed changes. Our findings document for the first time the scale dependency of developmental changes from childhood to early adulthood, challenging a parsimonious MSE-based account of brain maturation along a unidimensional, complexity measure. At the level of analysis permitted by electroencephalography (EEG, MSE could capture critical spatiotemporal variations in the role of noise in the brain. However, interpretations critically rely on defining how signal STD affects MSE properties.
A multiscale products technique for denoising of DNA capillary electrophoresis signals
Gao, Qingwei; Lu, Yixiang; Sun, Dong; Zhang, Dexiang
2013-06-01
Since noise degrades the accuracy and precision of DNA capillary electrophoresis (CE) analysis, signal denoising is thus important to facilitate the postprocessing of CE data. In this paper, a new denoising algorithm based on dyadic wavelet transform using multiscale products is applied for the removal of the noise in the DNA CE signal. The adjacent scale wavelet coefficients are first multiplied to amplify the significant features of the CE signal while diluting noise. Then, noise is suppressed by applying a multiscale threshold to the multiscale products instead of directly to the wavelet coefficients. Finally, the noise-free CE signal is recovered from the thresholded coefficients by using inverse dyadic wavelet transform. We compare the performance of the proposed algorithm with other denoising methods applied to the synthetic CE and real CE signals. Experimental results show that the new scheme achieves better removal of noise while preserving the shape of peaks corresponding to the analytes in the sample.
DEFF Research Database (Denmark)
Vermesi, Izabella; Rein, Guillermo; Colella, Francesco
2017-01-01
directly. The feasibility analysis showed a difference of only 2% in temperature results from the published reference work that was performed with Ansys Fluent (Colella et al., 2010). The reduction in simulation time was significantly larger when using multiscale modelling than when performing multiple......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...
Fast multiscale directional filter bank-based speckle mitigation in gallstone ultrasound images.
Leavline, Epiphany Jebamalar; Sutha, Shunmugam; Singh, Danasingh Asir Antony Gnana
2014-02-01
Speckle noise is a multiplicative type of noise commonly seen in medical and remote sensing images. It gives a granular appearance that degrades the quality of the recorded images. These speckle noise components need to be mitigated before the image is used for further processing and analysis. This paper presents a novel approach for removing granular speckle noise in gray scale images. We used an efficient multiscale image representation scheme named fast multiscale directional filter bank (FMDFB) along with simple threshold methods such as Vishushrink for image processing. It is a perfect reconstruction framework that can be used for a wide range of image processing applications because of its directionality and reduced computational complexity. The FMDFB-based speckle mitigation is appealing over other traditional multiscale approaches such as wavelets and Contourlets. Our experimental results show that the despeckling performance of the proposed method outperforms the wavelet and Contourlet-based despeckling methods.
Multiscale Design of Advanced Materials based on Hybrid Ab Initio and Quasicontinuum Methods
Energy Technology Data Exchange (ETDEWEB)
Luskin, Mitchell [University of Minnesota
2014-03-12
This project united researchers from mathematics, chemistry, computer science, and engineering for the development of new multiscale methods for the design of materials. Our approach was highly interdisciplinary, but it had two unifying themes: first, we utilized modern mathematical ideas about change-of-scale and state-of-the-art numerical analysis to develop computational methods and codes to solve real multiscale problems of DOE interest; and, second, we took very seriously the need for quantum mechanics-based atomistic forces, and based our methods on fast solvers of chemically accurate methods.
Biomimic design of multi-scale fabric with efficient heat transfer property
Directory of Open Access Journals (Sweden)
Fan Jie
2012-01-01
Full Text Available Wool fiber has a complex hierarchic structure. The multi-scale fibrils are assembled to form a tree-like channel net in wool fiber, providing an efficient heat transfer property. The optimal inner configuration of wool fiber can also be invited to biomimic design of textile fabrics to improve the thermal comfort of cloth. A heat transfer model of biomimic multi-scale fabric using the fractal derivative is established. Theoretical analysis indicates that the heat flux efficiency in the biomimic fabric can be 2 orders of magnitude comparing with that of the continuous medium.
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.
Anders, N.S.; Seijmonsbergen, A.C.; Bouten, W.; Purves, R.; Gruber, S.; Hengl, T.; Straumann, R.
2009-01-01
Geomorphological maps are useful to a wide variety of applications, such as hazard risk analysis (Seijmonsbergen 1992), forest ecological research (Van Noord 1996) and geoconservation evaluation studies (Seijmonsbergen et al. in press). Traditional field-based geomorphological mapping strategies are
Moving in a crowd: human perception as a multiscale process
Colombi, Annachiara; Tosin, Andrea
2015-01-01
The strategic behavior of pedestrians is largely determined by how they perceive and consequently react to neighboring people. Such interpersonal interactions may be dictated by the emotional state of the individuals, the purpose of their trip, the local crowding, the quality of the environment to mention but a few common examples. This issue is addressed in this paper by a mathematical model which combines, in an evolutionary time- and space-dependent way, discrete and continuous effects of pedestrian interactions. Numerical simulations and qualitative analysis suggest that human perception, and its impact on crowd dynamics, can be effectively modeled as a multiscale process based on such a dual representation of groups of agents.
Transferring Multi-Scale Approaches from 3d City Modeling to Ifc-Based Tunnel Modeling
Borrmann, A.; Kolbe, T. H.; Donaubauer, A.; Steuer, H.; Jubierre, J. R.
2013-09-01
A multi-scale representation of the built environment is required to provide information with the adequate level of detail (LoD) for different use cases and objectives. This applies not only to the visualization of city and building models, but in particular to their use in the context of planning and analysis tasks. While in the field of Geographic Information Systems, the handling of multi-scale representations is well established and understood, no formal approaches for incorporating multi-scale methods exist in the field of Building Information Modeling (BIM) so far. However, these concepts are much needed to better support highly dynamic planning processes that make use of very rough information about the facility under design in the early stages and provide increasingly detailed and fine-grained information in later stages. To meet these demands, this paper presents a comprehensive concept for incorporating multi-scale representations with infrastructural building information models, with a particular focus on the representation of shield tunnels. Based on a detailed analysis of the data modeling methods used in CityGML for capturing multiscale representations and the requirements present in the context of infrastructure planning projects, we discuss potential extensions to the BIM data model Industry Foundation Classes (IFC). Particular emphasis is put on providing means for preserving the consistency of the representation across the different Levels-of-Detail (LoD). To this end we make use of a procedural geometry description which makes it possible to define explicit dependencies between geometric entities on different LoDs. The modification of an object on a coarse level consequently results in an automated update of all dependent objects on the finer levels. Finally we discuss the transformation of the IFC-based multi-scale tunnel model into a CityGML compliant tunnel representation.
Multi-Scale Porous Ultra High Temperature Ceramics
2015-01-08
Final 3. DATES COVERED (From - To) 28-Mar-2013 - 27-Sep-2015 4. TITLE AND SUBTITLE Multi-Scale Porous Ultra High Temperature Ceramics ...report summarizes the main outcomes of research to develop multi-scale porosity Ultra High Temperature Ceramic materials. Processing conditions were...flights. 15. SUBJECT TERMS Ultra High Temperature Ceramics , Colloidal Powder Processing, Multi-scale Porous Materials, Lattice Monte
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.
Multiscale modelling of saliva secretion.
Sneyd, James; Crampin, Edmund; Yule, David
2014-11-01
We review a multiscale model of saliva secretion, describing in brief how the model is constructed and what we have so far learned from it. The model begins at the level of inositol trisphosphate receptors (IPR), and proceeds through the cellular level (with a model of acinar cell calcium dynamics) to the multicellular level (with a model of the acinus), finally to a model of a saliva production unit that includes an acinus and associated duct. The model at the level of the entire salivary gland is not yet completed. Particular results from the model so far include (i) the importance of modal behaviour of IPR, (ii) the relative unimportance of Ca(2+) oscillation frequency as a controller of saliva secretion, (iii) the need for the periodic Ca(2+) waves to be as fast as possible in order to maximise water transport, (iv) the presence of functional K(+) channels in the apical membrane increases saliva secretion, (v) the relative unimportance of acinar spatial structure for isotonic water transport, (vi) the prediction that duct cells are highly depolarised, (vii) the prediction that the secondary saliva takes at least 1mm (from the acinus) to reach ionic equilibrium. We end with a brief discussion of future directions for the model, both in construction and in the study of scientific questions.
Multiscale modelling of evolving foams
Saye, R. I.; Sethian, J. A.
2016-06-01
We present a set of multi-scale interlinked algorithms to model the dynamics of evolving foams. These algorithms couple the key effects of macroscopic bubble rearrangement, thin film drainage, and membrane rupture. For each of the mechanisms, we construct consistent and accurate algorithms, and couple them together to work across the wide range of space and time scales that occur in foam dynamics. These algorithms include second order finite difference projection methods for computing incompressible fluid flow on the macroscale, second order finite element methods to solve thin film drainage equations in the lamellae and Plateau borders, multiphase Voronoi Implicit Interface Methods to track interconnected membrane boundaries and capture topological changes, and Lagrangian particle methods for conservative liquid redistribution during rearrangement and rupture. We derive a full set of numerical approximations that are coupled via interface jump conditions and flux boundary conditions, and show convergence for the individual mechanisms. We demonstrate our approach by computing a variety of foam dynamics, including coupled evolution of three-dimensional bubble clusters attached to an anchored membrane and collapse of a foam cluster.
Evaluation of the Community Multiscale Air Quality model version 5.1
The Community Multiscale Air Quality model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Atmospheric Modeling and Analysis Division (AMAD) of the U.S. Environment...
Multiscale modeling in biomechanics and mechanobiology
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...
The Center for Multiscale Plasma Dynamics
Energy Technology Data Exchange (ETDEWEB)
Kevrekidis, Yannis G
2015-01-20
This final report describes research performed in Princeton University, led by Professor Yannis G. Kevrekidis, over a period of six years (August 1, 2014 to July 31, 2010, including a one-year, no-cost extension) as part of the Center for Multiscale Plasma Dynamics led by the University of Maryland. The work resulted in the development and implementation of several multiscale algorithms based on the equation-free approach pioneered by the PI, including its applications in plasma dynamics problems. These algoriithms include coarse projective integration and coarse stability/bifurcation computations. In the later stages of the work, new links were made between this multiscale, coarse-graining approach and advances in data mining/machine learning algorithms.
Generalized multiscale radial basis function networks.
Billings, Stephen A; Wei, Hua-Liang; Balikhin, Michael A
2007-12-01
A novel modelling framework is proposed for constructing parsimonious and flexible multiscale radial basis function networks (RBF). Unlike a conventional standard single scale RBF network, where all the basis functions have a common kernel width, the new network structure adopts multiscale Gaussian functions as the bases, where each selected centre has multiple kernel widths, to provide more flexible representations with better generalization properties for general nonlinear dynamical systems. As a direct extension of the traditional single scale Gaussian networks, the new multiscale network is easy to implement and is quick to learn using standard learning algorithms. A k-means clustering algorithm and an improved orthogonal least squares (OLS) algorithm are used to determine the unknown parameters in the network model including the centres and widths of the basis functions, and the weights between the basis functions. It is demonstrated that the new network can lead to a parsimonious model with much better generalization property compared with the traditional single width RBF networks.
The center for multiscale plasma dynamics
Energy Technology Data Exchange (ETDEWEB)
Kevrekidis, Yannis G [Princeton Univ., Princeton, NJ (United States)
2015-01-20
This final report describes research performed in Princeton University, led by Professor Yannis G. Kevrekidis, over a period of six years (August 1, 2014 to July 31, 2010, including a one-year, no-cost extension) as part of the Center for Multiscale Plasma Dynamics led by the University of Maryland. The work resulted in the development and implementation of several multiscale algorithms based on the equation-free approach pioneered by the PI, including its applications in plasma dynamics problems. These algoriithms include coarse projective integration and coarse stability/bifurcation computations. In the later stages of the work, new links were made between this multiscale, coarse-graining approach and advances in data mining/machine learning algorithms.
Multiscale Bone Remodelling with Spatial P Systems
Cacciagrano, Diletta; Merelli, Emanuela; Tesei, Luca; 10.4204/EPTCS.40.6
2010-01-01
Many biological phenomena are inherently multiscale, i.e. they are characterized by interactions involving different spatial and temporal scales simultaneously. Though several approaches have been proposed to provide "multilayer" models, only Complex Automata, derived from Cellular Automata, naturally embed spatial information and realize multiscaling with well-established inter-scale integration schemas. Spatial P systems, a variant of P systems in which a more geometric concept of space has been added, have several characteristics in common with Cellular Automata. We propose such a formalism as a basis to rephrase the Complex Automata multiscaling approach and, in this perspective, provide a 2-scale Spatial P system describing bone remodelling. The proposed model not only results to be highly faithful and expressive in a multiscale scenario, but also highlights the need of a deep and formal expressiveness study involving Complex Automata, Spatial P systems and other promising multiscale approaches, such as ...
A multiscale soil loss evaluation index
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Exploring the relationships between land use and soil erosion at different scales is a frontier research field and a hot spot topic in contemporary physical geography. Based on the scale-pattern-process theory in landscape ecology and with consideration of such influential factors as land use, topography, soil and rainfall, this paper applies the scale transition method to establishing a soil loss evaluation index at different scales and puts forward a research path and methodology for multiscale soil loss evaluation indices. The multiscale soil loss evaluation index is applied to the evaluation of relationships between land use and soil erosion and the research of soil erosion evaluation at multiple scales. It provides a new method for optimizing the design of regional land use patterns and integrated multiscale research.
Multi-scale characterization of topographic anisotropy
Roy, S. G.; Koons, P. O.; Osti, B.; Upton, P.; Tucker, G. E.
2016-05-01
We present the every-direction variogram analysis (EVA) method for quantifying orientation and scale dependence of topographic anisotropy to aid in differentiation of the fluvial and tectonic contributions to surface evolution. Using multi-directional variogram statistics to track the spatial persistence of elevation values across a landscape, we calculate anisotropy as a multiscale, direction-sensitive variance in elevation between two points on a surface. Tectonically derived topographic anisotropy is associated with the three-dimensional kinematic field, which contributes (1) differential surface displacement and (2) crustal weakening along fault structures, both of which amplify processes of surface erosion. Based on our analysis, tectonic displacements dominate the topographic field at the orogenic scale, while a combination of the local displacement and strength fields are well represented at the ridge and valley scale. Drainage network patterns tend to reflect the geometry of underlying active or inactive tectonic structures due to the rapid erosion of faults and differential uplift associated with fault motion. Regions that have uniform environmental conditions and have been largely devoid of tectonic strain, such as passive coastal margins, have predominantly isotropic topography with typically dendritic drainage network patterns. Isolated features, such as stratovolcanoes, are nearly isotropic at their peaks but exhibit a concentric pattern of anisotropy along their flanks. The methods we provide can be used to successfully infer the settings of past or present tectonic regimes, and can be particularly useful in predicting the location and orientation of structural features that would otherwise be impossible to elude interpretation in the field. Though we limit the scope of this paper to elevation, EVA can be used to quantify the anisotropy of any spatially variable property.
Multiscale Modeling of Ceramic Matrix Composites
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.
Directory of Open Access Journals (Sweden)
X. Wang
2010-05-01
Full Text Available In this study, the Community Multiscale Air Quality (CMAQ modeling system is used to simulate the ozone (O_{3} episodes during the Program of Regional Integrated Experiments of Air Quality over the Pearl River Delta, China, in October 2004 (PRIDE-PRD2004. The simulation suggests that O_{3} pollution is a regional phenomenon in the Pearl River Delta (PRD. Elevated O_{3} levels often occurred in the southwestern inland PRD, Pearl River estuary (PRE, and southern coastal areas during the 1-month field campaign. Three evolution patterns of simulated surface O_{3} are summarized based on different near-ground flow conditions. More than 75% of days featured interactions between weak synoptic forcing and local sea-land circulation. Integrated process rate (IPR analysis shows that photochemical production is a dominant contributor to O_{3} enhancement from 09:00 to 15:00 local standard time in the atmospheric boundary layer over most areas with elevated O_{3} occurrence in the mid-afternoon. The simulated ozone production efficiency is 2–8 O_{3} molecules per NO_{x} molecule oxidized in areas with high O_{3} chemical production. Precursors of O_{3} originating from different source regions in the central PRD are mixed during the course of transport to downwind rural areas during nighttime and early morning, where they then contribute to the daytime O_{3} photochemical production. The sea-land circulation plays an important role on the regional O_{3} formation and distribution over PRD. Sensitivity studies suggest that O_{3} formation is volatile-organic-compound-limited in the central inland PRD, PRE, and surrounding coastal areas with less chemical aging (NO_{x}/NO_{y}>0.6, but is NO_{x}-limited in the rural southwestern PRD with aged air (NO_{x}/NO_{y}<0.3.
Multiscale Regional Formula Fertilization Considering Environment Information Incompleteness
Institute of Scientific and Technical Information of China (English)
Qianqian ZHANG; Yan LIANG
2015-01-01
Conventional formula fertilization tends to calculate regional rate of fertilizer application by means of analyzing spatial distribution of regional cultivated land productivity combined with experiment data. However,as environment information of cultivated land is incomplete due to limitation of traditional cultivated land management technology and data acquisition,uncertainty of rate of fertilizer makes it hard to define the interval of formula fertilization and support the regional fertilization task. With the technique of spatial analysis and multiscale uncertainty theory,conventional fertilization can be optimized. Four steps are involved to calculate regional formula fertilization interval based on conventional formula fertilization:( i) To simulate cultivated land productivity according to EGLSN Model,and make it crop target field;( ii) To determine rate of fertilizer according to target field to define cultivated land productivity fertilizer interval and mid-value;( iii) To define region fertilizer interval length and value of region varying with scales as environment information becomes complete gradually;( iv) To apply block fertilizer combined with conventional formula by soil testing. Multiscale optimizing formula fertilization system has been established by using the Arc Engine as a platform to integrate the methods,which is applied in Xinjiang County,Shanxi Province,in order to optimize the existing fertilization formula in study area. It showed that the optimized formula fertilization had more spatial details of productivity than the original one.And the new method is available to support formula fertilization in any region or the block with uncertain environment information. It is therefore concluded that the proposed method has the potential for popularity,which provides a multiscale,multiple-factor and standardized formula fertilization method.
Directory of Open Access Journals (Sweden)
Lina Zhong
2014-04-01
Full Text Available In this study, statistical data on the national economic and social development, including the year-end actual area of arable land, the crop yield per unit area and 10 factors, were obtained for the period between 1980 and 2010 and used to analyze the factors driving changes in the arable land of the Loess Plateau in northern Shaanxi, China. The following areas of arable land, which represent different spatial scales, were investigated: the Baota District, the city of Yan’an, and the Northern Shaanxi region. The scale effects of the factors driving the changes to the arable land were analyzed using a canonical correlation analysis and a principal component analysis. Because it was difficult to quantify the impact of the national government policies on the arable land changes, the contributions of the national government policies to the changes in arable land were analyzed qualitatively. The primary conclusions of the study were as follows: between 1980 and 2010, the arable land area decreased. The trends of the year-end actual arable land proportion of the total area in the northern Shaanxi region and Yan’an City were broadly consistent, whereas the proportion in the Baota District had no obvious similarity with the northern Shaanxi region and Yan’an City. Remarkably different factors were shown to influence the changes in the arable land at different scales. Environmental factors exerted a greater effect for smaller scale arable land areas (the Baota District. The effect of socio-economic development was a major driving factor for the changes in the arable land area at the city and regional scales. At smaller scales, population change, urbanization and socio-economic development affected the crop yield per unit area either directly or indirectly. Socio-economic development and the modernization of agricultural technology had a greater effect on the crop yield per unit area at the large-scales. Furthermore, the qualitative analysis
Wang, Yulei; Liu, Jian
2016-01-01
In this paper, the secular full-orbit simulations of runaway electrons with synchrotron radiation in tokamak fields are carried out using a relativistic volume-preserving algorithm. Detailed phase-space behaviors of runaway electrons are investigated in different dynamical timescales spanning 11 orders. When looking into the small timescale, i.e., the characteristic timescale imposed by Lorentz force, the severely deformed helical trajectory of energetic runaway electron is witnessed. A qualitative analysis of the neoclassical scattering, a kind of collisionless pitch-angle scattering phenomena, is provided when considering the coupling between the rotation of momentum vector and the background magnetic field. In large timescale up to one second, it is found that the initial condition of runaway electrons in phase space globally influences the pitch-angle scattering, the momentum evolution, and the loss-gain ratio of runaway energy evidently. However, the initial value has little impact on the synchrotron ene...
Computer-Aided Multiscale Modelling for Chemical Process Engineering
DEFF Research Database (Denmark)
Morales Rodriguez, Ricardo; Gani, Rafiqul
2007-01-01
T) for model translation, analysis and solution. The integration of ModDev, MoT and ICAS or any other external software or process simulator (using COM-Objects) permits the generation of different models and/or process configurations for purposes of simulation, design and analysis. Consequently, it is possible......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...... for model generation, analysis, solution and implementation is necessary for the development and application of the desired model-based approach for product-centric process design/analysis. This goal is achieved through the combination of a system for model development (ModDev), and a modelling tool (Mo...
Directory of Open Access Journals (Sweden)
Stephen Pankavich
2015-02-01
Full Text Available Many mesoscopic N-atom systems derive their structural and dynamical properties from processes coupled across multiple scales in space and time. That is, they simultaneously deform or display collective behaviors, while experiencing atomic scale vibrations and collisions. Due to the large number of atoms involved and the need to simulate over long time periods of biological interest, traditional computational tools, like molecular dynamics, are often infeasible for such systems. Hence, in the current review article, we present and discuss two recent multiscale methods, stemming from the N-atom formulation and an underlying scale separation, that can be used to study such systems in a friction-dominated regime: multiscale perturbation theory and multiscale factorization. These novel analytic foundations provide a self-consistent approach to yield accurate and feasible long-time simulations with atomic detail for a variety of multiscale phenomena, such as viral structural transitions and macromolecular self-assembly. As such, the accuracy and efficiency of the associated algorithms are demonstrated for a few representative biological systems, including satellite tobacco mosaic virus (STMV and lactoferrin.
Interactive multiscale tensor reconstruction for multiresolution volume visualization.
Suter, Susanne K; Guitián, José A Iglesias; Marton, Fabio; Agus, Marco; Elsener, Andreas; Zollikofer, Christoph P E; Gopi, M; Gobbetti, Enrico; Pajarola, Renato
2011-12-01
Large scale and structurally complex volume datasets from high-resolution 3D imaging devices or computational simulations pose a number of technical challenges for interactive visual analysis. In this paper, we present the first integration of a multiscale volume representation based on tensor approximation within a GPU-accelerated out-of-core multiresolution rendering framework. Specific contributions include (a) a hierarchical brick-tensor decomposition approach for pre-processing large volume data, (b) a GPU accelerated tensor reconstruction implementation exploiting CUDA capabilities, and (c) an effective tensor-specific quantization strategy for reducing data transfer bandwidth and out-of-core memory footprint. Our multiscale representation allows for the extraction, analysis and display of structural features at variable spatial scales, while adaptive level-of-detail rendering methods make it possible to interactively explore large datasets within a constrained memory footprint. The quality and performance of our prototype system is evaluated on large structurally complex datasets, including gigabyte-sized micro-tomographic volumes.
Coppedè, Nicola
2016-03-18
Conducting polymers are materials displaying high electrical conductivity, easy of fabrication, flexibility and biocompatibility, for this, they are routinely employed in organic electronics, printed electronics, and bioelectronics. Organic electrochemical transistors (OECTs) are a second generation of organic thin transistors, in which the insulator layer is an electrolyte medium and the conductive polymer is electrochemically active. OECT devices have been demonstrated in chemical and biological sensing: while accurate in determining the size of individual ions in solution, similar devices break down if challenged with complex mixtures. Here, we combine a conductive PEODOT:PSS polymer with a super-hydrophobic scheme to obtain a family of advanced devices, in which the ability to manipulate a biological solution couples to a precise texture of the substrate (which incorporates five micro-electrodes in a line, and each is a site specific measurement point), and this permits to realize time and space resolved analysis of a solution. While the competition between convection and diffusion in a super-hydrophobic drop operates the separation of different species based on their size and charge, the described device delivers the ability to register a similar difference. In the following, we demonstrate the device in the sensing of a solution in which CTAB and adrenaline are separated with good sensitivity, selectivity and reliability.
EEMD-based multiscale ICA method for slewing bearing fault detection and diagnosis
Žvokelj, Matej; Zupan, Samo; Prebil, Ivan
2016-05-01
A novel multivariate and multiscale statistical process monitoring method is proposed with the aim of detecting incipient failures in large slewing bearings, where subjective influence plays a minor role. The proposed method integrates the strengths of the Independent Component Analysis (ICA) multivariate monitoring approach with the benefits of Ensemble Empirical Mode Decomposition (EEMD), which adaptively decomposes signals into different time scales and can thus cope with multiscale system dynamics. The method, which was named EEMD-based multiscale ICA (EEMD-MSICA), not only enables bearing fault detection but also offers a mechanism of multivariate signal denoising and, in combination with the Envelope Analysis (EA), a diagnostic tool. The multiscale nature of the proposed approach makes the method convenient to cope with data which emanate from bearings in complex real-world rotating machinery and frequently represent the cumulative effect of many underlying phenomena occupying different regions in the time-frequency plane. The efficiency of the proposed method was tested on simulated as well as real vibration and Acoustic Emission (AE) signals obtained through conducting an accelerated run-to-failure lifetime experiment on a purpose-built laboratory slewing bearing test stand. The ability to detect and locate the early-stage rolling-sliding contact fatigue failure of the bearing indicates that AE and vibration signals carry sufficient information on the bearing condition and that the developed EEMD-MSICA method is able to effectively extract it, thereby representing a reliable bearing fault detection and diagnosis strategy.
Morante-Filho, José Carlos; Arroyo-Rodríguez, Víctor; Faria, Deborah
2016-01-01
Biodiversity maintenance in human-altered landscapes (HALs) depends on the species turnover among localities, but the patterns and determinants of β-diversity in HALs are poorly known. In fact, declines, increases and neutral shifts in β-diversity have all been documented, depending on the landscape, ecological group and spatial scale of analysis. We shed some light on this controversy by assessing the patterns and predictors of bird β-diversity across multiple spatial scales considering forest specialist and habitat generalist bird assemblages. We surveyed birds from 144 point counts in 36 different forest sites across two landscapes with different amount of forest cover in the Brazilian Atlantic forest. We analysed β-diversity among points, among sites and between landscapes with multiplicative diversity partitioning of Hill numbers. We tested whether β-diversity among points was related to within-site variations in vegetation structure, and whether β-diversity among sites was related to site location and/or to differences among sites in vegetation structure and landscape composition (i.e. per cent forest and pasture cover surrounding each site). β-diversity between landscapes was lower than among sites and among points in both bird assemblages. In forest specialist birds, the landscape with less forest cover showed the highest β-diversity among sites (bird differentiation among sites), but generalist birds showed the opposite pattern. At the local scale, however, the less forested landscape showed the lowest β-diversity among points (bird homogenization within sites), independently of the bird assemblage. β-diversity among points was weakly related to vegetation structure, but higher β-diversity values were recorded among sites that were more isolated from each other, and among sites with higher differences in landscape composition, particularly in the less forested landscape. Our findings indicate that patterns of bird β-diversity vary across scales
Directory of Open Access Journals (Sweden)
L. Li
2012-11-01
Full Text Available A high O_{3} episode was detected in urban Shanghai, a typical city in the Yangtze River Delta (YRD region in August 2010. The CMAQ integrated process rate method is applied to account for the contribution of different atmospheric processes during the high pollution episode. The analysis shows that the maximum concentration of ozone occurs due to transport phenomena, including vertical diffusion and horizontal advective transport. Gas-phase chemistry producing O_{3} mainly occurs at the height of 300–1500 m, causing a strong vertical O_{3} transport from upper levels to the surface layer. The gas-phase chemistry is an important sink for O_{3} in the surface layer, coupled with dry deposition. Cloud processes may contribute slightly to the increase of O_{3} due to convective clouds or to the decrease of O_{3} due to scavenging. The horizontal diffusion and heterogeneous chemistry contributions are negligible during the whole episode. Modeling results show that the O_{3} pollution characteristics among the different cities in the YRD region have both similarities and differences. During the buildup period, the O_{3} starts to appear in the city regions of the YRD and is then transported to the surrounding areas under the prevailing wind conditions. The O_{3} production from photochemical reaction in Shanghai and the surrounding area is most significant, due to the high emission intensity in the large city; this ozone is then transported out to sea by the westerly wind flow, and later diffuses to rural areas like Chongming island, Wuxi and even to Nanjing. The O_{3} concentrations start to decrease in the cities after sunset, due to titration of the NO emissions, but ozone can still be transported and maintain a significant concentration in rural areas and even regions outside the YRD region, where the NO emissions are very small.
Directory of Open Access Journals (Sweden)
L. Li
2012-06-01
Full Text Available High ozone concentration has become an important issue in summer in most economically developed cities in Eastern China. In this paper, observations at an urban site within the Shanghai city are used to examine the typical high ozone episodes in August 2010, and the MM5-CMAQ modeling system is then applied to reproduce the typical high ozone episodes. In order to account for the contribution of different atmospheric processes during the high pollution episodes, the CMAQ integrated process rate (IPR is used to assess the different atmospheric dynamics in rural and urban sites of Shanghai, Nanjing and Hangzhou, which are typical cities of the Yangtze River Delta (YRD region. In order to study the contributions of the main atmospheric processes leading to ozone formation, vertical process analysis in layer 1 (0–40 m, layer 7 (350–500 m, layer 8 (500–900 m and layer 10 (1400–2000 m has been considered. The observations compare well with the results of the numerical model. IPR analysis shows that the maximum concentration of ozone occurs due to transport phenomena, including vertical diffusion and horizontal advective transport. The gas-phase chemistry producing O_{3} mainly occurs in the height of 300–1500 m, causing a strong vertical O_{3} transport from upper levels to the surface layer. The gas-phase chemistry is an important sink for O_{3} in the surface layer, coupled with dry deposition. The cloud processes, horizontal diffusion and heterogeneous chemistry contributions are negligible during the whole episode. In the urban Shanghai area, the average O_{3} production rates contributed by vertical diffusion and horizontal transport are 24.7 ppb h^{−1}, 3.6 ppb h^{−1}, accounting for 27.6% and 6.6% of net surface O_{3} change, respectively. The average contributions of chemistry, dry deposition and vertical advective transport to O_{3} production are −21.9, −4.3 and
Collaboratory for Multiscale Chemical Science (CMCS)
Energy Technology Data Exchange (ETDEWEB)
Allison, Thomas C [NIST
2012-07-03
This document provides details of the contributions made by NIST to the Collaboratory for Multiscale Chemical Science (CMCS) project. In particular, efforts related to the provision of data (and software in support of that data) relevant to the combustion pilot project are described.
Multiscale degradations of storage ring FEL optics
Gatto, A; Amra, C; Boccara, C; Couprie, Marie Emmanuelle; De Ninno, G; Feigl, T; Garzella, D; Grewe, M; Kaiser, N; Marsi, M; Paoloni, S; Reita, V; Roger, J P; Torchio, P; Trovò, M; Walker, R; Wille, K
2002-01-01
The advanced understanding of the complete degradation phenomena is crucial in order to develop robust optics for FEL. Under very harsh Synchrotron Radiation conditions, results show that multiscale wavelength damages could be observed, inducing local crystalline structure modifications of the high optical index material with a severe increase of the surface roughness.
Multiscale phenomenology of the cosmic web
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 M
Energy Technology Data Exchange (ETDEWEB)
Rundle, John B.
2004-12-31
Physical Review Letters (Tiampo et al., in press), demonstrate that the Southern California system is ergodic in the same way that is seen in the models. These results will be discussed in more detail below. However, the point that needs to be emphasized is that it was the combination of model investigation via theory and simulation coupled with assimilation and classification of real data and applying the methods of statistical mechanics to real fault systems that led to both a successful forecasting algorithm and a deeper understanding of the nature of earthquake fault systems. This paper describes in some detail the results obtained in the previous funding period. We present these in three groups. (A) Investigation of statistical physics models and applications. (B) Earthquake fault systems and Greens functions for complex sources and (C) Space time patterns, data analysis and forecasting.
Multi-Scale Change Detection Research of Remotely Sensed Big Data in CyberGIS
Xing, J.; Sieber, R.
2015-12-01
Big remotely sensed data, the heterogeneity of satellite platforms and file formats along with increasing volumes and velocities, offers new types of analyses. This makes big remotely sensed data a good candidate for CyberGIS, the aim of which is to enable knowledge discovery of big data in the cloud. We apply CyberGIS to feature-based multi-scale land use/cover change (LUCC) detection. There have been attempts to do multi-scale LUCC. However, studies were done with small data and could not consider the mismatch between multi-scale analysis and computational scale. They have yet to consider the possibilities for scalar research across numerous temporal and spatial scales afforded by big data, especially if we want to advance beyond pixel-based analysis and also reduce preprocessing requirements. We create a geospatial cyberinfrastructure (GCI) to handle multi-spatio-temporal scale change detection. We first clarify different meanings of scale in CyberGIS and LUCC to derive a feature scope layer in the GCI based on Stommel modelling. Our analysis layer contains a multi-scale segmentation-based method based on normalized cut image segmentation and wavelet-based image scaling algorithms. Our computer resource utilization layer uses Wang and Armstrong's (2009) method for mainly for memory, I/O and CPU time. Our case is urban-rural change detection in the Greater Montreal Area (5 time periods, 2006-2012, 100 virtual machines), 36,000km2 and varying from 0.6m to 38m resolution. We present a ground truthed accuracy assessment of a change matrix that is composed of 6 feature classes at 12 different spatio-temporal scales, and the performance of the change detection GCI for multi-scale LUCC study. The GCI allows us to extract and coordinate different types of changes by varying spatio-temporal scales from the big imagery datasets.
The triple decomposition of a fluctuating velocity field in a multiscale flow
Energy Technology Data Exchange (ETDEWEB)
Baj, P.; Bruce, P. J. K.; Buxton, O. R. H. [Department of Aeronautics, Imperial College London, London SW7 2AZ (United Kingdom)
2015-07-15
A new method for the triple decomposition of a multiscale flow, which is based on the novel optimal mode decomposition (OMD) technique, is presented. OMD provides low order linear dynamics, which fits a given data set in an optimal way and is used to distinguish between a coherent (periodic) part of a flow and a stochastic fluctuation. The method needs no external phase indication since this information, separate for coherent structures associated with each length scale introduced into the flow, appears as the output. The proposed technique is compared against two traditional methods of the triple decomposition, i.e., bin averaging and proper orthogonal decomposition. This is done with particle image velocimetry data documenting the near wake of a multiscale bar array. It is shown that both traditional methods are unable to provide a reliable estimation for the coherent fluctuation while the proposed technique performs very well. The crucial result is that the coherence peaks are not observed within the spectral properties of the stochastic fluctuation derived with the proposed method; however, these properties remain unaltered at the residual frequencies. This proves the method’s capability of making a distinction between both types of fluctuations. The sensitivity to some prescribed parameters is checked revealing the technique’s robustness. Additionally, an example of the method application for analysis of a multiscale flow is given, i.e., the phase conditioned transverse integral length is investigated in the near wake region of the multiscale object array.
Expanded Mixed Multiscale Finite Element Methods and Their Applications for Flows in Porous Media
Jiang, L.
2012-01-01
We develop a family of expanded mixed multiscale finite element methods (MsFEMs) and their hybridizations for second-order elliptic equations. This formulation expands the standard mixed multiscale finite element formulation in the sense that four unknowns (hybrid formulation) are solved simultaneously: pressure, gradient of pressure, velocity, and Lagrange multipliers. We use multiscale basis functions for both the velocity and the gradient of pressure. In the expanded mixed MsFEM framework, we consider both separable and nonseparable spatial scales. Specifically, we analyze the methods in three categories: periodic separable scales, G-convergent separable scales, and a continuum of scales. When there is no scale separation, using some global information can significantly improve the accuracy of the expanded mixed MsFEMs. We present a rigorous convergence analysis of these methods that includes both conforming and nonconforming formulations. Numerical results are presented for various multiscale models of flow in porous media with shale barriers that illustrate the efficacy of the proposed family of expanded mixed MsFEMs. © 2012 Society for Industrial and Applied Mathematics.
Genetic divergence among cupuaçu accessions by multiscale bootstrap resampling
Directory of Open Access Journals (Sweden)
Vinicius Silva dos Santos
2015-06-01
Full Text Available This study aimed at investigating the genetic divergence of eighteen accessions of cupuaçu trees based on fruit morphometric traits and comparing usual methods of cluster analysis with the proposed multiscale bootstrap resampling methodology. The data were obtained from an experiment conducted in Tomé-Açu city (PA, Brazil, arranged in a completely randomized design with eighteen cupuaçu accessions and 10 repetitions, from 2004 to 2011. Genetic parameters were estimated by restricted maximum likelihood/best linear unbiased prediction (REML/BLUP methodology. The predicted breeding values were used in the study on genetic divergence through Unweighted Pair Cluster Method with Arithmetic Mean (UPGMA hierarchical clustering and Tocher’s optimization method based on standardized Euclidean distance. Clustering consistency and optimal number of clusters in the UPGMA method were verified by the cophenetic correlation coefficient (CCC and Mojena’s criterion, respectively, besides the multiscale bootstrap resampling technique. The use of the clustering UPGMA method in situations with and without multiscale bootstrap resulted in four and five clusters, respectively, while the Tocher’s method resulted in seven clusters. The multiscale bootstrap resampling technique proves to be efficient to assess the consistency of clustering in hierarchical methods and, consequently, the optimal number of clusters.
Dual multi-scale filter with SSS and GW for infrared small target detection
Xin, Yun-hong; Zhou, Jiao; Chen, Yi-shuan
2017-03-01
Multi-scale analysis is a powerful tool in the field of signal processing. In this paper, we propose an efficient small target detection algorithm that is mainly based on the dual multi-scale filters which work sequentially. The algorithm consists of two stages: at the first stage, Spectrum Scale-Space (SSS) is used as the pre-process procedure to obtain the multi-scale saliency maps, which can suppress the low frequency background noise and make the target region prominently at different scale levels. As a result, the more detail information and feature information can be exhibited in the different decomposition image level. After then, the least information entropy is used as the criterion to select the optimal salient map out; At the second stage, the Gabor wavelets (GW) algorithm is utilized to suppress the high frequency noise remained in the optimal salient map and match the feature of size and direction of small target at different scales and angles, and next, to ensure the robustness of the target detection, Non-negative Matrix Factorization (NMF) is applied to fuse all the GW multi-scale images into one optimal target image, which is the final output of the presented method. Experimental results show that, compared with the contrast method, the proposed algorithm has high SCRG and high correct target detection rate, and works well in different types of complex backgrounds.
Multiscale Geometric Analysis: Theory, Applications, and Opportunities
2007-11-02
eiωΦν(x,t) ( a0ν(x, t) + a1ν(x, t) ω + a2ν(x, t) ω2 + . . . ) • Plug into wave equation – Eikonal equations ∂tΦν + λν(x,∇xΦ) = 0. λν(x, k) are the...space ẋ(t) = ∇kλν(x, k), x(0) = x0,k̇(t) = −∇xλν(x, k), k(0) = k0. • Eikonal equations from geometric optics ∂tΦν + λν(x,∇xΦ) = 0. Φ is constant
Multiscale modeling of polymer nanocomposites
Sheidaei, Azadeh
In recent years, polymer nano-composites (PNCs) have increasingly gained more attention due to their improved mechanical, barrier, thermal, optical, electrical and biodegradable properties in comparison with the conventional micro-composites or pristine polymer. With a modest addition of nanoparticles (usually less than 5wt. %), PNCs offer a wide range of improvements in moduli, strength, heat resistance, biodegradability, as well as decrease in gas permeability and flammability. Although PNCs offer enormous opportunities to design novel material systems, development of an effective numerical modeling approach to predict their properties based on their complex multi-phase and multiscale structure is still at an early stage. Developing a computational framework to predict the mechanical properties of PNC is the focus of this dissertation. A computational framework has been developed to predict mechanical properties of polymer nano-composites. In chapter 1, a microstructure inspired material model has been developed based on statistical technique and this technique has been used to reconstruct the microstructure of Halloysite nanotube (HNT) polypropylene composite. This technique also has been used to reconstruct exfoliated Graphene nanoplatelet (xGnP) polymer composite. The model was able to successfully predict the material behavior obtained from experiment. Chapter 2 is the summary of the experimental work to support the numerical work. First, different processing techniques to make the polymer nanocomposites have been reviewed. Among them, melt extrusion followed by injection molding was used to manufacture high density polyethylene (HDPE)---xGnP nanocomposties. Scanning electron microscopy (SEM) also was performed to determine particle size and distribution and to examine fracture surfaces. Particle size was measured from these images and has been used for calculating the probability density function for GNPs in chapter 1. A series of nanoindentation tests have
Energy Technology Data Exchange (ETDEWEB)
Shadid, John Nicolas; Lehoucq, Richard B.; Christon, Mark Allen; Slepoy, Alexander; Bochev, Pavel Blagoveston; Collis, Samuel Scott; Wagner, Gregory John
2004-05-01
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.
Chung, Eric
2015-12-11
In this paper, we develop a mass conservative multiscale method for coupled flow and transport in heterogeneous porous media. We consider a coupled system consisting of a convection-dominated transport equation and a flow equation. We construct a coarse grid solver based on the Generalized Multiscale Finite Element Method (GMsFEM) for a coupled system. In particular, multiscale basis functions are constructed based on some snapshot spaces for the pressure and the concentration equations and some local spectral decompositions in the snapshot spaces. The resulting approach uses a few multiscale basis functions in each coarse block (for both the pressure and the concentration) to solve the coupled system. We use the mixed framework, which allows mass conservation. Our main contributions are: (1) the development of a mass conservative GMsFEM for the coupled flow and transport; (2) the development of a robust multiscale method for convection-dominated transport problems by choosing appropriate test and trial spaces within Petrov-Galerkin mixed formulation. We present numerical results and consider several heterogeneous permeability fields. Our numerical results show that with only a few basis functions per coarse block, we can achieve a good approximation.
Directory of Open Access Journals (Sweden)
Eric T. Chung
2015-12-01
Full Text Available In this paper, we develop a mass conservative multiscale method for coupled flow and transport in heterogeneous porous media. We consider a coupled system consisting of a convection-dominated transport equation and a flow equation. We construct a coarse grid solver based on the Generalized Multiscale Finite Element Method (GMsFEM for a coupled system. In particular, multiscale basis functions are constructed based on some snapshot spaces for the pressure and the concentration equations and some local spectral decompositions in the snapshot spaces. The resulting approach uses a few multiscale basis functions in each coarse block (for both the pressure and the concentration to solve the coupled system. We use the mixed framework, which allows mass conservation. Our main contributions are: (1 the development of a mass conservative GMsFEM for the coupled flow and transport; (2 the development of a robust multiscale method for convection-dominated transport problems by choosing appropriate test and trial spaces within Petrov-Galerkin mixed formulation. We present numerical results and consider several heterogeneous permeability fields. Our numerical results show that with only a few basis functions per coarse block, we can achieve a good approximation.
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.
Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites
2016-03-09
AFRL-AFOSR-VA-TR-2016-0154 Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites Gregory Odegard MICHIGAN TECHNOLOGICAL UNIVERSITY Final Report...SUBTITLE Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-13-1-0030 5c. PROGRAM ELEMENT NUMBER...DISTRIBUTION A: Distribution approved for public release. Final Report Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites Grant FA9550-13-1-0030 PI
Multiscale mathematical modeling and simulation of cellular dynamical process.
Nakaoka, Shinji
2014-01-01
Epidermal homeostasis is maintained by dynamic interactions among molecules and cells at different spatiotemporal scales. Mathematical modeling and simulation is expected to provide clear understanding and precise description of multiscaleness in tissue homeostasis under systems perspective. We introduce a stochastic process-based description of multiscale dynamics. Agent-based modeling as a framework of multiscale modeling to achieve consistent integration of definitive subsystems is proposed. A newly developed algorithm that particularly aims to perform stochastic simulations of cellular dynamical process is introduced. Finally we review applications of multiscale modeling and quantitative study to important aspects of epidermal and epithelial homeostasis.
Colloca, Michele; Blanchard, Romane; Hellmich, Christian; Ito, Keita; van Rietbergen, Bert
2014-07-01
Bone is a dynamic and hierarchical porous material whose spatial and temporal mechanical properties can vary considerably due to differences in its microstructure and due to remodeling. Hence, a multiscale analytical approach, which combines bone structural information at multiple scales to the remodeling cellular activities, could form an efficient, accurate and beneficial framework for the prognosis of changes in bone properties due to, e.g., bone diseases. In this study, an analytical formulation of bone remodeling integrated with multiscale micromechanical models is proposed to investigate the effects of structural changes at the nanometer level (collagen scale) on those at higher levels (tissue scale). Specific goals of this study are to derive a mechanical stimulus sensed by the osteocytes using a multiscale framework, to test the accuracy of the multiscale model for the prediction of bone density, and to demonstrate its multiscale capabilities by predicting changes in bone density due to changes occurring at the molecular level. At each different level, the bone composition was modeled as a two-phase material which made it possible to: (1) find a closed-form solution for the energy-based mechanical stimulus sensed by the osteocytes and (2) describe the anisotropic elastic properties at higher levels as a function of the stiffness of the elementary components (collagen, hydroxyapatite and water) at lower levels. The accuracy of the proposed multiscale model of bone remodeling was tested first by comparing the analytical bone volume fraction predictions to those obtained from the corresponding μFE-based computational model. Differences between analytical and numerical predictions were less than 1% while the computational time was drastically reduced, namely by a factor of 1 million. In a further analysis, the effects of changes in collagen and hydroxyapatite volume fractions on the bone remodeling process were simulated, and it was found that such changes
Multiscale Investigation of Chemical Interference in Proteins
Samiotakis, Antonios; Cheung, Margaret S
2010-01-01
We developed a multiscale approach (MultiSCAAL) that integrates the potential of mean force (PMF) obtained from all-atomistic molecular dynamics simulations with a knowledge-based energy function for coarse-grained molecular simulations in better exploring the energy landscape of a small protein under chemical interference such as chemical denaturation. An excessive amount of water molecules in all-atomistic molecular dynamics simulations often negatively impacts the sampling efficiency of some advanced sampling techniques such as the replica exchange method and it makes the investigation of chemical interferences on protein dynamics difficult. Thus, there is a need to develop an effective strategy that focuses on sampling structural changes in protein conformations rather than solvent molecule fluctuations. In this work, we address this issue by devising a multiscale simulation scheme (MultiSCAAL) that bridges the gap between all-atomistic molecular dynamics simulation and coarse-grained molecular simulation...
Towards multiscale modeling of influenza infection.
Murillo, Lisa N; Murillo, Michael S; Perelson, Alan S
2013-09-07
Aided by recent advances in computational power, algorithms, and higher fidelity data, increasingly detailed theoretical models of infection with influenza A virus are being developed. We review single scale models as they describe influenza infection from intracellular to global scales, and, in particular, we consider those models that capture details specific to influenza and can be used to link different scales. We discuss the few multiscale models of influenza infection that have been developed in this emerging field. In addition to discussing modeling approaches, we also survey biological data on influenza infection and transmission that is relevant for constructing influenza infection models. We envision that, in the future, multiscale models that capitalize on technical advances in experimental biology and high performance computing could be used to describe the large spatial scale epidemiology of influenza infection, evolution of the virus, and transmission between hosts more accurately.
MULTI-SCALE GAUSSIAN PROCESSES MODEL
Institute of Scientific and Technical Information of China (English)
Zhou Yatong; Zhang Taiyi; Li Xiaohe
2006-01-01
A novel model named Multi-scale Gaussian Processes (MGP) is proposed. Motivated by the ideas of multi-scale representations in the wavelet theory, in the new model, a Gaussian process is represented at a scale by a linear basis that is composed of a scale function and its different translations. Finally the distribution of the targets of the given samples can be obtained at different scales. Compared with the standard Gaussian Processes (GP) model, the MGP model can control its complexity conveniently just by adjusting the scale parameter. So it can trade-off the generalization ability and the empirical risk rapidly. Experiments verify the feasibility of the MGP model, and exhibit that its performance is superior to the GP model if appropriate scales are chosen.
Tracking magnetogram proper motions by multiscale regularization
Jones, Harrison P.
1995-01-01
Long uninterrupted sequences of solar magnetograms from the global oscillations network group (GONG) network and from the solar and heliospheric observatory (SOHO) satellite will provide the opportunity to study the proper motions of magnetic features. The possible use of multiscale regularization, a scale-recursive estimation technique which begins with a prior model of how state variables and their statistical properties propagate over scale. Short magnetogram sequences are analyzed with the multiscale regularization algorithm as applied to optical flow. This algorithm is found to be efficient, provides results for all the spatial scales spanned by the data and provides error estimates for the solutions. It is found that the algorithm is less sensitive to evolutionary changes than correlation tracking.
Multiscale Phenomenology of the Cosmic Web
Aragon-Calvo, Miguel A; Jones, Bernard J T
2010-01-01
We analyze 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 $\\Lambda$CDM N-body computer simulation into cluster, filaments and walls. The MMF is ideally suited to adress both the anisotropic morphological character of filaments and sheets, as well as the multiscale nature of the hierarchically evolved cosmic matter distribution. The results of our study may be summarized as follows: i).- While all morphologies occupy a roughly well defined range in density, this alone is not sufficient to differentiate between them given their overlap. Environment defined only in terms of density fails to incorporate the intrinsic dynamics of each morphology. This plays an important role in both linear and non linear interactions between haloes. ii).- Most of the mass in the Universe is concentrated in filaments, narrowly followed by clusters. In terms of volume, clusters only r...
Zewail, R.; Elsafi, A.; Durdle, N.
2009-02-01
Medical experts often examine hundreds of spine x-rays to determine existence of diseases like osteoarthritis, osteoporoses, and osteophites. Accurate vertebrae segmentation plays a great role in the proper assessment of various vertebral abnormalities. Manual segmentation methods are both time consuming and non-reproducible, hence, developing efficient computer-assisted segmentation methods has been a long standing goal. Over the past decade, segmentation methods that utilize statistical models of shape and appearance have drawn much interest within the medical imaging community. However, despite being a promising approach, they are always faced with a number of challenges such as: poor image quality, and the ability to generalize well to unseen vertebral deformities. This paper presents a novel vertebral segmentation method using Contourlet-based salient point matching and a localized multi-scale shape prior. We employ a multi-scale directional analysis tool, namely contourlets, to build local appearance profiles at salient points of the vertebra's body. The contourlet-based local appearance model is used to detect the vertebral bodies in the test x-ray image. A novel localized multi-scale shape prior is used to drive the segmentation process. Within a best-basis selection framework, the proposed shape prior benefits from the multi-scale nature of wavelet packets, and the capability of ICA to capture hidden independent modes of variations. Experiments were conducted using a set of 100 digital x-ray images of lumbar spines. The contourlet-based appearance profiles and the localized multi-scale shape prior were constructed using a training subset of images, and then matched to unseen images. Promising results were obtained compared to related work in the literature with an average segmentation error of 1.1997 mm.
Generalized Multiscale Finite Element Methods for Wave Propagation in Heterogeneous Media
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.
Multiscale Models of Melting Arctic Sea Ice
2014-09-30
1 Multiscale Models of Melting Arctic Sea Ice Kenneth M. Golden University of Utah, Department of Mathematics phone: (801) 581-6851...feedback has played a major role in the recent declines of the summer Arctic sea ice pack. However, understanding the evolution of melt ponds and sea...Models of Melting Arctic Sea Ice 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER
Engineering Digestion: Multiscale Processes of Food Digestion.
Bornhorst, Gail M; Gouseti, Ourania; Wickham, Martin S J; Bakalis, Serafim
2016-03-01
Food digestion is a complex, multiscale process that has recently become of interest to the food industry due to the developing links between food and health or disease. Food digestion can be studied by using either in vitro or in vivo models, each having certain advantages or disadvantages. The recent interest in food digestion has resulted in a large number of studies in this area, yet few have provided an in-depth, quantitative description of digestion processes. To provide a framework to develop these quantitative comparisons, a summary is given here between digestion processes and parallel unit operations in the food and chemical industry. Characterization parameters and phenomena are suggested for each step of digestion. In addition to the quantitative characterization of digestion processes, the multiscale aspect of digestion must also be considered. In both food systems and the gastrointestinal tract, multiple length scales are involved in food breakdown, mixing, absorption. These different length scales influence digestion processes independently as well as through interrelated mechanisms. To facilitate optimized development of functional food products, a multiscale, engineering approach may be taken to describe food digestion processes. A framework for this approach is described in this review, as well as examples that demonstrate the importance of process characterization as well as the multiple, interrelated length scales in the digestion process.
Multiscale experimental characterization of solar cell defects
Škarvada, Pavel; Škvarenina, Lubomír.; Tománek, Pavel; Sobola, Dinara; Macků, Robert; Brüstlová, Jitka; Grmela, Lubomír.; Smith, Steve
2016-12-01
The search for alternative sources of renewable energy, including novel photovoltaics structures, is one of the principal tasks of 21th century development. In the field of photovoltaics there are three generations of solar cells of different structures going from monocrystalline silicon through thin-films to hybrid and organic cells, moreover using nanostructure details. Due to the diversity of these structures, their complex study requires the multiscale interpretations which common core includes an integrated approach bridging not only the length scales from macroscale to the atomistic, but also multispectral investigation under different working temperatures. The multiscale study is generally applied to theoretical aspects, but is also applied to experimental characterization. We investigate multiscale aspects of electrical, optical and thermal properties of solar cells under illumination and in dark conditions when an external bias is applied. We present the results of a research of the micron and sub-micron defects in a crystalline solar cell structure utilizing scanning probe microscopy and electric noise measurement.
Multiscale computation from a chemical engineering perspective
Institute of Scientific and Technical Information of China (English)
Li Jinghai
2014-01-01
This-paper-mainly-discusses-the-multiscale-computation-from-a-chemical-engineering-perspective.-From-the-application-designer’s-perspective,we-propose-a-new-approach-to-investigate-and-develop-both-flexi-ble-and-efficient-computer-architectures.-Based-on-the-requirements-of-applications-within-one-category,we-first-induce-and-extract-some-inherent-computing-patterns-or-core-computing-kernels-from-the-applications.-Some-computing-models-and-innovative-computing-architectures-will-then-be-developed-for-these-patterns-or-kernels,as-well-as-the-software-mapping-techniques.-Finally-those-applications-which-can-share-and-utilize-those-computing-patterns-or-kernels-can-be-executed-very-efficiently-on-those-novel-computing-architectures.-We-think-that-the-proposed-approach-may-not-be-achievable-within-the-existing-technology.-However,we-believe-that-it-will-be-available-in-the-near-future.-Hence,we-will-describe-this-approach-from-the-following-four-as-pects:multiscale-environment-in-the-world,-mesoscale-as-a-key-scale,-energy-minimization-multiscale-(EMMS)paradigm-and-our-perspective.
Multiscale modeling with smoothed dissipative particle dynamics.
Kulkarni, Pandurang M; Fu, Chia-Chun; Shell, M Scott; Leal, L Gary
2013-06-21
In this work, we consider two issues related to the use of Smoothed Dissipative Particle Dynamics (SDPD) as an intermediate mesoscale model in a multiscale scheme for solution of flow problems when there are local parts of a macroscopic domain that require molecular resolution. The first is to demonstrate that SDPD with different levels of resolution can accurately represent the fluid properties from the continuum scale all the way to the molecular scale. Specifically, while the thermodynamic quantities such as temperature, pressure, and average density remain scale-invariant, we demonstrate that the dynamic properties are quantitatively consistent with an all-atom Lennard-Jones reference system when the SDPD resolution approaches the atomistic scale. This supports the idea that SDPD can serve as a natural bridge between molecular and continuum descriptions. In the second part, a simple multiscale methodology is proposed within the SDPD framework that allows several levels of resolution within a single domain. Each particle is characterized by a unique physical length scale called the smoothing length, which is inversely related to the local number density and can change on-the-fly. This multiscale methodology is shown to accurately reproduce fluid properties for the simple problem of steady and transient shear flow.
Multiscale phenomena in the Earth's Magnetosphere
Surjalal Sharma, A.
The multiscale phenomena in the Earth's magnetosphere have been studied using data from ground-based and space-borne measurements. The ground-based observations provide data over decades and are suitable for characterizing the inherent nature of the multiscale behavior and for studying the dynamical and statistical features. On the other hand, the spacecraft data provide in-situ observations of the processes. The multipoint measurements by Cluster have provided a new understanding of the plasma processes at microand meso-scales and the cross-scale coupling among them. The role of cross-scale coupling is evident in phenomena such as bursty bulk flows, flux ropes, and reconnection. The characteristic scales of the processes range from electron skin depth to MHD scales and the modeling of these processes need different physical models, such as kinetic, EMHD, Hall MHD, and MHD. The ground-based data have been used to develop models based on techniques of nonlinear science and yield predictive models which can be used for forecasting. These models characterize the magnetospheric dynaics and yield its global and multiscale aspects. The distribution of scales in the magnetosphere is studied using an extensive database of the solar wind and the magnetosphere. The distributions of the waiting times deviate significantly from a power law as well as stretched exponential distributions, and show a scaling with respect to the mean, indicating a limited role of long-term correlations in the magnetospheric dynamics.
Brambilla, Mattia
2017-01-01
, although we found a consistent effect with the habitat selection model (and hence evidence for adaptiveness) only for the former. Discussion Our work suggests caution when interpreting adaptiveness of habitat preferences at a single spatial scale because such an approach may under- or over-estimate the importance of habitat factors. As an example, we found evidence only for a weak effect of water depth at territory scale on little crake nest survival; however, according to the multi-scale analysis, such effect turned out to be important and appeared highly adaptive. Therefore, multi-scale approaches to the study of adaptive explanations for habitat selection mechanisms should be promoted.
Dai, Jun; Zhou, Haigang; Zhao, Shaoquan
2017-01-01
This paper considers a multi-scale future hedge strategy that minimizes lower partial moments (LPM). To do this, wavelet analysis is adopted to decompose time series data into different components. Next, different parametric estimation methods with known distributions are applied to calculate the LPM of hedged portfolios, which is the key to determining multi-scale hedge ratios over different time scales. Then these parametric methods are compared with the prevailing nonparametric kernel metric method. Empirical results indicate that in the China Securities Index 300 (CSI 300) index futures and spot markets, hedge ratios and hedge efficiency estimated by the nonparametric kernel metric method are inferior to those estimated by parametric hedging model based on the features of sequence distributions. In addition, if minimum-LPM is selected as a hedge target, the hedging periods, degree of risk aversion, and target returns can affect the multi-scale hedge ratios and hedge efficiency, respectively.
Multiscale Entropy under the Inverse Gaussian Distribution: Analytical Results
Institute of Scientific and Technical Information of China (English)
TANG Ying; PEI Wen-Jiang; XIA Hai-Shan; HE Zhen-Ya
2007-01-01
The multiscale entropy (MSE) reveals the intrinsic multiple scales in the complexity of physical and physiological signals, which are usually featured by heavy-tailed distributions. However, most research results are pure experimental search. Recently, Costa et al. have made the first attempt to present the theoretical basis of MSE, but it only supports the Gaussian distribution [Phys Rev. E 71 (2005) 021906]. We present the theoretical basis of MSE under the inverse Gaussian distribution, a typical model for physiological, physical and financial data sets. The analysis allows for uncorrelated inverse Gaussian process and 1/f noise with the multivariate inverse Gaussian distribution, and then provides a reliable foundation for the potential applications of MSE to explore complex physical and physical time series.
Critical behavior of the contact process in a multiscale network
Ferreira, Silvio C; 10.1103/PhysRevE.76.036112
2011-01-01
Inspired by dengue and yellow fever epidemics, we investigated the contact process (CP) in a multiscale network constituted by one-dimensional chains connected through a Barab\\'asi-Albert scale-free network. In addition to the CP dynamics inside the chains, the exchange of individuals between connected chains (travels) occurs at a constant rate. A finite epidemic threshold and an epidemic mean lifetime diverging exponentially in the subcritical phase, concomitantly with a power law divergence of the outbreak's duration, were found. A generalized scaling function involving both regular and SF components was proposed for the quasistationary analysis and the associated critical exponents determined, demonstrating that the CP on this hybrid network and nonvanishing travel rates establishes a new universality class.
Multi-scale correlations in different future markets
Bartolozzi, M; Di Matteo, T; Aste, T
2007-01-01
In the present work we investigate the multiscale nature of the correlations for high frequency data (1 minute) in different futures markets over a period of two years, starting on the 1st of January 2003 and ending on the 31st of December 2004. In particular, by using the concept of "local" Hurst exponent, we point out how the behaviour of this parameter, usually considered as a benchmark for persistency/antipersistency recognition in time series, is largely time-scale dependent in the market context. These findings are a direct consequence of the intrinsic complexity of a system where trading strategies are scale-adaptive. Moreover, our analysis points out different regimes in the dynamical behaviour of the market indices under consideration.
Multi-scale correlations in different futures markets
Bartolozzi, M.; Mellen, C.; di Matteo, T.; Aste, T.
2007-07-01
In the present work we investigate the multiscale nature of the correlations for high frequency data (1 min) in different futures markets over a period of two years, starting on the 1st of January 2003 and ending on the 31st of December 2004. In particular, by using the concept of local Hurst exponent, we point out how the behaviour of this parameter, usually considered as a benchmark for persistency/antipersistency recognition in time series, is largely time-scale dependent in the market context. These findings are a direct consequence of the intrinsic complexity of a system where trading strategies are scale-adaptive. Moreover, our analysis points out different regimes in the dynamical behaviour of the market indices under consideration.
Multiscale vascular surface model generation from medical imaging data using hierarchical features.
Bekkers, Eric J; Taylor, Charles A
2008-03-01
Computational fluid dynamics (CFD) modeling of blood flow from image-based patient specific models can provide useful physiologic information for guiding clinical decision making. A novel method for the generation of image-based, 3-D, multiscale vascular surface models for CFD is presented. The method generates multiscale surfaces based on either a linear triangulated or a globally smooth nonuniform rational B-spline (NURB) representation. A robust local curvature analysis is combined with a novel global feature analysis to set mesh element size. The method is particularly useful for CFD modeling of complex vascular geometries that have a wide range of vasculature size scales, in conditions where 1) initial surface mesh density is an important consideration for balancing surface accuracy with manageable size volumetric meshes, 2) adaptive mesh refinement based on flow features makes an underlying explicit smooth surface representation desirable, and 3) semi-automated detection and trimming of a large number of inlet and outlet vessels expedites model construction.
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.
2009-08-14
dimensional Electrostatic Particle-in-Cell Metho - dology on Unstructured Delaunay-Voronoi Grids", Journal of Computational Physics , Vo- lume 228, Issue 10...addresses mathematical and computational issues of par dimensional simulation of flows at the nanoscale. The research addre phenomena in nanoscale flows...sses also the multi-scale physical devices and processes. The DSMC) method are presented, the analysis of statistical es obtained from U3DSMC es
What is a Multiscale Problem in Molecular Dynamics?
Directory of Open Access Journals (Sweden)
Luigi Delle Site
2013-12-01
Full Text Available In this work, we make an attempt to answer the question of what a multiscale problem is in Molecular Dynamics (MD, or, more in general, in Molecular Simulation (MS. By introducing the criterion of separability of scales, we identify three major (reference categories of multiscale problems and discuss their corresponding computational strategies by making explicit examples of applications.
Development of Improved Algorithms and Multiscale Modeling Capability with SUNTANS
2015-09-30
High-resolution simulations using nonhydrostatic models like SUNTANS are crucial for understanding multiscale processes that are unresolved, and...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Development of Improved Algorithms and Multiscale ... Modeling Capability with SUNTANS Oliver B. Fringer 473 Via Ortega, Room 187 Dept. of Civil and Environmental Engineering Stanford University
Transitions of the Multi-Scale Singularity Trees
DEFF Research Database (Denmark)
Somchaipeng, Kerawit; Sporring, Jon; Kreiborg, Sven
2005-01-01
Multi-Scale Singularity Trees(MSSTs) [10] are multi-scale image descriptors aimed at representing the deep structures of images. Changes in images are directly translated to changes in the deep structures; therefore transitions in MSSTs. Because MSSTs can be used to represent the deep structure...
Addressing the Multi-scale lapsus of landscape
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 landscape as the main driving factor behind many geo-environm
Cho, Changsoon; Lee, Jung-Yong
2013-03-11
An efficient light trapping scheme is a key to enhancing the power conversion efficiency (PCE) of thin-film photovoltaic (PV) cells by compensating for the insufficient light absorption. To handle optical components from nano-scale to micro-scale seamlessly, a multi-scale optical simulation is carefully designed in this study and is used to qualitatively analyze the light trapping performances of a micro lens array (MLA), a V-shaped configuration, and the newly proposed scheme, which is termed a double parabolic trapper (DPT) according to both daily and annual movement of the sun. DPT has the potential to enhance the PCE significantly, from 5.9% to 8.9%, for PCDTBT:PC(70)BM-based polymer solar cells by perfectly trapping the incident light between two parabolic PV cells.
2011-03-15
the constitutive micro-level like fiber failures, matrix damage , inelasticity, interfacial debonding to the global structural response level. The MAC...micromechanical analysis establishes the overall elastoplastic behavior of the multiphase inelastic composite. This is expressed as an effective elastic-plastic...fiber failures, matrix damage , interfacial debonding, throughout the structural response. This fully coupled multi-scale simulation frame will be
2007-07-10
The 2006 International Workshop on Multiscale Biological Imaging, Data Mining and Informatics was held at Santa Barbara, on Sept 7-8, 2006. Based on the presentations at the workshop, we selected and compiled this collection of research articles related to novel algorithms and enabling techniques for bio- and biomedical image analysis, mining, visualization, and biology applications.
Institute of Scientific and Technical Information of China (English)
马学虎; 彭本利; 兰忠; 王爱丽; 王四芳; 张崇峰; 白涛
2011-01-01
Dropwise condensation heat transfer process possesses typical multi-scale characteristics,such as the droplet size distribution on condensation surface, time sequence during droplet growth process, the physicochemical properties of condensation surfaces, and interaction effects between droplets and condensing surface. Based on the dropwise condensation heat transfer model with liquid-solid interfacial effect, multi-scale phenomenon of droplet size distribution and its effect on dropwise condensation heat transfer are analyzed in this paper, in addition, an optimal contact angle is obtained from analyzing the relationship among droplet size, contact angle and average heat transfer characteristics.%滴状冷凝传热过程具有典型的多尺度特征,一方面体现于壁面上液滴尺寸分布的空间多尺度特征以及液滴生长过程的时间多尺度分布,另一方面体现于冷凝壁面物理化学特性以及液固相互作用特性的描述和量度上的多尺度特征.本文基于包含界面效应影响的滴状冷凝传热模型,分析了液滴尺寸分布的多尺度特征及其对滴状冷凝传热性能的影响,并通过分析液滴尺寸、接触角等因素与平均冷凝传热性能的关系,进行多尺度分析规划,得到冷凝壁面传热性能最佳时的接触角.
A multiscale modeling technique for bridging molecular dynamics with finite element method
Energy Technology Data Exchange (ETDEWEB)
Lee, Yongchang, E-mail: yl83@buffalo.edu; Basaran, Cemal
2013-11-15
In computational mechanics, molecular dynamics (MD) and finite element (FE) analysis are well developed and most popular on nanoscale and macroscale analysis, respectively. MD can very well simulate the atomistic behavior, but cannot simulate macroscale length and time due to computational limits. FE can very well simulate continuum mechanics (CM) problems, but has the limitation of the lack of atomistic level degrees of freedom. Multiscale modeling is an expedient methodology with a potential to connect different levels of modeling such as quantum mechanics, molecular dynamics, and continuum mechanics. This study proposes a new multiscale modeling technique to couple MD with FE. The proposed method relies on weighted average momentum principle. A wave propagation example has been used to illustrate the challenges in coupling MD with FE and to verify the proposed technique. Furthermore, 2-Dimensional problem has also been used to demonstrate how this method would translate into real world applications. -- Highlights: •A weighted averaging momentum method is introduced for bridging molecular dynamics (MD) with finite element (FE) method. •The proposed method shows excellent coupling results in 1-D and 2-D examples. •The proposed method successfully reduces the spurious wave reflection at the border of MD and FE regions. •Big advantages of the proposed method are simplicity and inexpensive computational cost of multiscale analysis.
Efficient algorithms for multiscale modeling in porous media
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.
A Coupled Multiscale Model of Texture Evolution and Plastic Anisotropy
Gawad, J.; Van Bael, A.; Yerra, S. K.; Samaey, G.; Van Houtte, P.; Roose, D.
2010-06-01
In this paper we present a multiscale model of a plastic deformation process in which the anisotropy of plastic properties is related to the evolution of the crystallographic texture. The model spans several length scales from the macroscopic deformation of the workpiece to the microscale interactions between individual grains in a polycrystalline material. The macroscopic behaviour of the material is described by means of a Finite Element (FE) model. Plastic anisotropy is taken into account in a constitutive law, based on the concept of a plastic potential in strain rate space. The coefficients of a sixth-order Facet equation are determined using the Taylor theory, provided that the current crystallographic texture at a given FE integration point is known. Texture evolution in the FE integration points is predicted by an ALAMEL micromechanical model. Mutual interactions between coarse and fine scale are inherent in the physics of the deformation process. These dependencies are taken into account by full bidirectional coupling in the model. Therefore, the plastic deformation influences the crystallographic texture and the evolution of the texture induces anisotropy of the macroscopic deformation. The presented approach enables an adaptive texture and yield surface update scheme with respect to the local plastic deformation in the FE integration points. Additionally, the computational cost related to the updates of the constitutive law is reduced by application of parallel computing techniques. Suitability of on-demand computing for this computational problem is discussed. The parallelisation strategy addresses both distributed memory and shared memory architectures. The cup drawing process has been simulated using the multiscale model outlined above. The discussion of results includes the analysis of the planar anisotropy in the cup and the influence of complex deformation path on texture development. Evolution of texture at selected material points is assessed as
A multiscale systems perspective on cancer, immunotherapy, and Interleukin-12
Directory of Open Access Journals (Sweden)
Klinke David J
2010-09-01
Full Text Available Abstract Monoclonal antibodies represent some of the most promising molecular targeted immunotherapies. However, understanding mechanisms by which tumors evade elimination by the immune system of the host presents a significant challenge for developing effective cancer immunotherapies. The interaction of cancer cells with the host is a complex process that is distributed across a variety of time and length scales. The time scales range from the dynamics of protein refolding (i.e., microseconds to the dynamics of disease progression (i.e., years. The length scales span the farthest reaches of the human body (i.e., meters down to the range of molecular interactions (i.e., nanometers. Limited ranges of time and length scales are used experimentally to observe and quantify changes in physiology due to cancer. Translating knowledge obtained from the limited scales observed experimentally to predict patient response is an essential prerequisite for the rational design of cancer immunotherapies that improve clinical outcomes. In studying multiscale systems, engineers use systems analysis and design to identify important components in a complex system and to test conceptual understanding of the integrated system behavior using simulation. The objective of this review is to summarize interactions between the tumor and cell-mediated immunity from a multiscale perspective. Interleukin-12 and its role in coordinating antibody-dependent cell-mediated cytotoxicity is used illustrate the different time and length scale that underpin cancer immunoediting. An underlying theme in this review is the potential role that simulation can play in translating knowledge across scales.
Directory of Open Access Journals (Sweden)
Liyun Su
2011-01-01
Full Text Available In order to suppress the interference of the strong fractional noise signal in discrete-time ultrawideband (UWB systems, this paper presents a new UWB multi-scale Kalman filter (KF algorithm for the interference suppression. This approach solves the problem of the narrowband interference (NBI as nonstationary fractional signal in UWB communication, which does not need to estimate any channel parameter. In this paper, the received sampled signal is transformed through multiscale wavelet to obtain a state transition equation and an observation equation based on the stationarity theory of wavelet coefficients in time domain. Then through the Kalman filter method, fractional signal of arbitrary scale is easily figured out. Finally, fractional noise interference is subtracted from the received signal. Performance analysis and computer simulations reveal that this algorithm is effective to reduce the strong fractional noise when the sampling rate is low.
Multiscale limited penetrable horizontal visibility graph for analyzing nonlinear time series.
Gao, Zhong-Ke; Cai, Qing; Yang, Yu-Xuan; Dang, Wei-Dong; Zhang, Shan-Shan
2016-10-19
Visibility graph has established itself as a powerful tool for analyzing time series. We in this paper develop a novel multiscale limited penetrable horizontal visibility graph (MLPHVG). We use nonlinear time series from two typical complex systems, i.e., EEG signals and two-phase flow signals, to demonstrate the effectiveness of our method. Combining MLPHVG and support vector machine, we detect epileptic seizures from the EEG signals recorded from healthy subjects and epilepsy patients and the classification accuracy is 100%. In addition, we derive MLPHVGs from oil-water two-phase flow signals and find that the average clustering coefficient at different scales allows faithfully identifying and characterizing three typical oil-water flow patterns. These findings render our MLPHVG method particularly useful for analyzing nonlinear time series from the perspective of multiscale network analysis.
Adaptive time splitting method for multi-scale evolutionary partial differential equations
Descombes, Stéphane; Dumont, Thierry; Louvet, Violaine; Massot, Marc
2011-01-01
This paper introduces an adaptive time splitting technique for the solution of stiff evolutionary PDEs that guarantees an effective error control of the simulation, independent of the fastest physical time scale for highly unsteady problems. The strategy considers a second order Strang method and another lower order embedded splitting scheme that takes into account potential loss of order due to the stiffness featured by time-space multi-scale phenomena. The scheme is then built upon a precise numerical analysis of the method and a complementary numerical procedure, conceived to overcome classical restrictions of adaptive time stepping schemes based on lower order embedded methods, whenever asymptotic estimates fail to predict the dynamics of the problem. The performance of the method in terms of control of integration errors is evaluated by numerical simulations of stiff propagating waves coming from nonlinear chemical dynamics models as well as highly multi-scale nanosecond repetitively pulsed gas discharge...
Rolling Element Bearing Fault Diagnosis Based on Multiscale General Fractal Features
Directory of Open Access Journals (Sweden)
Weigang Wen
2015-01-01
Full Text Available Nonlinear characteristics are ubiquitous in the vibration signals produced by rolling element bearings. Fractal dimensions are effective tools to illustrate nonlinearity. This paper proposes a new approach based on Multiscale General Fractal Dimensions (MGFDs to realize fault diagnosis of rolling element bearings, which are robust to the effects of variation in operating conditions. The vibration signals of bearing are analyzed to extract the general fractal dimensions in multiscales, which are in turn utilized to construct a feature space to identify fault pattern. Finally, bearing faults are revealed by pattern recognition. Case studies are carried out to evaluate the validity and accuracy of the approach. It is verified that this approach is effective for fault diagnosis of rolling element bearings under various operating conditions via experiment and data analysis.
Adaptive multi-scale parameterization for one-dimensional flow in unsaturated porous media
Hayek, Mohamed; Lehmann, François; Ackerer, Philippe
2008-01-01
In the analysis of the unsaturated zone, one of the most challenging problems is to use inverse theory in the search for an optimal parameterization of the porous media. Adaptative multi-scale parameterization consists in solving the problem through successive approximations by refining the parameter at the next finer scale all over the domain and stopping the process when the refinement does not induce significant decrease of the objective function any more. In this context, the refinement indicators algorithm provides an adaptive parameterization technique that opens the degrees of freedom in an iterative way driven at first order by the model to locate the discontinuities of the sought parameters. We present a refinement indicators algorithm for adaptive multi-scale parameterization that is applicable to the estimation of multi-dimensional hydraulic parameters in unsaturated soil water flow. Numerical examples are presented which show the efficiency of the algorithm in case of noisy data and missing data.
Time-parallel multiscale/multiphysics framework
Energy Technology Data Exchange (ETDEWEB)
Frantziskonis, G. [University of Arizona; Muralidharan, Krishna [University of Arizona; Deymier, Pierre [University of Arizona; Simunovic, Srdjan [ORNL; Nukala, Phani K [ORNL; Pannala, Sreekanth [ORNL
2009-01-01
We introduce the time-parallel compound wavelet matrix method (tpCWM) for modeling the temporal evolution of multiscale and multiphysics systems. The method couples time parallel (TP) and CWM methods operating at different spatial and temporal scales. We demonstrate the efficiency of our approach on two examples: a chemical reaction kinetic system and a non-linear predator prey system. Our results indicate that the tpCWM technique is capable of accelerating time-to-solution by 2 3-orders of magnitude and is amenable to efficient parallel implementation.
Multi-scale Regions from Edge Fragments
DEFF Research Database (Denmark)
Kazmi, Wajahat; Andersen, Hans Jørgen
2014-01-01
In this article we introduce a novel method for detecting multi-scale salient regions around edges using a graph based image compression algorithm. Images are recursively decomposed into triangles arranged into a binary tree using linear interpolation. The entropy of any local region of the image...... is inherent in the areas of the triangles and tree depth. We introduce twin leaves as nodes whose sibling share the same characteristics. Triangles corresponding to the twin leaves are filtered out from the binary tree. Graph connectivity is exploited to get clusters of triangles followed by ellipse fitting...
Structure and multiscale mechanics of carbon nanomaterials
2016-01-01
This book aims at providing a broad overview on the relationship between structure and mechanical properties of carbon nanomaterials from world-leading scientists in the field. The main aim is to get an in-depth understanding of the broad range of mechanical properties of carbon materials based on their unique nanostructure and on defects of several types and at different length scales. Besides experimental work mainly based on the use of (in-situ) Raman and X-ray scattering and on nanoindentation, the book also covers some aspects of multiscale modeling of the mechanics of carbon nanomaterials.
Multi-Scale Modeling of an Integrated 3D Braided Composite with Applications to Helicopter Arm
Zhang, Diantang; Chen, Li; Sun, Ying; Zhang, Yifan; Qian, Kun
2017-01-01
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.
Multiscale measurement error models for aggregated small area health data.
Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin
2016-08-01
Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates.
Identify Precipitation Pattern Using Multi-scale Sample Entropy
Liang, X.; Zhou, X.; Lin, J. S.; Xu, W.
2015-12-01
In an effort to seek new perspectives on identifying precipitation patterns associated with the precipitation time series, this study explored the potential use of the information metrics through Multi-scale Sample Entropy (MSE) analysis. The objectives were to develop MSE analysis in investigating if discernable changes in long term patterns could be identified when the information metrics in the data were studied in terms of how they change with scales. Scales, in the present context, are the intervals of days that sample entropy (SE) is sampled within a time series. For this study we looked into the characteristics of precipitation before and after 1980 for the regions upstream of Yangtze River in southwestern China, based on the daily rain-gauge data collected from 70 gauges since 1951. The results suggest three main patterns of SE with scale, they are: significant decrease, relatively flat and significant increase. These three patterns correspond, respectively, to the downstream, midstream and upstream of the upper Yangtze River region. By the nature of entropy, a significant decrease in SE implies more regularity with scale, which could mean a longer continuous drought or a more evenly distributed continuous precipitation. In this case, our analysis shows that it is attributed to the longer continuous drought. For the case of significant SE increase, it was found to be tied to an increase in the rain frequency. These results appear to show that the MSE analysis could indeed be useful for long term precipitation study.
Multi-scale biomedical systems: measurement challenges
Summers, R.
2016-11-01
Multi-scale biomedical systems are those that represent interactions in materials, sensors, and systems from a holistic perspective. It is possible to view such multi-scale activity using measurement of spatial scale or time scale, though in this paper only the former is considered. The biomedical application paradigm comprises interactions that range from quantum biological phenomena at scales of 10-12 for one individual to epidemiological studies of disease spread in populations that in a pandemic lead to measurement at a scale of 10+7. It is clear that there are measurement challenges at either end of this spatial scale, but those challenges that relate to the use of new technologies that deal with big data and health service delivery at the point of care are also considered. The measurement challenges lead to the use, in many cases, of model-based measurement and the adoption of virtual engineering. It is these measurement challenges that will be uncovered in this paper.
Multiscale structure in eco-evolutionary dynamics
Stacey, Blake C.
In a complex system, the individual components are neither so tightly coupled or correlated that they can all be treated as a single unit, nor so uncorrelated that they can be approximated as independent entities. Instead, patterns of interdependency lead to structure at multiple scales of organization. Evolution excels at producing such complex structures. In turn, the existence of these complex interrelationships within a biological system affects the evolutionary dynamics of that system. I present a mathematical formalism for multiscale structure, grounded in information theory, which makes these intuitions quantitative, and I show how dynamics defined in terms of population genetics or evolutionary game theory can lead to multiscale organization. For complex systems, "more is different," and I address this from several perspectives. Spatial host--consumer models demonstrate the importance of the structures which can arise due to dynamical pattern formation. Evolutionary game theory reveals the novel effects which can result from multiplayer games, nonlinear payoffs and ecological stochasticity. Replicator dynamics in an environment with mesoscale structure relates to generalized conditionalization rules in probability theory. The idea of natural selection "acting at multiple levels" has been mathematized in a variety of ways, not all of which are equivalent. We will face down the confusion, using the experience developed over the course of this thesis to clarify the situation.
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.
Bayesian Integration of multiscale environmental data
Energy Technology Data Exchange (ETDEWEB)
2016-08-22
The software is designed for efficiently integrating large-size of multi-scale environmental data using the Bayesian framework. Suppose we need to estimate the spatial distribution of variable X with high spatial resolution. The available data include (1) direct measurements Z of the unknowns with high resolution in a subset of the spatial domain (small spatial coverage), (2) measurements C of the unknowns at the median scale, and (3) measurements A of the unknowns at the coarsest scale but with large spatial coverage. The goal is to estimate the unknowns at the fine grids by conditioning to all the available data. We first consider all the unknowns as random variables and estimate conditional probability distribution of those variables by conditioning to the limited high-resolution observations (Z). We then treat the estimated probability distribution as the prior distribution. Within the Bayesian framework, we combine the median and large-scale measurements (C and A) through likelihood functions. Since we assume that all the relevant multivariate distributions are Gaussian, the resulting posterior distribution is a multivariate Gaussian distribution. The developed software provides numerical solutions of the posterior probability distribution. The software can be extended in several different ways to solve more general multi-scale data integration problems.
Concurrent multiscale modeling of amorphous materials
Tan, Vincent
2013-03-01
An approach to multiscale modeling of amorphous materials is presented whereby atomistic scale domains coexist with continuum-like domains. The atomistic domains faithfully predict severe deformation while the continuum domains allow the computation to scale up the size of the model without incurring excessive computational costs associated with fully atomistic models and without the introduction of spurious forces across the boundary of atomistic and continuum-like domains. The material domain is firstly constructed as a tessellation of Amorphous Cells (AC). For regions of small deformation, the number of degrees of freedom is then reduced by computing the displacements of only the vertices of the ACs instead of the atoms within. This is achieved by determining, a priori, the atomistic displacements within such Pseudo Amorphous Cells associated with orthogonal deformation modes of the cell. Simulations of nanoscale polymer tribology using full molecular mechanics computation and our multiscale approach give almost identical prediction of indentation force and the strain contours of the polymer. We further demonstrate the capability of performing adaptive simulations during which domains that were discretized into cells revert to full atomistic domains when their strain attain a predetermined threshold. The authors would like to acknowledge the financial support given to this study by the Agency of Science, Technology and Research (ASTAR), Singapore (SERC Grant No. 092 137 0013).
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.
Residual-driven online generalized multiscale finite element methods
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.
Generalization Performance of Regularized Ranking With Multiscale Kernels.
Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin
2016-05-01
The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.
Manrique-Saide, P; Coleman, P; McCall, P J; Lenhart, A; Vázquez-Prokopec, G; Davies, C R
2014-09-01
Despite decades of research, there is still no agreement on which indices of Aedes aegypti (Stegomyia aegypti) (Diptera: Culicidae) presence and abundance better quantify entomological risk for dengue. This study reports the results of a multi-scale, cross-sectional entomological survey carried out in 1160 households in the city of Merida, Mexico to establish: (a) the correlation between levels of Ae. aegypti presence and abundance detected with aspirators and ovitraps; (b) which immature and egg indices correlate with the presence and abundance of Ae. aegypti females, and (c) the correlations amongst traditional Aedes indices and their modifications for pupae at the household level and within medium-sized geographic areas used for vector surveillance. Our analyses show that ovitrap positivity was significantly associated with indoor adult Ae. aegypti presence [odds ratio (OR) = 1.50; P = 0.03], that the presence of pupae is associated with adult presence at the household level (OR = 2.27; P = 0.001), that classic Aedes indices are informative only when they account for pupae, and that window screens provide a significant level of protection against peridomestic Ae. aegypti (OR = 0.59; P = 0.02). Results reinforce the potential of using both positive collections in outdoor ovitraps and the presence of pupae as sensitive indicators of indoor adult female presence.
Developing a multiscale, multi-resolution agent-based brain tumor model by graphics processing units
Directory of Open Access Journals (Sweden)
Zhang Le
2011-12-01
Full Text Available Abstract Multiscale agent-based modeling (MABM has been widely used to simulate Glioblastoma Multiforme (GBM and its progression. At the intracellular level, the MABM approach employs a system of ordinary differential equations to describe quantitatively specific intracellular molecular pathways that determine phenotypic switches among cells (e.g. from migration to proliferation and vice versa. At the intercellular level, MABM describes cell-cell interactions by a discrete module. At the tissue level, partial differential equations are employed to model the diffusion of chemoattractants, which are the input factors of the intracellular molecular pathway. Moreover, multiscale analysis makes it possible to explore the molecules that play important roles in determining the cellular phenotypic switches that in turn drive the whole GBM expansion. However, owing to limited computational resources, MABM is currently a theoretical biological model that uses relatively coarse grids to simulate a few cancer cells in a small slice of brain cancer tissue. In order to improve this theoretical model to simulate and predict actual GBM cancer progression in real time, a graphics processing unit (GPU-based parallel computing algorithm was developed and combined with the multi-resolution design to speed up the MABM. The simulated results demonstrated that the GPU-based, multi-resolution and multiscale approach can accelerate the previous MABM around 30-fold with relatively fine grids in a large extracellular matrix. Therefore, the new model has great potential for simulating and predicting real-time GBM progression, if real experimental data are incorporated.
Prasath, V B Surya; Vorotnikov, Dmitry; Pelapur, Rengarajan; Jose, Shani; Seetharaman, Guna; Palaniappan, Kannappan
2015-12-01
Edge preserving regularization using partial differential equation (PDE)-based methods although extensively studied and widely used for image restoration, still have limitations in adapting to local structures. We propose a spatially adaptive multiscale variable exponent-based anisotropic variational PDE method that overcomes current shortcomings, such as over smoothing and staircasing artifacts, while still retaining and enhancing edge structures across scale. Our innovative model automatically balances between Tikhonov and total variation (TV) regularization effects using scene content information by incorporating a spatially varying edge coherence exponent map constructed using the eigenvalues of the filtered structure tensor. The multiscale exponent model we develop leads to a novel restoration method that preserves edges better and provides selective denoising without generating artifacts for both additive and multiplicative noise models. Mathematical analysis of our proposed method in variable exponent space establishes the existence of a minimizer and its properties. The discretization method we use satisfies the maximum-minimum principle which guarantees that artificial edge regions are not created. Extensive experimental results using synthetic, and natural images indicate that the proposed multiscale Tikhonov-TV (MTTV) and dynamical MTTV methods perform better than many contemporary denoising algorithms in terms of several metrics, including signal-to-noise ratio improvement and structure preservation. Promising extensions to handle multiplicative noise models and multichannel imagery are also discussed.
Improvement and Extension of Shape Evaluation Criteria in Multi-Scale Image Segmentation
Sakamoto, M.; Honda, Y.; Kondo, A.
2016-06-01
From the last decade, the multi-scale image segmentation is getting a particular interest and practically being used for object-based image analysis. In this study, we have addressed the issues on multi-scale image segmentation, especially, in improving the performances for validity of merging and variety of derived region's shape. Firstly, we have introduced constraints on the application of spectral criterion which could suppress excessive merging between dissimilar regions. Secondly, we have extended the evaluation for smoothness criterion by modifying the definition on the extent of the object, which was brought for controlling the shape's diversity. Thirdly, we have developed new shape criterion called aspect ratio. This criterion helps to improve the reproducibility on the shape of object to be matched to the actual objectives of interest. This criterion provides constraint on the aspect ratio in the bounding box of object by keeping properties controlled with conventional shape criteria. These improvements and extensions lead to more accurate, flexible, and diverse segmentation results according to the shape characteristics of the target of interest. Furthermore, we also investigated a technique for quantitative and automatic parameterization in multi-scale image segmentation. This approach is achieved by comparing segmentation result with training area specified in advance by considering the maximization of the average area in derived objects or satisfying the evaluation index called F-measure. Thus, it has been possible to automate the parameterization that suited the objectives especially in the view point of shape's reproducibility.
Multiscale Enaction Model (MEM): the case of complexity and "context-sensitivity" in vision.
Laurent, Éric
2014-01-01
I review the data on human visual perception that reveal the critical role played by non-visual contextual factors influencing visual activity. The global perspective that progressively emerges reveals that vision is sensitive to multiple couplings with other systems whose nature and levels of abstraction in science are highly variable. Contrary to some views where vision is immersed in modular hard-wired modules, rather independent from higher-level or other non-cognitive processes, converging data gathered in this article suggest that visual perception can be theorized in the larger context of biological, physical, and social systems with which it is coupled, and through which it is enacted. Therefore, any attempt to model complexity and multiscale couplings, or to develop a complex synthesis in the fields of mind, brain, and behavior, shall involve a systematic empirical study of both connectedness between systems or subsystems, and the embodied, multiscale and flexible teleology of subsystems. The conceptual model (Multiscale Enaction Model [MEM]) that is introduced in this paper finally relates empirical evidence gathered from psychology to biocomputational data concerning the human brain. Both psychological and biocomputational descriptions of MEM are proposed in order to help fill in the gap between scales of scientific analysis and to provide an account for both the autopoiesis-driven search for information, and emerging perception.
Enveloped viruses understood via multiscale simulation: computer-aided vaccine design
Shreif, Z.; Adhangale, P.; Cheluvaraja, S.; Perera, R.; Kuhn, R.; Ortoleva, P.
Enveloped viruses are viewed as an opportunity to understand how highly organized and functional biosystems can emerge from a collection of millions of chaotically moving atoms. They are an intermediate level of complexity between macromolecules and bacteria. They are a natural system for testing theories of self-assembly and structural transitions, and for demonstrating the derivation of principles of microbiology from laws of molecular physics. As some constitute threats to human health, a computer-aided vaccine and drug design strategy that would follow from a quantitative model would be an important contribution. However, current molecular dynamics simulation approaches are not practical for modeling such systems. Our multiscale approach simultaneously accounts for the outer protein net and inner protein/genomic core, and their less structured membranous material and host fluid. It follows from a rigorous multiscale deductive analysis of laws of molecular physics. Two types of order parameters are introduced: (1) those for structures wherein constituent molecules retain long-lived connectivity (they specify the nanoscale structure as a deformation from a reference configuration) and (2) those for which there is no connectivity but organization is maintained on the average (they are field variables such as mass density or measures of preferred orientation). Rigorous multiscale techniques are used to derive equations for the order parameters dynamics. The equations account for thermal-average forces, diffusion coefficients, and effects of random forces. Statistical properties of the atomic-scale fluctuations and the order parameters are co-evolved. By combining rigorous multiscale techniques and modern supercomputing, systems of extreme complexity can be modeled.
Ricks, Trenton M.; Lacy, Thomas E., Jr.; Bednarcyk, Brett A.; Arnold, Steven M.; Hutchins, John W.
2014-01-01
A multiscale modeling methodology was developed for continuous fiber composites that incorporates a statistical distribution of fiber strengths into coupled multiscale micromechanics/finite element (FE) analyses. A modified two-parameter Weibull cumulative distribution function, which accounts for the effect of fiber length on the probability of failure, was used to characterize the statistical distribution of fiber strengths. A parametric study using the NASA Micromechanics Analysis Code with the Generalized Method of Cells (MAC/GMC) was performed to assess the effect of variable fiber strengths on local composite failure within a repeating unit cell (RUC) and subsequent global failure. The NASA code FEAMAC and the ABAQUS finite element solver were used to analyze the progressive failure of a unidirectional SCS-6/TIMETAL 21S metal matrix composite tensile dogbone specimen at 650 degC. Multiscale progressive failure analyses were performed to quantify the effect of spatially varying fiber strengths on the RUC-averaged and global stress-strain responses and failure. The ultimate composite strengths and distribution of failure locations (predominately within the gage section) reasonably matched the experimentally observed failure behavior. The predicted composite failure behavior suggests that use of macroscale models that exploit global geometric symmetries are inappropriate for cases where the actual distribution of local fiber strengths displays no such symmetries. This issue has not received much attention in the literature. Moreover, the model discretization at a specific length scale can have a profound effect on the computational costs associated with multiscale simulations.models that yield accurate yet tractable results.
Variational multiscale models for charge transport.
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
Simulation of Multiphysics Multiscale Systems, 5th International Workshop
Krzhizhanovskaya, V.V.; Hoekstra, A.G.
2008-01-01
Modeling and Simulation of Multiphysics Multiscale Systems (SMMS) poses a grand challenge to computational science. To adequately simulate numerous intertwined processes characterized by different spatial and temporal scales spanning many orders of magnitude, sophisticated models and advanced comput
Multiscale model reduction for shale gas transport in fractured media
Akkutlu, I Y; Vasilyeva, Maria
2015-01-01
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 \\cite{aes14}, 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. In this approach, the matrix and the fracture interaction is modeled via local multiscale basis functions. We developed the GMsFEM and applied for linear flows with horizontal or vertical fracture orientations on a Cartesian fine grid. In this paper, we consider arbitrary fracture orientations and use triangular fine grid and developed GMsFEM for nonlinear flows. Moreover, we develop online basis function strategies to adaptively improve the convergence. The number of multiscale basis functions in each coarse region ...
Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.
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.
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.
Simulation of Multiphysics Multiscale Systems, 7th International Workshop
Krzhizhanovskaya, V.
2010-01-01
Modeling and Simulation of Multiphysics Multiscale Systems (SMMS) poses a grand challenge to computational science. To adequately simulate numerous intertwined processes characterized by different spatial and temporal scales spanning many orders of magnitude, sophisticated models and advanced comput
Simulation of Multiphysics Multiscale Systems, 6th International Workshop
Krzhizhanovskaya, V.V.
2009-01-01
Modeling and Simulation of Multiphysics Multiscale Systems (SMMS) poses a grand challenge to computational science. To adequately simulate numerous intertwined processes characterized by different spatial and temporal scales spanning many orders of magnitude, sophisticated models and advanced comput
Point evaluation and Hardy space : the multiscale case.
Alpay, Daniel; Dijksma, Aad; Volok, Dan
2005-01-01
We define a point evaluation for transfer operators of multiscale causal dissipative systems. We associate to such a system a de Branges Rovnyak space, which serves as the state space of a coisometric realization.
A computational library for multiscale modeling of material failure
Talebi, Hossein; Silani, Mohammad; Bordas, Stéphane P. A.; Kerfriden, Pierre; Rabczuk, Timon
2014-05-01
We present an open-source software framework called PERMIX for multiscale modeling and simulation of fracture in solids. The framework is an object oriented open-source effort written primarily in Fortran 2003 standard with Fortran/C++ interfaces to a number of other libraries such as LAMMPS, ABAQUS, LS-DYNA and GMSH. Fracture on the continuum level is modeled by the extended finite element method (XFEM). Using several novel or state of the art methods, the piece software handles semi-concurrent multiscale methods as well as concurrent multiscale methods for fracture, coupling two continuum domains or atomistic domains to continuum domains, respectively. The efficiency of our open-source software is shown through several simulations including a 3D crack modeling in clay nanocomposites, a semi-concurrent FE-FE coupling, a 3D Arlequin multiscale example and an MD-XFEM coupling for dynamic crack propagation.
Multiscale simulation of molecular processes in cellular environments.
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'.
Multiscale simulation of molecular processes in cellular environments
Chiricotto, Mara; Sterpone, Fabio; Derreumaux, Philippe; Melchionna, Simone
2016-11-01
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'.
RFP for the Auroral Multiscale Midex (AMM) Mission star tracker
DEFF Research Database (Denmark)
Riis, Troels; Betto, Maurizio; Jørgensen, John Leif;
1999-01-01
This document is in response to the John Hopkins University - Applied Physics Laboratory RFP for the Auroral Multiscale Midex Mission star tracker.It describes the functionality, the requirements and the performance of the ASC Star Tracker.......This document is in response to the John Hopkins University - Applied Physics Laboratory RFP for the Auroral Multiscale Midex Mission star tracker.It describes the functionality, the requirements and the performance of the ASC Star Tracker....
On multi-scale representations of geographic features
Institute of Scientific and Technical Information of China (English)
WANG Yanhui; LI Xiaojuan; GONG Huili
2006-01-01
This paper contains a review of the development of research on multiple representations compiled from Geographic Information Systems (GIS), including data structure, formalization and storage, and intelligent zoom. A summary is also included of the problems of interconnectivity, consistency maintenance, dynamic query and coexisting updates, as well as a research review of multi-scale databases and related studies. Finally,research directions and foci are proposed for the future design and implementation of multi-scale GIS.
Discrete multiscale wavelet shrinkage and integrodifferential equations
Didas, S.; Steidl, G.; Weickert, J.
2008-04-01
We investigate the relation between discrete wavelet shrinkage and integrodifferential equations in the context of simplification and denoising of one-dimensional signals. In the continuous setting, strong connections between these two approaches were discovered in 6 (see references). The key observation is that the wavelet transform can be understood as derivative operator after the convolution with a smoothing kernel. In this paper, we extend these ideas to the practically relevant discrete setting with both orthogonal and biorthogonal wavelets. In the discrete case, the behaviour of the smoothing kernels for different scales requires additional investigation. The results of discrete multiscale wavelet shrinkage and related discrete versions of integrodifferential equations are compared with respect to their denoising quality by numerical experiments.
Multiscale Talbot effects in Fibonacci geometry
Ho, I-Lin
2014-01-01
This article investigates the Talbot effects in Fibonacci geometry by introducing the cut-and-project construction, which allows for capturing the entire infinite Fibonacci structure into a single computational cell. Theoretical and numerical calculations demonstrate the Talbot foci of Fibonacci geometry at distances that are multiples $(\\tau+2)(F_{\\mu}+\\tau F_{\\mu+1} )^{-1}p/(2q)$ or $(\\tau+2)(L_{\\mu}+\\tau L_{\\mu+1} )^{-1}p/(2q)$ of the Talbot distance. Here, ($p$, $q$) are coprime integers, $\\mu$ is an integer, $\\tau$ is the golden mean, and $F_{\\mu}$ and $L_{\\mu}$ are Fibonacci and Lucas numbers, respectively. The image of a single Talbot focus exhibits a multiscale pattern due to the self-similarity of the scaling Fourier spectrum.
Multi-scale Modelling of Segmentation
DEFF Research Database (Denmark)
Hartmann, Martin; Lartillot, Olivier; Toiviainen, Petri
2016-01-01
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...... of experimental task (i.e., real-time vs. annotated segmentation), nor of musicianship on boundary perception are clear. Our study assesses musicianship effects and differences between segmentation tasks. We conducted a real-time experiment to collect segmentations by musicians and nonmusicians from nine musical...... 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...
MUSIC: MUlti-Scale Initial Conditions
Hahn, Oliver; Abel, Tom
2013-11-01
MUSIC generates multi-scale initial conditions with multiple levels of refinements for cosmological ‘zoom-in’ simulations. The code uses an adaptive convolution of Gaussian white noise with a real-space transfer function kernel together with an adaptive multi-grid Poisson solver to generate displacements and velocities following first- (1LPT) or second-order Lagrangian perturbation theory (2LPT). MUSIC achieves rms relative errors of the order of 10-4 for displacements and velocities in the refinement region and thus improves in terms of errors by about two orders of magnitude over previous approaches. In addition, errors are localized at coarse-fine boundaries and do not suffer from Fourier space-induced interference ringing.
Nonlinear helicons bearing multi-scale structures
Abdelhamid, Hamdi M.; Yoshida, Zensho
2017-02-01
The helicon waves exhibit varying characters depending on plasma parameters, geometry, and wave numbers. Here, we elucidate an intrinsic multi-scale property embodied by the combination of the dispersive effect and nonlinearity. The extended magnetohydrodynamics model (exMHD) is capable of describing a wide range of parameter space. By using the underlying Hamiltonian structure of exMHD, we construct an exact nonlinear solution, which turns out to be a combination of two distinct modes, the helicon and Trivelpiece-Gould (TG) waves. In the regime of relatively low frequency or high density, however, the combination is made of the TG mode and an ion cyclotron wave (slow wave). The energy partition between these modes is determined by the helicities carried by the wave fields.
Multiscale simulation approach for battery production systems
Schönemann, Malte
2017-01-01
Addressing the challenge of improving battery quality while reducing high costs and environmental impacts of the production, this book presents a multiscale simulation approach for battery production systems along with a software environment and an application procedure. Battery systems are among the most important technologies of the 21st century since they are enablers for the market success of electric vehicles and stationary energy storage solutions. However, the performance of batteries so far has limited possible applications. Addressing this challenge requires an interdisciplinary understanding of dynamic cause-effect relationships between processes, equipment, materials, and environmental conditions. The approach in this book supports the integrated evaluation of improvement measures and is usable for different planning horizons. It is applied to an exemplary battery cell production and module assembly in order to demonstrate the effectiveness and potential benefits of the simulation.
Multiscale systems integration in the eye.
Jacobs, Marc D
2009-01-01
A series of research topics on the eye is reviewed with the aim of illustrating how integrative and systems-biological approaches can be used to understand complex properties and functions of ocular tissues. Emphasis is placed on the diversity of physiological systems represented in the eye, and the variety of approaches required to analyze those systems, both empirically and theoretically. Modeling and empirical studies reviewed focus mainly on problems that the eye presents, in the broad areas of biomechanics and fluid dynamics from the molecular to the whole-organ scale. Attention is given to the relevance of these studies in human disease and the current potential for development of medical therapies based upon a biophysical, integrative modeling approach. The creation of a multiscale hierarchy of numerical models of the eye is proposed as an important and unifying aim of integrative eye research.
Multi-scale Adaptive Computational Ghost Imaging
Sun, Shuai; Liu, Wei-Tao; Lin, Hui-Zu; Zhang, Er-Feng; Liu, Ji-Ying; Li, Quan; Chen, Ping-Xing
2016-11-01
In some cases of imaging, wide spatial range and high spatial resolution are both required, which requests high performance of detection devices and huge resource consumption for data processing. We propose and demonstrate a multi-scale adaptive imaging method based on the idea of computational ghost imaging, which can obtain a rough outline of the whole scene with a wide range then accordingly find out the interested parts and achieve high-resolution details of those parts, by controlling the field of view and the transverse coherence width of the pseudo-thermal field illuminated on the scene with a spatial light modulator. Compared to typical ghost imaging, the resource consumption can be dramatically reduced using our scheme.
Typograph: Multiscale Spatial Exploration of Text Documents
Energy Technology Data Exchange (ETDEWEB)
Endert, Alexander; Burtner, Edwin R.; Cramer, Nicholas O.; Perko, Ralph J.; Hampton, Shawn D.; Cook, Kristin A.
2013-12-01
Visualizing large document collections using a spatial layout of terms can enable quick overviews of information. However, these metaphors (e.g., word clouds, tag clouds, etc.) often lack interactivity to explore the information and the location and rendering of the terms are often not based on mathematical models that maintain relative distances from other information based on similarity metrics. Further, transitioning between levels of detail (i.e., from terms to full documents) can be challanging. In this paper, we present Typograph, a multi-scale spatial exploration visualization for large document collections. Based on the term-based visualization methods, Typograh enables multipel levels of detail (terms, phrases, snippets, and full documents) within the single spatialization. Further, the information is placed based on their relative similarity to other information to create the “near = similar” geography metaphor. This paper discusses the design principles and functionality of Typograph and presents a use case analyzing Wikipedia to demonstrate usage.
Ghaffari Motlagh, Yousef
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.
Dynamic Multiscale Averaging (DMA) of Turbulent Flow
Energy Technology Data Exchange (ETDEWEB)
Richard W. Johnson
2012-09-01
A new approach called dynamic multiscale averaging (DMA) for computing the effects of turbulent flow is described. The new method encompasses multiple applications of temporal and spatial averaging, that is, multiscale operations. Initially, a direct numerical simulation (DNS) is performed for a relatively short time; it is envisioned that this short time should be long enough to capture several fluctuating time periods of the smallest scales. The flow field variables are subject to running time averaging during the DNS. After the relatively short time, the time-averaged variables are volume averaged onto a coarser grid. Both time and volume averaging of the describing equations generate correlations in the averaged equations. These correlations are computed from the flow field and added as source terms to the computation on the next coarser mesh. They represent coupling between the two adjacent scales. Since they are computed directly from first principles, there is no modeling involved. However, there is approximation involved in the coupling correlations as the flow field has been computed for only a relatively short time. After the time and spatial averaging operations are applied at a given stage, new computations are performed on the next coarser mesh using a larger time step. The process continues until the coarsest scale needed is reached. New correlations are created for each averaging procedure. The number of averaging operations needed is expected to be problem dependent. The new DMA approach is applied to a relatively low Reynolds number flow in a square duct segment. Time-averaged stream-wise velocity and vorticity contours from the DMA approach appear to be very similar to a full DNS for a similar flow reported in the literature. Expected symmetry for the final results is produced for the DMA method. The results obtained indicate that DMA holds significant potential in being able to accurately compute turbulent flow without modeling for practical
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
Parallel multiscale simulations of a brain aneurysm.
Grinberg, Leopold; Fedosov, Dmitry A; Karniadakis, George Em
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 multi-scale 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 εκαr . 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 ( εκαr 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 300K computer processors. Validation of such coupled atomistic-continuum models is a main open issue that has to be addressed in future
Integrating Multiscale Modeling with Drug Effects for Cancer Treatment.
Li, Xiangfang L; Oduola, Wasiu O; Qian, Lijun; Dougherty, Edward R
2015-01-01
In this paper, we review multiscale modeling for cancer treatment with the incorporation of drug effects from an applied system's pharmacology perspective. Both the classical pharmacology and systems biology are inherently quantitative; however, systems biology focuses more on networks and multi factorial controls over biological processes rather than on drugs and targets in isolation, whereas systems pharmacology has a strong focus on studying drugs with regard to the pharmacokinetic (PK) and pharmacodynamic (PD) relations accompanying drug interactions with multiscale physiology as well as the prediction of dosage-exposure responses and economic potentials of drugs. Thus, it requires multiscale methods to address the need for integrating models from the molecular levels to the cellular, tissue, and organism levels. It is a common belief that tumorigenesis and tumor growth can be best understood and tackled by employing and integrating a multifaceted approach that includes in vivo and in vitro experiments, in silico models, multiscale tumor modeling, continuous/discrete modeling, agent-based modeling, and multiscale modeling with PK/PD drug effect inputs. We provide an example application of multiscale modeling employing stochastic hybrid system for a colon cancer cell line HCT-116 with the application of Lapatinib drug. It is observed that the simulation results are similar to those observed from the setup of the wet-lab experiments at the Translational Genomics Research Institute.
Reduced-Contrast Approximations for High-Contrast Multiscale Flow Problems
Chung, Eric T.
2010-01-01
contrast can be represented by piecewise constant functions with disparate values). We present analysis for the proposed approaches and the estimates for the approximations used in multiscale algorithms. Numerical examples are presented. © 2010 Society for Industrial and Applied Mathematics.
Multi-scale observation and cross-scale mechanistic modeling on terrestrial ecosystem carbon cycle
Institute of Scientific and Technical Information of China (English)
CAO; Mingkui; YU; Guirui; LIU; Jiyuan; LI; Kerang
2005-01-01
To predict global climate change and to implement the Kyoto Protocol for stabilizing atmospheric greenhouse gases concentrations require quantifying spatio-temporal variations in the terrestrial carbon sink accurately. During the past decade multi-scale ecological experiment and observation networks have been established using various new technologies (e.g. controlled environmental facilities, eddy covariance techniques and quantitative remote sensing), and have obtained a large amount of data about terrestrial ecosystem carbon cycle. However, uncertainties in the magnitude and spatio-temporal variations of the terrestrial carbon sink and in understanding the underlying mechanisms have not been reduced significantly. One of the major reasons is that the observations and experiments were conducted at individual scales independently, but it is the interactions of factors and processes at different scales that determine the dynamics of the terrestrial carbon sink. Since experiments and observations are always conducted at specific scales, to understand cross-scale interactions requires mechanistic analysis that is best to be achieved by mechanistic modeling. However, mechanistic ecosystem models are mainly based on data from single-scale experiments and observations and hence have no capacity to simulate mechanistic cross-scale interconnection and interactions of ecosystem processes. New-generation mechanistic ecosystem models based on new ecological theoretical framework are needed to quantify the mechanisms from micro-level fast eco-physiological responses to macro-level slow acclimation in the pattern and structure in disturbed ecosystems. Multi-scale data-model fusion is a recently emerging approach to assimilate multi-scale observational data into mechanistic, dynamic modeling, in which the structure and parameters of mechanistic models for simulating cross-scale interactions are optimized using multi-scale observational data. The models are validated and
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
Multiscale Seismic Inversion in the Data and Image Domains
Zhang, Sanzong
2015-12-01
I present a general methodology for inverting seismic data in either the data or image domains. It partially overcomes one of the most serious problems with current waveform inversion methods, which is the tendency to converge to models far from the actual one. The key idea is to develop a multiscale misfit function that is composed of both a simplified version of the data and one associated with the complex part of the data. Misfit functions based on simple data are characterized by many fewer local minima so that a gradient optimization method can make quick progress in getting to the general vicinity of the actual model. Once we are near the actual model, we then use the gradient based on the more complex data. Below, we describe two implementations of this multiscale strategy: wave equation traveltime inversion in the data domain and generalized differential semblance optimization in the image domain. • Wave Equation Traveltime Inversion in the Data Domain (WT): The main difficulty with iterative waveform inversion is that it tends to get stuck in local minima associated with the waveform misfit function. To mitigate this problem and avoid the need to fit amplitudes in the data, we present a waveequation method that inverts the traveltimes of reflection events, and so is less prone to the local minima problem. Instead of a waveform misfit function, the penalty function is a crosscorrelation of the downgoing direct wave and the upgoing reflection wave at the trial image point. The time lag which maximizes the crosscorrelation amplitude represents the reflection-traveltime residual that is back-projected along the reflection wavepath to update the velocity. Shot- and angle-domain crosscorrelation functions are introduced to estimate the reflection-traveltime residual by semblance analysis and scanning. In theory, only the traveltime information is inverted and there is no need to precisely fit the amplitudes or assume a high-frequency approximation. Results
Systematic multiscale models for deep convection on mesoscales
Energy Technology Data Exchange (ETDEWEB)
Klein, Rupert [Freie Universitaet Berlin and Potsdam Institute for Climate Impact Research, FB Mathematik and Informatik, Berlin (Germany); Majda, Andrew J. [New York University, Courant Institute of Mathematical Sciences, New York, NY (United States)
2006-11-15
This paper builds on recent developments of a unified asymptotic approach to meteorological modeling [ZAMM, 80: 765-777, 2000, SIAM Proc. App. Math. 116, 227-289, 2004], which was used successfully in the development of Systematic multiscale models for the tropics in Majda and Klein [J. Atmosph. Sci. 60: 393-408, 2003] and Majda and Biello [PNAS, 101: 4736-4741, 2004]. Biello and Majda [J. Atmosph. Sci. 62: 1694-1720, 2005]. Here we account for typical bulk microphysics parameterizations of moist processes within this framework. The key steps are careful nondimensionalization of the bulk microphysics equations and the choice of appropriate distinguished limits for the various nondimensional small parameters that appear. We are then in a position to study scale interactions in the atmosphere involving moist physics. We demonstrate this by developing two systematic multiscale models that are motivated by our interest in mesoscale organized convection. The emphasis here is on multiple length scales but common time scales. The first of these models describes the short-time evolution of slender, deep convective hot towers with horizontal scale {proportional_to}1 km interacting with the linearized momentum balance on length and time scales of (10 km/3 min). We expect this model to describe how convective inhibition may be overcome near the surface, how the onset of deep convection triggers convective-scale gravity waves, and that it will also yield new insight into how such local convective events may conspire to create larger-scale strong storms. The second model addresses the next larger range of length and time scales (10 km, 100 km, and 20 min) and exhibits mathematical features that are strongly reminiscent of mesoscale organized convection. In both cases, the asymptotic analysis reveals how the stiffness of condensation/evaporation processes induces highly nonlinear dynamics. Besides providing new theoretical insights, the derived models may also serve as a
Institute of Scientific and Technical Information of China (English)
李虹; 王惠南; 章哓国
2008-01-01
提出基于二进小波变换的血管内超声图像血液斑点噪声抑制和对比度增强算法.血液红细胞散射引起的斑点噪声属于乘性噪声,在对数域进行二进小波变换后,结合软阈值滤波法和硬阈值滤波法对不同尺度的小波系数进行萎缩处理,并提出了一种局部阈值估计方法.同时采用了基于多尺度边缘表示的,利用小波系数极值拉伸和Hermite多项式插值实现的快速增强算法.实验结果表明,与现有单独进行去噪处理的方法相比,该方法在抑制血液斑点噪声的同时增强了图像对比度,具有更好的实用性.%An algorithm based on dyadic wavelet transform for speckle reduction and contrast enhancement in intravascular ultrasound images was presented. Wavelet shrinkage techniques which combined soft and hard thresholding were applied to coefficients of logarithmically transformed images since scattering from red blood cells (blood speckle noise) was multiplicative noise and a method to estimate local threshold was proposed. In addition, a fast contrast enhancement algorithm based on multi-scale edges representation of images through stretching the local extrema and interpolating them with Hermite interpolation polynomials was carried out. Experiments with clinical images showed that this algorithm was capable of not only reducing the speckle noise of blood but also enhancing features of diagnostic importance of intravascular ultrasound images and produced superior results qualitatively when compared to results obtained from existing denoising methods alone.
Integrated and multiscale NDT for the study of architectural heritage
Nuzzo, Luigia; Masini, Nicola; Rizzo, Enzo; Lasaponara, Rosa
2008-10-01
The restoration of artistic and architectural heritage represents a bench mark of the cultural development of a society. To this end it is necessary to develop a suitable methodology for the analysis of the material and building components which are usually brittle and in a poor state of conservation. The paper outlines the advantages and the drawbacks in the use of Non-Destructive Testing (NDT) techniques and the need to integrate them in order to obtain a reliable reconstruction of the internal characteristics of the building elements as well as the detection of defects. In the study case we used Ground Penetrating Radar (GPR), infrared thermography (IRT), sonic and ultrasonic tests to analyze a 13th century precious rose window in Southern Italy, affected by widespread decay and instability problems. The theoretical capabilities and limitations of NDT are strictly related to the frequency content of the signals used by the different techniques. Therefore, integrating several physical methods and using different frequency bands allowed as a comprehensive, multi-scale approach to the restoration problem. This revealed to be a proper strategy in order to get high-resolution information on the building characteristics and the state of decay which could support a careful structural restoration.
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.
Multi-scale investigation of shrub encroachment in southern Africa
Aplin, Paul; Marston, Christopher; Wilkinson, David; Field, Richard; O'Regan, Hannah
2016-04-01
There is growing speculation that savannah environments throughout Africa have been subject to shrub encroachment in recent years, whereby grassland is lost to woody vegetation cover. Changes in the relative proportions of grassland and woodland are important in the context of conservation of savannah systems, with implications for faunal distributions, environmental management and tourism. Here, we focus on southern Kruger National Park, South Africa, and investigate whether or not shrub encroachment has occurred over the last decade and a half. We use a multi-scale approach, examining the complementarity of medium (e.g. Landsat TM and OLI) and fine (e.g. QuickBird and WorldView-2) spatial resolution satellite sensor imagery, supported by intensive field survey in 2002 and 2014. We employ semi-automated land cover classification, involving a hybrid unsupervised clustering approach with manual class grouping and checking, followed by change detection post-classification comparison analysis. The results show that shrub encroachment is indeed occurring, a finding evidenced through three fine resolution replicate images plus medium resolution imagery. The results also demonstrate the complementarity of medium and fine resolution imagery, though some thematic information must be sacrificed to maintain high medium resolution classification accuracy. Finally, the findings have broader implications for issues such as vegetation seasonality, spatial transferability and management practices.
Spectral characteristics of background error covariance and multiscale data assimilation
Energy Technology Data Exchange (ETDEWEB)
Li, Zhijin [Jet Propulsion Laboratory, California Institute of Technology, Pasadena California USA; Cheng, Xiaoping [The Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles California USA; Gustafson Jr., William I. [Pacific Northwest National Laboratory, Richland Washington USA; Vogelmann, Andrew M. [Brookhaven National Laboratory, Upton New York USA
2016-05-17
The spatial resolutions of numerical atmospheric and oceanic circulation models have steadily increased over the past decades. Horizontal grid spacing down to the order of 1 km is now often used to resolve cloud systems in the atmosphere and sub-mesoscale circulation systems in the ocean. These fine resolution models encompass a wide range of temporal and spatial scales, across which dynamical and statistical properties vary. In particular, dynamic flow systems for small scales can become spatially localized and temporarily intermittent. An analysis shows that the background correlation length scale is larger than 75 km for streamfunctions, even for a 2-km resolution model, and larger than 25 km for water vapor mixing ratios. The theoretical analyses suggest that such correlation length scales prevent the currently used data assimilation schemes from constraining spatial scales smaller than 150 km for streamfunctions and 50 km for water vapor mixing ratios. These results highlight the necessity of fundamentally modifying the currently used data assimilation algorithm for assimilating high-resolution observations into the aforementioned fine resolution models. A multiscale methodology based on scale decomposition is suggested, and challenges are discussed.
Multiscale adaptive basis function modeling of spatiotemporal vectorcardiogram signals.
Gang Liu; Hui Yang
2013-03-01
Mathematical modeling of cardiac electrical signals facilitates the simulation of realistic cardiac electrical behaviors, the evaluation of algorithms, and the characterization of underlying space-time patterns. However, there are practical issues pertinent to model efficacy, robustness, and generality. This paper presents a multiscale adaptive basis function modeling approach to characterize not only temporal but also spatial behaviors of vectorcardiogram (VCG) signals. Model parameters are adaptively estimated by the "best matching" projections of VCG characteristic waves onto a dictionary of nonlinear basis functions. The model performance is experimentally evaluated with respect to the number of basis functions, different types of basis function (i.e., Gaussian, Mexican hat, customized wavelet, and Hermitian wavelets), and various cardiac conditions, including 80 healthy controls and different myocardial infarctions (i.e., 89 inferior, 77 anterior-septal, 56 inferior-lateral, 47 anterior, and 43 anterior-lateral). Multiway analysis of variance shows that the basis function and the model complexity have significant effects on model performances while cardiac conditions are not significant. The customized wavelet is found to be an optimal basis function for the modeling of spacetime VCG signals. The comparison of QT intervals shows small relative errors (model representations and realworld VCG signals when the model complexity is greater than 10. The proposed model shows great potentials to model space-time cardiac pathological behaviors and can lead to potential benefits in feature extraction, data compression, algorithm evaluation, and disease prognostics.
Multiscale modeling of the trihexyltetradecylphosphonium chloride ionic liquid.
Wang, Yong-Lei; Sarman, Sten; Li, Bin; Laaksonen, Aatto
2015-09-14
A multiscale modeling protocol was sketched for the trihexyltetradecylphosphonium chloride ([P6,6,6,14]Cl) ionic liquid (IL). The optimized molecular geometries of an isolated [P6,6,6,14] cation and a tightly bound [P6,6,6,14]Cl ion pair structure were obtained from quantum chemistry ab initio calculations. A cost-effective united-atom model was proposed for the [P6,6,6,14] cation based on the corresponding atomistic model. Atomistic and coarse-grained molecular dynamics simulations were performed over a wide temperature range to validate the proposed united-atom [P6,6,6,14] model against the available experimental data. Through a systemic analysis of volumetric quantities, microscopic structures, and transport properties of the bulk [P6,6,6,14]Cl IL under varied thermodynamic conditions, it was identified that the proposed united-atom [P6,6,6,14] cationic model could essentially capture the local intermolecular structures and the nonlocal experimental thermodynamics, including liquid density, volume expansivity and isothermal compressibility, and transport properties, such as zero-shear viscosity, of the bulk [P6,6,6,14]Cl IL within a wide temperature range.
Module-based multiscale simulation of angiogenesis in skeletal muscle
Directory of Open Access Journals (Sweden)
Mac Gabhann Feilim
2011-04-01
Full Text Available Abstract Background Mathematical modeling of angiogenesis has been gaining momentum as a means to shed new light on the biological complexity underlying blood vessel growth. A variety of computational models have been developed, each focusing on different aspects of the angiogenesis process and occurring at different biological scales, ranging from the molecular to the tissue levels. Integration of models at different scales is a challenging and currently unsolved problem. Results We present an object-oriented module-based computational integration strategy to build a multiscale model of angiogenesis that links currently available models. As an example case, we use this approach to integrate modules representing microvascular blood flow, oxygen transport, vascular endothelial growth factor transport and endothelial cell behavior (sensing, migration and proliferation. Modeling methodologies in these modules include algebraic equations, partial differential equations and agent-based models with complex logical rules. We apply this integrated model to simulate exercise-induced angiogenesis in skeletal muscle. The simulation results compare capillary growth patterns between different exercise conditions for a single bout of exercise. Results demonstrate how the computational infrastructure can effectively integrate multiple modules by coordinating their connectivity and data exchange. Model parameterization offers simulation flexibility and a platform for performing sensitivity analysis. Conclusions This systems biology strategy can be applied to larger scale integration of computational models of angiogenesis in skeletal muscle, or other complex processes in other tissues under physiological and pathological conditions.
A multiscale model for red blood cell mechanics.
Hartmann, Dirk
2010-02-01
The objective of this article is the derivation of a continuum model for mechanics of red blood cells via multiscale analysis. On the microscopic level, we consider realistic discrete models in terms of energy functionals defined on networks/lattices. Using concepts of Gamma-convergence, convergence results as well as explicit homogenisation formulae are derived. Based on a characterisation via energy functionals, appropriate macroscopic stress-strain relationships (constitutive equations) can be determined. Further, mechanical moduli of the derived macroscopic continuum model are directly related to microscopic moduli. As a test case we consider optical tweezers experiments, one of the most common experiments to study mechanical properties of cells. Our simulations of the derived continuum model are based on finite element methods and account explicitly for membrane mechanics and its coupling with bulk mechanics. Since the discretisation of the continuum model can be chosen freely, rather than it is given by the topology of the microscopic cytoskeletal network, the approach allows a significant reduction of computational efforts. Our approach is highly flexible and can be generalised to many other cell models, also including biochemical control.
Agile multi-scale decompositions for automatic image registration
Murphy, James M.; Leija, Omar Navarro; Le Moigne, Jacqueline
2016-05-01
In recent works, the first and third authors developed an automatic image registration algorithm based on a multiscale hybrid image decomposition with anisotropic shearlets and isotropic wavelets. This prototype showed strong performance, improving robustness over registration with wavelets alone. However, this method imposed a strict hierarchy on the order in which shearlet and wavelet features were used in the registration process, and also involved an unintegrated mixture of MATLAB and C code. In this paper, we introduce a more agile model for generating features, in which a flexible and user-guided mix of shearlet and wavelet features are computed. Compared to the previous prototype, this method introduces a flexibility to the order in which shearlet and wavelet features are used in the registration process. Moreover, the present algorithm is now fully coded in C, making it more efficient and portable than the mixed MATLAB and C prototype. We demonstrate the versatility and computational efficiency of this approach by performing registration experiments with the fully-integrated C algorithm. In particular, meaningful timing studies can now be performed, to give a concrete analysis of the computational costs of the flexible feature extraction. Examples of synthetically warped and real multi-modal images are analyzed.
Multiscale Permutation Entropy Based Rolling Bearing Fault Diagnosis
Directory of Open Access Journals (Sweden)
Jinde Zheng
2014-01-01
Full Text Available A new rolling bearing fault diagnosis approach based on multiscale permutation entropy (MPE, Laplacian score (LS, and support vector machines (SVMs is proposed in this paper. Permutation entropy (PE was recently proposed and defined to measure the randomicity and detect dynamical changes of time series. However, for the complexity of mechanical systems, the randomicity and dynamic changes of the vibration signal will exist in different scales. Thus, the definition of MPE is introduced and employed to extract the nonlinear fault characteristics from the bearing vibration signal in different scales. Besides, the SVM is utilized to accomplish the fault feature classification to fulfill diagnostic procedure automatically. Meanwhile, in order to avoid a high dimension of features, the Laplacian score (LS is used to refine the feature vector by ranking the features according to their importance and correlations with the main fault information. Finally, the rolling bearing fault diagnosis method based on MPE, LS, and SVM is proposed and applied to the experimental data. The experimental data analysis results indicate that the proposed method could identify the fault categories effectively.
Assessing the diurnal cycle of precipitation in a multi-scale climate model
Directory of Open Access Journals (Sweden)
Michael S Pritchard
2009-10-01
Full Text Available A promising result that has emerged from the new Multi-scale Modeling Framework (MMF approach to atmospheric modeling is a global improvement in the daily timing of peak precipitation over the continents, which is suggestive of improved moist dynamics at diurnal timescales overall. We scrutinize the simulated seasonal composite diurnal cycle of precipitation in an MMF developed by the Center for Multiscale Modeling of Atmospheric Processes (CMMAP using a comprehensive suite of diurnal cycle diagnostics including traditional harmonic analysis, and non-traditional diagnostics such as the broadness of the peak precipitation in the mean summer day, reduced dimension transect analysis, and animations of the full spatial and temporal variability of the composite mean summer day. Precipitation in the MMF is evaluated against multi-satellite merged satellite data and a control simulation with a climate model that employs conventional cloud and boundary layer parameterizations. Our analysis highlights several improved features of the diurnal cycle of precipitation in the multi-scale climate model: It is less sinusoidal over the most energetic diurnal rainfall regimes, more horizontally inhomogeneous within continents and oceans, and more faithful to observed structural transitions in the composite diurnal cycle chronology straddling coastlines than the conventional climate model. A regional focus on North America links a seasonal summer dry bias over the continental United States in the CMMAP MMF at T42 resolution to its inability to capture diurnally propagating precipitation signals associated with organized convection in the lee of the Rockies. The chronology of precipitation events elsewhere in the vicinity of North America is improved in the MMF, especially over sea breeze circulation regions along the eastern seaboard and the Gulf of Mexico, as well as over the entirety of the Gulf Stream. Comparison of the convective heating and moistening
Barkaoui, Abdelwahed; Tlili, Brahim; Vercher-Martínez, Ana; Hambli, Ridha
2016-10-01
Bone is a living material with a complex hierarchical structure which entails exceptional mechanical properties, including high fracture toughness, specific stiffness and strength. Bone tissue is essentially composed by two phases distributed in approximately 30-70%: an organic phase (mainly type I collagen and cells) and an inorganic phase (hydroxyapatite-HA-and water). The nanostructure of bone can be represented throughout three scale levels where different repetitive structural units or building blocks are found: at the first level, collagen molecules are arranged in a pentameric structure where mineral crystals grow in specific sites. This primary bone structure constitutes the mineralized collagen microfibril. A structural organization of inter-digitating microfibrils forms the mineralized collagen fibril which represents the second scale level. The third scale level corresponds to the mineralized collagen fibre which is composed by the binding of fibrils. The hierarchical nature of the bone tissue is largely responsible of their significant mechanical properties; consequently, this is a current outstanding research topic. Scarce works in literature correlates the elastic properties in the three scale levels at the bone nanoscale. The main goal of this work is to estimate the elastic properties of the bone tissue in a multiscale approach including a sensitivity analysis of the elastic behaviour at each length scale. This proposal is achieved by means of a novel hybrid multiscale modelling that involves neural network (NN) computations and finite elements method (FEM) analysis. The elastic properties are estimated using a neural network simulation that previously has been trained with the database results of the finite element models. In the results of this work, parametric analysis and averaged elastic constants for each length scale are provided. Likewise, the influence of the elastic constants of the tissue constituents is also depicted. Results highlight
Multiscale structural gradients enhance the biomechanical functionality of the spider fang
Bar-On, Benny; Barth, Friedrich G.; Fratzl, Peter; Politi, Yael
2014-05-01
The spider fang is a natural injection needle, hierarchically built from a complex composite material comprising multiscale architectural gradients. Considering its biomechanical function, the spider fang has to sustain significant mechanical loads. Here we apply experiment-based structural modelling of the fang, followed by analytical mechanical description and Finite-Element simulations, the results of which indicate that the naturally evolved fang architecture results in highly adapted effective structural stiffness and damage resilience. The analysis methods and physical insights of this work are potentially important for investigating and understanding the architecture and structural motifs of sharp-edge biological elements such as stingers, teeth, claws and more.
Multi-scale variability of subsurface temperature in the South China Sea
Institute of Scientific and Technical Information of China (English)
高荣珍; 周发琇; 王东晓
2002-01-01
Using Morlet wavelet transform and harmonic analysis the multi-scale variability of subsurface temperature in the South China Sea is studied by analyzing one-year (from April 1998 to April 1999) ATLAS mooring data. By wavelet transform, annual and semi-annual cycle as well as intraseasonal variations are found, with different dominance, in subsurface temperature. For annual harmonic cycle, both the downward net surface heat flux and thermocline vertical movement partially control the subsurface temperature variability. For semi-annual cycle and intraseasonal variability, the subsurface temperature variability is mainly linked to the vertical displacement of thermocline.
A Multiscale Factorization Method for Simulating Mesoscopic Systems with Atomic Precision
Mansour, Andrew Abi
2013-01-01
Mesoscopic N-atom systems derive their structural and dynamical properties from processes coupled across multiple scales in space and time. An efficient method for understanding and simulating such systems from the underlying N-atom formulation is presented. The method integrates notions of multiscale analysis, Trotter factorization, and a hypothesis that the momenta conjugate to coarse-grained variables can be treated as a stationary random process. The method is demonstrated for Lactoferrin protein, Nudaurelia Capensis Omega Virus, and Cowpea Chlorotic Mottle Virus to assess its accuracy and scaling with system size.
A principled approach to distributed multiscale computing, from formalization to execution
Borgdorff, J.; Falcone, J.-L.; Lorenz, E.; Chopard, B.; Hoekstra, A.G.
2011-01-01
In several disciplines, a multiscale approach is being used to model complex natural processes yet a principled background to multiscale modeling is not clear. Additionally, some multiscale models requiring distributed resources to be computed in an acceptable timeframe, while no standard framework
Canadinç, Demircan; Önal, Orkun; Özmenci, Cemre
2014-01-01
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 ten...
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.
Multiscale Modeling in the Clinic: Drug Design and Development.
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
2016-09-01
A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multiscale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multiscale 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 multiscale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical and computational techniques employed for multiscale modeling approaches used in pharmacometric and systems pharmacology models in drug development and present several examples illustrating the current state-of-the-art models for (1) excitable systems and applications in cardiac disease; (2) stem cell driven complex biosystems; (3) nanoparticle delivery, with applications to angiogenesis and cancer therapy; (4) host-pathogen interactions and their use in metabolic disorders, inflammation and sepsis; and (5) computer-aided design of nanomedical systems. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multiscale models.
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.
MULTISCALE MATHEMATICS FOR BIOMASS CONVERSION TO RENEWABLE HYDROGEN
Energy Technology Data Exchange (ETDEWEB)
Vlachos, Dionisios; Plechac, Petr; Katsoulakis, Markos
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.
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.
Microphysics in Multi-scale Modeling System with Unified Physics
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.
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].
Multiscale Simulations of Energy Storage in Polymers
Ranjan, V.; van Duin, A.; Buongiorno Nardelli, M.; Bernholc, J.
2012-02-01
Polypropelene is the most used capacitor dielectric for high energy density storage. However, exotic materials such as copolymerized PVDF and, more recently, polythiourea, could potentially lead to an order of magnitude increase in the stored energy density [1,2]. In our previous investigations we demonstrated that PVDF-CTFE possesses non-linear dielectric properties under applied electric field. These are characterized by transitions from non-polar to polar phases that lead enhanced energy density. Recent experiments [3] have also suggested that polythiourea may be another potential system with high energy-density storage and low loss. However, the characteristics of this emerging material are not yet understood and even its preferred crystalline phases are not known. We have developed a multiscale approach to predicting polymer self-organization using the REAX force field and molecular dynamics simulations. We find that polythiourea chains tend to coalesce in nanoribbon-type structures and prefer an anti-polar interchain ordering similar to PVDF. These results suggest a possible role of topological phase transitions in shaping energy storage in this system.[4pt] [1] B. Chu et al, Science 313, 334 (2006).[0pt] [2] V. Ranjan et al., PRL 99, 047801 (2007).[0pt] [3] Q. Zhang, private communication
Multiscale methods for computational RNA enzymology
Panteva, Maria T.; Dissanayake, Thakshila; Chen, Haoyuan; Radak, Brian K.; Kuechler, Erich R.; Giambaşu, George M.; Lee, Tai-Sung; York, Darrin M.
2016-01-01
RNA catalysis is of fundamental importance to biology and yet remains ill-understood due to its complex nature. The multi-dimensional “problem space” of RNA catalysis includes both local and global conformational rearrangements, changes in the ion atmosphere around nucleic acids and metal ion binding, dependence on potentially correlated protonation states of key residues and bond breaking/forming in the chemical steps of the reaction. The goal of this article is to summarize and apply multiscale modeling methods in an effort to target the different parts of the RNA catalysis problem space while also addressing the limitations and pitfalls of these methods. Classical molecular dynamics (MD) simulations, reference interaction site model (RISM) calculations, constant pH molecular dynamics (CpHMD) simulations, Hamiltonian replica exchange molecular dynamics (HREMD) and quantum mechanical/molecular mechanical (QM/MM) simulations will be discussed in the context of the study of RNA backbone cleavage transesterification. This reaction is catalyzed by both RNA and protein enzymes, and here we examine the different mechanistic strategies taken by the hepatitis delta virus ribozyme (HDVr) and RNase A. PMID:25726472
Multiscale mechanobiology modeling for surgery assessment
Institute of Scientific and Technical Information of China (English)
M. Garbey; B. L. Bass; S. Berceli
2012-01-01
This paper discusses some of the concept of modeling surgery outcome.It is also an attempt to offer a road map for progress.This paper may serve as a common ground of discussion for both communities i.e surgeons and computational scientist in its broadest sense.Predicting surgery outcome is a very difficult task.All patients are different,and multiple factors such as genetic,or environment conditions plays a role.The difficulty is to construct models that are complex enough to address some of these significant multiscale elements and simple enough to be used in clinical conditions and calibrated on patient data.We will provide a multilevel progressive approach inspired by two applications in surgery that we have been working on.One is about vein graft adaptation after a transplantation,the other is the recovery of cosmesis outcome after a breast lumpectomy.This work,that is still very much in progress,may teach us some lessons.We are convinced that the digital revolution that is transforming the working environment of the surgeon makes closer collaboration between surgeons and computational scientist unavoidable.We believe that "computational surgery" will allow the community to develop predictive model of the surgery outcome and greatprogresses in surgery procedures that goes far beyond the operating room procedural aspect.
Laser Writing of Multiscale Chiral Polymer Metamaterials
Directory of Open Access Journals (Sweden)
E. P. Furlani
2012-01-01
Full Text Available A new approach to metamaterials is presented that involves laser-based patterning of novel chiral polymer media, wherein chirality is realized at two distinct length scales, intrinsically at the molecular level and geometrically at a length scale on the order of the wavelength of the incident field. In this approach, femtosecond-pulsed laser-induced two-photon lithography (TPL is used to pattern a photoresist-chiral polymer mixture into planar chiral shapes. Enhanced bulk chirality can be realized by tuning the wavelength-dependent chiral response at both the molecular and geometric level to ensure an overlap of their respective spectra. The approach is demonstrated via the fabrication of a metamaterial consisting of a two-dimensional array of chiral polymer-based L-structures. The fabrication process is described and modeling is performed to demonstrate the distinction between molecular and planar geometric-based chirality and the effects of the enhanced multiscale chirality on the optical response of such media. This new approach to metamaterials holds promise for the development of tunable, polymer-based optical metamaterials with low loss.
Navigation Operations for the Magnetospheric Multiscale Mission
Long, Anne; Farahmand, Mitra; Carpenter, Russell
2015-01-01
The Magnetospheric Multiscale (MMS) mission employs four identical spinning spacecraft flying in highly elliptical Earth orbits. These spacecraft will fly in a series of tetrahedral formations with separations of less than 10 km. MMS navigation operations use onboard navigation to satisfy the mission definitive orbit and time determination requirements and in addition to minimize operations cost and complexity. The onboard navigation subsystem consists of the Navigator GPS receiver with Goddard Enhanced Onboard Navigation System (GEONS) software, and an Ultra-Stable Oscillator. The four MMS spacecraft are operated from a single Mission Operations Center, which includes a Flight Dynamics Operations Area (FDOA) that supports MMS navigation operations, as well as maneuver planning, conjunction assessment and attitude ground operations. The System Manager component of the FDOA automates routine operations processes. The GEONS Ground Support System component of the FDOA provides the tools needed to support MMS navigation operations. This paper provides an overview of the MMS mission and associated navigation requirements and constraints and discusses MMS navigation operations and the associated MMS ground system components built to support navigation-related operations.
Magnetospheric MultiScale (MMS) System Manager
Schiff, Conrad; Maher, Francis Alfred; Henely, Sean Philip; Rand, David
2014-01-01
The Magnetospheric MultiScale (MMS) mission is an ambitious NASA space science mission in which 4 spacecraft are flown in tight formation about a highly elliptical orbit. Each spacecraft has multiple instruments that measure particle and field compositions in the Earths magnetosphere. By controlling the members relative motion, MMS can distinguish temporal and spatial fluctuations in a way that a single spacecraft cannot.To achieve this control, 2 sets of four maneuvers, distributed evenly across the spacecraft must be performed approximately every 14 days. Performing a single maneuver on an individual spacecraft is usually labor intensive and the complexity becomes clearly increases with four. As a result, the MMS flight dynamics team turned to the System Manager to put the routine or error-prone under machine control freeing the analysts for activities that require human judgment.The System Manager is an expert system that is capable of handling operations activities associated with performing MMS maneuvers. As an expert system, it can work off a known schedule, launching jobs based on a one-time occurrence or on a set reoccurring schedule. It is also able to detect situational changes and use event-driven programming to change schedules, adapt activities, or call for help.
Multiscale Modeling of UHTC: Thermal Conductivity
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.
Typograph: Multiscale Spatial Exploration of Text Documents
Energy Technology Data Exchange (ETDEWEB)
Endert, Alexander; Burtner, Edwin R.; Cramer, Nicholas O.; Perko, Ralph J.; Hampton, Shawn D.; Cook, Kristin A.
2013-10-06
Visualizing large document collections using a spatial layout of terms can enable quick overviews of information. These visual metaphors (e.g., word clouds, tag clouds, etc.) traditionally show a series of terms organized by space-filling algorithms. However, often lacking in these views is the ability to interactively explore the information to gain more detail, and the location and rendering of the terms are often not based on mathematical models that maintain relative distances from other information based on similarity metrics. In this paper, we present Typograph, a multi-scale spatial exploration visualization for large document collections. Based on the term-based visualization methods, Typograh enables multiple levels of detail (terms, phrases, snippets, and full documents) within the single spatialization. Further, the information is placed based on their relative similarity to other information to create the “near = similar” geographic metaphor. This paper discusses the design principles and functionality of Typograph and presents a use case analyzing Wikipedia to demonstrate usage.
Multiscale Modeling of Advanced Materials for Damage Prediction and Structural Health Monitoring
Borkowski, Luke
Advanced aerospace materials, including fiber reinforced polymer and ceramic matrix composites, are increasingly being used in critical and demanding applications, challenging the current damage prediction, detection, and quantification methodologies. Multiscale computational models offer key advantages over traditional analysis techniques and can provide the necessary capabilities for the development of a comprehensive virtual structural health monitoring (SHM) framework. Virtual SHM has the potential to drastically improve the design and analysis of aerospace components through coupling the complementary capabilities of models able to predict the initiation and propagation of damage under a wide range of loading and environmental scenarios, simulate interrogation methods for damage detection and quantification, and assess the health of a structure. A major component of the virtual SHM framework involves having micromechanics-based multiscale composite models that can provide the elastic, inelastic, and damage behavior of composite material systems under mechanical and thermal loading conditions and in the presence of microstructural complexity and variability. Quantification of the role geometric and architectural variability in the composite microstructure plays in the local and global composite behavior is essential to the development of appropriate scale-dependent unit cells and boundary conditions for the multiscale model. Once the composite behavior is predicted and variability effects assessed, wave-based SHM simulation models serve to provide knowledge on the probability of detection and characterization accuracy of damage present in the composite. The research presented in this dissertation provides the foundation for a comprehensive SHM framework for advanced aerospace materials. The developed models enhance the prediction of damage formation as a result of ceramic matrix composite processing, improve the understanding of the effects of architectural and
A Comparison of Multiscale Permutation Entropy Measures in On-Line Depth of Anesthesia Monitoring
Li, Xiaoli; Li, Duan; Li, Yongwang; Ursino, Mauro
2016-01-01
Objective Multiscale permutation entropy (MSPE) is becoming an interesting tool to explore neurophysiological mechanisms in recent years. In this study, six MSPE measures were proposed for on-line depth of anesthesia (DoA) monitoring to quantify the anesthetic effect on the real-time EEG recordings. The performance of these measures in describing the transient characters of simulated neural populations and clinical anesthesia EEG were evaluated and compared. Methods Six MSPE algorithms—derived from Shannon permutation entropy (SPE), Renyi permutation entropy (RPE) and Tsallis permutation entropy (TPE) combined with the decomposition procedures of coarse-graining (CG) method and moving average (MA) analysis—were studied. A thalamo-cortical neural mass model (TCNMM) was used to generate noise-free EEG under anesthesia to quantitatively assess the robustness of each MSPE measure against noise. Then, the clinical anesthesia EEG recordings from 20 patients were analyzed with these measures. To validate their effectiveness, the ability of six measures were compared in terms of tracking the dynamical changes in EEG data and the performance in state discrimination. The Pearson correlation coefficient (R) was used to assess the relationship among MSPE measures. Results CG-based MSPEs failed in on-line DoA monitoring at multiscale analysis. In on-line EEG analysis, the MA-based MSPE measures at 5 decomposed scales could track the transient changes of EEG recordings and statistically distinguish the awake state, unconsciousness and recovery of consciousness (RoC) state significantly. Compared to single-scale SPE and RPE, MSPEs had better anti-noise ability and MA-RPE at scale 5 performed best in this aspect. MA-TPE outperformed other measures with faster tracking speed of the loss of unconsciousness. Conclusions MA-based multiscale permutation entropies have the potential for on-line anesthesia EEG analysis with its simple computation and sensitivity to drug effect
2010-09-30
time (Fig. 1a – h). A new variational synthesis procedure called SAMURAI (Spline Analysis at Mesoscale Utilizing Radar and Aircraft Instrumentation...at ~00 UTC 14 September 2008, but the circulation is even more evident in a 1 km altitude SAMURAI streamline analysis in the co-moving frame, with a... SAMURAI analysis package, multi-scale analysis can be conducted that utilize a variety of data sources. Aircraft flight level data, SFMR data, and
A Collaborative Informatics Infrastructure for Multi-scale Science
Energy Technology Data Exchange (ETDEWEB)
Myers, J D; Allison, T C; Bittner, S; Didier, B; Frenklach, M; Green, Jr., W H; Ho, Y; Hewson, J; Koegler, W; Lansing, C; Leahy, D; Lee, M; McCoy, R; Minkoff, M; Nijsure, S; von Laszewski, G; Montoya, D; Pancerella, C; Pinzon, R; Pitz, W J; Rahn, L A; Ruscis, B; Schuchardt, K; Stephan, E; Wagner, A; Windus, T; Yang, C
2005-05-11
The Collaboratory for Multi-scale Chemical Science (CMCS) is developing a powerful informatics-based approach to synthesizing multi-scale information to support a systems-based research approach and is applying it in support of combustion research. An open source multi-scale informatics toolkit is being developed that addresses a number of issues core to the emerging concept of knowledge grids including provenance tracking and lightweight federation of data and application resources into cross-scale information flows. The CMCS portal is currently in use by a number of high-profile pilot groups and is playing a significant role in enabling their efforts to improve and extend community maintained chemical reference information.
A Collaborative Informatics Infrastructure for Multi-scale Science
Energy Technology Data Exchange (ETDEWEB)
Myers, James D.; Allison, Thomas C.; Bittner, Sandra J.; Didier, Brett T.; Frenklach, Michael; Green, William H.; Ho, Yen-Ling; Hewson, John; Koegler, Wendy S.; Lansing, Carina S.; Leahy, David; Lee, Michael; McCoy, Renata; Minkoff, Michael; Nijsure, Sandeep; von Laszewski, Gregor; Montoya, David; Oluwole, Luwi; Pancerella, Carmen M.; Pinzon, Reinhardt; Pitz, William; Rahn, Larry A.; Ruscic, Branko; Schuchardt, Karen L.; Stephan, Eric G.; Wagner, Al; Windus, Theresa L.; Yang, Christine
2005-10-01
The Collaboratory for Multi-scale Chemical Science (CMCS) is developing a powerful informatics-based approach to synthesizing multi-scale information to support a systems-based research approach and is applying it in support of combustion research. An open source multi-scale informatics toolkit is being developed that addresses a number of issues core to the emerging concept of knowledge grids including provenance tracking and lightweight federation of data and application resources into cross-scale information flows. The CMCS portal is currently in use by a number of high-profile pilot groups and is playing a significant role in enabling their efforts to improve and extend community maintained chemical reference information.
A Collaborative Informatics Infrastructure for Multi-scale Science
Energy Technology Data Exchange (ETDEWEB)
Myers, James D.; Allison, Thomas C.; Bittner, Sandra; Didier, Brett T.; Frenklach, Michael; Green, William H.; Ho, Yen-Ling; Hewson, John; Koegler, Wendy S.; Lansing, Carina S.; Leahy, David; Lee, Michael; McCoy, Renata; Minkoff, Michael; Nijsure, Sandeep; von Laszewski, Gregor; Montoya, David W.; Pancerella, Carmen M.; Pinzon, Reinhardt; Pitz, William; Rahn, Larry; Ruscic, Branko; Schuchardt, Karen L.; Stephan, Eric G.; Wagner, Albert F.; Windus, Theresa L.; Yang, Christine
2004-03-28
The Collaboratory for Multi-scale Chemical Science (CMCS) is developing a powerful informatics-based approach to synthesizing multi-scale information to support a systems-based research approach and is applying it in support of combustion research. An open source multi-scale informatics toolkit is being developed that addresses a number of issues core to the emerging concept of knowledge grids including provenance tracking and lightweight federation of data and application resources into cross-scale information flows. The CMCS portal is currently in use by a number of high-profile pilot groups and is playing a significant role in enabling their efforts to improve and extend community maintained chemical reference information.
Standard Model in multi-scale theories and observational constraints
Calcagni, Gianluca; Rodríguez-Fernández, David
2015-01-01
We construct and analyze the Standard Model of electroweak and strong interactions in multi-scale spacetimes with (i) weighted derivatives and (ii) $q$-derivatives. Both theories can be formulated in two different frames, called fractional and integer picture. By definition, the fractional picture is where physical predictions should be made. (i) In the theory with weighted derivatives, it is shown that gauge invariance and the requirement of having constant masses in all reference frames make the Standard Model in the integer picture indistinguishable from the ordinary one. Experiments involving only weak and strong forces are insensitive to a change of spacetime dimensionality also in the fractional picture, and only the electromagnetic and gravitational sectors can break the degeneracy. For the simplest multi-scale measures with only one characteristic time, length and energy scale $t_*$, $\\ell_*$ and $E_*$, we compute the Lamb shift in the hydrogen atom and constrain the multi-scale correction to the ordi...
Algorithmic foundation of multi-scale spatial representation
Li, Zhilin
2006-01-01
With the widespread use of GIS, multi-scale representation has become an important issue in the realm of spatial data handling. However, no book to date has systematically tackled the different aspects of this discipline. Emphasizing map generalization, Algorithmic Foundation of Multi-Scale Spatial Representation addresses the mathematical basis of multi-scale representation, specifically, the algorithmic foundation.Using easy-to-understand language, the author focuses on geometric transformations, with each chapter surveying a particular spatial feature. After an introduction to the essential operations required for geometric transformations as well as some mathematical and theoretical background, the book describes algorithms for a class of point features/clusters. It then examines algorithms for individual line features, such as the reduction of data points, smoothing (filtering), and scale-driven generalization, followed by a discussion of algorithms for a class of line features including contours, hydrog...
Multiscale Stategies in Automatic Image-Domain Waveform Tomography
Institute of Scientific and Technical Information of China (English)
Yujin Liu; Zhenchun Li
2015-01-01
Multiscale strategies are very important in the successful application of waveform-based velocity inversion. The strategy that sequentially preceeds from long to short scale of velocity model, has been well developed in full waveform inversion (FWI) to solve the local mininum problem. In contrast, it’s not well understood in the image-domain waveform tomography (IWT), which back-projects incoherent waveform components of the common image gather into velocity updates. IWT is less prone to local minimum problem but tends to build long-scale model with low resolution. In order to build both long- and short-scale model by IWT, we discuss several multiscale strategies restricted in the image domain. The strategies include model reparameterization, objective function switching and gradient rescaling. Numerical tests on Marmsousi model and real data demonstrate that our proposed multiscale IWT is effective in buidling velocity model with wide wavenumber spectrum.
Multiscale Universal Interface: A Concurrent Framework for Coupling Heterogeneous Solvers
Tang, Yu-Hang; Bian, Xin; Li, Zhen; Karniadakis, George E
2014-01-01
Concurrently coupled numerical simulations using heterogeneous solvers are powerful tools for modeling multiscale phenomena. However, major modifications to existing codes are often required to enable such simulations, posing significant difficulties in practice. In this paper we present a C++ library, i.e. the Multiscale Universal Interface (MUI), which is capable of facilitating the coupling effort for a wide range of multiscale simulations. The library adopts a header-only form with minimal external dependency and hence can be easily dropped into existing codes. A data sampler concept is introduced, combined with a hybrid dynamic/static typing mechanism, to create an easily customizable framework for solver-independent data interpretation. The library integrates MPI MPMD support and an asynchronous communication protocol to handle inter-solver information exchange irrespective of the solvers' own MPI awareness. Template metaprogramming is heavily employed to simultaneously improve runtime performance and c...
Waveform relaxation for the computational homogenization of multiscale magnetoquasistatic problems
Niyonzima, I.; Geuzaine, C.; Schöps, S.
2016-12-01
This paper proposes the application of the waveform relaxation method to the homogenization of multiscale magnetoquasistatic problems. In the monolithic heterogeneous multiscale method, the nonlinear macroscale problem is solved using the Newton-Raphson scheme. The resolution of many mesoscale problems per Gauß point allows to compute the homogenized constitutive law and its derivative by finite differences. In the proposed approach, the macroscale problem and the mesoscale problems are weakly coupled and solved separately using the finite element method on time intervals for several waveform relaxation iterations. The exchange of information between both problems is still carried out using the heterogeneous multiscale method. However, the partial derivatives can now be evaluated exactly by solving only one mesoscale problem per Gauß point.