Maher, G.D.; Hulshoff, S.J.
2014-01-01
The Variational Germano Identity [1, 2] is used to optimize the coefficients of residual-based subgrid-scale models that arise from the application of a Variational Multiscale Method [3, 4]. It is demonstrated that numerical iterative methods can be used to solve the Germano relations to obtain
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
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
Ghaffari Motlagh, Yousef; Ahn, Hyungtaek; Hughes, Thomas Jr R; Calo, Victor M.
2013-01-01
We present an application of the residual-based variational multiscale modeling methodology to the computation of laminar and turbulent concentric annular pipe flows. Isogeometric analysis is utilized for higher-order approximation of the solution using Non-Uniform Rational B-Splines (NURBS). The ability of NURBS to exactly represent curved geometries makes NURBS-based isogeometric analysis attractive for the application to the flow through annular channels. We demonstrate the applicability of the methodology to both laminar and turbulent flow regimes. © 2012 Elsevier Ltd.
Introduction and application of the multiscale coefficient of variation analysis.
Abney, Drew H; Kello, Christopher T; Balasubramaniam, Ramesh
2017-10-01
Quantifying how patterns of behavior relate across multiple levels of measurement typically requires long time series for reliable parameter estimation. We describe a novel analysis that estimates patterns of variability across multiple scales of analysis suitable for time series of short duration. The multiscale coefficient of variation (MSCV) measures the distance between local coefficient of variation estimates within particular time windows and the overall coefficient of variation across all time samples. We first describe the MSCV analysis and provide an example analytical protocol with corresponding MATLAB implementation and code. Next, we present a simulation study testing the new analysis using time series generated by ARFIMA models that span white noise, short-term and long-term correlations. The MSCV analysis was observed to be sensitive to specific parameters of ARFIMA models varying in the type of temporal structure and time series length. We then apply the MSCV analysis to short time series of speech phrases and musical themes to show commonalities in multiscale structure. The simulation and application studies provide evidence that the MSCV analysis can discriminate between time series varying in multiscale structure and length.
Evans, John; Coley, Christopher; Aronson, Ryan; Nelson, Corey
2017-11-01
In this talk, a large eddy simulation methodology for turbulent incompressible flow will be presented which combines the best features of divergence-conforming discretizations and the residual-based variational multiscale approach to large eddy simulation. In this method, the resolved motion is represented using a divergence-conforming discretization, that is, a discretization that preserves the incompressibility constraint in a pointwise manner, and the unresolved fluid motion is explicitly modeled by subgrid vortices that lie within individual grid cells. The evolution of the subgrid vortices is governed by dynamical model equations driven by the residual of the resolved motion. Consequently, the subgrid vortices appropriately vanish for laminar flow and fully resolved turbulent flow. As the resolved velocity field and subgrid vortices are both divergence-free, the methodology conserves mass in a pointwise sense and admits discrete balance laws for energy, enstrophy, and helicity. Numerical results demonstrate the methodology yields improved results versus state-of-the-art eddy viscosity models in the context of transitional, wall-bounded, and rotational flow when a divergence-conforming B-spline discretization is utilized to represent the resolved motion.
Multiscale mechanisms of nutritionally induced property variation in spider silks
Nobbs, Madeleine; Martens, Penny J.; Tso, I-Min; Chuang, Wei-Tsung; Chang, Chung-Kai; Sheu, Hwo-Shuenn
2018-01-01
Variability in spider major ampullate (MA) silk properties at different scales has proven difficult to determine and remains an obstacle to the development of synthetic fibers mimicking MA silk performance. A multitude of techniques may be used to measure multiscale aspects of silk properties. Here we fed five species of Araneoid spider solutions that either contained protein or were protein deprived and performed silk tensile tests, small and wide-angle X-ray scattering (SAXS/WAXS), amino acid composition analyses, and silk gene expression analyses, to resolve persistent questions about how nutrient deprivation induces variations in MA silk mechanical properties across scales. Our analyses found that the properties of each spider’s silk varied differently in response to variations in their protein intake. We found changes in the crystalline and non-crystalline nanostructures to play specific roles in inducing the property variations we found. Across treatment MaSp expression patterns differed in each of the five species. We found that in most species MaSp expression and amino acid composition variations did not conform with our predictions based on a traditional MaSp expression model. In general, changes to the silk’s alanine and proline compositions influenced the alignment of the proteins within the silk’s amorphous region, which influenced silk extensibility and toughness. Variations in structural alignment in the crystalline and non-crystalline regions influenced ultimate strength independent of genetic expression. Our study provides the deepest insights thus far into the mechanisms of how MA silk properties vary from gene expression to nanostructure formations to fiber mechanics. Such knowledge is imperative for promoting the production of synthetic silk fibers. PMID:29390013
Siddiq, A.; El Sayed, Tamer S.
2013-01-01
We present a variational multiscale constitutive model that accounts for intergranular failure in nanocrystalline fcc metals due to void growth and coalescence in the grain boundary region. Following previous work by the authors, a nanocrystalline
A variational multiscale constitutive model for nanocrystalline materials
Gurses, Ercan
2011-03-01
This paper presents a variational multi-scale constitutive model in the finite deformation regime capable of capturing the mechanical behavior of nanocrystalline (nc) fcc metals. The nc-material is modeled as a two-phase material consisting of a grain interior phase and a grain boundary effected zone (GBAZ). A rate-independent isotropic porous plasticity model is employed to describe the GBAZ, whereas a crystal-plasticity model which accounts for the transition from partial dislocation to full dislocation mediated plasticity is employed for the grain interior. The constitutive models of both phases are formulated in a small strain framework and extended to finite deformation by use of logarithmic and exponential mappings. Assuming the rule of mixtures, the overall behavior of a given grain is obtained via volume averaging. The scale transition from a single grain to a polycrystal is achieved by Taylor-type homogenization where a log-normal grain size distribution is assumed. It is shown that the proposed model is able to capture the inverse HallPetch effect, i.e., loss of strength with grain size refinement. Finally, the predictive capability of the model is validated against experimental results on nanocrystalline copper and nickel. © 2010 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Shadid, John Nicolas; Lehoucq, Richard B.; Christon, Mark Allen; Slepoy, Alexander; Bochev, Pavel Blagoveston; Collis, Samuel Scott; Wagner, Gregory John
2004-01-01
Existing approaches in multiscale science and engineering have evolved from a range of ideas and solutions that are reflective of their original problem domains. As a result, research in multiscale science has followed widely diverse and disjoint paths, which presents a barrier to cross pollination of ideas and application of methods outside their application domains. The status of the research environment calls for an abstract mathematical framework that can provide a common language to formulate and analyze multiscale problems across a range of scientific and engineering disciplines. In such a framework, critical common issues arising in multiscale problems can be identified, explored and characterized in an abstract setting. This type of overarching approach would allow categorization and clarification of existing models and approximations in a landscape of seemingly disjoint, mutually exclusive and ad hoc methods. More importantly, such an approach can provide context for both the development of new techniques and their critical examination. As with any new mathematical framework, it is necessary to demonstrate its viability on problems of practical importance. At Sandia, lab-centric, prototype application problems in fluid mechanics, reacting flows, magnetohydrodynamics (MHD), shock hydrodynamics and materials science span an important subset of DOE Office of Science applications and form an ideal proving ground for new approaches in multiscale science.
Variational Multi-Scale method with spectral approximation of the sub-scales.
Dia, Ben Mansour; Chá con-Rebollo, Tomas
2015-01-01
A variational multi-scale method where the sub-grid scales are computed by spectral approximations is presented. It is based upon an extension of the spectral theorem to non necessarily self-adjoint elliptic operators that have an associated base
Sensitivity of the scale partition for variational multiscale large-eddy simulation of channel flow
Holmen, J.; Hughes, T.J.R.; Oberai, A.A.; Wells, G.N.
2004-01-01
The variational multiscale method has been shown to perform well for large-eddy simulation (LES) of turbulent flows. The method relies upon a partition of the resolved velocity field into large- and small-scale components. The subgrid model then acts only on the small scales of motion, unlike
Bazile , Alban; Hachem , Elie; Larroya-Huguet , Juan-Carlos; Mesri , Youssef
2018-01-01
International audience; In this work, we present a new a posteriori error estimator based on the Variational Multiscale method for anisotropic adaptive fluid mechanics problems. The general idea is to combine the large scale error based on the solved part of the solution with the sub-mesh scale error based on the unresolved part of the solution. We compute the latter with two different methods: one using the stabilizing parameters and the other using bubble functions. We propose two different...
Variational Multi-Scale method with spectral approximation of the sub-scales.
Dia, Ben Mansour
2015-01-07
A variational multi-scale method where the sub-grid scales are computed by spectral approximations is presented. It is based upon an extension of the spectral theorem to non necessarily self-adjoint elliptic operators that have an associated base of eigenfunctions which are orthonormal in weighted L2 spaces. We propose a feasible VMS-spectral method by truncation of this spectral expansion to a nite number of modes.
Chang, Kyungsik
2012-09-01
We report on the isogeometric residual-based variational multiscale (VMS) large eddy simulation of a fully developed turbulent flow over a wavy wall. To assess the predictive capability of the VMS modeling framework, we compare its predictions against the results from direct numerical simulation (DNS) and large eddy simulation (LES) and, when available, against experimental measurements. We use C 1 quadratic B-spline basis functions to represent the smooth geometry of the sinusoidal lower wall and the solution variables. The Reynolds numbers of the flows considered are 6760 and 30,000 based on the bulk velocity and average channel height. The ratio of amplitude to wavelength (α/λ) of the sinusoidal wavy surface is set to 0.05. The computational domain is 2λ×1.05λ×λ in the streamwise, wall-normal and spanwise directions, respectively. For the Re=6760 case, mean averaged quantities, including velocity and pressure profiles, and the separation/reattachment points in the recirculation region, are compared with DNS and experimental data. The turbulent kinetic energy and Reynolds stress are in good agreement with benchmark data. Coherent structures over the wavy wall are observed in isosurfaces of the Q-criterion and show similar features to those previously reported in the literature. Comparable accuracy to DNS solutions is obtained with at least one order of magnitude fewer degrees of freedom. For the Re=30,000 case, good agreement was obtained for mean wall shear stress and velocity profiles compared with available LES results reported in the literature. © 2012 Elsevier Ltd.
Chang, Kyungsik; Hughes, Thomas Jr R; Calo, Victor M.
2012-01-01
We report on the isogeometric residual-based variational multiscale (VMS) large eddy simulation of a fully developed turbulent flow over a wavy wall. To assess the predictive capability of the VMS modeling framework, we compare its predictions against the results from direct numerical simulation (DNS) and large eddy simulation (LES) and, when available, against experimental measurements. We use C 1 quadratic B-spline basis functions to represent the smooth geometry of the sinusoidal lower wall and the solution variables. The Reynolds numbers of the flows considered are 6760 and 30,000 based on the bulk velocity and average channel height. The ratio of amplitude to wavelength (α/λ) of the sinusoidal wavy surface is set to 0.05. The computational domain is 2λ×1.05λ×λ in the streamwise, wall-normal and spanwise directions, respectively. For the Re=6760 case, mean averaged quantities, including velocity and pressure profiles, and the separation/reattachment points in the recirculation region, are compared with DNS and experimental data. The turbulent kinetic energy and Reynolds stress are in good agreement with benchmark data. Coherent structures over the wavy wall are observed in isosurfaces of the Q-criterion and show similar features to those previously reported in the literature. Comparable accuracy to DNS solutions is obtained with at least one order of magnitude fewer degrees of freedom. For the Re=30,000 case, good agreement was obtained for mean wall shear stress and velocity profiles compared with available LES results reported in the literature. © 2012 Elsevier Ltd.
Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction
Li, Zhijin; Chao, Yi; Li, P. Peggy
2012-01-01
A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.
Zhang, Shuhai; Oskay, Caglar
2015-04-01
This manuscript presents the formulation and implementation of the variational multiscale enrichment (VME) method for the analysis of elasto-viscoplastic problems. VME is a global-local approach that allows accurate fine scale representation at small subdomains, where important physical phenomena are likely to occur. The response within far-fields is idealized using a coarse scale representation. The fine scale representation not only approximates the coarse grid residual, but also accounts for the material heterogeneity. A one-parameter family of mixed boundary conditions that range from Dirichlet to Neumann is employed to study the effect of the choice of the boundary conditions at the fine scale on accuracy. The inelastic material behavior is modeled using Perzyna type viscoplasticity coupled with flow stress evolution idealized by the Johnson-Cook model. Numerical verifications are performed to assess the performance of the proposed approach against the direct finite element simulations. The results of verification studies demonstrate that VME with proper boundary conditions accurately model the inelastic response accounting for material heterogeneity.
A variational multiscale method for particle-cloud tracking in turbomachinery flows
Corsini, A.; Rispoli, F.; Sheard, A. G.; Takizawa, K.; Tezduyar, T. E.; Venturini, P.
2014-11-01
We present a computational method for simulation of particle-laden flows in turbomachinery. The method is based on a stabilized finite element fluid mechanics formulation and a finite element particle-cloud tracking method. We focus on induced-draft fans used in process industries to extract exhaust gases in the form of a two-phase fluid with a dispersed solid phase. The particle-laden flow causes material wear on the fan blades, degrading their aerodynamic performance, and therefore accurate simulation of the flow would be essential in reliable computational turbomachinery analysis and design. The turbulent-flow nature of the problem is dealt with a Reynolds-Averaged Navier-Stokes model and Streamline-Upwind/Petrov-Galerkin/Pressure-Stabilizing/Petrov-Galerkin stabilization, the particle-cloud trajectories are calculated based on the flow field and closure models for the turbulence-particle interaction, and one-way dependence is assumed between the flow field and particle dynamics. We propose a closure model utilizing the scale separation feature of the variational multiscale method, and compare that to the closure utilizing the eddy viscosity model. We present computations for axial- and centrifugal-fan configurations, and compare the computed data to those obtained from experiments, analytical approaches, and other computational methods.
Siddiq, A.
2013-09-01
We present a variational multiscale constitutive model that accounts for intergranular failure in nanocrystalline fcc metals due to void growth and coalescence in the grain boundary region. Following previous work by the authors, a nanocrystalline material is modeled as a two-phase material consisting of a grain interior phase and a grain boundary affected zone (GBAZ). A crystal plasticity model that accounts for the transition from partial dislocation to full dislocation mediated plasticity is used for the grain interior. Isotropic porous plasticity model with further extension to account for failure due to the void coalescence was used for the GBAZ. The extended model contains all the deformation phases, i.e. elastic deformation, plastic deformation including deviatoric and volumetric plasticity (void growth) followed by damage initiation and evolution due to void coalescence. Parametric studies have been performed to assess the model\\'s dependence on the different input parameters. The model is then validated against uniaxial loading experiments for different materials. Lastly we show the model\\'s ability to predict the damage and fracture of a dog-bone shaped specimen as observed experimentally. © 2013 Elsevier B.V.
Calo, Victor M.
2011-09-01
In this short note, we discuss variational multiscale methods for solving porous media flows in high-contrast heterogeneous media with rough source terms. Our objective is to separate, as much as possible, subgrid effects induced by the media properties from those due to heterogeneous source terms. For this reason, enriched coarse spaces designed for high-contrast multiscale problems are used to represent the effects of heterogeneities of the media. Furthermore, rough source terms are captured via auxiliary correction equations that appear in the formulation of variational multiscale methods [23]. These auxiliary equations are localized and one can use additive or multiplicative constructions for the subgrid corrections as discussed in the current paper. Our preliminary numerical results show that one can capture the effects due to both spatial heterogeneities in the coefficients (such as permeability field) and source terms (e.g., due to singular well terms) in one iteration. We test the cases for both smooth source terms and rough source terms and show that with the multiplicative correction, the numerical approximations are more accurate compared to the additive correction. © 2010 Elsevier Ltd.
Roushangar, Kiyoumars; Alizadeh, Farhad; Adamowski, Jan
2018-08-01
Understanding precipitation on a regional basis is an important component of water resources planning and management. The present study outlines a methodology based on continuous wavelet transform (CWT) and multiscale entropy (CWME), combined with self-organizing map (SOM) and k-means clustering techniques, to measure and analyze the complexity of precipitation. Historical monthly precipitation data from 1960 to 2010 at 31 rain gauges across Iran were preprocessed by CWT. The multi-resolution CWT approach segregated the major features of the original precipitation series by unfolding the structure of the time series which was often ambiguous. The entropy concept was then applied to components obtained from CWT to measure dispersion, uncertainty, disorder, and diversification of subcomponents. Based on different validity indices, k-means clustering captured homogenous areas more accurately, and additional analysis was performed based on the outcome of this approach. The 31 rain gauges in this study were clustered into 6 groups, each one having a unique CWME pattern across different time scales. The results of clustering showed that hydrologic similarity (multiscale variation of precipitation) was not based on geographic contiguity. According to the pattern of entropy across the scales, each cluster was assigned an entropy signature that provided an estimation of the entropy pattern of precipitation data in each cluster. Based on the pattern of mean CWME for each cluster, a characteristic signature was assigned, which provided an estimation of the CWME of a cluster across scales of 1-2, 3-8, and 9-13 months relative to other stations. The validity of the homogeneous clusters demonstrated the usefulness of the proposed approach to regionalize precipitation. Further analysis based on wavelet coherence (WTC) was performed by selecting central rain gauges in each cluster and analyzing against temperature, wind, Multivariate ENSO index (MEI), and East Atlantic (EA) and
Zhao, W.; Zhang, X.; Liu, Y.; Fang, X.
2017-12-01
Currently, the ecological restoration of the Loess Plateau has led to significant achievements such as increases in vegetation coverage, decreases in soil erosion, and enhancement of ecosystem services. Soil moisture shortages, however, commonly occur as a result of limited rainfall and strong evaporation in this semiarid region of China. Since soil moisture is critical in regulating plant growth in these semiarid regions, it is crucial to identify the spatial variation and factors affecting soil moisture at multi-scales in the Loess Plateau of China. In the last several years, extensive studies on soil moisture have been carried out by our research group at the plot, small watershed, watershed, and regional scale in the Loess Plateau, providing some information for vegetation restoration in the region. The main research results are as follows: (1) the highest soil moisture content was in the 0-0.1 m layer with a large coefficient of variation; (2) in the 0-0.1m layer, soil moisture content was negatively correlated with relative elevation, slope and vegetation cover, the correlations among slope, aspect and soil moisture increased with depth increased; (3) as for the deep soil moisture content, the higher spatial variation of deep SMC occurred at 1.2-1.4 m and 4.8-5.0m; (4) the deep soil moisture content in native grassland and farmland were significant higher than that of introduced vegetation; (5) at regional scale, the soil water content under different precipitation zones increased following the increase of precipitation, while, the influencing factors of deep SMC at watershed scale varied with land management types; (6) in the areas with multi-year precipitation of 370 - 440mm, natural grass is more suitable for restoration, and this should be treated as the key areas in vegetation restoration; (7) appropriate planting density and species selection should be taken into account for introduced vegetation management; (8) it is imperative to take the local
Controls for multi-scale temporal variation in methane flux of a subtropical tidal salt marsh
Li, H.
2016-12-01
Coastal wetlands provide critical carbon sequestration benefits, yet the production of methane (CH4) from these ecosystems can vary by an order of magnitude based on environmental and biological factors. Eddy covariance (EC) measurements for methane flux (FCH4) were performed in a subtropical tidal salt marsh of eastern China over 20 months. Spectral analysis techniques including the continuous wavelet transform, the wavelet coherence, the partial wavelet coherence and the multiple wavelet coherence were employed to analyze the periodicities and the main regulating factors of FCH4 in the tidal salt marsh. The annual budget of methane was 17.8 g C-CH4 m-2 yr-1, which was relatively high compared to those of most reported from inland wetland sites. In non-growing season, release of ebullition was the dominant driving mechanism for variability of FCH4 from hourly to monthly scales. There was no single dominant factor at short-term scale (half-day to 1-day) in growing season. It is worthwhile to note that tide was one of the most important factors regulating FCH4 at short time scale (half-day to 1-day). In comparison, the contribution of temperature to FCH4 at a short time scale (half-day to 1-day) was small due to its narrow range. In addition, plant-modulated transport and gross primary production also contributed to FCH4 at multiple temporal scales in this densely vegetated marsh, especially at weekly to monthly scales. Due to the complex interactive influences of tidal dynamics, temperature fluctuation, plant productivity, plant-mediated transport and release of ebullition on FCH4 exhibited no clear pattern of diurnal variation, but instead was highly variable.
Chacó n Rebollo, Tomá s; Dia, Ben Mansour
2015-01-01
This paper introduces a variational multi-scale method where the sub-grid scales are computed by spectral approximations. It is based upon an extension of the spectral theorem to non necessarily self-adjoint elliptic operators that have an associated base of eigenfunctions which are orthonormal in weighted L2 spaces. This allows to element-wise calculate the sub-grid scales by means of the associated spectral expansion. We propose a feasible VMS-spectral method by truncation of this spectral expansion to a finite number of modes. We apply this general framework to the convection-diffusion equation, by analytically computing the family of eigenfunctions. We perform a convergence and error analysis. We also present some numerical tests that show the stability of the method for an odd number of spectral modes, and an improvement of accuracy in the large resolved scales, due to the adding of the sub-grid spectral scales.
Rasthofer, U.; Wall, W. A.; Gravemeier, V.
2018-04-01
A novel and comprehensive computational method, referred to as the eXtended Algebraic Variational Multiscale-Multigrid-Multifractal Method (XAVM4), is proposed for large-eddy simulation of the particularly challenging problem of turbulent two-phase flow. The XAVM4 involves multifractal subgrid-scale modeling as well as a Nitsche-type extended finite element method as an approach for two-phase flow. The application of an advanced structural subgrid-scale modeling approach in conjunction with a sharp representation of the discontinuities at the interface between two bulk fluids promise high-fidelity large-eddy simulation of turbulent two-phase flow. The high potential of the XAVM4 is demonstrated for large-eddy simulation of turbulent two-phase bubbly channel flow, that is, turbulent channel flow carrying a single large bubble of the size of the channel half-width in this particular application.
Chacón Rebollo, Tomás
2015-03-01
This paper introduces a variational multi-scale method where the sub-grid scales are computed by spectral approximations. It is based upon an extension of the spectral theorem to non necessarily self-adjoint elliptic operators that have an associated base of eigenfunctions which are orthonormal in weighted L2 spaces. This allows to element-wise calculate the sub-grid scales by means of the associated spectral expansion. We propose a feasible VMS-spectral method by truncation of this spectral expansion to a finite number of modes. We apply this general framework to the convection-diffusion equation, by analytically computing the family of eigenfunctions. We perform a convergence and error analysis. We also present some numerical tests that show the stability of the method for an odd number of spectral modes, and an improvement of accuracy in the large resolved scales, due to the adding of the sub-grid spectral scales.
Distributed multiscale computing
Borgdorff, J.
2014-01-01
Multiscale models combine knowledge, data, and hypotheses from different scales. Simulating a multiscale model often requires extensive computation. This thesis evaluates distributing these computations, an approach termed distributed multiscale computing (DMC). First, the process of multiscale
Convergence of a residual based artificial viscosity finite element method
Nazarov, Murtazo
2013-02-01
We present a residual based artificial viscosity finite element method to solve conservation laws. The Galerkin approximation is stabilized by only residual based artificial viscosity, without any least-squares, SUPG, or streamline diffusion terms. We prove convergence of the method, applied to a scalar conservation law in two space dimensions, toward an unique entropy solution for implicit time stepping schemes. © 2012 Elsevier B.V. All rights reserved.
Mih, Nathan; Brunk, Elizabeth; Bordbar, Aarash; Palsson, Bernhard O
2016-07-01
Progress in systems medicine brings promise to addressing patient heterogeneity and individualized therapies. Recently, genome-scale models of metabolism have been shown to provide insight into the mechanistic link between drug therapies and systems-level off-target effects while being expanded to explicitly include the three-dimensional structure of proteins. The integration of these molecular-level details, such as the physical, structural, and dynamical properties of proteins, notably expands the computational description of biochemical network-level properties and the possibility of understanding and predicting whole cell phenotypes. In this study, we present a multi-scale modeling framework that describes biological processes which range in scale from atomistic details to an entire metabolic network. Using this approach, we can understand how genetic variation, which impacts the structure and reactivity of a protein, influences both native and drug-induced metabolic states. As a proof-of-concept, we study three enzymes (catechol-O-methyltransferase, glucose-6-phosphate dehydrogenase, and glyceraldehyde-3-phosphate dehydrogenase) and their respective genetic variants which have clinically relevant associations. Using all-atom molecular dynamic simulations enables the sampling of long timescale conformational dynamics of the proteins (and their mutant variants) in complex with their respective native metabolites or drug molecules. We find that changes in a protein's structure due to a mutation influences protein binding affinity to metabolites and/or drug molecules, and inflicts large-scale changes in metabolism.
Directory of Open Access Journals (Sweden)
Nathan Mih
2016-07-01
Full Text Available Progress in systems medicine brings promise to addressing patient heterogeneity and individualized therapies. Recently, genome-scale models of metabolism have been shown to provide insight into the mechanistic link between drug therapies and systems-level off-target effects while being expanded to explicitly include the three-dimensional structure of proteins. The integration of these molecular-level details, such as the physical, structural, and dynamical properties of proteins, notably expands the computational description of biochemical network-level properties and the possibility of understanding and predicting whole cell phenotypes. In this study, we present a multi-scale modeling framework that describes biological processes which range in scale from atomistic details to an entire metabolic network. Using this approach, we can understand how genetic variation, which impacts the structure and reactivity of a protein, influences both native and drug-induced metabolic states. As a proof-of-concept, we study three enzymes (catechol-O-methyltransferase, glucose-6-phosphate dehydrogenase, and glyceraldehyde-3-phosphate dehydrogenase and their respective genetic variants which have clinically relevant associations. Using all-atom molecular dynamic simulations enables the sampling of long timescale conformational dynamics of the proteins (and their mutant variants in complex with their respective native metabolites or drug molecules. We find that changes in a protein's structure due to a mutation influences protein binding affinity to metabolites and/or drug molecules, and inflicts large-scale changes in metabolism.
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.
Peng, L.; Sheffield, J.; Li, D.
2015-12-01
Evapotranspiration (ET) is a key link between the availability of water resources and climate change and climate variability. Variability of ET has important environmental and socioeconomic implications for managing hydrological hazards, food and energy production. Although there have been many observational and modeling studies of ET, how ET has varied and the drivers of the variations at different temporal scales remain elusive. Much of the uncertainty comes from the atmospheric evaporative demand (AED), which is the combined effect of radiative and aerodynamic controls. The inconsistencies among modeled AED estimates and the limited observational data may originate from multiple sources including the limited time span and uncertainties in the data. To fully investigate and untangle the intertwined drivers of AED, we present a spectrum analysis to identify key controls of AED across multiple temporal scales. We use long-term records of observed pan evaporation for 1961-2006 from 317 weather stations across China and physically-based model estimates of potential evapotranspiration (PET). The model estimates are based on surface meteorology and radiation derived from reanalysis, satellite retrievals and station data. Our analyses show that temperature plays a dominant role in regulating variability of AED at the inter-annual scale. At the monthly and seasonal scales, the primary control of AED shifts from radiation in humid regions to humidity in dry regions. Unlike many studies focusing on the spatial pattern of ET drivers based on a traditional supply and demand framework, this study underlines the importance of temporal scales when discussing controls of ET variations.
Food Access, Food Subsidy, and Residue-Based Bioenergy ...
International Development Research Centre (IDRC) Digital Library (Canada)
Food Access, Food Subsidy, and Residue-Based Bioenergy Production in ... The goal is to show how the Indian government can improve access to food ... IDRC has signed a Memorandum of Understanding (MoU) with the Government of ...
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.
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.
Multiscale methods in computational fluid and solid mechanics
Borst, de R.; Hulshoff, S.J.; Lenz, S.; Munts, E.A.; Brummelen, van E.H.; Wall, W.; Wesseling, P.; Onate, E.; Periaux, J.
2006-01-01
First, an attempt is made towards gaining a more systematic understanding of recent progress in multiscale modelling in computational solid and fluid mechanics. Sub- sequently, the discussion is focused on variational multiscale methods for the compressible and incompressible Navier-Stokes
Macklin, Paul; Cristini, Vittorio
2013-01-01
Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate predictions. A growing number of examples illustrate the value of this approach in providing quantitative insight on the initiation, progression, and treatment of cancer. In this review, we introduce the most recent and important multiscale cancer modeling works that have successfully established a mechanistic link between different biological scales. Biophysical, biochemical, and biomechanical factors are considered in these models. We also discuss innovative, cutting-edge modeling methods that are moving predictive multiscale cancer modeling toward clinical application. Furthermore, because the development of multiscale cancer models requires a new level of collaboration among scientists from a variety of fields such as biology, medicine, physics, mathematics, engineering, and computer science, an innovative Web-based infrastructure is needed to support this growing community. PMID:21529163
Multiscale Representations Phase II
National Research Council Canada - National Science Library
Bar-Yam, Yaneer
2004-01-01
.... Multiscale analysis provides an analytic tool that can be applied to evaluating force capabilities as well as the relevance of designs for technological innovations to support force structures and their modernization...
1990-02-21
LIDS-P-1953 Multiscale System Theory Albert Benveniste IRISA-INRIA, Campus de Beaulieu 35042 RENNES CEDEX, FRANCE Ramine Nikoukhah INRIA...TITLE AND SUBTITLE Multiscale System Theory 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e...the development of a corresponding system theory and a theory of stochastic processes and their estimation. The research presented in this and several
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...... dynamics. Recent work on the thermophoretic motion of water nanodroplets confined inside carbon nanotubes, and multiscale techniques for polar liquids will be discussed in detail at the symposium....
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
Multiscale Biological Materials
DEFF Research Database (Denmark)
Frølich, Simon
of multiscale biological systems have been investigated and new research methods for automated Rietveld refinement and diffraction scattering computed tomography developed. The composite nature of biological materials was investigated at the atomic scale by looking at the consequences of interactions between...
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
DEFF Research Database (Denmark)
Somchaipeng, Kerawit; Sporring, Jon; Johansen, Peter
2007-01-01
We propose MultiScale Singularity Trees (MSSTs) as a structure to represent images, and we propose an algorithm for image comparison based on comparing MSSTs. The algorithm is tested on 3 public image databases and compared to 2 state-of-theart methods. We conclude that the computational complexity...... of our algorithm only allows for the comparison of small trees, and that the results of our method are comparable with state-of-the-art using much fewer parameters for image representation....
Multiscale modelling of nanostructures
International Nuclear Information System (INIS)
Vvedensky, Dimitri D
2004-01-01
Most materials phenomena are manifestations of processes that are operative over a vast range of length and time scales. A complete understanding of the behaviour of materials thereby requires theoretical and computational tools that span the atomic-scale detail of first-principles methods and the more coarse-grained description provided by continuum equations. Recent efforts have focused on combining traditional methodologies-density functional theory, molecular dynamics, Monte Carlo methods and continuum descriptions-within a unified multiscale framework. This review covers the techniques that have been developed to model various aspects of materials behaviour with the ultimate aim of systematically coupling the atomistic to the continuum descriptions. The approaches described typically have been motivated by particular applications but can often be applied in wider contexts. The self-assembly of quantum dot ensembles will be used as a case study for the issues that arise and the methods used for all nanostructures. Although quantum dots can be obtained with all the standard growth methods and for a variety of material systems, their appearance is a quite selective process, involving the competition between equilibrium and kinetic effects, and the interplay between atomistic and long-range interactions. Most theoretical models have addressed particular aspects of the ordering kinetics of quantum dot ensembles, with far fewer attempts at a comprehensive synthesis of this inherently multiscale phenomenon. We conclude with an assessment of the current status of multiscale modelling strategies and highlight the main outstanding issues. (topical review)
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 computing in the exascale era
Alowayyed, S.; Groen, D.; Coveney, P.V.; Hoekstra, A.G.
We expect that multiscale simulations will be one of the main high performance computing workloads in the exascale era. We propose multiscale computing patterns as a generic vehicle to realise load balanced, fault tolerant and energy aware high performance multiscale computing. Multiscale computing
Multiscale reconstruction for MR fingerprinting.
Pierre, Eric Y; Ma, Dan; Chen, Yong; Badve, Chaitra; Griswold, Mark A
2016-06-01
To reduce the acquisition time needed to obtain reliable parametric maps with Magnetic Resonance Fingerprinting. An iterative-denoising algorithm is initialized by reconstructing the MRF image series at low image resolution. For subsequent iterations, the method enforces pixel-wise fidelity to the best-matching dictionary template then enforces fidelity to the acquired data at slightly higher spatial resolution. After convergence, parametric maps with desirable spatial resolution are obtained through template matching of the final image series. The proposed method was evaluated on phantom and in vivo data using the highly undersampled, variable-density spiral trajectory and compared with the original MRF method. The benefits of additional sparsity constraints were also evaluated. When available, gold standard parameter maps were used to quantify the performance of each method. The proposed approach allowed convergence to accurate parametric maps with as few as 300 time points of acquisition, as compared to 1000 in the original MRF work. Simultaneous quantification of T1, T2, proton density (PD), and B0 field variations in the brain was achieved in vivo for a 256 × 256 matrix for a total acquisition time of 10.2 s, representing a three-fold reduction in acquisition time. The proposed iterative multiscale reconstruction reliably increases MRF acquisition speed and accuracy. Magn Reson Med 75:2481-2492, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
Multiscale principal component analysis
International Nuclear Information System (INIS)
Akinduko, A A; Gorban, A N
2014-01-01
Principal component analysis (PCA) is an important tool in exploring data. The conventional approach to PCA leads to a solution which favours the structures with large variances. This is sensitive to outliers and could obfuscate interesting underlying structures. One of the equivalent definitions of PCA is that it seeks the subspaces that maximize the sum of squared pairwise distances between data projections. This definition opens up more flexibility in the analysis of principal components which is useful in enhancing PCA. In this paper we introduce scales into PCA by maximizing only the sum of pairwise distances between projections for pairs of datapoints with distances within a chosen interval of values [l,u]. The resulting principal component decompositions in Multiscale PCA depend on point (l,u) on the plane and for each point we define projectors onto principal components. Cluster analysis of these projectors reveals the structures in the data at various scales. Each structure is described by the eigenvectors at the medoid point of the cluster which represent the structure. We also use the distortion of projections as a criterion for choosing an appropriate scale especially for data with outliers. This method was tested on both artificial distribution of data and real data. For data with multiscale structures, the method was able to reveal the different structures of the data and also to reduce the effect of outliers in the principal component analysis
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.
A stochastic multiscale framework for modeling flow through random heterogeneous porous media
International Nuclear Information System (INIS)
Ganapathysubramanian, B.; Zabaras, N.
2009-01-01
Flow through porous media is ubiquitous, occurring from large geological scales down to the microscopic scales. Several critical engineering phenomena like contaminant spread, nuclear waste disposal and oil recovery rely on accurate analysis and prediction of these multiscale phenomena. Such analysis is complicated by inherent uncertainties as well as the limited information available to characterize the system. Any realistic modeling of these transport phenomena has to resolve two key issues: (i) the multi-length scale variations in permeability that these systems exhibit, and (ii) the inherently limited information available to quantify these property variations that necessitates posing these phenomena as stochastic processes. A stochastic variational multiscale formulation is developed to incorporate uncertain multiscale features. A stochastic analogue to a mixed multiscale finite element framework is used to formulate the physical stochastic multiscale process. Recent developments in linear and non-linear model reduction techniques are used to convert the limited information available about the permeability variation into a viable stochastic input model. An adaptive sparse grid collocation strategy is used to efficiently solve the resulting stochastic partial differential equations (SPDEs). The framework is applied to analyze flow through random heterogeneous media when only limited statistics about the permeability variation are given
Quantitative determination of pefloxacin mesylate by residual-base neutralisation method
Directory of Open Access Journals (Sweden)
HULIKALCHANDRA SHEKAR PRAMEELA
2004-05-01
Full Text Available This work describes two procedures based on residual base determination for the quantification of pefloxacin mesylate (PFM in bulk drug and in pharmaceutical products. In the first method involving titrimetry, the drug solution is treated with a measured excess of sodium hydroxide followed by back titration of the residual base with hydrochloric acid using a phenol red-bromothymol blue mixed indicator. The second spectrophotometrie method involves treatment of a fixed amount of sodium hydroxide phenol red mixture with varying amounts of the drug, and measuring the decrease in the absorbance of the dye at 560 nm. In the titrimetric method, a reaction stoichiometry of 1:1 was found in the quantification range of 420 mg of drug. The spectrophotometric method allows the determination of PFM in the 540 mg ml-1 range. The molar absorptivity is 5.91¤103 l mol-1 cm-1 and the Sandell sensitivity is 56.37 ng cm-2. The methods were applied successfully to the determination of PFM in pharmaceutical preparations.
Hybrid continuum–molecular modelling of multiscale internal gas flows
International Nuclear Information System (INIS)
Patronis, Alexander; Lockerby, Duncan A.; Borg, Matthew K.; Reese, Jason M.
2013-01-01
We develop and apply an efficient multiscale method for simulating a large class of low-speed internal rarefied gas flows. The method is an extension of the hybrid atomistic–continuum approach proposed by Borg et al. (2013) [28] for the simulation of micro/nano flows of high-aspect ratio. The major new extensions are: (1) incorporation of fluid compressibility; (2) implementation using the direct simulation Monte Carlo (DSMC) method for dilute rarefied gas flows, and (3) application to a broader range of geometries, including periodic, non-periodic, pressure-driven, gravity-driven and shear-driven internal flows. The multiscale method is applied to micro-scale gas flows through a periodic converging–diverging channel (driven by an external acceleration) and a non-periodic channel with a bend (driven by a pressure difference), as well as the flow between two eccentric cylinders (with the inner rotating relative to the outer). In all these cases there exists a wide variation of Knudsen number within the geometries, as well as substantial compressibility despite the Mach number being very low. For validation purposes, our multiscale simulation results are compared to those obtained from full-scale DSMC simulations: very close agreement is obtained in all cases for all flow variables considered. Our multiscale simulation is an order of magnitude more computationally efficient than the full-scale DSMC for the first and second test cases, and two orders of magnitude more efficient for the third case
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.;
2014-01-01
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 onboard 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.
Statistical CT noise reduction with multiscale decomposition and penalized weighted least squares in the projection domain
International Nuclear Information System (INIS)
Tang Shaojie; Tang Xiangyang
2012-01-01
Purposes: The suppression of noise in x-ray computed tomography (CT) imaging is of clinical relevance for diagnostic image quality and the potential for radiation dose saving. Toward this purpose, statistical noise reduction methods in either the image or projection domain have been proposed, which employ a multiscale decomposition to enhance the performance of noise suppression while maintaining image sharpness. Recognizing the advantages of noise suppression in the projection domain, the authors propose a projection domain multiscale penalized weighted least squares (PWLS) method, in which the angular sampling rate is explicitly taken into consideration to account for the possible variation of interview sampling rate in advanced clinical or preclinical applications. Methods: The projection domain multiscale PWLS method is derived by converting an isotropic diffusion partial differential equation in the image domain into the projection domain, wherein a multiscale decomposition is carried out. With adoption of the Markov random field or soft thresholding objective function, the projection domain multiscale PWLS method deals with noise at each scale. To compensate for the degradation in image sharpness caused by the projection domain multiscale PWLS method, an edge enhancement is carried out following the noise reduction. The performance of the proposed method is experimentally evaluated and verified using the projection data simulated by computer and acquired by a CT scanner. Results: The preliminary results show that the proposed projection domain multiscale PWLS method outperforms the projection domain single-scale PWLS method and the image domain multiscale anisotropic diffusion method in noise reduction. In addition, the proposed method can preserve image sharpness very well while the occurrence of “salt-and-pepper” noise and mosaic artifacts can be avoided. Conclusions: Since the interview sampling rate is taken into account in the projection domain
Prediction of interface residue based on the features of residue interaction network.
Jiao, Xiong; Ranganathan, Shoba
2017-11-07
Protein-protein interaction plays a crucial role in the cellular biological processes. Interface prediction can improve our understanding of the molecular mechanisms of the related processes and functions. In this work, we propose a classification method to recognize the interface residue based on the features of a weighted residue interaction network. The random forest algorithm is used for the prediction and 16 network parameters and the B-factor are acting as the element of the input feature vector. Compared with other similar work, the method is feasible and effective. The relative importance of these features also be analyzed to identify the key feature for the prediction. Some biological meaning of the important feature is explained. The results of this work can be used for the related work about the structure-function relationship analysis via a residue interaction network model. Copyright © 2017 Elsevier Ltd. All rights reserved.
Multiscale decomposition for heterogeneous land-atmosphere systems
Liu, Shaofeng; Shao, Yaping; Hintz, Michael; Lennartz-Sassinek, Sabine
2015-02-01
The land-atmosphere system is characterized by pronounced land surface heterogeneity and vigorous atmospheric turbulence both covering a wide range of scales. The multiscale surface heterogeneities and multiscale turbulent eddies interact nonlinearly with each other. Understanding these multiscale processes quantitatively is essential to the subgrid parameterizations for weather and climate models. In this paper, we propose a method for surface heterogeneity quantification and turbulence structure identification. The first part of the method is an orthogonal transform in the probability density function (PDF) domain, in contrast to the orthogonal wavelet transforms which are performed in the physical space. As the basis of the whole method, the orthogonal PDF transform (OPT) is used to asymptotically reconstruct the original signals by representing the signal values with multilevel approximations. The "patch" idea is then applied to these reconstructed fields in order to recognize areas at the land surface or in turbulent flows that are of the same characteristics. A patch here is a connected area with the same approximation. For each recognized patch, a length scale is then defined to build the energy spectrum. The OPT and related energy spectrum analysis, as a whole referred to as the orthogonal PDF decomposition (OPD), is applied to two-dimensional heterogeneous land surfaces and atmospheric turbulence fields for test. The results show that compared to the wavelet transforms, the OPD can reconstruct the original signal more effectively, and accordingly, its energy spectrum represents the signal's multiscale variation more accurately. The method we propose in this paper is of general nature and therefore can be of interest for problems of multiscale process description in other geophysical disciplines.
Multiscale scenarios for nature futures
CSIR Research Space (South Africa)
Rosa, IMD
2017-09-01
Full Text Available & Evolution, vol. 1: 1416-1419 Multiscale scenarios for nature futures Rosa IMD Pereira HM Ferrier S Alkemade R Acosta LA Akcakaya HR den Belder E Fazel AM Fujimori S Sitas NE ABSTRACT: Targets for human development are increasingly...
Multiscale mechanics of dynamical metamaterials
Geers, M.G.D.; Kouznetsova, V.; Sridhar, A.; Krushynska, A.; Kleiber, M.; Burczynski, T.; Wilde, K.; Gorski, J.; Winkelmann, K.; Smakosz, L.
2016-01-01
This contribution focuses on the computational multi-scale solution of wave propagation phenomena in dynamic metamaterials. Taking the Bloch-Floquet solution for the standard elastic case as a point of departure, an extended scheme is presented to solve for heterogeneous visco-elastic materials. The
Multiscale geometric modeling of macromolecules II: Lagrangian representation
Feng, Xin; Xia, Kelin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei
2013-01-01
Geometric modeling of biomolecules plays an essential role in the conceptualization of biolmolecular structure, function, dynamics and transport. Qualitatively, geometric modeling offers a basis for molecular visualization, which is crucial for the understanding of molecular structure and interactions. Quantitatively, geometric modeling bridges the gap between molecular information, such as that from X-ray, NMR and cryo-EM, and theoretical/mathematical models, such as molecular dynamics, the Poisson-Boltzmann equation and the Nernst-Planck equation. In this work, we present a family of variational multiscale geometric models for macromolecular systems. Our models are able to combine multiresolution geometric modeling with multiscale electrostatic modeling in a unified variational framework. We discuss a suite of techniques for molecular surface generation, molecular surface meshing, molecular volumetric meshing, and the estimation of Hadwiger’s functionals. Emphasis is given to the multiresolution representations of biomolecules and the associated multiscale electrostatic analyses as well as multiresolution curvature characterizations. The resulting fine resolution representations of a biomolecular system enable the detailed analysis of solvent-solute interaction, and ion channel dynamics, while our coarse resolution representations highlight the compatibility of protein-ligand bindings and possibility of protein-protein interactions. PMID:23813599
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
Raman, M R Gauthama; Somu, Nivethitha; Kirthivasan, Kannan; Sriram, V S Shankar
2017-08-01
Over the past few decades, the design of an intelligent Intrusion Detection System (IDS) remains an open challenge to the research community. Continuous efforts by the researchers have resulted in the development of several learning models based on Artificial Neural Network (ANN) to improve the performance of the IDSs. However, there exists a tradeoff with respect to the stability of ANN architecture and the detection rate for less frequent attacks. This paper presents a novel approach based on Helly property of Hypergraph and Arithmetic Residue-based Probabilistic Neural Network (HG AR-PNN) to address the classification problem in IDS. The Helly property of Hypergraph was exploited for the identification of the optimal feature subset and the arithmetic residue of the optimal feature subset was used to train the PNN. The performance of HG AR-PNN was evaluated using KDD CUP 1999 intrusion dataset. Experimental results prove the dominance of HG AR-PNN classifier over the existing classifiers with respect to the stability and improved detection rate for less frequent attacks. Copyright © 2017 Elsevier Ltd. All rights reserved.
MULTISCALE THERMOHYDROLOGIC MODEL
International Nuclear Information System (INIS)
T. Buscheck
2005-01-01
The intended purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. The goal of the MSTHM is to predict a reasonable range of possible thermal-hydrologic conditions within the emplacement drift. To be reasonable, this range includes the influence of waste-package-to-waste-package heat output variability relevant to the license application design, as well as the influence of uncertainty and variability in the geologic and hydrologic conditions relevant to predicting the thermal-hydrologic response in emplacement drifts. This goal is quite different from the goal of a model to predict a single expected thermal-hydrologic response. As a result, the development and validation of the MSTHM and the associated analyses using this model are focused on the goal of predicting a reasonable range of thermal-hydrologic conditions resulting from parametric uncertainty and waste-package-to-waste-package heat-output variability. Thermal-hydrologic conditions within emplacement drifts depend primarily on thermal-hydrologic conditions in the host rock at the drift wall and on the temperature difference between the drift wall and the drip-shield and waste-package surfaces. Thus, the ability to predict a reasonable range of relevant in-drift MSTHM output parameters (e.g., temperature and relative humidity) is based on valid predictions of thermal-hydrologic processes in the host rock, as well as valid predictions of heat-transfer processes between the drift wall and the drip-shield and waste-package surfaces. Because the invert contains crushed gravel derived from the host rock, the invert is, in effect, an extension of the host rock, with thermal and hydrologic properties that have been modified by virtue of the crushing (and the resulting
The Magnetospheric Multiscale Mission
Burch, James
Magnetospheric Multiscale (MMS), a NASA four-spacecraft mission scheduled for launch in November 2014, will investigate magnetic reconnection in the boundary regions of the Earth’s magnetosphere, particularly along its dayside boundary with the solar wind and the neutral sheet in the magnetic tail. Among the important questions about reconnection that will be addressed are the following: Under what conditions can magnetic-field energy be converted to plasma energy by the annihilation of magnetic field through reconnection? How does reconnection vary with time, and what factors influence its temporal behavior? What microscale processes are responsible for reconnection? What determines the rate of reconnection? In order to accomplish its goals the MMS spacecraft must probe both those regions in which the magnetic fields are very nearly antiparallel and regions where a significant guide field exists. From previous missions we know the approximate speeds with which reconnection layers move through space to be from tens to hundreds of km/s. For electron skin depths of 5 to 10 km, the full 3D electron population (10 eV to above 20 keV) has to be sampled at rates greater than 10/s. The MMS Fast-Plasma Instrument (FPI) will sample electrons at greater than 30/s. Because the ion skin depth is larger, FPI will make full ion measurements at rates of greater than 6/s. 3D E-field measurements will be made by MMS once every ms. MMS will use an Active Spacecraft Potential Control device (ASPOC), which emits indium ions to neutralize the photoelectron current and keep the spacecraft from charging to more than +4 V. Because ion dynamics in Hall reconnection depend sensitively on ion mass, MMS includes a new-generation Hot Plasma Composition Analyzer (HPCA) that corrects problems with high proton fluxes that have prevented accurate ion-composition measurements near the dayside magnetospheric boundary. Finally, Energetic Particle Detector (EPD) measurements of electrons and
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
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.
Zanin, Massimiliano; Chorbev, Ivan; Stres, Blaz; Stalidzans, Egils; Vera, Julio; Tieri, Paolo; Castiglione, Filippo; Groen, Derek; Zheng, Huiru; Baumbach, Jan; Schmid, Johannes A; Basilio, José; Klimek, Peter; Debeljak, Nataša; Rozman, Damjana; Schmidt, Harald H H W
2017-12-05
Systems medicine holds many promises, but has so far provided only a limited number of proofs of principle. To address this road block, possible barriers and challenges of translating systems medicine into clinical practice need to be identified and addressed. The members of the European Cooperation in Science and Technology (COST) Action CA15120 Open Multiscale Systems Medicine (OpenMultiMed) wish to engage the scientific community of systems medicine and multiscale modelling, data science and computing, to provide their feedback in a structured manner. This will result in follow-up white papers and open access resources to accelerate the clinical translation of systems medicine. © The Author 2017. Published by Oxford University Press.
Differential Geometry Based Multiscale Models
Wei, Guo-Wei
2010-01-01
Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atom-istic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier–Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson–Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson–Nernst–Planck equations that
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
Julia I. Burton; Lisa M. Ganio; Klaus J. Puettmann
2014-01-01
Forest understory vegetation is influenced by broad-scale variation in climate, intermediate scale variation in topography, disturbance and neighborhood interactions. However, little is known about how these multi-scale controls interact to influence observed spatial patterns. We examined relationships between the aggregated cover of understory plant species (%...
Multiscale Simulation of Breaking Wave Impacts
DEFF Research Database (Denmark)
Lindberg, Ole
compare reasonably well. The incompressible and inviscid ALE-WLS model is coupled with the potential flow model of Engsig-Karup et al. [2009], to perform multiscale calculation of breaking wave impacts on a vertical breakwater. The potential flow model provides accurate calculation of the wave...... with a potential flow model to provide multiscale calculation of forces from breaking wave impacts on structures....
Multi-scale organization of water vapor over low and mid-tropical Africa
CSIR Research Space (South Africa)
Botai, OJ
2009-01-01
Full Text Available stream_source_info Botai_2009.pdf.txt stream_content_type text/plain stream_size 23192 Content-Encoding UTF-8 stream_name Botai_2009.pdf.txt Content-Type text/plain; charset=UTF-8 1 MULTI-SCALE ORGANIZATION OF WATER.... Integrated water vapor field and multiscale variations over China from GPS measurements. J. appl., Meteo., Climatol., 47, pp. 3008-3015 8. Johnsen K. P., 2003. GPS atmosphere sounding project- An innovative approach for the recovery of atmospheric...
Multivariate refined composite multiscale entropy analysis
International Nuclear Information System (INIS)
Humeau-Heurtier, Anne
2016-01-01
Multiscale entropy (MSE) has become a prevailing method to quantify signals complexity. MSE relies on sample entropy. However, MSE may yield imprecise complexity estimation at large scales, because sample entropy does not give precise estimation of entropy when short signals are processed. A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. Nevertheless, RCMSE is for univariate signals only. The simultaneous analysis of multi-channel (multivariate) data often over-performs studies based on univariate signals. We therefore introduce an extension of RCMSE to multivariate data. Applications of multivariate RCMSE to simulated processes reveal its better performances over the standard multivariate MSE. - Highlights: • Multiscale entropy quantifies data complexity but may be inaccurate at large scale. • A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. • Nevertheless, RCMSE is adapted to univariate time series only. • We herein introduce an extension of RCMSE to multivariate data. • It shows better performances than the standard multivariate multiscale entropy.
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.
Multiscale spatial and temporal estimation of the b-value
García-Hernández, R.; D'Auria, L.; Barrancos, J.; Padilla, G.
2017-12-01
The estimation of the spatial and temporal variations of the Gutenberg-Richter b-value is of great importance in different seismological applications. One of the problems affecting its estimation is the heterogeneous distribution of the seismicity which makes its estimate strongly dependent upon the selected spatial and/or temporal scale. This is especially important in volcanoes where dense clusters of earthquakes often overlap the background seismicity. Proposed solutions for estimating temporal variations of the b-value include considering equally spaced time intervals or variable intervals having an equal number of earthquakes. Similar approaches have been proposed to image the spatial variations of this parameter as well.We propose a novel multiscale approach, based on the method of Ogata and Katsura (1993), allowing a consistent estimation of the b-value regardless of the considered spatial and/or temporal scales. Our method, named MUST-B (MUltiscale Spatial and Temporal characterization of the B-value), basically consists in computing estimates of the b-value at multiple temporal and spatial scales, extracting for a give spatio-temporal point a statistical estimator of the value, as well as and indication of the characteristic spatio-temporal scale. This approach includes also a consistent estimation of the completeness magnitude (Mc) and of the uncertainties over both b and Mc.We applied this method to example datasets for volcanic (Tenerife, El Hierro) and tectonic areas (Central Italy) as well as an example application at global scale.
Multiscale Molecular Dynamics Model for Heterogeneous Charged Systems
Stanton, L. G.; Glosli, J. N.; Murillo, M. S.
2018-04-01
Modeling matter across large length scales and timescales using molecular dynamics simulations poses significant challenges. These challenges are typically addressed through the use of precomputed pair potentials that depend on thermodynamic properties like temperature and density; however, many scenarios of interest involve spatiotemporal variations in these properties, and such variations can violate assumptions made in constructing these potentials, thus precluding their use. In particular, when a system is strongly heterogeneous, most of the usual simplifying assumptions (e.g., spherical potentials) do not apply. Here, we present a multiscale approach to orbital-free density functional theory molecular dynamics (OFDFT-MD) simulations that bridges atomic, interionic, and continuum length scales to allow for variations in hydrodynamic quantities in a consistent way. Our multiscale approach enables simulations on the order of micron length scales and 10's of picosecond timescales, which exceeds current OFDFT-MD simulations by many orders of magnitude. This new capability is then used to study the heterogeneous, nonequilibrium dynamics of a heated interface characteristic of an inertial-confinement-fusion capsule containing a plastic ablator near a fuel layer composed of deuterium-tritium ice. At these scales, fundamental assumptions of continuum models are explored; features such as the separation of the momentum fields among the species and strong hydrogen jetting from the plastic into the fuel region are observed, which had previously not been seen in hydrodynamic simulations.
Quantum theory of multiscale coarse-graining.
Han, Yining; Jin, Jaehyeok; Wagner, Jacob W; Voth, Gregory A
2018-03-14
Coarse-grained (CG) models serve as a powerful tool to simulate molecular systems at much longer temporal and spatial scales. Previously, CG models and methods have been built upon classical statistical mechanics. The present paper develops a theory and numerical methodology for coarse-graining in quantum statistical mechanics, by generalizing the multiscale coarse-graining (MS-CG) method to quantum Boltzmann statistics. A rigorous derivation of the sufficient thermodynamic consistency condition is first presented via imaginary time Feynman path integrals. It identifies the optimal choice of CG action functional and effective quantum CG (qCG) force field to generate a quantum MS-CG (qMS-CG) description of the equilibrium system that is consistent with the quantum fine-grained model projected onto the CG variables. A variational principle then provides a class of algorithms for optimally approximating the qMS-CG force fields. Specifically, a variational method based on force matching, which was also adopted in the classical MS-CG theory, is generalized to quantum Boltzmann statistics. The qMS-CG numerical algorithms and practical issues in implementing this variational minimization procedure are also discussed. Then, two numerical examples are presented to demonstrate the method. Finally, as an alternative strategy, a quasi-classical approximation for the thermal density matrix expressed in the CG variables is derived. This approach provides an interesting physical picture for coarse-graining in quantum Boltzmann statistical mechanics in which the consistency with the quantum particle delocalization is obviously manifest, and it opens up an avenue for using path integral centroid-based effective classical force fields in a coarse-graining methodology.
Quantum theory of multiscale coarse-graining
Han, Yining; Jin, Jaehyeok; Wagner, Jacob W.; Voth, Gregory A.
2018-03-01
Coarse-grained (CG) models serve as a powerful tool to simulate molecular systems at much longer temporal and spatial scales. Previously, CG models and methods have been built upon classical statistical mechanics. The present paper develops a theory and numerical methodology for coarse-graining in quantum statistical mechanics, by generalizing the multiscale coarse-graining (MS-CG) method to quantum Boltzmann statistics. A rigorous derivation of the sufficient thermodynamic consistency condition is first presented via imaginary time Feynman path integrals. It identifies the optimal choice of CG action functional and effective quantum CG (qCG) force field to generate a quantum MS-CG (qMS-CG) description of the equilibrium system that is consistent with the quantum fine-grained model projected onto the CG variables. A variational principle then provides a class of algorithms for optimally approximating the qMS-CG force fields. Specifically, a variational method based on force matching, which was also adopted in the classical MS-CG theory, is generalized to quantum Boltzmann statistics. The qMS-CG numerical algorithms and practical issues in implementing this variational minimization procedure are also discussed. Then, two numerical examples are presented to demonstrate the method. Finally, as an alternative strategy, a quasi-classical approximation for the thermal density matrix expressed in the CG variables is derived. This approach provides an interesting physical picture for coarse-graining in quantum Boltzmann statistical mechanics in which the consistency with the quantum particle delocalization is obviously manifest, and it opens up an avenue for using path integral centroid-based effective classical force fields in a coarse-graining methodology.
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.
Peridynamic Multiscale Finite Element Methods
Energy Technology Data Exchange (ETDEWEB)
Costa, Timothy [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bond, Stephen D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Littlewood, David John [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Moore, Stan Gerald [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-12-01
The problem of computing quantum-accurate design-scale solutions to mechanics problems is rich with applications and serves as the background to modern multiscale science research. The prob- lem can be broken into component problems comprised of communicating across adjacent scales, which when strung together create a pipeline for information to travel from quantum scales to design scales. Traditionally, this involves connections between a) quantum electronic structure calculations and molecular dynamics and between b) molecular dynamics and local partial differ- ential equation models at the design scale. The second step, b), is particularly challenging since the appropriate scales of molecular dynamic and local partial differential equation models do not overlap. The peridynamic model for continuum mechanics provides an advantage in this endeavor, as the basic equations of peridynamics are valid at a wide range of scales limiting from the classical partial differential equation models valid at the design scale to the scale of molecular dynamics. In this work we focus on the development of multiscale finite element methods for the peridynamic model, in an effort to create a mathematically consistent channel for microscale information to travel from the upper limits of the molecular dynamics scale to the design scale. In particular, we first develop a Nonlocal Multiscale Finite Element Method which solves the peridynamic model at multiple scales to include microscale information at the coarse-scale. We then consider a method that solves a fine-scale peridynamic model to build element-support basis functions for a coarse- scale local partial differential equation model, called the Mixed Locality Multiscale Finite Element Method. Given decades of research and development into finite element codes for the local partial differential equation models of continuum mechanics there is a strong desire to couple local and nonlocal models to leverage the speed and state of the
DEFF Research Database (Denmark)
Adamczyk, Andrzej Grzegorz; Teodorescu, Remus; Iov, Florin
2012-01-01
Low frequency inter-area oscillations are known stability issue of large interconnected electrical grids. It was demonstrated that additional control loop can be applied for static power sources, like FACTS, HVDC or modern Wind Power Plants, to modulate their power output and successfully attenuate......, it is proposed to give more attention to additional indices like transfer function zero location and interactions between mode of interest and other system dynamics. Consequently, additional rules are proposed for residue based damping control design....
Multiscale Reconstruction for Magnetic Resonance Fingerprinting
Pierre, Eric Y.; Ma, Dan; Chen, Yong; Badve, Chaitra; Griswold, Mark A.
2015-01-01
Purpose To reduce acquisition time needed to obtain reliable parametric maps with Magnetic Resonance Fingerprinting. Methods An iterative-denoising algorithm is initialized by reconstructing the MRF image series at low image resolution. For subsequent iterations, the method enforces pixel-wise fidelity to the best-matching dictionary template then enforces fidelity to the acquired data at slightly higher spatial resolution. After convergence, parametric maps with desirable spatial resolution are obtained through template matching of the final image series. The proposed method was evaluated on phantom and in-vivo data using the highly-undersampled, variable-density spiral trajectory and compared with the original MRF method. The benefits of additional sparsity constraints were also evaluated. When available, gold standard parameter maps were used to quantify the performance of each method. Results The proposed approach allowed convergence to accurate parametric maps with as few as 300 time points of acquisition, as compared to 1000 in the original MRF work. Simultaneous quantification of T1, T2, proton density (PD) and B0 field variations in the brain was achieved in vivo for a 256×256 matrix for a total acquisition time of 10.2s, representing a 3-fold reduction in acquisition time. Conclusions The proposed iterative multiscale reconstruction reliably increases MRF acquisition speed and accuracy. PMID:26132462
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
Multiscale geometric modeling of macromolecules I: Cartesian representation
Energy Technology Data Exchange (ETDEWEB)
Xia, Kelin [Department of Mathematics, Michigan State University, MI 48824 (United States); Feng, Xin [Department of Computer Science and Engineering, Michigan State University, MI 48824 (United States); Chen, Zhan [Department of Mathematics, Michigan State University, MI 48824 (United States); Tong, Yiying [Department of Computer Science and Engineering, Michigan State University, MI 48824 (United States); Wei, Guo-Wei, E-mail: wei@math.msu.edu [Department of Mathematics, Michigan State University, MI 48824 (United States); Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824 (United States)
2014-01-15
This paper focuses on the geometric modeling and computational algorithm development of biomolecular structures from two data sources: Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in the Eulerian (or Cartesian) representation. Molecular surface (MS) contains non-smooth geometric singularities, such as cusps, tips and self-intersecting facets, which often lead to computational instabilities in molecular simulations, and violate the physical principle of surface free energy minimization. Variational multiscale surface definitions are proposed based on geometric flows and solvation analysis of biomolecular systems. Our approach leads to geometric and potential driven Laplace–Beltrami flows for biomolecular surface evolution and formation. The resulting surfaces are free of geometric singularities and minimize the total free energy of the biomolecular system. High order partial differential equation (PDE)-based nonlinear filters are employed for EMDB data processing. We show the efficacy of this approach in feature-preserving noise reduction. After the construction of protein multiresolution surfaces, we explore the analysis and characterization of surface morphology by using a variety of curvature definitions. Apart from the classical Gaussian curvature and mean curvature, maximum curvature, minimum curvature, shape index, and curvedness are also applied to macromolecular surface analysis for the first time. Our curvature analysis is uniquely coupled to the analysis of electrostatic surface potential, which is a by-product of our variational multiscale solvation models. As an expository investigation, we particularly emphasize the numerical algorithms and computational protocols for practical applications of the above multiscale geometric models. Such information may otherwise be scattered over the vast literature on this topic. Based on the curvature and electrostatic analysis from our multiresolution surfaces, we introduce a new concept, the
Multiscale modelling for tokamak pedestals
Abel, I. G.
2018-04-01
Pedestal modelling is crucial to predict the performance of future fusion devices. Current modelling efforts suffer either from a lack of kinetic physics, or an excess of computational complexity. To ameliorate these problems, we take a first-principles multiscale approach to the pedestal. We will present three separate sets of equations, covering the dynamics of edge localised modes (ELMs), the inter-ELM pedestal and pedestal turbulence, respectively. Precisely how these equations should be coupled to each other is covered in detail. This framework is completely self-consistent; it is derived from first principles by means of an asymptotic expansion of the fundamental Vlasov-Landau-Maxwell system in appropriate small parameters. The derivation exploits the narrowness of the pedestal region, the smallness of the thermal gyroradius and the low plasma (the ratio of thermal to magnetic pressures) typical of current pedestal operation to achieve its simplifications. The relationship between this framework and gyrokinetics is analysed, and possibilities to directly match our systems of equations onto multiscale gyrokinetics are explored. A detailed comparison between our model and other models in the literature is performed. Finally, the potential for matching this framework onto an open-field-line region is briefly discussed.
Multifunctional multiscale composites: Processing, modeling and characterization
Qiu, Jingjing
Carbon nanotubes (CNTs) demonstrate extraordinary properties and show great promise in enhancing out-of-plane properties of traditional polymer/fiber composites and enabling functionality. However, current manufacturing challenges hinder the realization of their potential. In the dissertation research, both experimental and computational efforts have been conducted to investigate effective manufacturing techniques of CNT integrated multiscale composites. The fabricated composites demonstrated significant improvements in physical properties, such as tensile strength, tensile modulus, inter-laminar shear strength, thermal dimension stability and electrical conductivity. Such multiscale composites were truly multifunctional with the addition of CNTs. Furthermore, a novel hierarchical multiscale modeling method was developed in this research. Molecular dynamic (MD) simulation offered reasonable explanation of CNTs dispersion and their motion in polymer solution. Bi-mode finite-extensible-nonlinear-elastic (FENE) dumbbell simulation was used to analyze the influence of CNT length distribution on the stress tensor and shear-rate-dependent viscosity. Based on the simulated viscosity profile and empirical equations from experiments, a macroscale flow simulation model on the finite element method (FEM) method was developed and validated to predict resin flow behavior in the processing of CNT-enhanced multiscale composites. The proposed multiscale modeling method provided a comprehensive understanding of micro/nano flow in both atomistic details and mesoscale. The simulation model can be used to optimize process design and control of the mold-filling process in multiscale composite manufacturing. This research provided systematic investigations into the CNT-based multiscale composites. The results from this study may be used to leverage the benefits of CNTs and open up new application opportunities for high-performance multifunctional multiscale composites. Keywords. Carbon
Gao, Kai
2015-04-14
It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both boundaries and the interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale medium property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.
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. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Foundations for a multiscale collaborative Earth model
Afanasiev, M.; Peter, Daniel; Sager, K.; Simut, S.; Ermert, L.; Krischer, L.; Fichtner, A.
2015-01-01
. The CSEM as a computational framework is intended to help bridging the gap between local, regional and global tomography, and to contribute to the development of a global multiscale Earth model. While the current construction serves as a first proof
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 Wear Degradation
Moraes, Alvaro; Ruggeri, Fabrizio; Tempone, Raul; Vilanova, Pedro
2016-01-01
Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.
Multiscale Modeling of Wear Degradation
Moraes, Alvaro; Ruggeri, Fabrizio; Tempone, Raul; Vilanova, Pedro
2015-01-01
Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.
Multiscale Modeling of Wear Degradation
Moraes, Alvaro
2015-01-07
Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.
Multiscale Modeling of Wear Degradation
Moraes, Alvaro
2014-01-06
Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.
Multiscale Modeling of Wear Degradation
Moraes, Alvaro
2016-01-06
Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.
Wavelets and multiscale signal processing
Cohen, Albert
1995-01-01
Since their appearance in mid-1980s, wavelets and, more generally, multiscale methods have become powerful tools in mathematical analysis and in applications to numerical analysis and signal processing. This book is based on "Ondelettes et Traitement Numerique du Signal" by Albert Cohen. It has been translated from French by Robert D. Ryan and extensively updated by both Cohen and Ryan. It studies the existing relations between filter banks and wavelet decompositions and shows how these relations can be exploited in the context of digital signal processing. Throughout, the book concentrates on the fundamentals. It begins with a chapter on the concept of multiresolution analysis, which contains complete proofs of the basic results. The description of filter banks that are related to wavelet bases is elaborated in both the orthogonal case (Chapter 2), and in the biorthogonal case (Chapter 4). The regularity of wavelets, how this is related to the properties of the filters and the importance of regularity for t...
Multiphysics/multiscale multifluid computations
International Nuclear Information System (INIS)
Yadigaroglu, George
2014-01-01
Regarding experimentation, interesting examples of multi-scale approaches are found: the small-scale experiments to understand the mechanisms of counter-current flow limitations (CCFL) such as the growth of instabilities on films, droplet entrainment, etc; meso-scale experiments to quantify the CCFL conditions in typical geometries such as tubes and gaps between parallel plates, and finally full-scale experimentation in a typical reactor geometry - the UPTF tests. Another example is the mixing of the atmosphere produced by plumes and jets in a reactor containment: one needs first basic turbulence information that can be obtained at the microscopic level; follow medium-scale experiments to understand the behaviour of jets and plumes; finally reactor-scale tests can be conducted in facilities such as PANDA at PSI, in Switzerland to study the phenomena at large scale
Multiscale modelling of DNA mechanics
International Nuclear Information System (INIS)
Dršata, Tomáš; Lankaš, Filip
2015-01-01
Mechanical properties of DNA are important not only in a wide range of biological processes but also in the emerging field of DNA nanotechnology. We review some of the recent developments in modeling these properties, emphasizing the multiscale nature of the problem. Modern atomic resolution, explicit solvent molecular dynamics simulations have contributed to our understanding of DNA fine structure and conformational polymorphism. These simulations may serve as data sources to parameterize rigid base models which themselves have undergone major development. A consistent buildup of larger entities involving multiple rigid bases enables us to describe DNA at more global scales. Free energy methods to impose large strains on DNA, as well as bead models and other approaches, are also briefly discussed. (topical review)
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.
Integrated multi-scale modelling and simulation of nuclear fuels
International Nuclear Information System (INIS)
Valot, C.; Bertolus, M.; Masson, R.; Malerba, L.; Rachid, J.; Besmann, T.; Phillpot, S.; Stan, M.
2015-01-01
This chapter aims at discussing the objectives, implementation and integration of multi-scale modelling approaches applied to nuclear fuel materials. We will first show why the multi-scale modelling approach is required, due to the nature of the materials and by the phenomena involved under irradiation. We will then present the multiple facets of multi-scale modelling approach, while giving some recommendations with regard to its application. We will also show that multi-scale modelling must be coupled with appropriate multi-scale experiments and characterisation. Finally, we will demonstrate how multi-scale modelling can contribute to solving technology issues. (authors)
A concurrent multiscale micromorphic molecular dynamics
International Nuclear Information System (INIS)
Li, Shaofan; Tong, Qi
2015-01-01
In this work, we have derived a multiscale micromorphic molecular dynamics (MMMD) from first principle to extend the (Andersen)-Parrinello-Rahman molecular dynamics to mesoscale and continuum scale. The multiscale micromorphic molecular dynamics is a con-current three-scale dynamics that couples a fine scale molecular dynamics, a mesoscale micromorphic dynamics, and a macroscale nonlocal particle dynamics together. By choosing proper statistical closure conditions, we have shown that the original Andersen-Parrinello-Rahman molecular dynamics is the homogeneous and equilibrium case of the proposed multiscale micromorphic molecular dynamics. In specific, we have shown that the Andersen-Parrinello-Rahman molecular dynamics can be rigorously formulated and justified from first principle, and its general inhomogeneous case, i.e., the three scale con-current multiscale micromorphic molecular dynamics can take into account of macroscale continuum mechanics boundary condition without the limitation of atomistic boundary condition or periodic boundary conditions. The discovered multiscale scale structure and the corresponding multiscale dynamics reveal a seamless transition from atomistic scale to continuum scale and the intrinsic coupling mechanism among them based on first principle formulation
Multiscale Model Reduction with Generalized Multiscale Finite Element Methods in Geomathematics
Efendiev, Yalchin R.; Presho, Michael
2015-01-01
In this chapter, we discuss multiscale model reduction using Generalized Multiscale Finite Element Methods (GMsFEM) in a number of geomathematical applications. GMsFEM has been recently introduced (Efendiev et al. 2012) and applied to various problems. In the current chapter, we consider some of these applications and outline the basic methodological concepts.
Distributed multiscale computing with MUSCLE 2, the Multiscale Coupling Library and Environment
Borgdorff, J.; Mamonski, M.; Bosak, B.; Kurowski, K.; Ben Belgacem, M.; Chopard, B.; Groen, D.; Coveney, P.V.; Hoekstra, A.G.
2014-01-01
We present the Multiscale Coupling Library and Environment: MUSCLE 2. This multiscale component-based execution environment has a simple to use Java, C++, C, Python and Fortran API, compatible with MPI, OpenMP and threading codes. We demonstrate its local and distributed computing capabilities and
Borgdorff, J.; Bona-Casas, C.; Mamonski, M.; Kurowski, K.; Piontek, T.; Bosak, B.; Rycerz, K.; Ciepiela, E.; Gubala, T.; Harezlak, D.; Bubak, M.; Lorenz, E.; Hoekstra, A.G.
2012-01-01
Nature is observed at all scales; with multiscale modeling, scientists bring together several scales for a holistic analysis of a phenomenon. The models on these different scales may require significant but also heterogeneous computational resources, creating the need for distributed multiscale
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.
A variational multiscale constitutive model for nanocrystalline materials
Gurses, Ercan; El Sayed, Tamer S.
2011-01-01
grain interior phase and a grain boundary effected zone (GBAZ). A rate-independent isotropic porous plasticity model is employed to describe the GBAZ, whereas a crystal-plasticity model which accounts for the transition from partial dislocation to full
Directory of Open Access Journals (Sweden)
Charles C. Rhoades
2017-01-01
Full Text Available Wildfire is a natural disturbance, though elemental losses and changes that occur during combustion and post-fire erosion can have long-term impacts on soil properties, ecosystem productivity, and watershed condition. Here we evaluate the potential of forest residue-based materials to rehabilitate burned soils. We compare soil nutrient and water availability, and plant recovery after application of 37 t ha−1 of wood mulch, 20 t ha−1 of biochar, and the combination of the two amendments with untreated, burned soils. We also conducted a greenhouse trial to examine how biochar influenced soil nutrient and water content under two wetting regimes. The effects of wood mulch on plant-available soil N and water content were significant and seasonally consistent during the three-year field study. Biochar applied alone had few effects under field conditions, but significantly increased soil pH, Ca, P, and water in the greenhouse. The mulched biochar treatment had the greatest effects on soil N and water availability and increased cover of the most abundant native plant. We found that rehabilitation treatments consisting of forest residue-based products have potential to enhance soil N and water dynamics and plant recovery following severe wildfire and may be justified where erosion risk or water supply protection are crucial.
Multiscale peak detection in wavelet space.
Zhang, Zhi-Min; Tong, Xia; Peng, Ying; Ma, Pan; Zhang, Ming-Jin; Lu, Hong-Mei; Chen, Xiao-Qing; Liang, Yi-Zeng
2015-12-07
Accurate peak detection is essential for analyzing high-throughput datasets generated by analytical instruments. Derivatives with noise reduction and matched filtration are frequently used, but they are sensitive to baseline variations, random noise and deviations in the peak shape. A continuous wavelet transform (CWT)-based method is more practical and popular in this situation, which can increase the accuracy and reliability by identifying peaks across scales in wavelet space and implicitly removing noise as well as the baseline. However, its computational load is relatively high and the estimated features of peaks may not be accurate in the case of peaks that are overlapping, dense or weak. In this study, we present multi-scale peak detection (MSPD) by taking full advantage of additional information in wavelet space including ridges, valleys, and zero-crossings. It can achieve a high accuracy by thresholding each detected peak with the maximum of its ridge. It has been comprehensively evaluated with MALDI-TOF spectra in proteomics, the CAMDA 2006 SELDI dataset as well as the Romanian database of Raman spectra, which is particularly suitable for detecting peaks in high-throughput analytical signals. Receiver operating characteristic (ROC) curves show that MSPD can detect more true peaks while keeping the false discovery rate lower than MassSpecWavelet and MALDIquant methods. Superior results in Raman spectra suggest that MSPD seems to be a more universal method for peak detection. MSPD has been designed and implemented efficiently in Python and Cython. It is available as an open source package at .
Multivariate and multiscale data assimilation in terrestrial systems: a review.
Montzka, Carsten; Pauwels, Valentijn R N; Franssen, Harrie-Jan Hendricks; Han, Xujun; Vereecken, Harry
2012-11-26
More and more terrestrial observational networks are being established to monitor climatic, hydrological and land-use changes in different regions of the World. In these networks, time series of states and fluxes are recorded in an automated manner, often with a high temporal resolution. These data are important for the understanding of water, energy, and/or matter fluxes, as well as their biological and physical drivers and interactions with and within the terrestrial system. Similarly, the number and accuracy of variables, which can be observed by spaceborne sensors, are increasing. Data assimilation (DA) methods utilize these observations in terrestrial models in order to increase process knowledge as well as to improve forecasts for the system being studied. The widely implemented automation in observing environmental states and fluxes makes an operational computation more and more feasible, and it opens the perspective of short-time forecasts of the state of terrestrial systems. In this paper, we review the state of the art with respect to DA focusing on the joint assimilation of observational data precedents from different spatial scales and different data types. An introduction is given to different DA methods, such as the Ensemble Kalman Filter (EnKF), Particle Filter (PF) and variational methods (3/4D-VAR). In this review, we distinguish between four major DA approaches: (1) univariate single-scale DA (UVSS), which is the approach used in the majority of published DA applications, (2) univariate multiscale DA (UVMS) referring to a methodology which acknowledges that at least some of the assimilated data are measured at a different scale than the computational grid scale, (3) multivariate single-scale DA (MVSS) dealing with the assimilation of at least two different data types, and (4) combined multivariate multiscale DA (MVMS). Finally, we conclude with a discussion on the advantages and disadvantages of the assimilation of multiple data types in a
Multivariate and Multiscale Data Assimilation in Terrestrial Systems: A Review
Directory of Open Access Journals (Sweden)
Harry Vereecken
2012-11-01
Full Text Available More and more terrestrial observational networks are being established to monitor climatic, hydrological and land-use changes in different regions of the World. In these networks, time series of states and fluxes are recorded in an automated manner, often with a high temporal resolution. These data are important for the understanding of water, energy, and/or matter fluxes, as well as their biological and physical drivers and interactions with and within the terrestrial system. Similarly, the number and accuracy of variables, which can be observed by spaceborne sensors, are increasing. Data assimilation (DA methods utilize these observations in terrestrial models in order to increase process knowledge as well as to improve forecasts for the system being studied. The widely implemented automation in observing environmental states and fluxes makes an operational computation more and more feasible, and it opens the perspective of short-time forecasts of the state of terrestrial systems. In this paper, we review the state of the art with respect to DA focusing on the joint assimilation of observational data precedents from different spatial scales and different data types. An introduction is given to different DA methods, such as the Ensemble Kalman Filter (EnKF, Particle Filter (PF and variational methods (3/4D-VAR. In this review, we distinguish between four major DA approaches: (1 univariate single-scale DA (UVSS, which is the approach used in the majority of published DA applications, (2 univariate multiscale DA (UVMS referring to a methodology which acknowledges that at least some of the assimilated data are measured at a different scale than the computational grid scale, (3 multivariate single-scale DA (MVSS dealing with the assimilation of at least two different data types, and (4 combined multivariate multiscale DA (MVMS. Finally, we conclude with a discussion on the advantages and disadvantages of the assimilation of multiple data types in a
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 mod...
Multiscale study of metal nanoparticles
Lee, Byeongchan
Extremely small structures with reduced dimensionality have emerged as a scientific motif for their interesting properties. In particular, metal nanoparticles have been identified as a fundamental material in many catalytic activities; as a consequence, a better understanding of structure-function relationship of nanoparticles has become crucial. The functional analysis of nanoparticles, reactivity for example, requires an accurate method at the electronic structure level, whereas the structural analysis to find energetically stable local minima is beyond the scope of quantum mechanical methods as the computational cost becomes prohibitingly high. The challenge is that the inherent length scale and accuracy associated with any single method hardly covers the broad scale range spanned by both structural and functional analyses. In order to address this, and effectively explore the energetics and reactivity of metal nanoparticles, a hierarchical multiscale modeling is developed, where methodologies of different length scales, i.e. first principles density functional theory, atomistic calculations, and continuum modeling, are utilized in a sequential fashion. This work has focused on identifying the essential information that bridges two different methods so that a successive use of different methods is seamless. The bond characteristics of low coordination systems have been obtained with first principles calculations, and incorporated into the atomistic simulation. This also rectifies the deficiency of conventional interatomic potentials fitted to bulk properties, and improves the accuracy of atomistic calculations for nanoparticles. For the systematic shape selection of nanoparticles, we have improved the Wulff-type construction using a semi-continuum approach, in which atomistic surface energetics and crystallinity of materials are added on to the continuum framework. The developed multiscale modeling scheme is applied to the rational design of platinum
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 Processes in Magnetic Reconnection
Surjalal Sharma, A.; Jain, Neeraj
The characteristic scales of the plasma processes in magnetic reconnection range from the elec-tron skin-depth to the magnetohydrodynamic (MHD) scale, and cross-scale coupling among them play a key role. Modeling these processes requires different physical models, viz. kinetic, electron-magnetohydrodynamics (EMHD), Hall-MHD, and MHD. The shortest scale processes are at the electron scale and these are modeled using an EMHD code, which provides many features of the multiscale behavior. In simulations using initial conditions consisting of pertur-bations with many scale sizes the reconnection takes place at many sites and the plasma flows from these interact with each other. This leads to thin current sheets with length less than 10 electron skin depths. The plasma flows also generate current sheets with multiple peaks, as observed by Cluster. The quadrupole structure of the magnetic field during reconnection starts on the electron scale and the interaction of inflow to the secondary sites and outflow from the dominant site generates a nested structure. In the outflow regions, the interaction of the electron outflows generated at the neighboring sites lead to the development of electron vortices. A signature of the nested structure of the Hall field is seen in Cluster observations, and more details of these features are expected from MMS.
A residual-based a posteriori error estimator for single-phase Darcy flow in fractured porous media
Chen, Huangxin
2016-12-09
In this paper we develop an a posteriori error estimator for a mixed finite element method for single-phase Darcy flow in a two-dimensional fractured porous media. The discrete fracture model is applied to model the fractures by one-dimensional fractures in a two-dimensional domain. We consider Raviart–Thomas mixed finite element method for the approximation of the coupled Darcy flows in the fractures and the surrounding porous media. We derive a robust residual-based a posteriori error estimator for the problem with non-intersecting fractures. The reliability and efficiency of the a posteriori error estimator are established for the error measured in an energy norm. Numerical results verifying the robustness of the proposed a posteriori error estimator are given. Moreover, our numerical results indicate that the a posteriori error estimator also works well for the problem with intersecting fractures.
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...
Uncertainty propagation in a multiscale model of nanocrystalline plasticity
International Nuclear Information System (INIS)
Koslowski, M.; Strachan, Alejandro
2011-01-01
We characterize how uncertainties propagate across spatial and temporal scales in a physics-based model of nanocrystalline plasticity of fcc metals. Our model combines molecular dynamics (MD) simulations to characterize atomic-level processes that govern dislocation-based-plastic deformation with a phase field approach to dislocation dynamics (PFDD) that describes how an ensemble of dislocations evolve and interact to determine the mechanical response of the material. We apply this approach to a nanocrystalline Ni specimen of interest in micro-electromechanical (MEMS) switches. Our approach enables us to quantify how internal stresses that result from the fabrication process affect the properties of dislocations (using MD) and how these properties, in turn, affect the yield stress of the metallic membrane (using the PFMM model). Our predictions show that, for a nanocrystalline sample with small grain size (4 nm), a variation in residual stress of 20 MPa (typical in today's microfabrication techniques) would result in a variation on the critical resolved shear yield stress of approximately 15 MPa, a very small fraction of the nominal value of approximately 9 GPa. - Highlights: → Quantify how fabrication uncertainties affect yield stress in a microswitch component. → Propagate uncertainties in a multiscale model of single crystal plasticity. → Molecular dynamics quantifies how fabrication variations affect dislocations. → Dislocation dynamics relate variations in dislocation properties to yield stress.
Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei
2018-06-01
Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.
Correlations of multiscale entropy in the FX market
Stosic, Darko; Stosic, Dusan; Ludermir, Teresa; Stosic, Tatijana
2016-09-01
The regularity of price fluctuations in exchange rates plays a crucial role in FX market dynamics. Distinct variations in regularity arise from economic, social and political events, such as interday trading and financial crisis. This paper applies a multiscale time-dependent entropy method on thirty-three exchange rates to analyze price fluctuations in the FX. Correlation matrices of entropy values, termed entropic correlations, are in turn used to describe global behavior of the market. Empirical results suggest a weakly correlated market with pronounced collective behavior at bi-weekly trends. Correlations arise from cycles of low and high regularity in long-term trends. Eigenvalues of the correlation matrix also indicate a dominant European market, followed by shifting American, Asian, African, and Pacific influences. As a result, we find that entropy is a powerful tool for extracting important information from the FX market.
Plant trait detection with multi-scale spectrometry
Gamon, J. A.; Wang, R.
2017-12-01
Proximal and remote sensing using imaging spectrometry offers new opportunities for detecting plant traits, with benefits for phenotyping, productivity estimation, stress detection, and biodiversity studies. Using proximal and airborne spectrometry, we evaluated variation in plant optical properties at various spatial and spectral scales with the goal of identifying optimal scales for distinguishing plant traits related to photosynthetic function. Using directed approaches based on physiological vegetation indices, and statistical approaches based on spectral information content, we explored alternate ways of distinguishing plant traits with imaging spectrometry. With both leaf traits and canopy structure contributing to the signals, results exhibit a strong scale dependence. Our results demonstrate the benefits of multi-scale experimental approaches within a clear conceptual framework when applying remote sensing methods to plant trait detection for phenotyping, productivity, and biodiversity studies.
MULTISCALE SPARSE APPEARANCE MODELING AND SIMULATION OF PATHOLOGICAL DEFORMATIONS
Directory of Open Access Journals (Sweden)
Rami Zewail
2017-08-01
Full Text Available Machine learning and statistical modeling techniques has drawn much interest within the medical imaging research community. However, clinically-relevant modeling of anatomical structures continues to be a challenging task. This paper presents a novel method for multiscale sparse appearance modeling in medical images with application to simulation of pathological deformations in X-ray images of human spine. The proposed appearance model benefits from the non-linear approximation power of Contourlets and its ability to capture higher order singularities to achieve a sparse representation while preserving the accuracy of the statistical model. Independent Component Analysis is used to extract statistical independent modes of variations from the sparse Contourlet-based domain. The new model is then used to simulate clinically-relevant pathological deformations in radiographic images.
Deductive multiscale simulation using order parameters
Ortoleva, Peter J.
2017-05-16
Illustrative embodiments of systems and methods for the deductive multiscale simulation of macromolecules are disclosed. In one illustrative embodiment, a deductive multiscale simulation method may include (i) constructing a set of order parameters that model one or more structural characteristics of a macromolecule, (ii) simulating an ensemble of atomistic configurations for the macromolecule using instantaneous values of the set of order parameters, (iii) simulating thermal-average forces and diffusivities for the ensemble of atomistic configurations, and (iv) evolving the set of order parameters via Langevin dynamics using the thermal-average forces and diffusivities.
Multiscale phase inversion of seismic marine data
Fu, Lei
2017-08-17
We test the feasibility of applying multiscale phase inversion (MPI) to seismic marine data. To avoid cycle-skipping, the multiscale strategy temporally integrates the traces several times, i.e. high-order integration, to produce low-boost seismograms that are used as input data for the initial iterations of MPI. As the iterations proceed, higher frequencies in the data are boosted by using integrated traces of lower order as the input data. Results with synthetic data and field data from the Gulf of Mexico produce robust and accurate results if the model does not contain strong velocity contrasts such as salt-sediment interfaces.
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.
International Nuclear Information System (INIS)
Gao, Kai; Fu, Shubin; Gibson, Richard L.; Chung, Eric T.; Efendiev, Yalchin
2015-01-01
It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale medium property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system
Energy Technology Data Exchange (ETDEWEB)
Gao, Kai, E-mail: kaigao87@gmail.com [Department of Geology and Geophysics, Texas A& M University, College Station, TX 77843 (United States); Fu, Shubin, E-mail: shubinfu89@gmail.com [Department of Mathematics, Texas A& M University, College Station, TX 77843 (United States); Gibson, Richard L., E-mail: gibson@tamu.edu [Department of Geology and Geophysics, Texas A& M University, College Station, TX 77843 (United States); Chung, Eric T., E-mail: tschung@math.cuhk.edu.hk [Department of Mathematics, The Chinese University of Hong Kong, Shatin, NT (Hong Kong); Efendiev, Yalchin, E-mail: efendiev@math.tamu.edu [Department of Mathematics, Texas A& M University, College Station, TX 77843 (United States); Numerical Porous Media SRI Center (NumPor), King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)
2015-08-15
It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale medium property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.
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.
Foundations for a multiscale collaborative Earth model
Afanasiev, M.
2015-11-11
We present a computational framework for the assimilation of local to global seismic data into a consistent model describing Earth structure on all seismically accessible scales. This Collaborative Seismic Earth Model (CSEM) is designed to meet the following requirements: (i) Flexible geometric parametrization, capable of capturing topography and bathymetry, as well as all aspects of potentially resolvable structure, including small-scale heterogeneities and deformations of internal discontinuities. (ii) Independence of any particular wave equation solver, in order to enable the combination of inversion techniques suitable for different types of seismic data. (iii) Physical parametrization that allows for full anisotropy and for variations in attenuation and density. While not all of these parameters are always resolvable, the assimilation of data that constrain any parameter subset should be possible. (iv) Ability to accommodate successive refinements through the incorporation of updates on any scale as new data or inversion techniques become available. (v) Enable collaborative Earth model construction. The structure of the initial CSEM is represented on a variable-resolution tetrahedral mesh. It is assembled from a long-wavelength 3-D global model into which several regional-scale tomographies are embedded. We illustrate the CSEM workflow of successive updating with two examples from Japan and the Western Mediterranean, where we constrain smaller scale structure using full-waveform inversion. Furthermore, we demonstrate the ability of the CSEM to act as a vehicle for the combination of different tomographic techniques with a joint full-waveform and traveltime ray tomography of Europe. This combination broadens the exploitable frequency range of the individual techniques, thereby improving resolution. We perform two iterations of a whole-Earth full-waveform inversion using a long-period reference data set from 225 globally recorded earthquakes. At this early stage
A multiscale approach to mutual information matching
Pluim, J.P.W.; Maintz, J.B.A.; Viergever, M.A.; Hanson, K.M.
1998-01-01
Methods based on mutual information have shown promising results for matching of multimodal brain images. This paper discusses a multiscale approach to mutual information matching, aiming for an acceleration of the matching process while considering the accuracy and robustness of the method. Scaling
Multiscale Lyapunov exponent for 2-microlocal functions
International Nuclear Information System (INIS)
Dhifaoui, Zouhaier; Kortas, Hedi; Ammou, Samir Ben
2009-01-01
The Lyapunov exponent is an important indicator of chaotic dynamics. Using wavelet analysis, we define a multiscale representation of this exponent which we demonstrate the scale-wise dependence for functions belonging to C x 0 s,s ' spaces. An empirical study involving simulated processes and financial time series corroborates the theoretical findings.
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
Multiscale Phase Inversion of Seismic Data
Fu, Lei; Guo, Bowen; Sun, Yonghe; Schuster, Gerard T.
2017-01-01
-skipping, the multiscale strategy temporally integrates the traces several times, i.e. high-order integration, to produce low-boost seismograms that are used as input data for the initial iterations of MPI. As the iterations proceed, higher frequencies in the data
Multiscale Modeling of Poromechanics in Geologic Media
Castelletto, N.; Hajibeygi, H.; Klevtsov, S.; Tchelepi, H.
2017-12-01
We describe a hybrid MultiScale Finite Element-Finite Volume (h-MSFE-FV) framework for the simulation of single-phase Darcy flow through deformable porous media that exhibit highly heterogeneous poromechanical properties over a wide range of length scales. In such systems, high resolution characterizations are a key requirement to obtain reliable modeling predictions and motivate the development of multiscale solution strategies to cope with the computational burden. A coupled two-field fine-scale mixed FE-FV discretization of the governing equations, namely conservation laws of linear momentum and mass, is first implemented based on a displacement-pressure formulation. After imposing a coarse-scale grid on the given fine-scale problem, for the MSFE displacement stage, the coarse-scale basis functions are obtained by solving local equilibrium problems within coarse elements. Such MSFE stage is then coupled with the MSFV method for flow, in which a dual-coarse grid is introduced to obtain approximate but conservative multiscale solutions. Robustness and accuracy of the proposed multiscale framework is demonstrated using a variety of challenging test problems.
Multiscale empirical interpolation for solving nonlinear PDEs
Calo, Victor M.; Efendiev, Yalchin R.; Galvis, Juan; Ghommem, Mehdi
2014-01-01
residuals and Jacobians on the fine grid. We use empirical interpolation concepts to evaluate these residuals and Jacobians of the multiscale system with a computational cost which is proportional to the size of the coarse-scale problem rather than the fully
Multiscale information modelling for heart morphogenesis
Energy Technology Data Exchange (ETDEWEB)
Abdulla, T; Imms, R; Summers, R [Department of Electronic and Electrical Engineering, Loughborough University, Loughborough (United Kingdom); Schleich, J M, E-mail: T.Abdulla@lboro.ac.u [LTSI Signal and Image Processing Laboratory, University of Rennes 1, Rennes (France)
2010-07-01
Science is made feasible by the adoption of common systems of units. As research has become more data intensive, especially in the biomedical domain, it requires the adoption of a common system of information models, to make explicit the relationship between one set of data and another, regardless of format. This is being realised through the OBO Foundry to develop a suite of reference ontologies, and NCBO Bioportal to provide services to integrate biomedical resources and functionality to visualise and create mappings between ontology terms. Biomedical experts tend to be focused at one level of spatial scale, be it biochemistry, cell biology, or anatomy. Likewise, the ontologies they use tend to be focused at a particular level of scale. There is increasing interest in a multiscale systems approach, which attempts to integrate between different levels of scale to gain understanding of emergent effects. This is a return to physiological medicine with a computational emphasis, exemplified by the worldwide Physiome initiative, and the European Union funded Network of Excellence in the Virtual Physiological Human. However, little work has been done on how information modelling itself may be tailored to a multiscale systems approach. We demonstrate how this can be done for the complex process of heart morphogenesis, which requires multiscale understanding in both time and spatial domains. Such an effort enables the integration of multiscale metrology.
Multiscale information modelling for heart morphogenesis
International Nuclear Information System (INIS)
Abdulla, T; Imms, R; Summers, R; Schleich, J M
2010-01-01
Science is made feasible by the adoption of common systems of units. As research has become more data intensive, especially in the biomedical domain, it requires the adoption of a common system of information models, to make explicit the relationship between one set of data and another, regardless of format. This is being realised through the OBO Foundry to develop a suite of reference ontologies, and NCBO Bioportal to provide services to integrate biomedical resources and functionality to visualise and create mappings between ontology terms. Biomedical experts tend to be focused at one level of spatial scale, be it biochemistry, cell biology, or anatomy. Likewise, the ontologies they use tend to be focused at a particular level of scale. There is increasing interest in a multiscale systems approach, which attempts to integrate between different levels of scale to gain understanding of emergent effects. This is a return to physiological medicine with a computational emphasis, exemplified by the worldwide Physiome initiative, and the European Union funded Network of Excellence in the Virtual Physiological Human. However, little work has been done on how information modelling itself may be tailored to a multiscale systems approach. We demonstrate how this can be done for the complex process of heart morphogenesis, which requires multiscale understanding in both time and spatial domains. Such an effort enables the integration of multiscale metrology.
Multiscale approach to equilibrating model polymer melts
DEFF Research Database (Denmark)
Svaneborg, Carsten; Ali Karimi-Varzaneh, Hossein; Hojdis, Nils
2016-01-01
We present an effective and simple multiscale method for equilibrating Kremer Grest model polymer melts of varying stiffness. In our approach, we progressively equilibrate the melt structure above the tube scale, inside the tube and finally at the monomeric scale. We make use of models designed...
Multiscale optimization of saturated poroelastic actuators
DEFF Research Database (Denmark)
Andreasen, Casper Schousboe; Sigmund, Ole
A multiscale method for optimizing the material micro structure in a macroscopically heterogeneous saturated poroelastic media with respect to macro properties is presented. The method is based on topology optimization using the homogenization technique, here applied to the optimization of a bi...
Generalized multiscale finite element methods: Oversampling strategies
Efendiev, Yalchin R.; Galvis, Juan; Li, Guanglian; Presho, Michael
2014-01-01
In this paper, we propose oversampling strategies in the generalized multiscale finite element method (GMsFEM) framework. The GMsFEM, which has been recently introduced in Efendiev et al. (2013b) [Generalized Multiscale Finite Element Methods, J. Comput. Phys., vol. 251, pp. 116-135, 2013], allows solving multiscale parameter-dependent problems at a reduced computational cost by constructing a reduced-order representation of the solution on a coarse grid. The main idea of the method consists of (1) the construction of snapshot space, (2) the construction of the offline space, and (3) construction of the online space (the latter for parameter-dependent problems). In Efendiev et al. (2013b) [Generalized Multiscale Finite Element Methods, J. Comput. Phys., vol. 251, pp. 116-135, 2013], it was shown that the GMsFEM provides a flexible tool to solve multiscale problems with a complex input space by generating appropriate snapshot, offline, and online spaces. In this paper, we develop oversampling techniques to be used in this context (see Hou and Wu (1997) where oversampling is introduced for multiscale finite element methods). It is known (see Hou and Wu (1997)) that the oversampling can improve the accuracy of multiscale methods. In particular, the oversampling technique uses larger regions (larger than the target coarse block) in constructing local basis functions. Our motivation stems from the analysis presented in this paper, which shows that when using oversampling techniques in the construction of the snapshot space and offline space, GMsFEM will converge independent of small scales and high contrast under certain assumptions. We consider the use of a multiple eigenvalue problems to improve the convergence and discuss their relation to single spectral problems that use oversampled regions. The oversampling procedures proposed in this paper differ from those in Hou and Wu (1997). In particular, the oversampling domains are partially used in constructing local
El-Amin, Mohamed F.; Kou, Jisheng; Sun, Shuyu
2017-01-01
Recently, applications of nanoparticles have been considered in many branches of petroleum engineering, especially, enhanced oil recovery. The current paper is devoted to investigate the problem of nanoparticles transport in fractured porous media, numerically. We employed the discrete-fracture model (DFM) to represent the flow and transport in the fractured formations. The system of the governing equations consists of the mass conservation law, Darcy's law, nanoparticles concentration in water, deposited nanoparticles concentration on the pore-wall, and entrapped nanoparticles concentration in the pore-throat. The variation of porosity and permeability due to the nanoparticles deposition/entrapment on/in the pores is also considered. We employ the multiscale time-splitting strategy to control different time-step sizes for different physics, such as pressure and concentration. The cell-centered finite difference (CCFD) method is used for the spatial discretization. Numerical examples are provided to demonstrate the efficiency of the proposed multiscale time splitting approach.
El-Amin, Mohamed F.
2017-06-06
Recently, applications of nanoparticles have been considered in many branches of petroleum engineering, especially, enhanced oil recovery. The current paper is devoted to investigate the problem of nanoparticles transport in fractured porous media, numerically. We employed the discrete-fracture model (DFM) to represent the flow and transport in the fractured formations. The system of the governing equations consists of the mass conservation law, Darcy\\'s law, nanoparticles concentration in water, deposited nanoparticles concentration on the pore-wall, and entrapped nanoparticles concentration in the pore-throat. The variation of porosity and permeability due to the nanoparticles deposition/entrapment on/in the pores is also considered. We employ the multiscale time-splitting strategy to control different time-step sizes for different physics, such as pressure and concentration. The cell-centered finite difference (CCFD) method is used for the spatial discretization. Numerical examples are provided to demonstrate the efficiency of the proposed multiscale time splitting approach.
Simulation of left atrial function using a multi-scale model of the cardiovascular system.
Directory of Open Access Journals (Sweden)
Antoine Pironet
Full Text Available During a full cardiac cycle, the left atrium successively behaves as a reservoir, a conduit and a pump. This complex behavior makes it unrealistic to apply the time-varying elastance theory to characterize the left atrium, first, because this theory has known limitations, and second, because it is still uncertain whether the load independence hypothesis holds. In this study, we aim to bypass this uncertainty by relying on another kind of mathematical model of the cardiac chambers. In the present work, we describe both the left atrium and the left ventricle with a multi-scale model. The multi-scale property of this model comes from the fact that pressure inside a cardiac chamber is derived from a model of the sarcomere behavior. Macroscopic model parameters are identified from reference dog hemodynamic data. The multi-scale model of the cardiovascular system including the left atrium is then simulated to show that the physiological roles of the left atrium are correctly reproduced. This include a biphasic pressure wave and an eight-shaped pressure-volume loop. We also test the validity of our model in non basal conditions by reproducing a preload reduction experiment by inferior vena cava occlusion with the model. We compute the variation of eight indices before and after this experiment and obtain the same variation as experimentally observed for seven out of the eight indices. In summary, the multi-scale mathematical model presented in this work is able to correctly account for the three roles of the left atrium and also exhibits a realistic left atrial pressure-volume loop. Furthermore, the model has been previously presented and validated for the left ventricle. This makes it a proper alternative to the time-varying elastance theory if the focus is set on precisely representing the left atrial and left ventricular behaviors.
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.
Chung, Eric; Efendiev, Yalchin R.; Leung, Wing; Ren, Jun
2015-01-01
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.
Residual-driven online generalized multiscale finite element methods
Chung, Eric T.; Efendiev, Yalchin R.; Leung, Wing Tat
2015-01-01
In the paper, theoretical and numerical results are presented. Our numerical results show that if the offline space is sufficiently large (in terms of the dimension) such that the coarse space contains all multiscale spectral basis functions that correspond to small eigenvalues, then the error reduction by adding online multiscale basis function is independent of the contrast. We discuss various ways computing online multiscale basis functions which include a use of small dimensional offline spaces.
Multiscale Modeling of Point and Line Defects in Cubic Lattices
National Research Council Canada - National Science Library
Chung, P. W; Clayton, J. D
2007-01-01
.... This multiscale theory explicitly captures heterogeneity in microscopic atomic motion in crystalline materials, attributed, for example, to the presence of various point and line lattice defects...
Towards practical multiscale approach for analysis of reinforced concrete structures
Moyeda, Arturo; Fish, Jacob
2017-12-01
We present a novel multiscale approach for analysis of reinforced concrete structural elements that overcomes two major hurdles in utilization of multiscale technologies in practice: (1) coupling between material and structural scales due to consideration of large representative volume elements (RVE), and (2) computational complexity of solving complex nonlinear multiscale problems. The former is accomplished using a variant of computational continua framework that accounts for sizeable reinforced concrete RVEs by adjusting the location of quadrature points. The latter is accomplished by means of reduced order homogenization customized for structural elements. The proposed multiscale approach has been verified against direct numerical simulations and validated against experimental results.
Multiscale Cues Drive Collective Cell Migration
Nam, Ki-Hwan; Kim, Peter; Wood, David K.; Kwon, Sunghoon; Provenzano, Paolo P.; Kim, Deok-Ho
2016-07-01
To investigate complex biophysical relationships driving directed cell migration, we developed a biomimetic platform that allows perturbation of microscale geometric constraints with concomitant nanoscale contact guidance architectures. This permits us to elucidate the influence, and parse out the relative contribution, of multiscale features, and define how these physical inputs are jointly processed with oncogenic signaling. We demonstrate that collective cell migration is profoundly enhanced by the addition of contract guidance cues when not otherwise constrained. However, while nanoscale cues promoted migration in all cases, microscale directed migration cues are dominant as the geometric constraint narrows, a behavior that is well explained by stochastic diffusion anisotropy modeling. Further, oncogene activation (i.e. mutant PIK3CA) resulted in profoundly increased migration where extracellular multiscale directed migration cues and intrinsic signaling synergistically conspire to greatly outperform normal cells or any extracellular guidance cues in isolation.
Multiscale Study of Currents Affected by Topography
2015-09-30
1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Multiscale Study of Currents Affected by Topography ...the effects of topography on the ocean general and regional circulation with a focus on the wide range of scales of interactions. The small-scale...details of the topography and the waves, eddies, drag, and turbulence it generates (at spatial scales ranging from meters to mesoscale) interact in the
A multiscale approach to Brownian motors
International Nuclear Information System (INIS)
Pavliotis, G.A.
2005-01-01
The problem of Brownian motion in a periodic potential, under the influence of external forcing, which is either random or periodic in time, is studied in this Letter. Multiscale techniques are used to derive general formulae for the steady state particle current and the effective diffusion tensor. These formulae are then applied to calculate the effective diffusion coefficient for a Brownian particle in a periodic potential driven simultaneously by additive Gaussian white and colored noise. Our theoretical findings are supported by numerical simulations
Multiscale modeling of mucosal immune responses
2015-01-01
Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM. Background Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Implementation Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. Conclusion We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut
Multiscale modeling of mucosal immune responses.
Mei, Yongguo; Abedi, Vida; Carbo, Adria; Zhang, Xiaoying; Lu, Pinyi; Philipson, Casandra; Hontecillas, Raquel; Hoops, Stefan; Liles, Nathan; Bassaganya-Riera, Josep
2015-01-01
Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation.Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T
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......), their performance is comparable to SIFT (Lowe, 2004).We also show that when they are used together with MSERs (Matas et al., 2002), the performance of MSERs is boosted....
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. © 2016 Institute of Food Technologists®
Adaptive multiscale processing for contrast enhancement
Laine, Andrew F.; Song, Shuwu; Fan, Jian; Huda, Walter; Honeyman, Janice C.; Steinbach, Barbara G.
1993-07-01
This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms within a continuum of scale space and used to enhance features of importance to mammography. Choosing analyzing functions that are well localized in both space and frequency, results in a powerful methodology for image analysis. We describe methods of contrast enhancement based on two overcomplete (redundant) multiscale representations: (1) Dyadic wavelet transform (2) (phi) -transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by non-linear, logarithmic and constant scale-space weight functions. Multiscale edges identified within distinct levels of transform space provide a local support for enhancement throughout each decomposition. We demonstrate that features extracted from wavelet spaces can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification.
Acoustics of multiscale sorptive porous materials
Venegas, R.; Boutin, C.; Umnova, O.
2017-08-01
This paper investigates sound propagation in multiscale rigid-frame porous materials that support mass transfer processes, such as sorption and different types of diffusion, in addition to the usual visco-thermo-inertial interactions. The two-scale asymptotic method of homogenization for periodic media is successively used to derive the macroscopic equations describing sound propagation through the material. This allowed us to conclude that the macroscopic mass balance is significantly modified by sorption, inter-scale (micro- to/from nanopore scales) mass diffusion, and inter-scale (pore to/from micro- and nanopore scales) pressure diffusion. This modification is accounted for by the dynamic compressibility of the effective saturating fluid that presents atypical properties that lead to slower speed of sound and higher sound attenuation, particularly at low frequencies. In contrast, it is shown that the physical processes occurring at the micro-nano-scale do not affect the macroscopic fluid flow through the material. The developed theory is exemplified by introducing an analytical model for multiscale sorptive granular materials, which is experimentally validated by comparing its predictions with acoustic measurements on granular activated carbons. Furthermore, we provide empirical evidence supporting an alternative method for measuring sorption and mass diffusion properties of multiscale sorptive materials using sound waves.
Multivariate multiscale entropy of financial markets
Lu, Yunfan; Wang, Jun
2017-11-01
In current process of quantifying the dynamical properties of the complex phenomena in financial market system, the multivariate financial time series are widely concerned. In this work, considering the shortcomings and limitations of univariate multiscale entropy in analyzing the multivariate time series, the multivariate multiscale sample entropy (MMSE), which can evaluate the complexity in multiple data channels over different timescales, is applied to quantify the complexity of financial markets. Its effectiveness and advantages have been detected with numerical simulations with two well-known synthetic noise signals. For the first time, the complexity of four generated trivariate return series for each stock trading hour in China stock markets is quantified thanks to the interdisciplinary application of this method. We find that the complexity of trivariate return series in each hour show a significant decreasing trend with the stock trading time progressing. Further, the shuffled multivariate return series and the absolute multivariate return series are also analyzed. As another new attempt, quantifying the complexity of global stock markets (Asia, Europe and America) is carried out by analyzing the multivariate returns from them. Finally we utilize the multivariate multiscale entropy to assess the relative complexity of normalized multivariate return volatility series with different degrees.
Multiscale Phase Inversion of Seismic Data
Fu, Lei
2017-12-02
We present a scheme for multiscale phase inversion (MPI) of seismic data that is less sensitive to the unmodeled physics of wave propagation and a poor starting model than standard full waveform inversion (FWI). To avoid cycle-skipping, the multiscale strategy temporally integrates the traces several times, i.e. high-order integration, to produce low-boost seismograms that are used as input data for the initial iterations of MPI. As the iterations proceed, higher frequencies in the data are boosted by using integrated traces of lower order as the input data. The input data are also filtered into different narrow frequency bands for the MPI implementation. At low frequencies, we show that MPI with windowed reflections approximates wave equation inversion of the reflection traveltimes, except no traveltime picking is needed. Numerical results with synthetic acoustic data show that MPI is more robust than conventional multiscale FWI when the initial model is far from the true model. Results from synthetic viscoacoustic and elastic data show that MPI is less sensitive than FWI to some of the unmodeled physics. Inversion of marine data shows that MPI is more robust and produces modestly more accurate results than FWI for this data set.
Multiscale Persistent Functions for Biomolecular Structure Characterization
Energy Technology Data Exchange (ETDEWEB)
Xia, Kelin [Nanyang Technological University (Singapore). Division of Mathematical Sciences, School of Physical, Mathematical Sciences and School of Biological Sciences; Li, Zhiming [Central China Normal University, Wuhan (China). Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics; Mu, Lin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computer Science and Mathematics Division
2017-11-02
Here in this paper, we introduce multiscale persistent functions for biomolecular structure characterization. The essential idea is to combine our multiscale rigidity functions (MRFs) with persistent homology analysis, so as to construct a series of multiscale persistent functions, particularly multiscale persistent entropies, for structure characterization. To clarify the fundamental idea of our method, the multiscale persistent entropy (MPE) model is discussed in great detail. Mathematically, unlike the previous persistent entropy (Chintakunta et al. in Pattern Recognit 48(2):391–401, 2015; Merelli et al. in Entropy 17(10):6872–6892, 2015; Rucco et al. in: Proceedings of ECCS 2014, Springer, pp 117–128, 2016), a special resolution parameter is incorporated into our model. Various scales can be achieved by tuning its value. Physically, our MPE can be used in conformational entropy evaluation. More specifically, it is found that our method incorporates in it a natural classification scheme. This is achieved through a density filtration of an MRF built from angular distributions. To further validate our model, a systematical comparison with the traditional entropy evaluation model is done. Additionally, it is found that our model is able to preserve the intrinsic topological features of biomolecular data much better than traditional approaches, particularly for resolutions in the intermediate range. Moreover, by comparing with traditional entropies from various grid sizes, bond angle-based methods and a persistent homology-based support vector machine method (Cang et al. in Mol Based Math Biol 3:140–162, 2015), we find that our MPE method gives the best results in terms of average true positive rate in a classic protein structure classification test. More interestingly, all-alpha and all-beta protein classes can be clearly separated from each other with zero error only in our model. Finally, a special protein structure index (PSI) is proposed, for the first
Classification of high-resolution remote sensing images based on multi-scale superposition
Wang, Jinliang; Gao, Wenjie; Liu, Guangjie
2017-07-01
Landscape structures and process on different scale show different characteristics. In the study of specific target landmarks, the most appropriate scale for images can be attained by scale conversion, which improves the accuracy and efficiency of feature identification and classification. In this paper, the authors carried out experiments on multi-scale classification by taking the Shangri-la area in the north-western Yunnan province as the research area and the images from SPOT5 HRG and GF-1 Satellite as date sources. Firstly, the authors upscaled the two images by cubic convolution, and calculated the optimal scale for different objects on the earth shown in images by variation functions. Then the authors conducted multi-scale superposition classification on it by Maximum Likelyhood, and evaluated the classification accuracy. The results indicates that: (1) for most of the object on the earth, the optimal scale appears in the bigger scale instead of the original one. To be specific, water has the biggest optimal scale, i.e. around 25-30m; farmland, grassland, brushwood, roads, settlement places and woodland follows with 20-24m. The optimal scale for shades and flood land is basically as the same as the original one, i.e. 8m and 10m respectively. (2) Regarding the classification of the multi-scale superposed images, the overall accuracy of the ones from SPOT5 HRG and GF-1 Satellite is 12.84% and 14.76% higher than that of the original multi-spectral images, respectively, and Kappa coefficient is 0.1306 and 0.1419 higher, respectively. Hence, the multi-scale superposition classification which was applied in the research area can enhance the classification accuracy of remote sensing images .
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...
Evaluating and Improving Cloud Processes in the Multi-Scale Modeling Framework
Energy Technology Data Exchange (ETDEWEB)
Ackerman, Thomas P. [Univ. of Washington, Seattle, WA (United States)
2015-03-01
The research performed under this grant was intended to improve the embedded cloud model in the Multi-scale Modeling Framework (MMF) for convective clouds by using a 2-moment microphysics scheme rather than the single moment scheme used in all the MMF runs to date. The technical report and associated documents describe the results of testing the cloud resolving model with fixed boundary conditions and evaluation of model results with data. The overarching conclusion is that such model evaluations are problematic because errors in the forcing fields control the results so strongly that variations in parameterization values cannot be usefully constrained
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…
Efficient algorithms for multiscale modeling in porous media
Wheeler, Mary F.; Wildey, Tim; Xue, Guangri
2010-01-01
We describe multiscale mortar mixed finite element discretizations for second-order elliptic and nonlinear parabolic equations modeling Darcy flow in porous media. The continuity of flux is imposed via a mortar finite element space on a coarse grid scale, while the equations in the coarse elements (or subdomains) are discretized on a fine grid scale. We discuss the construction of multiscale mortar basis and extend this concept to nonlinear interface operators. We present a multiscale preconditioning strategy to minimize the computational cost associated with construction of the multiscale mortar basis. We also discuss the use of appropriate quadrature rules and approximation spaces to reduce the saddle point system to a cell-centered pressure scheme. In particular, we focus on multiscale mortar multipoint flux approximation method for general hexahedral grids and full tensor permeabilities. Numerical results are presented to verify the accuracy and efficiency of these approaches. © 2010 John Wiley & Sons, Ltd.
A complete categorization of multiscale models of infectious disease systems.
Garira, Winston
2017-12-01
Modelling of infectious disease systems has entered a new era in which disease modellers are increasingly turning to multiscale modelling to extend traditional modelling frameworks into new application areas and to achieve higher levels of detail and accuracy in characterizing infectious disease systems. In this paper we present a categorization framework for categorizing multiscale models of infectious disease systems. The categorization framework consists of five integration frameworks and five criteria. We use the categorization framework to give a complete categorization of host-level immuno-epidemiological models (HL-IEMs). This categorization framework is also shown to be applicable in categorizing other types of multiscale models of infectious diseases beyond HL-IEMs through modifying the initial categorization framework presented in this study. Categorization of multiscale models of infectious disease systems in this way is useful in bringing some order to the discussion on the structure of these multiscale models.
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.
Multiscale approaches to high efficiency photovoltaics
Directory of Open Access Journals (Sweden)
Connolly James Patrick
2016-01-01
Full Text Available While renewable energies are achieving parity around the globe, efforts to reach higher solar cell efficiencies becomes ever more difficult as they approach the limiting efficiency. The so-called third generation concepts attempt to break this limit through a combination of novel physical processes and new materials and concepts in organic and inorganic systems. Some examples of semi-empirical modelling in the field are reviewed, in particular for multispectral solar cells on silicon (French ANR project MultiSolSi. Their achievements are outlined, and the limits of these approaches shown. This introduces the main topic of this contribution, which is the use of multiscale experimental and theoretical techniques to go beyond the semi-empirical understanding of these systems. This approach has already led to great advances at modelling which have led to modelling software, which is widely known. Yet, a survey of the topic reveals a fragmentation of efforts across disciplines, firstly, such as organic and inorganic fields, but also between the high efficiency concepts such as hot carrier cells and intermediate band concepts. We show how this obstacle to the resolution of practical research obstacles may be lifted by inter-disciplinary cooperation across length scales, and across experimental and theoretical fields, and finally across materials systems. We present a European COST Action “MultiscaleSolar” kicking off in early 2015, which brings together experimental and theoretical partners in order to develop multiscale research in organic and inorganic materials. The goal of this defragmentation and interdisciplinary collaboration is to develop understanding across length scales, which will enable the full potential of third generation concepts to be evaluated in practise, for societal and industrial applications.
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.
Multiscale agent-based cancer modeling.
Zhang, Le; Wang, Zhihui; Sagotsky, Jonathan A; Deisboeck, Thomas S
2009-04-01
Agent-based modeling (ABM) is an in silico technique that is being used in a variety of research areas such as in social sciences, economics and increasingly in biomedicine as an interdisciplinary tool to study the dynamics of complex systems. Here, we describe its applicability to integrative tumor biology research by introducing a multi-scale tumor modeling platform that understands brain cancer as a complex dynamic biosystem. We summarize significant findings of this work, and discuss both challenges and future directions for ABM in the field of cancer research.
Multi-scale Modelling of Segmentation
DEFF Research Database (Denmark)
Hartmann, Martin; Lartillot, Olivier; Toiviainen, Petri
2016-01-01
pieces. In a second experiment on non-real-time segmentation, musicians indicated boundaries and their strength for six examples. Kernel density estimation was used to develop multi-scale segmentation models. Contrary to previous research, no relationship was found between boundary strength and boundary......While listening to music, people often unwittingly break down musical pieces into constituent chunks such as verses and choruses. Music segmentation studies have suggested that some consensus regarding boundary perception exists, despite individual differences. However, neither the effects...
A Liver-Centric Multiscale Modeling Framework for Xenobiotics.
Directory of Open Access Journals (Sweden)
James P Sluka
Full Text Available We describe a multi-scale, liver-centric in silico modeling framework for acetaminophen pharmacology and metabolism. We focus on a computational model to characterize whole body uptake and clearance, liver transport and phase I and phase II metabolism. We do this by incorporating sub-models that span three scales; Physiologically Based Pharmacokinetic (PBPK modeling of acetaminophen uptake and distribution at the whole body level, cell and blood flow modeling at the tissue/organ level and metabolism at the sub-cellular level. We have used standard modeling modalities at each of the three scales. In particular, we have used the Systems Biology Markup Language (SBML to create both the whole-body and sub-cellular scales. Our modeling approach allows us to run the individual sub-models separately and allows us to easily exchange models at a particular scale without the need to extensively rework the sub-models at other scales. In addition, the use of SBML greatly facilitates the inclusion of biological annotations directly in the model code. The model was calibrated using human in vivo data for acetaminophen and its sulfate and glucuronate metabolites. We then carried out extensive parameter sensitivity studies including the pairwise interaction of parameters. We also simulated population variation of exposure and sensitivity to acetaminophen. Our modeling framework can be extended to the prediction of liver toxicity following acetaminophen overdose, or used as a general purpose pharmacokinetic model for xenobiotics.
A multiscale model for virus capsid dynamics.
Chen, Changjun; Saxena, Rishu; Wei, Guo-Wei
2010-01-01
Viruses are infectious agents that can cause epidemics and pandemics. The understanding of virus formation, evolution, stability, and interaction with host cells is of great importance to the scientific community and public health. Typically, a virus complex in association with its aquatic environment poses a fabulous challenge to theoretical description and prediction. In this work, we propose a differential geometry-based multiscale paradigm to model complex biomolecule systems. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum domain of the fluid mechanical description of the aquatic environment from the microscopic discrete domain of the atomistic description of the biomolecule. A multiscale action functional is constructed as a unified framework to derive the governing equations for the dynamics of different scales. We show that the classical Navier-Stokes equation for the fluid dynamics and Newton's equation for the molecular dynamics can be derived from the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows.
Neural network based multiscale image restoration approach
de Castro, Ana Paula A.; da Silva, José D. S.
2007-02-01
This paper describes a neural network based multiscale image restoration approach. Multilayer perceptrons are trained with artificial images of degraded gray level circles, in an attempt to make the neural network learn inherent space relations of the degraded pixels. The present approach simulates the degradation by a low pass Gaussian filter blurring operation and the addition of noise to the pixels at pre-established rates. The training process considers the degraded image as input and the non-degraded image as output for the supervised learning process. The neural network thus performs an inverse operation by recovering a quasi non-degraded image in terms of least squared. The main difference of the approach to existing ones relies on the fact that the space relations are taken from different scales, thus providing relational space data to the neural network. The approach is an attempt to come up with a simple method that leads to an optimum solution to the problem. Considering different window sizes around a pixel simulates the multiscale operation. In the generalization phase the neural network is exposed to indoor, outdoor, and satellite degraded images following the same steps use for the artificial circle image.
Multiscale coherent structures in tokamak plasma turbulence
International Nuclear Information System (INIS)
Xu, G. S.; Wan, B. N.; Zhang, W.; Yang, Q. W.; Wang, L.; Wen, Y. Z.
2006-01-01
A 12-tip poloidal probe array is used on the HT-7 superconducting tokamak [Li, Wan, and Mao, Plasma Phys. Controlled Fusion 42, 135 (2000)] to measure plasma turbulence in the edge region. Some statistical analysis techniques are used to characterize the turbulence structures. It is found that the plasma turbulence is composed of multiscale coherent structures, i.e., turbulent eddies and there is self-similarity in a relative short scale range. The presence of the self-similarity is found due to the structural similarity of these eddies between different scales. These turbulent eddies constitute the basic convection cells, so the self-similar range is just the dominant scale range relevant to transport. The experimental results also indicate that the plasma turbulence is dominated by low-frequency and long-wavelength fluctuation components and its dispersion relation shows typical electron-drift-wave characteristics. Some large-scale coherent structures intermittently burst out and exhibit a very long poloidal extent, even longer than 6 cm. It is found that these large-scale coherent structures are mainly contributed by the low-frequency and long-wavelength fluctuating components and their presence is responsible for the observations of long-range correlations, i.e., the correlation in the scale range much longer than the turbulence decorrelation scale. These experimental observations suggest that the coexistence of multiscale coherent structures results in the self-similar turbulent state
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.
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.
Multi-scale biomedical systems: measurement challenges
International Nuclear Information System (INIS)
Summers, R
2016-01-01
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. (paper)
Mammographic feature enhancement by multiscale analysis
International Nuclear Information System (INIS)
Laine, A.F.; Schuler, S.; Fan, J.; Huda, W.
1994-01-01
This paper introduces a novel approach for accomplishing mammographic feature analysis by overcomplete multiresolution representations. The authors show that efficient representations may be identified within a continuum of scale-space and used to enhance features of importance to mammography. Methods of contrast enhancement are described based on three overcomplete multiscale representations: (1) the dyadic wavelet transform (separable), (2) the var-phi-transform (nonseparable, nonorthogonal), and (3) the hexagonal wavelet transform (nonseparable). Multiscale edges identified within distinct levels of transform space provide local support for image enhancement. Mammograms are reconstructed from wavelet coefficients modified at one or more levels by local and global nonlinear operators. In each case, edges and gain parameters are identified adaptively by a measure of energy within each level of scale-space. The authors show quantitatively that transform coefficients, modified by adaptive nonlinear operators, can make more obvious unseen or barely seen features of mammography without requiring additional radiation. The results are compared with traditional image enhancement techniques by measuring the local contrast of known mammographic features. The authors demonstrate that features extracted from multiresolution representations can provide an adaptive mechanism for accomplishing local contrast enhancement. By improving the visualization of breast pathology, they can improve chances of early detection while requiring less time to evaluate mammograms for most patients
Multiscale permutation entropy analysis of electrocardiogram
Liu, Tiebing; Yao, Wenpo; Wu, Min; Shi, Zhaorong; Wang, Jun; Ning, Xinbao
2017-04-01
To make a comprehensive nonlinear analysis to ECG, multiscale permutation entropy (MPE) was applied to ECG characteristics extraction to make a comprehensive nonlinear analysis of ECG. Three kinds of ECG from PhysioNet database, congestive heart failure (CHF) patients, healthy young and elderly subjects, are applied in this paper. We set embedding dimension to 4 and adjust scale factor from 2 to 100 with a step size of 2, and compare MPE with multiscale entropy (MSE). As increase of scale factor, MPE complexity of the three ECG signals are showing first-decrease and last-increase trends. When scale factor is between 10 and 32, complexities of the three ECG had biggest difference, entropy of the elderly is 0.146 less than the CHF patients and 0.025 larger than the healthy young in average, in line with normal physiological characteristics. Test results showed that MPE can effectively apply in ECG nonlinear analysis, and can effectively distinguish different ECG signals.
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.
Multiscale Convolutional Neural Networks for Hand Detection
Directory of Open Access Journals (Sweden)
Shiyang Yan
2017-01-01
Full Text Available Unconstrained hand detection in still images plays an important role in many hand-related vision problems, for example, hand tracking, gesture analysis, human action recognition and human-machine interaction, and sign language recognition. Although hand detection has been extensively studied for decades, it is still a challenging task with many problems to be tackled. The contributing factors for this complexity include heavy occlusion, low resolution, varying illumination conditions, different hand gestures, and the complex interactions between hands and objects or other hands. In this paper, we propose a multiscale deep learning model for unconstrained hand detection in still images. Deep learning models, and deep convolutional neural networks (CNNs in particular, have achieved state-of-the-art performances in many vision benchmarks. Developed from the region-based CNN (R-CNN model, we propose a hand detection scheme based on candidate regions generated by a generic region proposal algorithm, followed by multiscale information fusion from the popular VGG16 model. Two benchmark datasets were applied to validate the proposed method, namely, the Oxford Hand Detection Dataset and the VIVA Hand Detection Challenge. We achieved state-of-the-art results on the Oxford Hand Detection Dataset and had satisfactory performance in the VIVA Hand Detection Challenge.
Variational integrators for electric circuits
International Nuclear Information System (INIS)
Ober-Blöbaum, Sina; Tao, Molei; Cheng, Mulin; Owhadi, Houman; Marsden, Jerrold E.
2013-01-01
In this contribution, we develop a variational integrator for the simulation of (stochastic and multiscale) electric circuits. When considering the dynamics of an electric circuit, one is faced with three special situations: 1. The system involves external (control) forcing through external (controlled) voltage sources and resistors. 2. The system is constrained via the Kirchhoff current (KCL) and voltage laws (KVL). 3. The Lagrangian is degenerate. Based on a geometric setting, an appropriate variational formulation is presented to model the circuit from which the equations of motion are derived. A time-discrete variational formulation provides an iteration scheme for the simulation of the electric circuit. Dependent on the discretization, the intrinsic degeneracy of the system can be canceled for the discrete variational scheme. In this way, a variational integrator is constructed that gains several advantages compared to standard integration tools for circuits; in particular, a comparison to BDF methods (which are usually the method of choice for the simulation of electric circuits) shows that even for simple LCR circuits, a better energy behavior and frequency spectrum preservation can be observed using the developed variational integrator
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.
Analysis of complex time series using refined composite multiscale entropy
International Nuclear Information System (INIS)
Wu, Shuen-De; Wu, Chiu-Wen; Lin, Shiou-Gwo; Lee, Kung-Yen; Peng, Chung-Kang
2014-01-01
Multiscale entropy (MSE) is an effective algorithm for measuring the complexity of a time series that has been applied in many fields successfully. However, MSE may yield an inaccurate estimation of entropy or induce undefined entropy because the coarse-graining procedure reduces the length of a time series considerably at large scales. Composite multiscale entropy (CMSE) was recently proposed to improve the accuracy of MSE, but it does not resolve undefined entropy. Here we propose a refined composite multiscale entropy (RCMSE) to improve CMSE. For short time series analyses, we demonstrate that RCMSE increases the accuracy of entropy estimation and reduces the probability of inducing undefined entropy.
Multi-Scale Scattering Transform in Music Similarity Measuring
Wang, Ruobai
Scattering transform is a Mel-frequency spectrum based, time-deformation stable method, which can be used in evaluating music similarity. Compared with Dynamic time warping, it has better performance in detecting similar audio signals under local time-frequency deformation. Multi-scale scattering means to combine scattering transforms of different window lengths. This paper argues that, multi-scale scattering transform is a good alternative of dynamic time warping in music similarity measuring. We tested the performance of multi-scale scattering transform against other popular methods, with data designed to represent different conditions.
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.
Multi-scale salient feature extraction on mesh models
Yang, Yongliang; Shen, ChaoHui
2012-01-01
We present a new method of extracting multi-scale salient features on meshes. It is based on robust estimation of curvature on multiple scales. The coincidence between salient feature and the scale of interest can be established straightforwardly, where detailed feature appears on small scale and feature with more global shape information shows up on large scale. We demonstrate this multi-scale description of features accords with human perception and can be further used for several applications as feature classification and viewpoint selection. Experiments exhibit that our method as a multi-scale analysis tool is very helpful for studying 3D shapes. © 2012 Springer-Verlag.
International Nuclear Information System (INIS)
NiewieczerzaŁ, Daniel; Oleksy, CzesŁaw; Szczepkowicz, Andrzej
2012-01-01
Multi-scale simulations of field ion microscopy images of faceted and hemispherical samples are performed using a 3D model. It is shown that faceted crystals have compressed images even in cases with no shank. The presence of the shank increases the compression of images of faceted crystals quantitatively in the same way as for hemispherical samples. It is hereby proven that the shank does not influence significantly the local, relative variations of the magnification caused by the atomic-scale structure of the sample. -- Highlights: ► Multi-scale simulations of field ion microscopy images. ► Faceted and hemispherical samples with and without shank. ► Shank causes overall compression, but does not influence local magnification effects. ► Image compression linearly increases with the shank angle. ► Shank changes compression of image of faceted tip in the same way as for smooth sample.
RBF Multiscale Collocation for Second Order Elliptic Boundary Value Problems
Farrell, Patricio; Wendland, Holger
2013-01-01
In this paper, we discuss multiscale radial basis function collocation methods for solving elliptic partial differential equations on bounded domains. The approximate solution is constructed in a multilevel fashion, each level using compactly
A multiscale mortar multipoint flux mixed finite element method
Wheeler, Mary Fanett; Xue, Guangri; Yotov, Ivan
2012-01-01
In this paper, we develop a multiscale mortar multipoint flux mixed finite element method for second order elliptic problems. The equations in the coarse elements (or subdomains) are discretized on a fine grid scale by a multipoint flux mixed finite
Fast Multiscale Reservoir Simulations using POD-DEIM Model Reduction
Ghasemi, Mohammadreza; Yang, Yanfang; Gildin, Eduardo; Efendiev, Yalchin R.; Calo, Victor M.
2015-01-01
snapshots are inexpensively computed using local model reduction techniques based on Generalized Multiscale Finite Element Method (GMsFEM) which provides (1) a hierarchical approximation of snapshot vectors (2) adaptive computations by using coarse grids (3
Multi-Scale Simulation of High Energy Density Ionic Liquids
National Research Council Canada - National Science Library
Voth, Gregory A
2007-01-01
The focus of this AFOSR project was the molecular dynamics (MD) simulation of ionic liquid structure, dynamics, and interfacial properties, as well as multi-scale descriptions of these novel liquids (e.g...
Multi-scale modeling strategies in materials science—The ...
Indian Academy of Sciences (India)
Unknown
Multi-scale models; quasicontinuum method; finite elements. 1. Introduction ... boundary with external stresses, and the interaction of a lattice dislocation with a grain ..... mum value of se over the elements that touch node α. The acceleration of ...
Lifetime statistics of quantum chaos studied by a multiscale analysis
Di Falco, A.; Krauss, T. F.; Fratalocchi, Andrea
2012-01-01
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
Randomized Oversampling for Generalized Multiscale Finite Element Methods
Calo, Victor M.; Efendiev, Yalchin R.; Galvis, Juan; Li, Guanglian
2016-01-01
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
Toward the multiscale nature of stress corrosion cracking
Directory of Open Access Journals (Sweden)
Xiaolong Liu
2018-02-01
Full Text Available This article reviews the multiscale nature of stress corrosion cracking (SCC observed by high-resolution characterizations in austenite stainless steels and Ni-base superalloys in light water reactors (including boiling water reactors, pressurized water reactors, and supercritical water reactors with related opinions. A new statistical summary and comparison of observed degradation phenomena at different length scales is included. The intrinsic causes of this multiscale nature of SCC are discussed based on existing evidence and related opinions, ranging from materials theory to practical processing technologies. Questions of interest are then discussed to improve bottom-up understanding of the intrinsic causes. Last, a multiscale modeling and simulation methodology is proposed as a promising interdisciplinary solution to understand the intrinsic causes of the multiscale nature of SCC in light water reactors, based on a review of related supporting application evidence.
Multiscale model reduction for shale gas transport in fractured media
Akkutlu, I. Y.; Efendiev, Yalchin R.; Vasilyeva, Maria
2016-01-01
fracture distributions on an unstructured grid; (2) develop GMsFEM for nonlinear flows; and (3) develop online basis function strategies to adaptively improve the convergence. The number of multiscale basis functions in each coarse region represents
Distributed Multiscale Data Analysis and Processing for Sensor Networks
National Research Council Canada - National Science Library
Wagner, Raymond; Sarvotham, Shriram; Choi, Hyeokho; Baraniuk, Richard
2005-01-01
.... Second, the communication overhead of multiscale algorithms can become prohibitive. In this paper, we take a first step in addressing both shortcomings by introducing two new distributed multiresolution transforms...
Examining Multiscale Movement Coordination in Collaborative Problem Solving
DEFF Research Database (Denmark)
Wiltshire, Travis; Steffensen, Sune Vork
2017-01-01
During collaborative problem solving (CPS), coordination occurs at different spatial and temporal scales. This multiscale coordination should, at least on some scales, play a functional role in facilitating effective collaboration outcomes. To evaluate this, we conducted a study of computer...
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.
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.
An approach to multiscale modelling with graph grammars.
Ong, Yongzhi; Streit, Katarína; Henke, Michael; Kurth, Winfried
2014-09-01
Functional-structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.
Long-term Stable Conservative Multiscale Methods for Vortex Flows
2017-10-31
Computing Department, Florida State (January 2016) - L. Rebholz, SIAM Southeast 2016, Special session on Recent advances in fluid flow and...Multiscale Methods for Vortex Flows (x) Material has been given an OPSEC review and it has been determined to be non sensitive and, except for...distribution is unlimited. UU UU UU UU 31-10-2017 1-Aug-2014 31-Jul-2017 Final Report: Long-term Stable Conservative Multiscale Methods for Vortex Flows
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....
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.
Multi-scale modeling of composites
DEFF Research Database (Denmark)
Azizi, Reza
A general method to obtain the homogenized response of metal-matrix composites is developed. It is assumed that the microscopic scale is sufficiently small compared to the macroscopic scale such that the macro response does not affect the micromechanical model. Therefore, the microscopic scale......-Mandel’s energy principle is used to find macroscopic operators based on micro-mechanical analyses using the finite element method under generalized plane strain condition. A phenomenologically macroscopic model for metal matrix composites is developed based on constitutive operators describing the elastic...... to plastic deformation. The macroscopic operators found, can be used to model metal matrix composites on the macroscopic scale using a hierarchical multi-scale approach. Finally, decohesion under tension and shear loading is studied using a cohesive law for the interface between matrix and fiber....
Quantifying multiscale inefficiency in electricity markets
Energy Technology Data Exchange (ETDEWEB)
Uritskaya, Olga Y. [Department of Economics, University of Calgary, Calgary, Alberta T2N 1N4, and Department of Economics and Management, St. Petersburg Polytechnic University, St. Petersburg (Russian Federation); Serletis, Apostolos [Department of Economics, University of Calgary, Calgary, Alberta (Canada)
2008-11-15
One of the basic features of efficient markets is the absence of correlations between price increments over any time scale leading to random walk-type behavior of prices. In this paper, we propose a new approach for measuring deviations from the efficient market state based on an analysis of scale-dependent fractal exponent characterizing correlations at different time scales. The approach is applied to two electricity markets, Alberta and Mid Columbia (Mid-C), as well as to the AECO Alberta natural gas market (for purposes of providing a comparison between storable and non-storable commodities). We show that price fluctuations in all studied markets are not efficient, with electricity prices exhibiting complex multiscale correlated behavior not captured by monofractal methods used in previous studies. (author)
On multiscale moving contact line theory.
Li, Shaofan; Fan, Houfu
2015-07-08
In this paper, a multiscale moving contact line (MMCL) theory is presented and employed to simulate liquid droplet spreading and capillary motion. The proposed MMCL theory combines a coarse-grained adhesive contact model with a fluid interface membrane theory, so that it can couple molecular scale adhesive interaction and surface tension with hydrodynamics of microscale flow. By doing so, the intermolecular force, the van der Waals or double layer force, separates and levitates the liquid droplet from the supporting solid substrate, which avoids the shear stress singularity caused by the no-slip condition in conventional hydrodynamics theory of moving contact line. Thus, the MMCL allows the difference of the surface energies and surface stresses to drive droplet spreading naturally. To validate the proposed MMCL theory, we have employed it to simulate droplet spreading over various elastic substrates. The numerical simulation results obtained by using MMCL are in good agreement with the molecular dynamics results reported in the literature.
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.
Quantifying multiscale inefficiency in electricity markets
International Nuclear Information System (INIS)
Uritskaya, Olga Y.; Serletis, Apostolos
2008-01-01
One of the basic features of efficient markets is the absence of correlations between price increments over any time scale leading to random walk-type behavior of prices. In this paper, we propose a new approach for measuring deviations from the efficient market state based on an analysis of scale-dependent fractal exponent characterizing correlations at different time scales. The approach is applied to two electricity markets, Alberta and Mid Columbia (Mid-C), as well as to the AECO Alberta natural gas market (for purposes of providing a comparison between storable and non-storable commodities). We show that price fluctuations in all studied markets are not efficient, with electricity prices exhibiting complex multiscale correlated behavior not captured by monofractal methods used in previous studies. (author)
Multiscale modeling of three-dimensional genome
Zhang, Bin; Wolynes, Peter
The genome, the blueprint of life, contains nearly all the information needed to build and maintain an entire organism. A comprehensive understanding of the genome is of paramount interest to human health and will advance progress in many areas, including life sciences, medicine, and biotechnology. The overarching goal of my research is to understand the structure-dynamics-function relationships of the human genome. In this talk, I will be presenting our efforts in moving towards that goal, with a particular emphasis on studying the three-dimensional organization, the structure of the genome with multi-scale approaches. Specifically, I will discuss the reconstruction of genome structures at both interphase and metaphase by making use of data from chromosome conformation capture experiments. Computationally modeling of chromatin fiber at atomistic level from first principles will also be presented as our effort for studying the genome structure from bottom up.
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.
Hybrid stochastic simplifications for multiscale gene networks
Directory of Open Access Journals (Sweden)
Debussche Arnaud
2009-09-01
Full Text Available Abstract Background Stochastic simulation of gene networks by Markov processes has important applications in molecular biology. The complexity of exact simulation algorithms scales with the number of discrete jumps to be performed. Approximate schemes reduce the computational time by reducing the number of simulated discrete events. Also, answering important questions about the relation between network topology and intrinsic noise generation and propagation should be based on general mathematical results. These general results are difficult to obtain for exact models. Results We propose a unified framework for hybrid simplifications of Markov models of multiscale stochastic gene networks dynamics. We discuss several possible hybrid simplifications, and provide algorithms to obtain them from pure jump processes. In hybrid simplifications, some components are discrete and evolve by jumps, while other components are continuous. Hybrid simplifications are obtained by partial Kramers-Moyal expansion 123 which is equivalent to the application of the central limit theorem to a sub-model. By averaging and variable aggregation we drastically reduce simulation time and eliminate non-critical reactions. Hybrid and averaged simplifications can be used for more effective simulation algorithms and for obtaining general design principles relating noise to topology and time scales. The simplified models reproduce with good accuracy the stochastic properties of the gene networks, including waiting times in intermittence phenomena, fluctuation amplitudes and stationary distributions. The methods are illustrated on several gene network examples. Conclusion Hybrid simplifications can be used for onion-like (multi-layered approaches to multi-scale biochemical systems, in which various descriptions are used at various scales. Sets of discrete and continuous variables are treated with different methods and are coupled together in a physically justified approach.
MULTISCALE DYNAMICS OF SOLAR MAGNETIC STRUCTURES
International Nuclear Information System (INIS)
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.
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
Multiscale sampling model for motion integration.
Sherbakov, Lena; Yazdanbakhsh, Arash
2013-09-30
Biologically plausible strategies for visual scene integration across spatial and temporal domains continues to be a challenging topic. The fundamental question we address is whether classical problems in motion integration, such as the aperture problem, can be solved in a model that samples the visual scene at multiple spatial and temporal scales in parallel. We hypothesize that fast interareal connections that allow feedback of information between cortical layers are the key processes that disambiguate motion direction. We developed a neural model showing how the aperture problem can be solved using different spatial sampling scales between LGN, V1 layer 4, V1 layer 6, and area MT. Our results suggest that multiscale sampling, rather than feedback explicitly, is the key process that gives rise to end-stopped cells in V1 and enables area MT to solve the aperture problem without the need for calculating intersecting constraints or crafting intricate patterns of spatiotemporal receptive fields. Furthermore, the model explains why end-stopped cells no longer emerge in the absence of V1 layer 6 activity (Bolz & Gilbert, 1986), why V1 layer 4 cells are significantly more end-stopped than V1 layer 6 cells (Pack, Livingstone, Duffy, & Born, 2003), and how it is possible to have a solution to the aperture problem in area MT with no solution in V1 in the presence of driving feedback. In summary, while much research in the field focuses on how a laminar architecture can give rise to complicated spatiotemporal receptive fields to solve problems in the motion domain, we show that one can reframe motion integration as an emergent property of multiscale sampling achieved concurrently within lamina and across multiple visual areas.
Parallel multiscale simulations of a brain aneurysm
International Nuclear Information System (INIS)
Grinberg, Leopold; Fedosov, Dmitry A.; Karniadakis, George Em
2013-01-01
Cardiovascular pathologies, such as a brain aneurysm, are affected by the global blood circulation as well as by the local microrheology. Hence, developing computational models for such cases requires the coupling of disparate spatial and temporal scales often governed by diverse mathematical descriptions, e.g., by partial differential equations (continuum) and ordinary differential equations for discrete particles (atomistic). However, interfacing atomistic-based with continuum-based domain discretizations is a challenging problem that requires both mathematical and computational advances. We present here a hybrid methodology that enabled us to perform the first multiscale simulations of platelet depositions on the wall of a brain aneurysm. The large scale flow features in the intracranial network are accurately resolved by using the high-order spectral element Navier–Stokes solver NεκTαr. The blood rheology inside the aneurysm is modeled using a coarse-grained stochastic molecular dynamics approach (the dissipative particle dynamics method) implemented in the parallel code LAMMPS. The continuum and atomistic domains overlap with interface conditions provided by effective forces computed adaptively to ensure continuity of states across the interface boundary. A two-way interaction is allowed with the time-evolving boundary of the (deposited) platelet clusters tracked by an immersed boundary method. The corresponding heterogeneous solvers (NεκTαr and LAMMPS) are linked together by a computational multilevel message passing interface that facilitates modularity and high parallel efficiency. Results of multiscale simulations of clot formation inside the aneurysm in a patient-specific arterial tree are presented. We also discuss the computational challenges involved and present scalability results of our coupled solver on up to 300 K computer processors. Validation of such coupled atomistic-continuum models is a main open issue that has to be addressed in
Porta, Alberto; Bari, Vlasta; Ranuzzi, Giovanni; De Maria, Beatrice; Baselli, Giuseppe
2017-09-01
We propose a multiscale complexity (MSC) method assessing irregularity in assigned frequency bands and being appropriate for analyzing the short time series. It is grounded on the identification of the coefficients of an autoregressive model, on the computation of the mean position of the poles generating the components of the power spectral density in an assigned frequency band, and on the assessment of its distance from the unit circle in the complex plane. The MSC method was tested on simulations and applied to the short heart period (HP) variability series recorded during graded head-up tilt in 17 subjects (age from 21 to 54 years, median = 28 years, 7 females) and during paced breathing protocols in 19 subjects (age from 27 to 35 years, median = 31 years, 11 females) to assess the contribution of time scales typical of the cardiac autonomic control, namely in low frequency (LF, from 0.04 to 0.15 Hz) and high frequency (HF, from 0.15 to 0.5 Hz) bands to the complexity of the cardiac regulation. The proposed MSC technique was compared to a traditional model-free multiscale method grounded on information theory, i.e., multiscale entropy (MSE). The approach suggests that the reduction of HP variability complexity observed during graded head-up tilt is due to a regularization of the HP fluctuations in LF band via a possible intervention of sympathetic control and the decrement of HP variability complexity observed during slow breathing is the result of the regularization of the HP variations in both LF and HF bands, thus implying the action of physiological mechanisms working at time scales even different from that of respiration. MSE did not distinguish experimental conditions at time scales larger than 1. Over a short time series MSC allows a more insightful association between cardiac control complexity and physiological mechanisms modulating cardiac rhythm compared to a more traditional tool such as MSE.
Directory of Open Access Journals (Sweden)
Khairul Salleh Basaruddin
Full Text Available Randomness in the microstructure due to variations in microscopic properties and geometrical information is used to predict the stochastically homogenised properties of cellular media. Two stochastic problems at the micro-scale level that commonly occur due to fabrication inaccuracies, degradation mechanisms or natural heterogeneity were analysed using a stochastic homogenisation method based on a first-order perturbation. First, the influence of Young's modulus variation in an adhesive on the macroscopic properties of an aluminium-adhesive honeycomb structure was investigated. The fluctuations in the microscopic properties were then combined by varying the microstructure periodicity in a corrugated-core sandwich plate to obtain the variation of the homogenised property. The numerical results show that the uncertainties in the microstructure affect the dispersion of the homogenised property. These results indicate the importance of the presented stochastic multi-scale analysis for the design and fabrication of cellular solids when considering microscopic random variation.
Expanded Mixed Multiscale Finite Element Methods and Their Applications for Flows in Porous Media
Jiang, L.; Copeland, D.; Moulton, J. D.
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
Refined composite multiscale weighted-permutation entropy of financial time series
Zhang, Yongping; Shang, Pengjian
2018-04-01
For quantifying the complexity of nonlinear systems, multiscale weighted-permutation entropy (MWPE) has recently been proposed. MWPE has incorporated amplitude information and been applied to account for the multiple inherent dynamics of time series. However, MWPE may be unreliable, because its estimated values show large fluctuation for slight variation of the data locations, and a significant distinction only for the different length of time series. Therefore, we propose the refined composite multiscale weighted-permutation entropy (RCMWPE). By comparing the RCMWPE results with other methods' results on both synthetic data and financial time series, RCMWPE method shows not only the advantages inherited from MWPE but also lower sensitivity to the data locations, more stable and much less dependent on the length of time series. Moreover, we present and discuss the results of RCMWPE method on the daily price return series from Asian and European stock markets. There are significant differences between Asian markets and European markets, and the entropy values of Hang Seng Index (HSI) are close to but higher than those of European markets. The reliability of the proposed RCMWPE method has been supported by simulations on generated and real data. It could be applied to a variety of fields to quantify the complexity of the systems over multiple scales more accurately.
Luo, Aiwen; An, Fengwei; Zhang, Xiangyu; Chen, Lei; Huang, Zunkai; Jürgen Mattausch, Hans
2018-04-01
Feature extraction techniques are a cornerstone of object detection in computer-vision-based applications. The detection performance of vison-based detection systems is often degraded by, e.g., changes in the illumination intensity of the light source, foreground-background contrast variations or automatic gain control from the camera. In order to avoid such degradation effects, we present a block-based L1-norm-circuit architecture which is configurable for different image-cell sizes, cell-based feature descriptors and image resolutions according to customization parameters from the circuit input. The incorporated flexibility in both the image resolution and the cell size for multi-scale image pyramids leads to lower computational complexity and power consumption. Additionally, an object-detection prototype for performance evaluation in 65 nm CMOS implements the proposed L1-norm circuit together with a histogram of oriented gradients (HOG) descriptor and a support vector machine (SVM) classifier. The proposed parallel architecture with high hardware efficiency enables real-time processing, high detection robustness, small chip-core area as well as low power consumption for multi-scale object detection.
Multi-scale approximation of Vlasov equation
International Nuclear Information System (INIS)
Mouton, A.
2009-09-01
One of the most important difficulties of numerical simulation of magnetized plasmas is the existence of multiple time and space scales, which can be very different. In order to produce good simulations of these multi-scale phenomena, it is recommended to develop some models and numerical methods which are adapted to these problems. Nowadays, the two-scale convergence theory introduced by G. Nguetseng and G. Allaire is one of the tools which can be used to rigorously derive multi-scale limits and to obtain new limit models which can be discretized with a usual numerical method: this procedure is so-called a two-scale numerical method. The purpose of this thesis is to develop a two-scale semi-Lagrangian method and to apply it on a gyrokinetic Vlasov-like model in order to simulate a plasma submitted to a large external magnetic field. However, the physical phenomena we have to simulate are quite complex and there are many questions without answers about the behaviour of a two-scale numerical method, especially when such a method is applied on a nonlinear model. In a first part, we develop a two-scale finite volume method and we apply it on the weakly compressible 1D isentropic Euler equations. Even if this mathematical context is far from a Vlasov-like model, it is a relatively simple framework in order to study the behaviour of a two-scale numerical method in front of a nonlinear model. In a second part, we develop a two-scale semi-Lagrangian method for the two-scale model developed by E. Frenod, F. Salvarani et E. Sonnendrucker in order to simulate axisymmetric charged particle beams. Even if the studied physical phenomena are quite different from magnetic fusion experiments, the mathematical context of the one-dimensional paraxial Vlasov-Poisson model is very simple for establishing the basis of a two-scale semi-Lagrangian method. In a third part, we use the two-scale convergence theory in order to improve M. Bostan's weak-* convergence results about the finite
Multiscale Modeling of Mesoscale and Interfacial Phenomena
Petsev, Nikolai Dimitrov
we provide a novel and general framework for multiscale modeling of systems featuring one or more dissolved species. This makes it possible to retain molecular detail for parts of the problem that require it while using a simple, continuum description for parts where high detail is unnecessary, reducing the number of degrees of freedom (i.e. number of particles) dramatically. This opens the possibility for modeling ion transport in biological processes and biomolecule assembly in ionic solution, as well as electrokinetic phenomena at interfaces such as corrosion. The number of particles in the system is further reduced through an integrated boundary approach, which we apply to colloidal suspensions. In this thesis, we describe this general framework for multiscale modeling single- and multicomponent systems, provide several simple equilibrium and non-equilibrium case studies, and discuss future applications.
Lu, Qian; Li, Jun; Wang, Jinghan; Li, Kun; Li, Jingjing; Han, Pei; Chen, Paul; Zhou, Wenguang
2017-11-01
The ability of algae to produce lipids comprising of unsaturated fatty acids varies with strains and culture conditions. This study investigates the effect of temperature on the production of unsaturated fatty acids in Scenedesmus sp. grown on oil crop residue based medium. At low temperature (10°C), synthesis of lipids compromising of high contents of unsaturated fatty acids took place primarily in the early stage while protein accumulation mainly occurred in the late stage. This stepwise lipid-protein synthesis process was found to be associated with the contents of acetyl-CoA and α-KG in the algal cells. A mechanism was proposed and tested through simulation experiments which quantified the carbon flux allocation in algal cells at different cultivation stages. It is concluded that low culture temperature such as 10°C is suitable for the production of lipids comprising of unsaturated fatty acids. Copyright © 2017 Elsevier Ltd. All rights reserved.
Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen
Energy Technology Data Exchange (ETDEWEB)
Plechac, Petr [Univ. of Tennessee, Knoxville, TN (United States). Dept. of Mathematics; Univ. of Delaware, Newark, DE (United States). Dept. of Mathematics; Vlachos, Dionisios [Univ. of Delaware, Newark, DE (United States). Dept. of Chemical and Biomolecular Engineering; Katsoulakis, Markos [Univ. of Massachusetts, Amherst, MA (United States). Dept. of Mathematics
2013-09-05
The overall objective of this project is to develop multiscale models for understanding and eventually designing complex processes for renewables. To the best of our knowledge, our work is the first attempt at modeling complex reacting systems, whose performance relies on underlying multiscale mathematics. Our specific application lies at the heart of biofuels initiatives of DOE and entails modeling of catalytic systems, to enable economic, environmentally benign, and efficient conversion of biomass into either hydrogen or valuable chemicals. Specific goals include: (i) Development of rigorous spatio-temporal coarse-grained kinetic Monte Carlo (KMC) mathematics and simulation for microscopic processes encountered in biomass transformation. (ii) Development of hybrid multiscale simulation that links stochastic simulation to a deterministic partial differential equation (PDE) model for an entire reactor. (iii) Development of hybrid multiscale simulation that links KMC simulation with quantum density functional theory (DFT) calculations. (iv) Development of parallelization of models of (i)-(iii) to take advantage of Petaflop computing and enable real world applications of complex, multiscale models. In this NCE period, we continued addressing these objectives and completed the proposed work. Main initiatives, key results, and activities are outlined.
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.
2D deblending using the multi-scale shaping scheme
Li, Qun; Ban, Xingan; Gong, Renbin; Li, Jinnuo; Ge, Qiang; Zu, Shaohuan
2018-01-01
Deblending can be posed as an inversion problem, which is ill-posed and requires constraint to obtain unique and stable solution. In blended record, signal is coherent, whereas interference is incoherent in some domains (e.g., common receiver domain and common offset domain). Due to the different sparsity, coefficients of signal and interference locate in different curvelet scale domains and have different amplitudes. Take into account the two differences, we propose a 2D multi-scale shaping scheme to constrain the sparsity to separate the blended record. In the domain where signal concentrates, the multi-scale scheme passes all the coefficients representing signal, while, in the domain where interference focuses, the multi-scale scheme suppresses the coefficients representing interference. Because the interference is suppressed evidently at each iteration, the constraint of multi-scale shaping operator in all scale domains are weak to guarantee the convergence of algorithm. We evaluate the performance of the multi-scale shaping scheme and the traditional global shaping scheme by using two synthetic and one field data examples.
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
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.
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 image restoration in nulear medicine
International Nuclear Information System (INIS)
Jammal, G.
2001-01-01
This work develops, analyzes and validates a new multiscale restoration framework for denoising and deconvolution in photon limited imagery. Denoising means the estimation of the intensity of a Poisson process from a single observation of the counts, whereas deconvolution refers to the recovery of an object related through a linear system of equations to the intensity function of the Poisson data. The developed framework has been named DeQuant in analogy to Denoising when the noise is of Quantum nature. DeQuant works according to the following scheme. (1) It starts by testing the statistical significance of the wavelet coefficients of the Poisson process, based on the knowledge of their probability density function. (2) A regularization constraint assigns a new value to the non significant coefficients enabling therewith to reduce artifacts and incorporate realistic prior information into the estimation process. Finally, (3) the application of the inverse wavelet transform yields the restored object. The whole procedure is iterated before obtaining the final estimate. The validation of DeQuant on nuclear medicine images showed excellent results. The obtained estimates enable a greater diagnostic confidence in clinical nuclear medicine since they give the physician the access to the diagnosis relevant information with a measure of the significance of the detected structures [de
Predicting FLDs Using a Multiscale Modeling Scheme
Wu, Z.; Loy, C.; Wang, E.; Hegadekatte, V.
2017-09-01
The measurement of a single forming limit diagram (FLD) requires significant resources and is time consuming. We have developed a multiscale modeling scheme to predict FLDs using a combination of limited laboratory testing, crystal plasticity (VPSC) modeling, and dual sequential-stage finite element (ABAQUS/Explicit) modeling with the Marciniak-Kuczynski (M-K) criterion to determine the limit strain. We have established a means to work around existing limitations in ABAQUS/Explicit by using an anisotropic yield locus (e.g., BBC2008) in combination with the M-K criterion. We further apply a VPSC model to reduce the number of laboratory tests required to characterize the anisotropic yield locus. In the present work, we show that the predicted FLD is in excellent agreement with the measured FLD for AA5182 in the O temper. Instead of 13 different tests as for a traditional FLD determination within Novelis, our technique uses just four measurements: tensile properties in three orientations; plane strain tension; biaxial bulge; and the sheet crystallographic texture. The turnaround time is consequently far less than for the traditional laboratory measurement of the FLD.
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.
A multiscale modeling approach for biomolecular systems
Energy Technology Data Exchange (ETDEWEB)
Bowling, Alan, E-mail: bowling@uta.edu; Haghshenas-Jaryani, Mahdi, E-mail: mahdi.haghshenasjaryani@mavs.uta.edu [The University of Texas at Arlington, Department of Mechanical and Aerospace Engineering (United States)
2015-04-15
This paper presents a new multiscale molecular dynamic model for investigating the effects of external interactions, such as contact and impact, during stepping and docking of motor proteins and other biomolecular systems. The model retains the mass properties ensuring that the result satisfies Newton’s second law. This idea is presented using a simple particle model to facilitate discussion of the rigid body model; however, the particle model does provide insights into particle dynamics at the nanoscale. The resulting three-dimensional model predicts a significant decrease in the effect of the random forces associated with Brownian motion. This conclusion runs contrary to the widely accepted notion that the motor protein’s movements are primarily the result of thermal effects. This work focuses on the mechanical aspects of protein locomotion; the effect ATP hydrolysis is estimated as internal forces acting on the mechanical model. In addition, the proposed model can be numerically integrated in a reasonable amount of time. Herein, the differences between the motion predicted by the old and new modeling approaches are compared using a simplified model of myosin V.
Multiscale wavelet representations for mammographic feature analysis
Laine, Andrew F.; Song, Shuwu
1992-12-01
This paper introduces a novel approach for accomplishing mammographic feature analysis through multiresolution representations. We show that efficient (nonredundant) representations may be identified from digital mammography and used to enhance specific mammographic features within a continuum of scale space. The multiresolution decomposition of wavelet transforms provides a natural hierarchy in which to embed an interactive paradigm for accomplishing scale space feature analysis. Choosing wavelets (or analyzing functions) that are simultaneously localized in both space and frequency, results in a powerful methodology for image analysis. Multiresolution and orientation selectivity, known biological mechanisms in primate vision, are ingrained in wavelet representations and inspire the techniques presented in this paper. Our approach includes local analysis of complete multiscale representations. Mammograms are reconstructed from wavelet coefficients, enhanced by linear, exponential and constant weight functions localized in scale space. By improving the visualization of breast pathology we can improve the changes of early detection of breast cancers (improve quality) while requiring less time to evaluate mammograms for most patients (lower costs).
Multiscale modeling of polyisoprene on graphite
International Nuclear Information System (INIS)
Pandey, Yogendra Narayan; Brayton, Alexander; Doxastakis, Manolis; Burkhart, Craig; Papakonstantopoulos, George J.
2014-01-01
The local dynamics and the conformational properties of polyisoprene next to a smooth graphite surface constructed by graphene layers are studied by a multiscale methodology. First, fully atomistic molecular dynamics simulations of oligomers next to the surface are performed. Subsequently, Monte Carlo simulations of a systematically derived coarse-grained model generate numerous uncorrelated structures for polymer systems. A new reverse backmapping strategy is presented that reintroduces atomistic detail. Finally, multiple extensive fully atomistic simulations with large systems of long macromolecules are employed to examine local dynamics in proximity to graphite. Polyisoprene repeat units arrange close to a parallel configuration with chains exhibiting a distribution of contact lengths. Efficient Monte Carlo algorithms with the coarse-grain model are capable of sampling these distributions for any molecular weight in quantitative agreement with predictions from atomistic models. Furthermore, molecular dynamics simulations with well-equilibrated systems at all length-scales support an increased dynamic heterogeneity that is emerging from both intermolecular interactions with the flat surface and intramolecular cooperativity. This study provides a detailed comprehensive picture of polyisoprene on a flat surface and consists of an effort to characterize such systems in atomistic detail
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.
Fast Plasma Investigation for Magnetospheric Multiscale
Pollock, C.; Moore, T.; Coffey, V.; Dorelli J.; Giles, B.; Adrian, M.; Chandler, M.; Duncan, C.; Figueroa-Vinas, A.; Garcia, K.;
2016-01-01
The Fast Plasma Investigation (FPI) was developed for flight on the Magnetospheric Multiscale (MMS) mission to measure the differential directional flux of magnetospheric electrons and ions with unprecedented time resolution to resolve kinetic-scale plasma dynamics. This increased resolution has been accomplished by placing four dual 180-degree top hat spectrometers for electrons and four dual 180-degree top hat spectrometers for ions around the periphery of each of four MMS spacecraft. Using electrostatic field-of-view deflection, the eight spectrometers for each species together provide 4pi-sr-field-of-view with, at worst, 11.25-degree sample spacing. Energy/charge sampling is provided by swept electrostatic energy/charge selection over the range from 10 eVq to 30000 eVq. The eight dual spectrometers on each spacecraft are controlled and interrogated by a single block redundant Instrument Data Processing Unit, which in turn interfaces to the observatory's Instrument Suite Central Instrument Data processor. This paper described the design of FPI, its ground and in-flight calibration, its operational concept, and its data products.
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].
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.
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...
Generalized multiscale finite element method. Symmetric interior penalty coupling
Efendiev, Yalchin R.; Galvis, Juan; Lazarov, Raytcho D.; Moon, M.; Sarkis, Marcus V.
2013-01-01
Motivated by applications to numerical simulations of flows in highly heterogeneous porous media, we develop multiscale finite element methods for second order elliptic equations. We discuss a multiscale model reduction technique in the framework of the discontinuous Galerkin finite element method. We propose two different finite element spaces on the coarse mesh. The first space is based on a local eigenvalue problem that uses an interior weighted L2-norm and a boundary weighted L2-norm for computing the "mass" matrix. The second choice is based on generation of a snapshot space and subsequent selection of a subspace of a reduced dimension. The approximation with these multiscale spaces is based on the discontinuous Galerkin finite element method framework. We investigate the stability and derive error estimates for the methods and further experimentally study their performance on a representative number of numerical examples. © 2013 Elsevier Inc.
Generalized multiscale finite element method. Symmetric interior penalty coupling
Efendiev, Yalchin R.
2013-12-01
Motivated by applications to numerical simulations of flows in highly heterogeneous porous media, we develop multiscale finite element methods for second order elliptic equations. We discuss a multiscale model reduction technique in the framework of the discontinuous Galerkin finite element method. We propose two different finite element spaces on the coarse mesh. The first space is based on a local eigenvalue problem that uses an interior weighted L2-norm and a boundary weighted L2-norm for computing the "mass" matrix. The second choice is based on generation of a snapshot space and subsequent selection of a subspace of a reduced dimension. The approximation with these multiscale spaces is based on the discontinuous Galerkin finite element method framework. We investigate the stability and derive error estimates for the methods and further experimentally study their performance on a representative number of numerical examples. © 2013 Elsevier Inc.
Integrated multiscale biomaterials experiment and modelling: a perspective
Buehler, Markus J.; Genin, Guy M.
2016-01-01
Advances in multiscale models and computational power have enabled a broad toolset to predict how molecules, cells, tissues and organs behave and develop. A key theme in biological systems is the emergence of macroscale behaviour from collective behaviours across a range of length and timescales, and a key element of these models is therefore hierarchical simulation. However, this predictive capacity has far outstripped our ability to validate predictions experimentally, particularly when multiple hierarchical levels are involved. The state of the art represents careful integration of multiscale experiment and modelling, and yields not only validation, but also insights into deformation and relaxation mechanisms across scales. We present here a sampling of key results that highlight both challenges and opportunities for integrated multiscale experiment and modelling in biological systems. PMID:28981126
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.
Study on high density multi-scale calculation technique
International Nuclear Information System (INIS)
Sekiguchi, S.; Tanaka, Y.; Nakada, H.; Nishikawa, T.; Yamamoto, N.; Yokokawa, M.
2004-01-01
To understand degradation of nuclear materials under irradiation, it is essential to know as much about each phenomenon observed from multi-scale points of view; they are micro-scale in atomic-level, macro-level in structural scale and intermediate level. In this study for application to meso-scale materials (100A ∼ 2μm), computer technology approaching from micro- and macro-scales was developed including modeling and computer application using computational science and technology method. And environmental condition of grid technology for multi-scale calculation was prepared. The software and MD (molecular dynamics) stencil for verifying the multi-scale calculation were improved and their movement was confirmed. (A. Hishinuma)
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.
Generalized multiscale finite element methods (GMsFEM)
Efendiev, Yalchin R.; Galvis, Juan; Hou, Thomasyizhao
2013-01-01
In this paper, we propose a general approach called Generalized Multiscale Finite Element Method (GMsFEM) for performing multiscale simulations for problems without scale separation over a complex input space. As in multiscale finite element methods (MsFEMs), the main idea of the proposed approach is to construct a small dimensional local solution space that can be used to generate an efficient and accurate approximation to the multiscale solution with a potentially high dimensional input parameter space. In the proposed approach, we present a general procedure to construct the offline space that is used for a systematic enrichment of the coarse solution space in the online stage. The enrichment in the online stage is performed based on a spectral decomposition of the offline space. In the online stage, for any input parameter, a multiscale space is constructed to solve the global problem on a coarse grid. The online space is constructed via a spectral decomposition of the offline space and by choosing the eigenvectors corresponding to the largest eigenvalues. The computational saving is due to the fact that the construction of the online multiscale space for any input parameter is fast and this space can be re-used for solving the forward problem with any forcing and boundary condition. Compared with the other approaches where global snapshots are used, the local approach that we present in this paper allows us to eliminate unnecessary degrees of freedom on a coarse-grid level. We present various examples in the paper and some numerical results to demonstrate the effectiveness of our method. © 2013 Elsevier Inc.
Generalized multiscale finite element methods (GMsFEM)
Efendiev, Yalchin R.
2013-10-01
In this paper, we propose a general approach called Generalized Multiscale Finite Element Method (GMsFEM) for performing multiscale simulations for problems without scale separation over a complex input space. As in multiscale finite element methods (MsFEMs), the main idea of the proposed approach is to construct a small dimensional local solution space that can be used to generate an efficient and accurate approximation to the multiscale solution with a potentially high dimensional input parameter space. In the proposed approach, we present a general procedure to construct the offline space that is used for a systematic enrichment of the coarse solution space in the online stage. The enrichment in the online stage is performed based on a spectral decomposition of the offline space. In the online stage, for any input parameter, a multiscale space is constructed to solve the global problem on a coarse grid. The online space is constructed via a spectral decomposition of the offline space and by choosing the eigenvectors corresponding to the largest eigenvalues. The computational saving is due to the fact that the construction of the online multiscale space for any input parameter is fast and this space can be re-used for solving the forward problem with any forcing and boundary condition. Compared with the other approaches where global snapshots are used, the local approach that we present in this paper allows us to eliminate unnecessary degrees of freedom on a coarse-grid level. We present various examples in the paper and some numerical results to demonstrate the effectiveness of our method. © 2013 Elsevier Inc.
Multiscale Finite Element Methods for Flows on Rough Surfaces
Efendiev, Yalchin
2013-01-01
In this paper, we present the Multiscale Finite Element Method (MsFEM) for problems on rough heterogeneous surfaces. We consider the diffusion equation on oscillatory surfaces. Our objective is to represent small-scale features of the solution via multiscale basis functions described on a coarse grid. This problem arises in many applications where processes occur on surfaces or thin layers. We present a unified multiscale finite element framework that entails the use of transformations that map the reference surface to the deformed surface. The main ingredients of MsFEM are (1) the construction of multiscale basis functions and (2) a global coupling of these basis functions. For the construction of multiscale basis functions, our approach uses the transformation of the reference surface to a deformed surface. On the deformed surface, multiscale basis functions are defined where reduced (1D) problems are solved along the edges of coarse-grid blocks to calculate nodalmultiscale basis functions. Furthermore, these basis functions are transformed back to the reference configuration. We discuss the use of appropriate transformation operators that improve the accuracy of the method. The method has an optimal convergence if the transformed surface is smooth and the image of the coarse partition in the reference configuration forms a quasiuniform partition. In this paper, we consider such transformations based on harmonic coordinates (following H. Owhadi and L. Zhang [Comm. Pure and Applied Math., LX(2007), pp. 675-723]) and discuss gridding issues in the reference configuration. Numerical results are presented where we compare the MsFEM when two types of deformations are used formultiscale basis construction. The first deformation employs local information and the second deformation employs a global information. Our numerical results showthat one can improve the accuracy of the simulations when a global information is used. © 2013 Global-Science Press.
Multiscale registration of remote sensing image using robust SIFT features in Steerable-Domain
Directory of Open Access Journals (Sweden)
Xiangzeng Liu
2011-12-01
Full Text Available This paper proposes a multiscale registration technique using robust Scale Invariant Feature Transform (SIFT features in Steerable-Domain, which can deal with the large variations of scale, rotation and illumination between images. First, a new robust SIFT descriptor is presented, which is invariant under affine transformation. Then, an adaptive similarity measure is developed according to the robust SIFT descriptor and the adaptive normalized cross correlation of feature point’s neighborhood. Finally, the corresponding feature points can be determined by the adaptive similarity measure in Steerable-Domain of the two input images, and the final refined transformation parameters determined by using gradual optimization are adopted to achieve the registration results. Quantitative comparisons of our algorithm with the related methods show a significant improvement in the presence of large scale, rotation changes, and illumination contrast. The effectiveness of the proposed method is demonstrated by the experimental results.
Multiscale approach to the physics of radiation damage with ions
Energy Technology Data Exchange (ETDEWEB)
Surdutovich, Eugene [Physics Department, Oakland University, 2200 N. Squirrel Rd., Rochester MI 48309 (United States); Solov' yov, Andrey V. [Frankfurt Institute for Advanced Studies, Goethe University, Ruth-Moufang-Str. 1, Frankfurt am Main 60438 (Germany)
2013-04-19
We review a multiscale approach to the physics of ion-beam cancer therapy, an approach suggested in order to understand the interplay of a large number of phenomena involved in radiation damage scenario occurring on a range of temporal, spatial, and energy scales. We briefly overview its history and present the current stage of its development. The differences of the multiscale approach from other methods of understanding and assessment of radiation damage are discussed as well as its relationship to other branches of physics, chemistry and biology.
Multiscale integration schemes for jump-diffusion systems
Energy Technology Data Exchange (ETDEWEB)
Givon, D.; Kevrekidis, I.G.
2008-12-09
We study a two-time-scale system of jump-diffusion stochastic differential equations. We analyze a class of multiscale integration methods for these systems, which, in the spirit of [1], consist of a hybridization between a standard solver for the slow components and short runs for the fast dynamics, which are used to estimate the effect that the fast components have on the slow ones. We obtain explicit bounds for the discrepancy between the results of the multiscale integration method and the slow components of the original system.
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'. © 2016 The Author(s).
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.
Multiscale entropy based study of the pathological time series
International Nuclear Information System (INIS)
Wang Jun; Ma Qianli
2008-01-01
This paper studies the multiscale entropy (MSE) of electrocardiogram's ST segment and compares the MSE results of ST segment with that of electrocardiogram in the first time. Electrocardiogram complexity changing characteristics has important clinical significance for early diagnosis. Study shows that the average MSE values and the varying scope fluctuation could be more effective to reveal the heart health status. Particularly the multiscale values varying scope fluctuation is a more sensitive parameter for early heart disease detection and has a clinical diagnostic significance. (general)
Multiscale Shannon entropy and its application in the stock market
Gu, Rongbao
2017-10-01
In this paper, we perform a multiscale entropy analysis on the Dow Jones Industrial Average Index using the Shannon entropy. The stock index shows the characteristic of multi-scale entropy that caused by noise in the market. The entropy is demonstrated to have significant predictive ability for the stock index in both long-term and short-term, and empirical results verify that noise does exist in the market and can affect stock price. It has important implications on market participants such as noise traders.
Multiscale modeling of complex materials phenomenological, theoretical and computational aspects
Trovalusci, Patrizia
2014-01-01
The papers in this volume deal with materials science, theoretical mechanics and experimental and computational techniques at multiple scales, providing a sound base and a framework for many applications which are hitherto treated in a phenomenological sense. The basic principles are formulated of multiscale modeling strategies towards modern complex multiphase materials subjected to various types of mechanical, thermal loadings and environmental effects. The focus is on problems where mechanics is highly coupled with other concurrent physical phenomena. Attention is also focused on the historical origins of multiscale modeling and foundations of continuum mechanics currently adopted to model non-classical continua with substructure, for which internal length scales play a crucial role.
Multi-scale magnetic field intermittence in the plasma sheet
Directory of Open Access Journals (Sweden)
Z. Vörös
2003-09-01
Full Text Available This paper demonstrates that intermittent magnetic field fluctuations in the plasma sheet exhibit transitory, localized, and multi-scale features. We propose a multifractal-based algorithm, which quantifies intermittence on the basis of the statistical distribution of the "strength of burstiness", estimated within a sliding window. Interesting multi-scale phenomena observed by the Cluster spacecraft include large-scale motion of the current sheet and bursty bulk flow associated turbulence, interpreted as a cross-scale coupling (CSC process.Key words. Magnetospheric physics (magnetotail; plasma sheet – Space plasma physics (turbulence
Modeling Temporal Evolution and Multiscale Structure in Networks
DEFF Research Database (Denmark)
Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard
2013-01-01
Many real-world networks exhibit both temporal evolution and multiscale structure. We propose a model for temporally correlated multifurcating hierarchies in complex networks which jointly capture both effects. We use the Gibbs fragmentation tree as prior over multifurcating trees and a change......-point model to account for the temporal evolution of each vertex. We demonstrate that our model is able to infer time-varying multiscale structure in synthetic as well as three real world time-evolving complex networks. Our modeling of the temporal evolution of hierarchies brings new insights...
Multiscale modeling of emergent materials: biological and soft matter
DEFF Research Database (Denmark)
Murtola, Teemu; Bunker, Alex; Vattulainen, Ilpo
2009-01-01
In this review, we focus on four current related issues in multiscale modeling of soft and biological matter. First, we discuss how to use structural information from detailed models (or experiments) to construct coarse-grained ones in a hierarchical and systematic way. This is discussed in the c......In this review, we focus on four current related issues in multiscale modeling of soft and biological matter. First, we discuss how to use structural information from detailed models (or experiments) to construct coarse-grained ones in a hierarchical and systematic way. This is discussed...
Multiscale simulation of water flow past a C540 fullerene
DEFF Research Database (Denmark)
Walther, Jens Honore; Praprotnik, Matej; Kotsalis, Evangelos M.
2012-01-01
We present a novel, three-dimensional, multiscale algorithm for simulations of water flow past a fullerene. We employ the Schwarz alternating overlapping domain method to couple molecular dynamics (MD) of liquid water around the C540 buckyball with a Lattice–Boltzmann (LB) description for the Nav......We present a novel, three-dimensional, multiscale algorithm for simulations of water flow past a fullerene. We employ the Schwarz alternating overlapping domain method to couple molecular dynamics (MD) of liquid water around the C540 buckyball with a Lattice–Boltzmann (LB) description...
Rough Set Approach to Incomplete Multiscale Information System
Yang, Xibei; Qi, Yong; Yu, Dongjun; Yu, Hualong; Song, Xiaoning; Yang, Jingyu
2014-01-01
Multiscale information system is a new knowledge representation system for expressing the knowledge with different levels of granulations. In this paper, by considering the unknown values, which can be seen everywhere in real world applications, the incomplete multiscale information system is firstly investigated. The descriptor technique is employed to construct rough sets at different scales for analyzing the hierarchically structured data. The problem of unravelling decision rules at different scales is also addressed. Finally, the reduct descriptors are formulated to simplify decision rules, which can be derived from different scales. Some numerical examples are employed to substantiate the conceptual arguments. PMID:25276852
Integrated multiscale modeling of molecular computing devices
International Nuclear Information System (INIS)
Cummings, Peter T; Leng Yongsheng
2005-01-01
Molecular electronics, in which single organic molecules are designed to perform the functions of transistors, diodes, switches and other circuit elements used in current siliconbased microelecronics, is drawing wide interest as a potential replacement technology for conventional silicon-based lithographically etched microelectronic devices. In addition to their nanoscopic scale, the additional advantage of molecular electronics devices compared to silicon-based lithographically etched devices is the promise of being able to produce them cheaply on an industrial scale using wet chemistry methods (i.e., self-assembly from solution). The design of molecular electronics devices, and the processes to make them on an industrial scale, will require a thorough theoretical understanding of the molecular and higher level processes involved. Hence, the development of modeling techniques for molecular electronics devices is a high priority from both a basic science point of view (to understand the experimental studies in this field) and from an applied nanotechnology (manufacturing) point of view. Modeling molecular electronics devices requires computational methods at all length scales - electronic structure methods for calculating electron transport through organic molecules bonded to inorganic surfaces, molecular simulation methods for determining the structure of self-assembled films of organic molecules on inorganic surfaces, mesoscale methods to understand and predict the formation of mesoscale patterns on surfaces (including interconnect architecture), and macroscopic scale methods (including finite element methods) for simulating the behavior of molecular electronic circuit elements in a larger integrated device. Here we describe a large Department of Energy project involving six universities and one national laboratory aimed at developing integrated multiscale methods for modeling molecular electronics devices. The project is funded equally by the Office of Basic
A multiscale approach to mapping seabed sediments.
Directory of Open Access Journals (Sweden)
Benjamin Misiuk
Full Text Available Benthic habitat maps, including maps of seabed sediments, have become critical spatial-decision support tools for marine ecological management and conservation. Despite the increasing recognition that environmental variables should be considered at multiple spatial scales, variables used in habitat mapping are often implemented at a single scale. The objective of this study was to evaluate the potential for using environmental variables at multiple scales for modelling and mapping seabed sediments. Sixteen environmental variables were derived from multibeam echosounder data collected near Qikiqtarjuaq, Nunavut, Canada at eight spatial scales ranging from 5 to 275 m, and were tested as predictor variables for modelling seabed sediment distributions. Using grain size data obtained from grab samples, we tested which scales of each predictor variable contributed most to sediment models. Results showed that the default scale was often not the best. Out of 129 potential scale-dependent variables, 11 were selected to model the additive log-ratio of mud and sand at five different scales, and 15 were selected to model the additive log-ratio of gravel and sand, also at five different scales. Boosted Regression Tree models that explained between 46.4 and 56.3% of statistical deviance produced multiscale predictions of mud, sand, and gravel that were correlated with cross-validated test data (Spearman's ρmud = 0.77, ρsand = 0.71, ρgravel = 0.58. Predictions of individual size fractions were classified to produce a map of seabed sediments that is useful for marine spatial planning. Based on the scale-dependence of variables in this study, we concluded that spatial scale consideration is at least as important as variable selection in seabed mapping.
First results from the Magnetospheric Multiscale mission
Lavraud, B.
2017-12-01
Since its launch in March 2015, NASA's Magnetospheric Multiscale mission (MMS) provides a wealth of unprecedented high resolution measurements of space plasma properties and dynamics in the near-Earth environment. MMS was designed in the first place to study the fundamental process of collision-less magnetic reconnection. The two first results reviewed here pertain to this topic and highlight how the extremely high resolution MMS data (electrons, in particular, with full three dimensional measurements at 30 ms in burst mode) have permitted to tackle electron dynamics in unprecedented details. The first result demonstrates how electrons become demagnetized and scattered near the magnetic reconnection X line as a result of increased magnetic field curvature, together with a decrease in its magnitude. The second result demonstrates that electrons form crescent-shaped, agyrotropic distribution functions very near the X line, suggestive of the existence of a perpendicular current aligned with the local electric field and consistent with the energy conversion expected in magnetic reconnection (such that J\\cdot E > 0). Aside from magnetic reconnection, we show how MMS contributes to topics such as wave properties and their interaction with particles. Thanks again to extremely high resolution measurements, the lossless and periodical energy exchange between wave electromagnetic fields and particles, as expected in the case of kinetic Alfvén waves, was confirmed. Although not discussed, MMS has the potential to solve many other outstanding issues in collision-less plasma physics, for example regarding shock or turbulence acceleration, with obvious broader impacts in astrophysics in general.
Multiscale Drivers of Global Environmental Health
Desai, Manish Anil
In this dissertation, I motivate, develop, and demonstrate three such approaches for investigating multiscale drivers of global environmental health: (1) a metric for analyzing contributions and responses to climate change from global to sectoral scales, (2) a framework for unraveling the influence of environmental change on infectious diseases at regional to local scales, and (3) a model for informing the design and evaluation of clean cooking interventions at community to household scales. The full utility of climate debt as an analytical perspective will remain untapped without tools that can be manipulated by a wide range of analysts, including global environmental health researchers. Chapter 2 explains how international natural debt (IND) apportions global radiative forcing from fossil fuel carbon dioxide and methane, the two most significant climate altering pollutants, to individual entities -- primarily countries but also subnational states and economic sectors, with even finer scales possible -- as a function of unique trajectories of historical emissions, taking into account the quite different radiative efficiencies and atmospheric lifetimes of each pollutant. Owing to its straightforward and transparent derivation, IND can readily operationalize climate debt to consider issues of equity and efficiency and drive scenario exercises that explore the response to climate change at multiple scales. Collectively, the analyses presented in this chapter demonstrate how IND can inform a range of key question on climate change mitigation at multiple scales, compelling environmental health towards an appraisal of the causes and not just the consequences of climate change. The environmental change and infectious disease (EnvID) conceptual framework of Chapter 3 builds on a rich history of prior efforts in epidemiologic theory, environmental science, and mathematical modeling by: (1) articulating a flexible and logical system specification; (2) incorporating
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
Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun
2014-01-01
Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding
Multiscale Multiphysics and Multidomain Models I: Basic Theory.
Wei, Guo-Wei
2013-12-01
This work extends our earlier two-domain formulation of a differential geometry based multiscale paradigm into a multidomain theory, which endows us the ability to simultaneously accommodate multiphysical descriptions of aqueous chemical, physical and biological systems, such as fuel cells, solar cells, nanofluidics, ion channels, viruses, RNA polymerases, molecular motors and large macromolecular complexes. The essential idea is to make use of the differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain of solvent from the microscopic domain of solute, and dynamically couple continuum and discrete descriptions. Our main strategy is to construct energy functionals to put on an equal footing of multiphysics, including polar (i.e., electrostatic) solvation, nonpolar solvation, chemical potential, quantum mechanics, fluid mechanics, molecular mechanics, coarse grained dynamics and elastic dynamics. The variational principle is applied to the energy functionals to derive desirable governing equations, such as multidomain Laplace-Beltrami (LB) equations for macromolecular morphologies, multidomain Poisson-Boltzmann (PB) equation or Poisson equation for electrostatic potential, generalized Nernst-Planck (NP) equations for the dynamics of charged solvent species, generalized Navier-Stokes (NS) equation for fluid dynamics, generalized Newton's equations for molecular dynamics (MD) or coarse-grained dynamics and equation of motion for elastic dynamics. Unlike the classical PB equation, our PB equation is an integral-differential equation due to solvent-solute interactions. To illustrate the proposed formalism, we have explicitly constructed three models, a multidomain solvation model, a multidomain charge transport model and a multidomain chemo-electro-fluid-MD-elastic model. Each solute domain is equipped with distinct surface tension, pressure, dielectric function, and charge density distribution. In addition to long
Multiscale multiphysics and multidomain models—Flexibility and rigidity
International Nuclear Information System (INIS)
Xia, Kelin; Opron, Kristopher; Wei, Guo-Wei
2013-01-01
The emerging complexity of large macromolecules has led to challenges in their full scale theoretical description and computer simulation. Multiscale multiphysics and multidomain models have been introduced to reduce the number of degrees of freedom while maintaining modeling accuracy and achieving computational efficiency. A total energy functional is constructed to put energies for polar and nonpolar solvation, chemical potential, fluid flow, molecular mechanics, and elastic dynamics on an equal footing. The variational principle is utilized to derive coupled governing equations for the above mentioned multiphysical descriptions. Among these governing equations is the Poisson-Boltzmann equation which describes continuum electrostatics with atomic charges. The present work introduces the theory of continuum elasticity with atomic rigidity (CEWAR). The essence of CEWAR is to formulate the shear modulus as a continuous function of atomic rigidity. As a result, the dynamics complexity of a macromolecular system is separated from its static complexity so that the more time-consuming dynamics is handled with continuum elasticity theory, while the less time-consuming static analysis is pursued with atomic approaches. We propose a simple method, flexibility-rigidity index (FRI), to analyze macromolecular flexibility and rigidity in atomic detail. The construction of FRI relies on the fundamental assumption that protein functions, such as flexibility, rigidity, and energy, are entirely determined by the structure of the protein and its environment, although the structure is in turn determined by all the interactions. As such, the FRI measures the topological connectivity of protein atoms or residues and characterizes the geometric compactness of the protein structure. As a consequence, the FRI does not resort to the interaction Hamiltonian and bypasses matrix diagonalization, which underpins most other flexibility analysis methods. FRI's computational complexity is of O
Image quality assessment based on multiscale geometric analysis.
Gao, Xinbo; Lu, Wen; Tao, Dacheng; Li, Xuelong
2009-07-01
Reduced-reference (RR) image quality assessment (IQA) has been recognized as an effective and efficient way to predict the visual quality of distorted images. The current standard is the wavelet-domain natural image statistics model (WNISM), which applies the Kullback-Leibler divergence between the marginal distributions of wavelet coefficients of the reference and distorted images to measure the image distortion. However, WNISM fails to consider the statistical correlations of wavelet coefficients in different subbands and the visual response characteristics of the mammalian cortical simple cells. In addition, wavelet transforms are optimal greedy approximations to extract singularity structures, so they fail to explicitly extract the image geometric information, e.g., lines and curves. Finally, wavelet coefficients are dense for smooth image edge contours. In this paper, to target the aforementioned problems in IQA, we develop a novel framework for IQA to mimic the human visual system (HVS) by incorporating the merits from multiscale geometric analysis (MGA), contrast sensitivity function (CSF), and the Weber's law of just noticeable difference (JND). In the proposed framework, MGA is utilized to decompose images and then extract features to mimic the multichannel structure of HVS. Additionally, MGA offers a series of transforms including wavelet, curvelet, bandelet, contourlet, wavelet-based contourlet transform (WBCT), and hybrid wavelets and directional filter banks (HWD), and different transforms capture different types of image geometric information. CSF is applied to weight coefficients obtained by MGA to simulate the appearance of images to observers by taking into account many of the nonlinearities inherent in HVS. JND is finally introduced to produce a noticeable variation in sensory experience. Thorough empirical studies are carried out upon the LIVE database against subjective mean opinion score (MOS) and demonstrate that 1) the proposed framework has
Multiscale Hy3S: Hybrid stochastic simulation for supercomputers
Directory of Open Access Journals (Sweden)
Kaznessis Yiannis N
2006-02-01
Full Text Available Abstract Background Stochastic simulation has become a useful tool to both study natural biological systems and design new synthetic ones. By capturing the intrinsic molecular fluctuations of "small" systems, these simulations produce a more accurate picture of single cell dynamics, including interesting phenomena missed by deterministic methods, such as noise-induced oscillations and transitions between stable states. However, the computational cost of the original stochastic simulation algorithm can be high, motivating the use of hybrid stochastic methods. Hybrid stochastic methods partition the system into multiple subsets and describe each subset as a different representation, such as a jump Markov, Poisson, continuous Markov, or deterministic process. By applying valid approximations and self-consistently merging disparate descriptions, a method can be considerably faster, while retaining accuracy. In this paper, we describe Hy3S, a collection of multiscale simulation programs. Results Building on our previous work on developing novel hybrid stochastic algorithms, we have created the Hy3S software package to enable scientists and engineers to both study and design extremely large well-mixed biological systems with many thousands of reactions and chemical species. We have added adaptive stochastic numerical integrators to permit the robust simulation of dynamically stiff biological systems. In addition, Hy3S has many useful features, including embarrassingly parallelized simulations with MPI; special discrete events, such as transcriptional and translation elongation and cell division; mid-simulation perturbations in both the number of molecules of species and reaction kinetic parameters; combinatorial variation of both initial conditions and kinetic parameters to enable sensitivity analysis; use of NetCDF optimized binary format to quickly read and write large datasets; and a simple graphical user interface, written in Matlab, to help users
Riparian ecosystems and buffers - multiscale structure, function, and management: introduction
Kathleen A. Dwire; Richard R. Lowrance
2006-01-01
Given the importance of issues related to improved understanding and management of riparian ecosystems and buffers, the American Water Resources Association (AWRA) sponsored a Summer Specialty Conference in June 2004 at Olympic Valley, California, entitled 'Riparian Ecosystems and Buffers: Multiscale Structure, Function, and Management.' The primary objective...
A Multiscale Enrichment Procedure for Nonlinear Monotone Operators
Efendiev, Yalchin R.; Galvis, J.; Presho, M.; Zhou, J.
2014-01-01
. Galvis, R. Lazarov, S. Margenov and J. Ren, Robust two-level domain decomposition preconditioners for high-contrast anisotropic flows in multiscale media. Submitted.; Y. Efendiev, J. Galvis and X. Wu, J. Comput. Phys. 230 (2011) 937–955; J. Galvis and Y
Multiscale Modeling of Wear Degradation in Cylinder Liners
Moraes, Alvaro; Ruggeri, Fabrizio; Tempone, Raul; Vilanova, Pedro
2014-01-01
both to predict and to avoid them. To achieve this, a monitoring system of the wear level should be implemented to decrease the risk of failure. In this work, we take a first step into the development of a multiscale indirect inference methodology
Multiscale approach to the physics of radiation damage with ions
International Nuclear Information System (INIS)
Surdutovich, E.; Solov'yov, A.
2014-01-01
The multiscale approach to the assessment of bio-damage resulting upon irradiation of biological media with ions is reviewed, explained and compared to other approaches. The processes of ion propagation in the medium concurrent with ionization and excitation of molecules, transport of secondary products, dynamics of the medium, and biological damage take place on a number of different temporal, spatial and energy scales. The multiscale approach, a physical phenomenon-based analysis of the scenario that leads to radiation damage, has been designed to consider all relevant effects on a variety of scales and develop an approach to the quantitative assessment of biological damage as a result of irradiation with ions. Presently, physical and chemical effects are included in the scenario while the biological effects such as DNA repair are only mentioned. This paper explains the scenario of radiation damage with ions, overviews its major parts, and applies the multiscale approach to different experimental conditions. On the basis of this experience, the recipe for application of the multiscale approach is formulated. The recipe leads to the calculation of relative biological effectiveness. (authors)
Multiscale modeling and simulation of brain blood flow
Energy Technology Data Exchange (ETDEWEB)
Perdikaris, Paris, E-mail: parisp@mit.edu [Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Grinberg, Leopold, E-mail: leopoldgrinberg@us.ibm.com [IBM T.J Watson Research Center, 1 Rogers St, Cambridge, Massachusetts 02142 (United States); Karniadakis, George Em, E-mail: george-karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, Rhode Island 02912 (United States)
2016-02-15
The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process taking place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.
Multiscale Path Metrics for the Analysis of Discrete Geometric Structures
2017-11-30
Report: Multiscale Path Metrics for the Analysis of Discrete Geometric Structures The views, opinions and/or findings contained in this report are those...Analysis of Discrete Geometric Structures Report Term: 0-Other Email: tomasi@cs.duke.edu Distribution Statement: 1-Approved for public release
Multiscale analysis of structure development in expanded starch snacks
van der Sman, R. G. M.; Broeze, J.
2014-11-01
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 moisture content, where the glass transition and the boiling line intersect. In our analysis we make use of several tools, (1) time scale analysis from the field of physical transport phenomena, (2) the scale separation map (SSM) developed within a multiscale simulation framework of complex automata, (3) the supplemented state diagram (SSD), depicting phase transition and glass transition lines, and (4) a multiscale simulation model for the bubble expansion. Results of the time scale analysis are plotted in the SSD, and give insight into the dominant physical processes involved in expansion. Furthermore, the results of the time scale analysis are used to construct the SSM, which has aided us in the construction of the multiscale simulation model. Simulation results are plotted in the SSD. This clearly shows that the hypothesis of Kokini is qualitatively true, but has to be refined. Our results show that bubble expansion is optimal for moisture content, where the boiling line for gas pressure of 4 bars intersects the isoviscosity line of the critical viscosity 106 Pa.s, which runs parallel to the glass transition line.
On a multiscale approach for filter efficiency simulations
Iliev, Oleg
2014-07-01
Filtration in general, and the dead end depth filtration of solid particles out of fluid in particular, is intrinsic multiscale problem. The deposition (capturing of particles) essentially depends on local velocity, on microgeometry (pore scale geometry) of the filtering medium and on the diameter distribution of the particles. The deposited (captured) particles change the microstructure of the porous media what leads to change of permeability. The changed permeability directly influences the velocity field and pressure distribution inside the filter element. To close the loop, we mention that the velocity influences the transport and deposition of particles. In certain cases one can evaluate the filtration efficiency considering only microscale or only macroscale models, but in general an accurate prediction of the filtration efficiency requires multiscale models and algorithms. This paper discusses the single scale and the multiscale models, and presents a fractional time step discretization algorithm for the multiscale problem. The velocity within the filter element is computed at macroscale, and is used as input for the solution of microscale problems at selected locations of the porous medium. The microscale problem is solved with respect to transport and capturing of individual particles, and its solution is postprocessed to provide permeability values for macroscale computations. Results from computational experiments with an oil filter are presented and discussed.
Multi-scale and multi-orientation medical image analysis
Haar Romenij, ter B.M.; Deserno, T.M.
2011-01-01
Inspired by multi-scale and multi-orientation mechanisms recognized in the first stages of our visual system, this chapter gives a tutorial overview of the basic principles. Images are discrete, measured data. The optimal aperture for an observation with as little artefacts as possible, is derived
Multiscale Modeling of Fracture Processes in Cementitious Materials
Qian, Z.
2012-01-01
Concrete is a composite construction material, which is composed primarily of coarse aggregates, sands and cement paste. The fracture processes in concrete are complicated, because of the multiscale and multiphase nature of the material. In the past decades, comprehensive effort has been put to
Multiscale time-dependent density functional theory: Demonstration for plasmons.
Jiang, Jiajian; Abi Mansour, Andrew; Ortoleva, Peter J
2017-08-07
Plasmon properties are of significant interest in pure and applied nanoscience. While time-dependent density functional theory (TDDFT) can be used to study plasmons, it becomes impractical for elucidating the effect of size, geometric arrangement, and dimensionality in complex nanosystems. In this study, a new multiscale formalism that addresses this challenge is proposed. This formalism is based on Trotter factorization and the explicit introduction of a coarse-grained (CG) structure function constructed as the Weierstrass transform of the electron wavefunction. This CG structure function is shown to vary on a time scale much longer than that of the latter. A multiscale propagator that coevolves both the CG structure function and the electron wavefunction is shown to bring substantial efficiency over classical propagators used in TDDFT. This efficiency follows from the enhanced numerical stability of the multiscale method and the consequence of larger time steps that can be used in a discrete time evolution. The multiscale algorithm is demonstrated for plasmons in a group of interacting sodium nanoparticles (15-240 atoms), and it achieves improved efficiency over TDDFT without significant loss of accuracy or space-time resolution.
Covariance, correlation matrix, and the multiscale community structure of networks.
Shen, Hua-Wei; Cheng, Xue-Qi; Fang, Bin-Xing
2010-07-01
Empirical studies show that real world networks often exhibit multiple scales of topological descriptions. However, it is still an open problem how to identify the intrinsic multiple scales of networks. In this paper, we consider detecting the multiscale community structure of network from the perspective of dimension reduction. According to this perspective, a covariance matrix of network is defined to uncover the multiscale community structure through the translation and rotation transformations. It is proved that the covariance matrix is the unbiased version of the well-known modularity matrix. We then point out that the translation and rotation transformations fail to deal with the heterogeneous network, which is very common in nature and society. To address this problem, a correlation matrix is proposed through introducing the rescaling transformation into the covariance matrix. Extensive tests on real world and artificial networks demonstrate that the correlation matrix significantly outperforms the covariance matrix, identically the modularity matrix, as regards identifying the multiscale community structure of network. This work provides a novel perspective to the identification of community structure and thus various dimension reduction methods might be used for the identification of community structure. Through introducing the correlation matrix, we further conclude that the rescaling transformation is crucial to identify the multiscale community structure of network, as well as the translation and rotation transformations.
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.
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 basis
A Liver-centric Multiscale Modeling Framework for Xenobiotics
We describe a multi-scale framework for modeling acetaminophen-induced liver toxicity. Acetaminophen is a widely used analgesic. Overdose of acetaminophen can result in liver injury via its biotransformation into toxic product, which further induce massive necrosis. Our study foc...
Adaptive Multiscale Finite Element Method for Subsurface Flow Simulation
Van Esch, J.M.
2010-01-01
Natural geological formations generally show multiscale structural and functional heterogeneity evolving over many orders of magnitude in space and time. In subsurface hydrological simulations the geological model focuses on the structural hierarchy of physical sub units and the flow model addresses
Multiscale topology optimization of solid and fluid structures
DEFF Research Database (Denmark)
Andreasen, Casper Schousboe
This thesis considers the application of the topology optimization method to multiscale problems, specifically the fluid-structure interaction problem. By multiple-scale methods the governing equations, the Navier-Cauchy and the incompressible Navier-Stokes equations are expanded and separated...
A practical multiscale approach for optimization of structural damping
DEFF Research Database (Denmark)
Andreassen, Erik; Jensen, Jakob Søndergaard
2016-01-01
A simple and practical multiscale approach suitable for topology optimization of structural damping in a component ready for additive manufacturing is presented.The approach consists of two steps: First, the homogenized loss factor of a two-phase material is maximized. This is done in order...
Musical Instrument Identification using Multiscale Mel-frequency Cepstral Coefficients
DEFF Research Database (Denmark)
Sturm, Bob L.; Morvidone, Marcela; Daudet, Laurent
2010-01-01
We investigate the benefits of evaluating Mel-frequency cepstral coefficients (MFCCs) over several time scales in the context of automatic musical instrument identification for signals that are monophonic but derived from real musical settings. We define several sets of features derived from MFCC...... multiscale decompositions perform significantly better than features computed using a single time-resolution....
Fast 2D Simulation of Superconductors: a Multiscale Approach
DEFF Research Database (Denmark)
Rodriguez Zermeno, Victor Manuel; Sørensen, Mads Peter; Pedersen, Niels Falsig
2009-01-01
This work presents a method to calculate AC losses in thin conductors such as the commercially available second generation superconducting wires through a multiscale meshing technique. The main idea is to use large aspect ratio elements to accurately simulate thin material layers. For a single thin...
Control algorithm for multiscale flow simulations of water
DEFF Research Database (Denmark)
Kotsalis, E. M.; Walther, Jens Honore; Kaxiras, E.
2009-01-01
We present a multiscale algorithm to couple atomistic water models with continuum incompressible flow simulations via a Schwarz domain decomposition approach. The coupling introduces an inhomogeneity in the description of the atomistic domain and prevents the use of periodic boundary conditions...
Hypoglycemia-Related Electroencephalogram Changes Assessed by Multiscale Entropy
DEFF Research Database (Denmark)
Fabris, C.; Sparacino, G.; Sejling, A. S.
2014-01-01
derivation in the two glycemic intervals was assessed using the multiscale entropy (MSE) approach, obtaining measures of sample entropy (SampEn) at various temporal scales. The comparison of how signal irregularity measured by SampEn varies as the temporal scale increases in the two glycemic states provides...
Elimination of intermediate species in multiscale stochastic reaction networks
DEFF Research Database (Denmark)
Cappelletti, Daniele; Wiuf, Carsten
2016-01-01
such as the substrate-enzyme complex in the Michaelis-Menten mechanism. Such species are virtually in all real-world networks, they are typically short-lived, degraded at a fast rate and hard to observe experimentally. We provide conditions under which the Markov process of a multiscale reaction network...
Efficient topology optimisation of multiscale and multiphysics problems
DEFF Research Database (Denmark)
Alexandersen, Joe
The aim of this Thesis is to present efficient methods for optimising high-resolution problems of a multiscale and multiphysics nature. The Thesis consists of two parts: one treating topology optimisation of microstructural details and the other treating topology optimisation of conjugate heat...
Computer-Aided Multiscale Modelling for Chemical Process Engineering
DEFF Research Database (Denmark)
Morales Rodriguez, Ricardo; Gani, Rafiqul
2007-01-01
Chemical processes are generally modeled through monoscale approaches, which, while not adequate, satisfy a useful role in product-process design. In this case, use of a multi-dimensional and multi-scale model-based approach has importance in product-process development. A computer-aided framework...
Cyclic Matching Pursuits with Multiscale Time-frequency Dictionaries
DEFF Research Database (Denmark)
Sturm, Bob L.; Christensen, Mads Græsbøll
2010-01-01
We generalize cyclic matching pursuit (CMP), propose an orthogonal variant, and examine their performance using multiscale time-frequency dictionaries in the sparse approximation of signals. Overall, we find that the cyclic approach of CMP produces signal models that have a much lower approximation...
Multiscale perspectives of species richness in East Africa
Said, M.
2003-01-01
This dissertation describes and analyses animal species richness in East Africa from a multi-scale perspective. We studied diversity patterns at sub-continental, national and sub-national level. The study demonstrated that species diversity patterns were scale-dependent. Diversity patterns varied
Multiscale equation-free algorithms for molecular dynamics
Abi Mansour, Andrew
Molecular dynamics is a physics-based computational tool that has been widely employed to study the dynamics and structure of macromolecules and their assemblies at the atomic scale. However, the efficiency of molecular dynamics simulation is limited because of the broad spectrum of timescales involved. To overcome this limitation, an equation-free algorithm is presented for simulating these systems using a multiscale model cast in terms of atomistic and coarse-grained variables. Both variables are evolved in time in such a way that the cross-talk between short and long scales is preserved. In this way, the coarse-grained variables guide the evolution of the atom-resolved states, while the latter provide the Newtonian physics for the former. While the atomistic variables are evolved using short molecular dynamics runs, time advancement at the coarse-grained level is achieved with a scheme that uses information from past and future states of the system while accounting for both the stochastic and deterministic features of the coarse-grained dynamics. To complete the multiscale cycle, an atom-resolved state consistent with the updated coarse-grained variables is recovered using algorithms from mathematical optimization. This multiscale paradigm is extended to nanofluidics using concepts from hydrodynamics, and it is demonstrated for macromolecular and nanofluidic systems. A toolkit is developed for prototyping these algorithms, which are then implemented within the GROMACS simulation package and released as an open source multiscale simulator.
Multiscale modeling of transdermal drug delivery
Rim, Jee Eun
2006-04-01
This study addresses the modeling of transdermal diffusion of drugs, to better understand the permeation of molecules through the skin, and especially the stratum corneum, which forms the main permeation barrier of the skin. In transdermal delivery of systemic drugs, the drugs diffuse from a patch placed on the skin through the epidermis to the underlying blood vessels. The epidermis is the outermost layer of the skin and can be further divided into the stratum corneum (SC) and the viable epidermis layers. The SC consists of keratinous cells (corneocytes) embedded in the lipid multi-bilayers of the intercellular space. It is widely accepted that the barrier properties of the skin mostly arises from the ordered structure of the lipid bilayers. The diffusion path, at least for lipophilic molecules, seems to be mainly through the lipid bilayers. Despite the advantages of transdermal drug delivery compared to other drug delivery routes such as oral dosing and injections, the low percutaneous permeability of most compounds is a major difficulty in the wide application of transdermal drug delivery. In fact, many transdermal drug formulations include one or more permeation enhancers that increase the permeation of the drug significantly. During the last two decades, many researchers have studied percutaneous absorption of drugs both experimentally and theoretically. However, many are based on pharmacokinetic compartmental models, in which steady or pseudo-steady state conditions are assumed, with constant diffusivity and partitioning for single component systems. This study presents a framework for studying the multi-component diffusion of drugs coupled with enhancers through the skin by considering the microstructure of the stratum corneum (SC). A multiscale framework of modeling the transdermal diffusion of molecules is presented, by first calculating the microscopic diffusion coefficient in the lipid bilayers of the SC using molecular dynamics (MD). Then a
Directory of Open Access Journals (Sweden)
Juan Guillermo eDiaz Ochoa
2013-01-01
Full Text Available In this study, we focus on a novel multi-scale modeling approach for spatiotemporal prediction of the distribution of substances and resulting hepatotoxicity by combining cellular models, a 2D liver model, and whole-body model. As a case study, we focused on predicting human hepatotoxicity upon treatment with acetaminophen based on in vitro toxicity data and potential inter-individual variability in gene expression and enzyme activities. By aggregating mechanistic, genome-based in silico cells to a novel 2D liver model and eventually to a whole body model, we predicted pharmacokinetic properties, metabolism, and the onset of hepatotoxicity in an in silico patient. Depending on the concentration of acetaminophen in the liver and the accumulation of toxic metabolites, cell integrity in the liver as a function of space and time as well as changes in the elimination rate of substances were estimated. We show that the variations in elimination rates also influence the distribution of acetaminophen and its metabolites in the whole body. Our results are in agreement with experimental results. What is more, the integrated model also predicted variations in drug toxicity depending on alterations of metabolic enzyme activities. Variations in enzyme activity, in turn, reflect genetic characteristics or diseases of individuals. In conclusion, this framework presents an important basis for efficiently integrating inter-individual variability data into models, paving the way for personalized or stratified predictions of drug toxicity and efficacy.
Multiscale model reduction for shale gas transport in fractured media
Akkutlu, I. Y.
2016-05-18
In this paper, we develop a multiscale model reduction technique that describes shale gas transport in fractured media. Due to the pore-scale heterogeneities and processes, we use upscaled models to describe the matrix. We follow our previous work (Akkutlu et al. Transp. Porous Media 107(1), 235–260, 2015), where we derived an upscaled model in the form of generalized nonlinear diffusion model to describe the effects of kerogen. To model the interaction between the matrix and the fractures, we use Generalized Multiscale Finite Element Method (Efendiev et al. J. Comput. Phys. 251, 116–135, 2013, 2015). In this approach, the matrix and the fracture interaction is modeled via local multiscale basis functions. In Efendiev et al. (2015), we developed the GMsFEM and applied for linear flows with horizontal or vertical fracture orientations aligned with a Cartesian fine grid. The approach in Efendiev et al. (2015) does not allow handling arbitrary fracture distributions. In this paper, we (1) consider arbitrary fracture distributions on an unstructured grid; (2) develop GMsFEM for nonlinear flows; and (3) develop online basis function strategies to adaptively improve the convergence. The number of multiscale basis functions in each coarse region represents the degrees of freedom needed to achieve a certain error threshold. Our approach is adaptive in a sense that the multiscale basis functions can be added in the regions of interest. Numerical results for two-dimensional problem are presented to demonstrate the efficiency of proposed approach. © 2016 Springer International Publishing Switzerland
Multiscale stabilization for convection-dominated diffusion in heterogeneous media
Calo, Victor M.
2016-02-23
We develop a Petrov-Galerkin stabilization method for multiscale convection-diffusion transport systems. Existing stabilization techniques add a limited number of degrees of freedom in the form of bubble functions or a modified diffusion, which may not be sufficient to stabilize multiscale systems. We seek a local reduced-order model for this kind of multiscale transport problems and thus, develop a systematic approach for finding reduced-order approximations of the solution. We start from a Petrov-Galerkin framework using optimal weighting functions. We introduce an auxiliary variable to a mixed formulation of the problem. The auxiliary variable stands for the optimal weighting function. The problem reduces to finding a test space (a dimensionally reduced space for this auxiliary variable), which guarantees that the error in the primal variable (representing the solution) is close to the projection error of the full solution on the dimensionally reduced space that approximates the solution. To find the test space, we reformulate some recent mixed Generalized Multiscale Finite Element Methods. We introduce snapshots and local spectral problems that appropriately define local weight and trial spaces. In particular, we use energy minimizing snapshots and local spectral decompositions in the natural norm associated with the auxiliary variable. The resulting spectral decomposition adaptively identifies and builds the optimal multiscale space to stabilize the system. We discuss the stability and its relation to the approximation property of the test space. We design online basis functions, which accelerate convergence in the test space, and consequently, improve stability. We present several numerical examples and show that one needs a few test functions to achieve an error similar to the projection error in the primal variable irrespective of the Peclet number.
Multiscale bilateral filtering for improving image quality in digital breast tomosynthesis
Lu, Yao; Chan, Heang-Ping; Wei, Jun; Hadjiiski, Lubomir M.; Samala, Ravi K.
2015-01-01
Purpose: Detection of subtle microcalcifications in digital breast tomosynthesis (DBT) is a challenging task because of the large, noisy DBT volume. It is important to enhance the contrast-to-noise ratio (CNR) of microcalcifications in DBT reconstruction. Most regularization methods depend on local gradient and may treat the ill-defined margins or subtle spiculations of masses and subtle microcalcifications as noise because of their small gradient. The authors developed a new multiscale bilateral filtering (MSBF) regularization method for the simultaneous algebraic reconstruction technique (SART) to improve the CNR of microcalcifications without compromising the quality of masses. Methods: The MSBF exploits a multiscale structure of DBT images to suppress noise and selectively enhance high frequency structures. At the end of each SART iteration, every DBT slice is decomposed into several frequency bands via Laplacian pyramid decomposition. No regularization is applied to the low frequency bands so that subtle edges of masses and structured background are preserved. Bilateral filtering is applied to the high frequency bands to enhance microcalcifications while suppressing noise. The regularized DBT images are used for updating in the next SART iteration. The new MSBF method was compared with the nonconvex total p-variation (TpV) method for noise regularization with SART. A GE GEN2 prototype DBT system was used for acquisition of projections at 21 angles in 3° increments over a ±30° range. The reconstruction image quality with no regularization (NR) and that with the two regularization methods were compared using the DBT scans of a heterogeneous breast phantom and several human subjects with masses and microcalcifications. The CNR and the full width at half maximum (FWHM) of the line profiles of microcalcifications and across the spiculations within their in-focus DBT slices were used as image quality measures. Results: The MSBF method reduced contouring artifacts
Response of Moist Convection to Multi-scale Surface Flux Heterogeneity
Kang, S. L.; Ryu, J. H.
2015-12-01
We investigate response of moist convection to multi-scale feature of the spatial variation of surface sensible heat fluxes (SHF) in the afternoon evolution of the convective boundary layer (CBL), utilizing a mesoscale-domain large eddy simulation (LES) model. The multi-scale surface heterogeneity feature is analytically created as a function of the spectral slope in the wavelength range from a few tens of km to a few hundreds of m in the spectrum of surface SHF on a log-log scale. The response of moist convection to the κ-3 - slope (where κ is wavenumber) surface SHF field is compared with that to the κ-2 - slope surface, which has a relatively weak mesoscale feature, and the homogeneous κ0 - slope surface. Given the surface energy balance with a spatially uniform available energy, the prescribed SHF has a 180° phase lag with the latent heat flux (LHF) in a horizontal domain of (several tens of km)2. Thus, warmer (cooler) surface is relatively dry (moist). For all the cases, the same observation-based sounding is prescribed for the initial condition. For all the κ-3 - slope surface heterogeneity cases, early non-precipitating shallow clouds further develop into precipitating deep thunderstorms. But for all the κ-2 - slope cases, only shallow clouds develop. We compare the vertical profiles of domain-averaged fluxes and variances, and the contribution of the mesoscale and turbulence contributions to the fluxes and variances, between the κ-3 versus κ-2 slope cases. Also the cross-scale processes are investigated.
Individual-specific multi-scale finite element simulation of cortical bone of human proximal femur
International Nuclear Information System (INIS)
Ascenzi, Maria-Grazia; Kawas, Neal P.; Lutz, Andre; Kardas, Dieter; Nackenhorst, Udo; Keyak, Joyce H.
2013-01-01
We present an innovative method to perform multi-scale finite element analyses of the cortical component of the femur using the individual’s (1) computed tomography scan; and (2) a bone specimen obtained in conjunction with orthopedic surgery. The method enables study of micro-structural characteristics regulating strains and stresses under physiological loading conditions. The analysis of the micro-structural scenarios that cause variation of strain and stress is the first step in understanding the elevated strains and stresses in bone tissue, which are indicative of higher likelihood of micro-crack formation in bone, implicated in consequent remodeling or macroscopic bone fracture. Evidence that micro-structure varies with clinical history and contributes in significant, but poorly understood, ways to bone function, motivates the method’s development, as does need for software tools to investigate relationships between macroscopic loading and micro-structure. Three applications – varying region of interest, bone mineral density, and orientation of collagen type I, illustrate the method. We show, in comparison between physiological loading and simple compression of a patient’s femur, that strains computed at the multi-scale model’s micro-level: (i) differ; and (ii) depend on local collagen-apatite orientation and degree of calcification. Our findings confirm the strain concentration role of osteocyte lacunae, important for mechano-transduction. We hypothesize occurrence of micro-crack formation, leading either to remodeling or macroscopic fracture, when the computed strains exceed the elastic range observed in micro-structural testing
Individual-specific multi-scale finite element simulation of cortical bone of human proximal femur
Energy Technology Data Exchange (ETDEWEB)
Ascenzi, Maria-Grazia, E-mail: mgascenzi@mednet.ucla.edu [UCLA/Orthopaedic Hospital, Department of Orthopaedic Surgery, Rehabilitation Bldg, Room 22-69, 1000 Veteran Avenue, University of California, Los Angeles, CA 90095 (United States); Kawas, Neal P., E-mail: nealkawas@ucla.edu [UCLA/Orthopaedic Hospital, Department of Orthopaedic Surgery, Rehabilitation Bldg, Room 22-69, 1000 Veteran Avenue, University of California, Los Angeles, CA 90095 (United States); Lutz, Andre, E-mail: andre.lutz@hotmail.de [Institute of Biomechanics and Numerical Mechanics, Leibniz University Hannover, 30167 Hannover (Germany); Kardas, Dieter, E-mail: kardas@ibnm.uni-hannover.de [ContiTech Vibration Control, Jaedekamp 30 None, 30419 Hannover (Germany); Nackenhorst, Udo, E-mail: nackenhorst@ibnm.uni-hannover.de [Institute of Biomechanics and Numerical Mechanics, Leibniz University Hannover, 30167 Hannover (Germany); Keyak, Joyce H., E-mail: jhkeyak@uci.edu [Department of Radiological Sciences, Medical Sciences I, Bldg 811, Room B140, University of California, Irvine, CA 92697-5000 (United States)
2013-07-01
We present an innovative method to perform multi-scale finite element analyses of the cortical component of the femur using the individual’s (1) computed tomography scan; and (2) a bone specimen obtained in conjunction with orthopedic surgery. The method enables study of micro-structural characteristics regulating strains and stresses under physiological loading conditions. The analysis of the micro-structural scenarios that cause variation of strain and stress is the first step in understanding the elevated strains and stresses in bone tissue, which are indicative of higher likelihood of micro-crack formation in bone, implicated in consequent remodeling or macroscopic bone fracture. Evidence that micro-structure varies with clinical history and contributes in significant, but poorly understood, ways to bone function, motivates the method’s development, as does need for software tools to investigate relationships between macroscopic loading and micro-structure. Three applications – varying region of interest, bone mineral density, and orientation of collagen type I, illustrate the method. We show, in comparison between physiological loading and simple compression of a patient’s femur, that strains computed at the multi-scale model’s micro-level: (i) differ; and (ii) depend on local collagen-apatite orientation and degree of calcification. Our findings confirm the strain concentration role of osteocyte lacunae, important for mechano-transduction. We hypothesize occurrence of micro-crack formation, leading either to remodeling or macroscopic fracture, when the computed strains exceed the elastic range observed in micro-structural testing.
Multiscale deep drawing analysis of dual-phase steels using grain cluster-based RGC scheme
International Nuclear Information System (INIS)
Tjahjanto, D D; Eisenlohr, P; Roters, F
2015-01-01
Multiscale modelling and simulation play an important role in sheet metal forming analysis, since the overall material responses at macroscopic engineering scales, e.g. formability and anisotropy, are strongly influenced by microstructural properties, such as grain size and crystal orientations (texture). In the present report, multiscale analysis on deep drawing of dual-phase steels is performed using an efficient grain cluster-based homogenization scheme.The homogenization scheme, called relaxed grain cluster (RGC), is based on a generalization of the grain cluster concept, where a (representative) volume element consists of p × q × r (hexahedral) grains. In this scheme, variation of the strain or deformation of individual grains is taken into account through the, so-called, interface relaxation, which is formulated within an energy minimization framework. An interfacial penalty term is introduced into the energy minimization framework in order to account for the effects of grain boundaries.The grain cluster-based homogenization scheme has been implemented and incorporated into the advanced material simulation platform DAMASK, which purposes to bridge the macroscale boundary value problems associated with deep drawing analysis to the micromechanical constitutive law, e.g. crystal plasticity model. Standard Lankford anisotropy tests are performed to validate the model parameters prior to the deep drawing analysis. Model predictions for the deep drawing simulations are analyzed and compared to the corresponding experimental data. The result shows that the predictions of the model are in a very good agreement with the experimental measurement. (paper)
Moiseiwitsch, B L
2004-01-01
This graduate-level text's primary objective is to demonstrate the expression of the equations of the various branches of mathematical physics in the succinct and elegant form of variational principles (and thereby illuminate their interrelationship). Its related intentions are to show how variational principles may be employed to determine the discrete eigenvalues for stationary state problems and to illustrate how to find the values of quantities (such as the phase shifts) that arise in the theory of scattering. Chapter-by-chapter treatment consists of analytical dynamics; optics, wave mecha
Yang, T.; Lee, C.
2017-12-01
The biases in the Global Circulation Models (GCMs) are crucial for understanding future climate changes. Currently, most bias correction methodologies suffer from the assumption that model bias is stationary. This paper provides a non-stationary bias correction model, termed Residual-based Bagging Tree (RBT) model, to reduce simulation biases and to quantify the contributions of single models. Specifically, the proposed model estimates the residuals between individual models and observations, and takes the differences between observations and the ensemble mean into consideration during the model training process. A case study is conducted for 10 major river basins in Mainland China during different seasons. Results show that the proposed model is capable of providing accurate and stable predictions while including the non-stationarities into the modeling framework. Significant reductions in both bias and root mean squared error are achieved with the proposed RBT model, especially for the central and western parts of China. The proposed RBT model has consistently better performance in reducing biases when compared to the raw ensemble mean, the ensemble mean with simple additive bias correction, and the single best model for different seasons. Furthermore, the contribution of each single GCM in reducing the overall bias is quantified. The single model importance varies between 3.1% and 7.2%. For different future scenarios (RCP 2.6, RCP 4.5, and RCP 8.5), the results from RBT model suggest temperature increases of 1.44 ºC, 2.59 ºC, and 4.71 ºC by the end of the century, respectively, when compared to the average temperature during 1970 - 1999.
A posteriori error analysis of multiscale operator decomposition methods for multiphysics models
International Nuclear Information System (INIS)
Estep, D; Carey, V; Tavener, S; Ginting, V; Wildey, T
2008-01-01
Multiphysics, multiscale models present significant challenges in computing accurate solutions and for estimating the error in information computed from numerical solutions. In this paper, we describe recent advances in extending the techniques of a posteriori error analysis to multiscale operator decomposition solution methods. While the particulars of the analysis vary considerably with the problem, several key ideas underlie a general approach being developed to treat operator decomposition multiscale methods. We explain these ideas in the context of three specific examples
DEFF Research Database (Denmark)
Dai, Gaoming; Mishnaevsky, Leon, Jr.
2014-01-01
3D numerical simulations of fatigue damage of multiscale fiber reinforced polymer composites with secondary nanoclay reinforcement are carried out. Macro–micro FE models of the multiscale composites are generated automatically using Python based software. The effect of the nanoclay reinforcement....... Multiscale composites with exfoliated nanoreinforcement and aligned nanoplatelets ensure the better fatigue resistance than those with intercalated/clustered and randomly oriented nanoreinforcement....
Li, Xin; Liu, Shaomin; Xiao, Qin; Ma, Mingguo; Jin, Rui; Che, Tao; Wang, Weizhen; Hu, Xiaoli; Xu, Ziwei; Wen, Jianguang; Wang, Liangxu
2017-01-01
We introduce a multiscale dataset obtained from Heihe Watershed Allied Telemetry Experimental Research (HiWATER) in an oasis-desert area in 2012. Upscaling of eco-hydrological processes on a heterogeneous surface is a grand challenge. Progress in this field is hindered by the poor availability of multiscale observations. HiWATER is an experiment designed to address this challenge through instrumentation on hierarchically nested scales to obtain multiscale and multidisciplinary data. The HiWAT...
OBJECT-ORIENTED CHANGE DETECTION BASED ON MULTI-SCALE APPROACH
Directory of Open Access Journals (Sweden)
Y. Jia
2016-06-01
Full Text Available The change detection of remote sensing images means analysing the change information quantitatively and recognizing the change types of the surface coverage data in different time phases. With the appearance of high resolution remote sensing image, object-oriented change detection method arises at this historic moment. In this paper, we research multi-scale approach for high resolution images, which includes multi-scale segmentation, multi-scale feature selection and multi-scale classification. Experimental results show that this method has a stronger advantage than the traditional single-scale method of high resolution remote sensing image change detection.
Multiscale analysis of surface morphologies by curvelet and contourlet transforms
International Nuclear Information System (INIS)
Li, Linfu; Zhang, Xiangchao; Zhang, Hao; He, Xiaoying; Xu, Min
2015-01-01
The surface topographies of precision components are critical to their functionalities. However, it is challenging to characterize the topographies of complex surfaces, especially for structured surfaces. The wavelet families are promising for the multiscale geometry analysis of nonstochastic surfaces. The second-generation curvelet transform provides a sparse representation and good multiscale decomposition for curve singularities. However, the contourlet expansion, composed of bases oriented along various directions in multiple scales with smaller redundancy rates, has a remarkable capability of representing borderlines. In this paper they are both adopted for the characterization of surface topographies. Different components can be extracted according to their scales and morphological characteristics; as a result, the corresponding manufacturing processes and functionalities can be analyzed specifically. Numerical experiments are given to demonstrate the capabilities of these methods in sparse representation and effective extraction of geometry features of different nonstochastic surfaces. (paper)
The Multiscale Material Point Method for Simulating Transient Responses
Chen, Zhen; Su, Yu-Chen; Zhang, Hetao; Jiang, Shan; Sewell, Thomas
2015-06-01
To effectively simulate multiscale transient responses such as impact and penetration without invoking master/slave treatment, the multiscale material point method (Multi-MPM) is being developed in which molecular dynamics at nanoscale and dissipative particle dynamics at mesoscale might be concurrently handled within the framework of the original MPM at microscale (continuum level). The proposed numerical scheme for concurrently linking different scales is described in this paper with simple examples for demonstration. It is shown from the preliminary study that the mapping and re-mapping procedure used in the original MPM could coarse-grain the information at fine scale and that the proposed interfacial scheme could provide a smooth link between different scales. Since the original MPM is an extension from computational fluid dynamics to solid dynamics, the proposed Multi-MPM might also become robust for dealing with multiphase interactions involving failure evolution. This work is supported in part by DTRA and NSFC.
Multiscale correlations in highly resolved Large Eddy Simulations
Biferale, Luca; Buzzicotti, Michele; Linkmann, Moritz
2017-11-01
Understanding multiscale turbulent statistics is one of the key challenges for many modern applied and fundamental problems in fluid dynamics. One of the main obstacles is the existence of anomalously strong non Gaussian fluctuations, which become more and more important with increasing Reynolds number. In order to assess the performance of LES models in reproducing these extreme events with reasonable accuracy, it is helpful to further understand the statistical properties of the coupling between the resolved and the subgrid scales. We present analytical and numerical results focussing on the multiscale correlations between the subgrid stress and the resolved velocity field obtained both from LES and filtered DNS data. Furthermore, a comparison is carried out between LES and DNS results concerning the scaling behaviour of higher-order structure functions using both Smagorinsky or self-similar Fourier sub-grid models. ERC AdG Grant No 339032 NewTURB.
Multiscale Modeling of Composites: Toward Virtual Testing … and Beyond
LLorca, J.; González, C.; Molina-Aldareguía, J. M.; Lópes, C. S.
2013-02-01
Recent developments in the area of multiscale modeling of fiber-reinforced polymers are presented. The overall strategy takes advantage of the separation of length scales between different entities (ply, laminate, and component) found in composite structures. This allows us to carry out multiscale modeling by computing the properties of one entity (e.g., individual plies) at the relevant length scale, homogenizing the results into a constitutive model, and passing this information to the next length scale to determine the mechanical behavior of the larger entity (e.g., laminate). As a result, high-fidelity numerical simulations of the mechanical behavior of composite coupons and small components are nowadays feasible starting from the matrix, fiber, and interface properties and spatial distribution. Finally, the roadmap is outlined for extending the current strategy to include functional properties and processing into the simulation scheme.
MULTISCALE TENSOR ANISOTROPIC FILTERING OF FLUORESCENCE MICROSCOPY FOR DENOISING MICROVASCULATURE.
Prasath, V B S; Pelapur, R; Glinskii, O V; Glinsky, V V; Huxley, V H; Palaniappan, K
2015-04-01
Fluorescence microscopy images are contaminated by noise and improving image quality without blurring vascular structures by filtering is an important step in automatic image analysis. The application of interest here is to automatically extract the structural components of the microvascular system with accuracy from images acquired by fluorescence microscopy. A robust denoising process is necessary in order to extract accurate vascular morphology information. For this purpose, we propose a multiscale tensor with anisotropic diffusion model which progressively and adaptively updates the amount of smoothing while preserving vessel boundaries accurately. Based on a coherency enhancing flow with planar confidence measure and fused 3D structure information, our method integrates multiple scales for microvasculature preservation and noise removal membrane structures. Experimental results on simulated synthetic images and epifluorescence images show the advantage of our improvement over other related diffusion filters. We further show that the proposed multiscale integration approach improves denoising accuracy of different tensor diffusion methods to obtain better microvasculature segmentation.
RBF Multiscale Collocation for Second Order Elliptic Boundary Value Problems
Farrell, Patricio
2013-01-01
In this paper, we discuss multiscale radial basis function collocation methods for solving elliptic partial differential equations on bounded domains. The approximate solution is constructed in a multilevel fashion, each level using compactly supported radial basis functions of smaller scale on an increasingly fine mesh. On each level, standard symmetric collocation is employed. A convergence theory is given, which builds on recent theoretical advances for multiscale approximation using compactly supported radial basis functions. We are able to show that the convergence is linear in the number of levels. We also discuss the condition numbers of the arising systems and the effect of simple, diagonal preconditioners, now proving rigorously previous numerical observations. © 2013 Society for Industrial and Applied Mathematics.
Global sensitivity analysis of multiscale properties of porous materials
Um, Kimoon; Zhang, Xuan; Katsoulakis, Markos; Plechac, Petr; Tartakovsky, Daniel M.
2018-02-01
Ubiquitous uncertainty about pore geometry inevitably undermines the veracity of pore- and multi-scale simulations of transport phenomena in porous media. It raises two fundamental issues: sensitivity of effective material properties to pore-scale parameters and statistical parameterization of Darcy-scale models that accounts for pore-scale uncertainty. Homogenization-based maps of pore-scale parameters onto their Darcy-scale counterparts facilitate both sensitivity analysis (SA) and uncertainty quantification. We treat uncertain geometric characteristics of a hierarchical porous medium as random variables to conduct global SA and to derive probabilistic descriptors of effective diffusion coefficients and effective sorption rate. Our analysis is formulated in terms of solute transport diffusing through a fluid-filled pore space, while sorbing to the solid matrix. Yet it is sufficiently general to be applied to other multiscale porous media phenomena that are amenable to homogenization.
Multiscale singular value manifold for rotating machinery fault diagnosis
Energy Technology Data Exchange (ETDEWEB)
Feng, Yi; Lu, BaoChun; Zhang, Deng Feng [School of Mechanical Engineering, Nanjing University of Science and Technology,Nanjing (United States)
2017-01-15
Time-frequency distribution of vibration signal can be considered as an image that contains more information than signal in time domain. Manifold learning is a novel theory for image recognition that can be also applied to rotating machinery fault pattern recognition based on time-frequency distributions. However, the vibration signal of rotating machinery in fault condition contains cyclical transient impulses with different phrases which are detrimental to image recognition for time-frequency distribution. To eliminate the effects of phase differences and extract the inherent features of time-frequency distributions, a multiscale singular value manifold method is proposed. The obtained low-dimensional multiscale singular value manifold features can reveal the differences of different fault patterns and they are applicable to classification and diagnosis. Experimental verification proves that the performance of the proposed method is superior in rotating machinery fault diagnosis.
Multiscale Modeling and Uncertainty Quantification for Nuclear Fuel Performance
Energy Technology Data Exchange (ETDEWEB)
Estep, Donald [Colorado State Univ., Fort Collins, CO (United States); El-Azab, Anter [Florida State Univ., Tallahassee, FL (United States); Pernice, Michael [Idaho National Lab. (INL), Idaho Falls, ID (United States); Peterson, John W. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Polyakov, Peter [Univ. of Wyoming, Laramie, WY (United States); Tavener, Simon [Colorado State Univ., Fort Collins, CO (United States); Xiu, Dongbin [Purdue Univ., West Lafayette, IN (United States); Univ. of Utah, Salt Lake City, UT (United States)
2017-03-23
In this project, we will address the challenges associated with constructing high fidelity multiscale models of nuclear fuel performance. We (*) propose a novel approach for coupling mesoscale and macroscale models, (*) devise efficient numerical methods for simulating the coupled system, and (*) devise and analyze effective numerical approaches for error and uncertainty quantification for the coupled multiscale system. As an integral part of the project, we will carry out analysis of the effects of upscaling and downscaling, investigate efficient methods for stochastic sensitivity analysis of the individual macroscale and mesoscale models, and carry out a posteriori error analysis for computed results. We will pursue development and implementation of solutions in software used at Idaho National Laboratories on models of interest to the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program.
Versatile Micromechanics Model for Multiscale Analysis of Composite Structures
Kwon, Y. W.; Park, M. S.
2013-08-01
A general-purpose micromechanics model was developed so that the model could be applied to various composite materials such as reinforced by particles, long fibers and short fibers as well as those containing micro voids. Additionally, the model can be used with hierarchical composite materials. The micromechanics model can be used to compute effective material properties like elastic moduli, shear moduli, Poisson's ratios, and coefficients of thermal expansion for the various composite materials. The model can also calculate the strains and stresses at the constituent material level such as fibers, particles, and whiskers from the composite level stresses and strains. The model was implemented into ABAQUS using the UMAT option for multiscale analysis. An extensive set of examples are presented to demonstrate the reliability and accuracy of the developed micromechanics model for different kinds of composite materials. Another set of examples is provided to study the multiscale analysis of composite structures.
Information theory and stochastics for multiscale nonlinear systems
Majda, Andrew J; Grote, Marcus J
2005-01-01
This book introduces mathematicians to the fascinating emerging mathematical interplay between ideas from stochastics and information theory and important practical issues in studying complex multiscale nonlinear systems. It emphasizes the serendipity between modern applied mathematics and applications where rigorous analysis, the development of qualitative and/or asymptotic models, and numerical modeling all interact to explain complex phenomena. After a brief introduction to the emerging issues in multiscale modeling, the book has three main chapters. The first chapter is an introduction to information theory with novel applications to statistical mechanics, predictability, and Jupiter's Red Spot for geophysical flows. The second chapter discusses new mathematical issues regarding fluctuation-dissipation theorems for complex nonlinear systems including information flow, various approximations, and illustrates applications to various mathematical models. The third chapter discusses stochastic modeling of com...
Formalizing Knowledge in Multi-Scale Agent-Based Simulations.
Somogyi, Endre; Sluka, James P; Glazier, James A
2016-10-01
Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused.
ProtoMD: A prototyping toolkit for multiscale molecular dynamics
Somogyi, Endre; Mansour, Andrew Abi; Ortoleva, Peter J.
2016-05-01
ProtoMD is a toolkit that facilitates the development of algorithms for multiscale molecular dynamics (MD) simulations. It is designed for multiscale methods which capture the dynamic transfer of information across multiple spatial scales, such as the atomic to the mesoscopic scale, via coevolving microscopic and coarse-grained (CG) variables. ProtoMD can be also be used to calibrate parameters needed in traditional CG-MD methods. The toolkit integrates 'GROMACS wrapper' to initiate MD simulations, and 'MDAnalysis' to analyze and manipulate trajectory files. It facilitates experimentation with a spectrum of coarse-grained variables, prototyping rare events (such as chemical reactions), or simulating nanocharacterization experiments such as terahertz spectroscopy, AFM, nanopore, and time-of-flight mass spectroscopy. ProtoMD is written in python and is freely available under the GNU General Public License from github.com/CTCNano/proto_md.
Multiscale Methods for Accurate, Efficient, and Scale-Aware Models
Energy Technology Data Exchange (ETDEWEB)
Larson, Vincent [Univ. of Wisconsin, Milwaukee, WI (United States)
2017-07-14
The goal of UWM’s portion of the Multiscale project was to develop a unified cloud parameterization that could simulate all cloud types --- including stratocumulus, shallow cumulus, and deep cumulus --- using the single equation set implemented in CLUBB. An advantage of a unified parameterization methodology is that it avoids the difficult task of interfacing different cloud parameterizations for different cloud types. To interface CLUBB’s clouds to the microphysics, a Monte Carlo interface, SILHS, was further developed.
Nonlinear dynamics of the complex multi-scale network
Makarov, Vladimir V.; Kirsanov, Daniil; Goremyko, Mikhail; Andreev, Andrey; Hramov, Alexander E.
2018-04-01
In this paper, we study the complex multi-scale network of nonlocally coupled oscillators for the appearance of chimera states. Chimera is a special state in which, in addition to the asynchronous cluster, there are also completely synchronous parts in the system. We show that the increase of nodes in subgroups leads to the destruction of the synchronous interaction within the common ring and to the narrowing of the chimera region.
Simplifying Differential Equations for Multiscale Feynman Integrals beyond Multiple Polylogarithms.
Adams, Luise; Chaubey, Ekta; Weinzierl, Stefan
2017-04-07
In this Letter we exploit factorization properties of Picard-Fuchs operators to decouple differential equations for multiscale Feynman integrals. The algorithm reduces the differential equations to blocks of the size of the order of the irreducible factors of the Picard-Fuchs operator. As a side product, our method can be used to easily convert the differential equations for Feynman integrals which evaluate to multiple polylogarithms to an ϵ form.
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.
Multiscale eddy simulation for moist atmospheric convection: Preliminary investigation
Energy Technology Data Exchange (ETDEWEB)
Stechmann, Samuel N., E-mail: stechmann@wisc.edu [Department of Mathematics, University of Wisconsin-Madison (United States); Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison (United States)
2014-08-15
A multiscale computational framework is designed for simulating atmospheric convection and clouds. In this multiscale framework, large eddy simulation (LES) is used to model the coarse scales of 100 m and larger, and a stochastic, one-dimensional turbulence (ODT) model is used to represent the fine scales of 100 m and smaller. Coupled and evolving together, these two components provide a multiscale eddy simulation (MES). Through its fine-scale turbulence and moist thermodynamics, MES allows coarse grid cells to be partially cloudy and to encompass cloudy–clear air mixing on scales down to 1 m; in contrast, in typical LES such fine-scale processes are not represented or are parameterized using bulk deterministic closures. To illustrate MES and investigate its multiscale dynamics, a shallow cumulus cloud field is simulated. The fine-scale variability is seen to take a plausible form, with partially cloudy grid cells prominent near cloud edges and cloud top. From earlier theoretical work, this mixing of cloudy and clear air is believed to have an important impact on buoyancy. However, contrary to expectations based on earlier theoretical studies, the mean statistics of the bulk cloud field are essentially the same in MES and LES; possible reasons for this are discussed, including possible limitations in the present formulation of MES. One difference between LES and MES is seen in the coarse-scale turbulent kinetic energy, which appears to grow slowly in time due to incoherent stochastic fluctuations in the buoyancy. This and other considerations suggest the need for some type of spatial and/or temporal filtering to attenuate undersampling of the stochastic fine-scale processes.
Multiscale Universal Interface: A concurrent framework for coupling heterogeneous solvers
Energy Technology Data Exchange (ETDEWEB)
Tang, Yu-Hang, E-mail: yuhang_tang@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI (United States); Kudo, Shuhei, E-mail: shuhei-kudo@outlook.jp [Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe, 657-8501 (Japan); Bian, Xin, E-mail: xin_bian@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI (United States); Li, Zhen, E-mail: zhen_li@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI (United States); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI (United States); Collaboratory on Mathematics for Mesoscopic Modeling of Materials, Pacific Northwest National Laboratory, Richland, WA 99354 (United States)
2015-09-15
Graphical abstract: - Abstract: 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 code flexibility. We validated the library by solving three different multiscale problems, which also serve to demonstrate the flexibility of the framework in handling heterogeneous models and solvers. In the first example, a Couette flow was simulated using two concurrently coupled Smoothed Particle Hydrodynamics (SPH) simulations of different spatial resolutions. In the second example, we coupled the deterministic SPH method with the stochastic Dissipative Particle Dynamics (DPD) method to study the effect of surface grafting on the hydrodynamics properties on the surface. In the third example, we consider conjugate heat transfer between a solid domain and a fluid domain by coupling the particle-based energy-conserving DPD (eDPD) method with the Finite Element Method (FEM)
Multiscale eddy simulation for moist atmospheric convection: Preliminary investigation
International Nuclear Information System (INIS)
Stechmann, Samuel N.
2014-01-01
A multiscale computational framework is designed for simulating atmospheric convection and clouds. In this multiscale framework, large eddy simulation (LES) is used to model the coarse scales of 100 m and larger, and a stochastic, one-dimensional turbulence (ODT) model is used to represent the fine scales of 100 m and smaller. Coupled and evolving together, these two components provide a multiscale eddy simulation (MES). Through its fine-scale turbulence and moist thermodynamics, MES allows coarse grid cells to be partially cloudy and to encompass cloudy–clear air mixing on scales down to 1 m; in contrast, in typical LES such fine-scale processes are not represented or are parameterized using bulk deterministic closures. To illustrate MES and investigate its multiscale dynamics, a shallow cumulus cloud field is simulated. The fine-scale variability is seen to take a plausible form, with partially cloudy grid cells prominent near cloud edges and cloud top. From earlier theoretical work, this mixing of cloudy and clear air is believed to have an important impact on buoyancy. However, contrary to expectations based on earlier theoretical studies, the mean statistics of the bulk cloud field are essentially the same in MES and LES; possible reasons for this are discussed, including possible limitations in the present formulation of MES. One difference between LES and MES is seen in the coarse-scale turbulent kinetic energy, which appears to grow slowly in time due to incoherent stochastic fluctuations in the buoyancy. This and other considerations suggest the need for some type of spatial and/or temporal filtering to attenuate undersampling of the stochastic fine-scale processes
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.
Multiscale structural study using scanning X-ray microscope
International Nuclear Information System (INIS)
Ohsumi, Hiroyuki; Arima, Taka-hisa
2016-01-01
Correspondence between structures at the atomic- and meso-scales can be given by scanning X-ray microscopy integrated with polarized X-ray diffractometry. Symmetry is the common structural feature available across multiple hierarchies. This article introduces a symmetry evaluation technique based on polarized X-ray diffractometry and describes two embodiments: chirality domain observation and antiferromagnetic domain observation. Multiscale structural studies would play an important role in uncovering universality of hierarchical structure. (author)
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
Multiscale computer modeling in biomechanics and biomedical engineering
2013-01-01
This book reviews the state-of-the-art in multiscale computer modeling, in terms of both accomplishments and challenges. The information in the book is particularly useful for biomedical engineers, medical physicists and researchers in systems biology, mathematical biology, micro-biomechanics and biomaterials who are interested in how to bridge between traditional biomedical engineering work at the organ and tissue scales, and the newer arenas of cellular and molecular bioengineering.
Multiscale methods in turbulent combustion: strategies and computational challenges
International Nuclear Information System (INIS)
Echekki, Tarek
2009-01-01
A principal challenge in modeling turbulent combustion flows is associated with their complex, multiscale nature. Traditional paradigms in the modeling of these flows have attempted to address this nature through different strategies, including exploiting the separation of turbulence and combustion scales and a reduced description of the composition space. The resulting moment-based methods often yield reasonable predictions of flow and reactive scalars' statistics under certain conditions. However, these methods must constantly evolve to address combustion at different regimes, modes or with dominant chemistries. In recent years, alternative multiscale strategies have emerged, which although in part inspired by the traditional approaches, also draw upon basic tools from computational science, applied mathematics and the increasing availability of powerful computational resources. This review presents a general overview of different strategies adopted for multiscale solutions of turbulent combustion flows. Within these strategies, some specific models are discussed or outlined to illustrate their capabilities and underlying assumptions. These strategies may be classified under four different classes, including (i) closure models for atomistic processes, (ii) multigrid and multiresolution strategies, (iii) flame-embedding strategies and (iv) hybrid large-eddy simulation-low-dimensional strategies. A combination of these strategies and models can potentially represent a robust alternative strategy to moment-based models; but a significant challenge remains in the development of computational frameworks for these approaches as well as their underlying theories. (topical review)
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.
Multi-scale symbolic transfer entropy analysis of EEG
Yao, Wenpo; Wang, Jun
2017-10-01
From both global and local perspectives, we symbolize two kinds of EEG and analyze their dynamic and asymmetrical information using multi-scale transfer entropy. Multi-scale process with scale factor from 1 to 199 and step size of 2 is applied to EEG of healthy people and epileptic patients, and then the permutation with embedding dimension of 3 and global approach are used to symbolize the sequences. The forward and reverse symbol sequences are taken as the inputs of transfer entropy. Scale factor intervals of permutation and global way are (37, 57) and (65, 85) where the two kinds of EEG have satisfied entropy distinctions. When scale factor is 67, transfer entropy of the healthy and epileptic subjects of permutation, 0.1137 and 0.1028, have biggest difference. And the corresponding values of the global symbolization is 0.0641 and 0.0601 which lies in the scale factor of 165. Research results show that permutation which takes contribution of local information has better distinction and is more effectively applied to our multi-scale transfer entropy analysis of EEG.
Numerical Simulations of a Multiscale Model of Stratified Langmuir Circulation
Malecha, Ziemowit; Chini, Gregory; Julien, Keith
2012-11-01
Langmuir circulation (LC), a prominent form of wind and surface-wave driven shear turbulence in the ocean surface boundary layer (BL), is commonly modeled using the Craik-Leibovich (CL) equations, a phase-averaged variant of the Navier-Stokes (NS) equations. Although surface-wave filtering renders the CL equations more amenable to simulation than are the instantaneous NS equations, simulations in wide domains, hundreds of times the BL depth, currently earn the ``grand challenge'' designation. To facilitate simulations of LC in such spatially-extended domains, we have derived multiscale CL equations by exploiting the scale separation between submesoscale and BL flows in the upper ocean. The numerical algorithm for simulating this multiscale model resembles super-parameterization schemes used in meteorology, but retains a firm mathematical basis. We have validated our algorithm and here use it to perform multiscale simulations of the interaction between LC and upper ocean density stratification. ZMM, GPC, KJ gratefully acknowledge funding from NSF CMG Award 0934827.
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.
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.
Multi-scale simulation for homogenization of cement media
International Nuclear Information System (INIS)
Abballe, T.
2011-01-01
To solve diffusion problems on cement media, two scales must be taken into account: a fine scale, which describes the micrometers wide microstructures present in the media, and a work scale, which is usually a few meters long. Direct numerical simulations are almost impossible because of the huge computational resources (memory, CPU time) required to assess both scales at the same time. To overcome this problem, we present in this thesis multi-scale resolution methods using both Finite Volumes and Finite Elements, along with their efficient implementations. More precisely, we developed a multi-scale simulation tool which uses the SALOME platform to mesh domains and post-process data, and the parallel calculation code MPCube to solve problems. This SALOME/MPCube tool can solve automatically and efficiently multi-scale simulations. Parallel structure of computer clusters can be use to dispatch the more time-consuming tasks. We optimized most functions to account for cement media specificities. We presents numerical experiments on various cement media samples, e.g. mortar and cement paste. From these results, we manage to compute a numerical effective diffusivity of our cement media and to reconstruct a fine scale solution. (author) [fr
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.
Learning multiscale and deep representations for classifying remotely sensed imagery
Zhao, Wenzhi; Du, Shihong
2016-03-01
It is widely agreed that spatial features can be combined with spectral properties for improving interpretation performances on very-high-resolution (VHR) images in urban areas. However, many existing methods for extracting spatial features can only generate low-level features and consider limited scales, leading to unpleasant classification results. In this study, multiscale convolutional neural network (MCNN) algorithm was presented to learn spatial-related deep features for hyperspectral remote imagery classification. Unlike traditional methods for extracting spatial features, the MCNN first transforms the original data sets into a pyramid structure containing spatial information at multiple scales, and then automatically extracts high-level spatial features using multiscale training data sets. Specifically, the MCNN has two merits: (1) high-level spatial features can be effectively learned by using the hierarchical learning structure and (2) multiscale learning scheme can capture contextual information at different scales. To evaluate the effectiveness of the proposed approach, the MCNN was applied to classify the well-known hyperspectral data sets and compared with traditional methods. The experimental results shown a significant increase in classification accuracies especially for urban areas.
Multiscale modeling of radiation effects in nuclear reactor structural materials
Energy Technology Data Exchange (ETDEWEB)
Kwon, Junhyun [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2015-10-15
Most problems in irradiated materials originate from the atomic collision of high-energy particles and lattice atoms. This collision leads to displacement cascades through the energy transfer reaction and causes various types of defects such as vacancies, interstitials, and clusters. The behavior of the point defects created in the displacement cascades is important because these defects play a major role in a microstructural evolution and further affect the changes in material properties. Rapid advances have been made in the computational capabilities for a realistic simulation of complex physical phenomena, such as irradiation and aging effects. At the same time, progress has been made in understanding the effect of radiation in metals, especially iron-based alloys. In this work, we present some of our ongoing work in this area, which illustrates a multiscale modeling for evaluating a microstructural evolution and mechanical property changes during irradiation. Multiscale modeling approaches are briefly presented here in the following order: nuclear interaction, atomic-level interaction, atomistic modeling, microstructural evolution modeling and mechanical property modeling. This is one of many possible methods for classifying techniques. The effort in developing physical multiscale models applied to radiation damage has been focused on a single crystal or single-grain materials.
A multiscale mortar multipoint flux mixed finite element method
Wheeler, Mary Fanett
2012-02-03
In this paper, we develop a multiscale mortar multipoint flux mixed finite element method for second order elliptic problems. The equations in the coarse elements (or subdomains) are discretized on a fine grid scale by a multipoint flux mixed finite element method that reduces to cell-centered finite differences on irregular grids. The subdomain grids do not have to match across the interfaces. Continuity of flux between coarse elements is imposed via a mortar finite element space on a coarse grid scale. With an appropriate choice of polynomial degree of the mortar space, we derive optimal order convergence on the fine scale for both the multiscale pressure and velocity, as well as the coarse scale mortar pressure. Some superconvergence results are also derived. The algebraic system is reduced via a non-overlapping domain decomposition to a coarse scale mortar interface problem that is solved using a multiscale flux basis. Numerical experiments are presented to confirm the theory and illustrate the efficiency and flexibility of the method. © EDP Sciences, SMAI, 2012.
Multiscale modelling and experimentation of hydrogen embrittlement in aerospace materials
Jothi, Sathiskumar
Pulse plated nickel and nickel based superalloys have been used extensively in the Ariane 5 space launcher engines. Large structural Ariane 5 space launcher engine components such as combustion chambers with complex microstructures have usually been manufactured using electrodeposited nickel with advanced pulse plating techniques with smaller parts made of nickel based superalloys joined or welded to the structure to fabricate Ariane 5 space launcher engines. One of the major challenges in manufacturing these space launcher components using newly developed materials is a fundamental understanding of how different materials and microstructures react with hydrogen during welding which can lead to hydrogen induced cracking. The main objective of this research has been to examine and interpret the effects of microstructure on hydrogen diffusion and hydrogen embrittlement in (i) nickel based superalloy 718, (ii) established and (iii) newly developed grades of pulse plated nickel used in the Ariane 5 space launcher engine combustion chamber. Also, the effect of microstructures on hydrogen induced hot and cold cracking and weldability of three different grades of pulse plated nickel were investigated. Multiscale modelling and experimental methods have been used throughout. The effect of microstructure on hydrogen embrittlement was explored using an original multiscale numerical model (exploiting synthetic and real microstructures) and a wide range of material characterization techniques including scanning electron microscopy, 2D and 3D electron back scattering diffraction, in-situ and ex-situ hydrogen charged slow strain rate tests, thermal spectroscopy analysis and the Varestraint weldability test. This research shows that combined multiscale modelling and experimentation is required for a fundamental understanding of microstructural effects in hydrogen embrittlement in these materials. Methods to control the susceptibility to hydrogen induced hot and cold cracking and
Sun, S.; Kou, J.; Yu, B.
2011-01-01
The temporal discretization scheme is one important ingredient of efficient simulator for two-phase flow in the fractured porous media. The application of single-scale temporal scheme is restricted by the rapid changes of the pressure and saturation in the fractured system with capillarity. In this paper, we propose a multi-scale time splitting strategy to simulate multi-scale multi-physics processes of two-phase flow in fractured porous media. We use the multi-scale time schemes for both the pressure and saturation equations; that is, a large time-step size is employed for the matrix domain, along with a small time-step size being applied in the fractures. The total time interval is partitioned into four temporal levels: the first level is used for the pressure in the entire domain, the second level matching rapid changes of the pressure in the fractures, the third level treating the response gap between the pressure and the saturation, and the fourth level applied for the saturation in the fractures. This method can reduce the computational cost arisen from the implicit solution of the pressure equation. Numerical examples are provided to demonstrate the efficiency of the proposed method.
Variational Multiscale Finite Element Method for Flows in Highly Porous Media
Iliev, O.; Lazarov, R.; Willems, J.
2011-01-01
We present a two-scale finite element method (FEM) for solving Brinkman's and Darcy's equations. These systems of equations model fluid flows in highly porous and porous media, respectively. The method uses a recently proposed discontinuous Galerkin FEM for Stokes' equations by Wang and Ye and the concept of subgrid approximation developed by Arbogast for Darcy's equations. In order to reduce the "resonance error" and to ensure convergence to the global fine solution, the algorithm is put in the framework of alternating Schwarz iterations using subdomains around the coarse-grid boundaries. The discussed algorithms are implemented using the Deal.II finite element library and are tested on a number of model problems. © 2011 Society for Industrial and Applied Mathematics.
Variational Multiscale Finite Element Method for Flows in Highly Porous Media
Iliev, O.
2011-10-01
We present a two-scale finite element method (FEM) for solving Brinkman\\'s and Darcy\\'s equations. These systems of equations model fluid flows in highly porous and porous media, respectively. The method uses a recently proposed discontinuous Galerkin FEM for Stokes\\' equations by Wang and Ye and the concept of subgrid approximation developed by Arbogast for Darcy\\'s equations. In order to reduce the "resonance error" and to ensure convergence to the global fine solution, the algorithm is put in the framework of alternating Schwarz iterations using subdomains around the coarse-grid boundaries. The discussed algorithms are implemented using the Deal.II finite element library and are tested on a number of model problems. © 2011 Society for Industrial and Applied Mathematics.
Pernot, Dominique
2014-01-01
Les derniers romans de Gabriel Josipovici offrent beaucoup de variété, allant de la parodie, de la fiction comique légère, dans Only Joking et Making Mistakes, à des sujets plus graves, plus personnels, ontologiques. Dans un court roman, Everything Passes, et dans un roman majeur, Goldberg: Variations, le lecteur est amené à se poser des questions sur la nature mystérieuse de la réalité, qui est, trop souvent, acceptée sans conteste par de nombreux roma...
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
Carmeliet, J.; Descamps, F.; Houvenaghel, G.
1999-01-01
A multiscale network model is presented to model unsaturated moisture transfer in hygroscopic capillary-porous materials showing a broad pore-size distribution. Both capillary effects and water sorption phenomena, water vapour and liquid water transfer are considered. The multiscale approach is
Multiscale finite element methods for high-contrast problems using local spectral basis functions
Efendiev, Yalchin
2011-02-01
In this paper we study multiscale finite element methods (MsFEMs) using spectral multiscale basis functions that are designed for high-contrast problems. Multiscale basis functions are constructed using eigenvectors of a carefully selected local spectral problem. This local spectral problem strongly depends on the choice of initial partition of unity functions. The resulting space enriches the initial multiscale space using eigenvectors of local spectral problem. The eigenvectors corresponding to small, asymptotically vanishing, eigenvalues detect important features of the solutions that are not captured by initial multiscale basis functions. Multiscale basis functions are constructed such that they span these eigenfunctions that correspond to small, asymptotically vanishing, eigenvalues. We present a convergence study that shows that the convergence rate (in energy norm) is proportional to (H/Λ*)1/2, where Λ* is proportional to the minimum of the eigenvalues that the corresponding eigenvectors are not included in the coarse space. Thus, we would like to reach to a larger eigenvalue with a smaller coarse space. This is accomplished with a careful choice of initial multiscale basis functions and the setup of the eigenvalue problems. Numerical results are presented to back-up our theoretical results and to show higher accuracy of MsFEMs with spectral multiscale basis functions. We also present a hierarchical construction of the eigenvectors that provides CPU savings. © 2010.
Multiscale analysis of heart rate dynamics: entropy and time irreversibility measures.
Costa, Madalena D; Peng, Chung-Kang; Goldberger, Ary L
2008-06-01
Cardiovascular signals are largely analyzed using traditional time and frequency domain measures. However, such measures fail to account for important properties related to multiscale organization and non-equilibrium dynamics. The complementary role of conventional signal analysis methods and emerging multiscale techniques, is, therefore, an important frontier area of investigation. The key finding of this presentation is that two recently developed multiscale computational tools--multiscale entropy and multiscale time irreversibility--are able to extract information from cardiac interbeat interval time series not contained in traditional methods based on mean, variance or Fourier spectrum (two-point correlation) techniques. These new methods, with careful attention to their limitations, may be useful in diagnostics, risk stratification and detection of toxicity of cardiac drugs.
Jiang, Lijian; Efendiev, Yalchin; Ginting, Victor
2010-01-01
In this paper, we discuss a numerical multiscale approach for solving wave equations with heterogeneous coefficients. Our interest comes from geophysics applications and we assume that there is no scale separation with respect to spatial variables. To obtain the solution of these multiscale problems on a coarse grid, we compute global fields such that the solution smoothly depends on these fields. We present a Galerkin multiscale finite element method using the global information and provide a convergence analysis when applied to solve the wave equations. We investigate the relation between the smoothness of the global fields and convergence rates of the global Galerkin multiscale finite element method for the wave equations. Numerical examples demonstrate that the use of global information renders better accuracy for wave equations with heterogeneous coefficients than the local multiscale finite element method. © 2010 IMACS.
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 Pigment Analysis of Medieval Illuminated Manuscripts
Sestak, Erica; Manukyan, Khachatur; Wiescher, Michael; Gura, David
2017-09-01
Three medieval illuminated manuscripts (codd. Lat. b. 1; Lat. b. 2; Lat. e. 4), housed at the University of Notre Dame's Hesburgh Library, vary in style, pigments, scribes, and regions, despite all three being Psalters used in the Late Middle Ages. XRF and Raman spectroscopy, which provided the elemental and molecular composition of the pigments, respectively, were used to analyze the pigments' compositions in an attempt to narrow further the manuscripts' possible origins. This experimental investigation emphasizes the importance of understanding the history of the manuscript through their pigments. Codd. Lat. b. 1 and Lat. b. 2 are Latinate German Psalters from the fifteenth century likely used in Katharinenkloster in Nuremberg. While there are visible differences in style within each Psalter, the variations in some of the pigment compositions, such as the inconstant presence of zinc, suggest different admixtures. Cod. Lat. e. 4 is a Latinate English Psalter from the fourteenth century, and it was written by two scribes and illuminated by two distinct painters. It is currently being tested to determine whether there are any correlations between the scribes and painters. These physical analyses will clarify the origins and provenances of the manuscripts.
DEFF Research Database (Denmark)
Kobayashi, Sofie; Berge, Maria; Grout, Brian William Wilson
2017-01-01
This study contributes towards a better understanding of learning dynamics in doctoral supervision by analysing how learning opportunities are created in the interaction between supervisors and PhD students, using the notion of experiencing variation as a key to learning. Empirically, we have based...... the study on four video-recorded sessions, with four different PhD students and their supervisors, all from life sciences. Our analysis revealed that learning opportunities in the supervision sessions concerned either the content matter of research (for instance, understanding soil structure......), or the research methods— more specifically how to produce valid results. Our results illustrate how supervisors and PhD students create a space of learning together in their particular discipline by varying critical aspects of their research in their discussions. Situations where more openended research issues...
Ricks, Trenton M.; Lacy, Jr., Thomas E.; Bednarcyk, Brett A.; Arnold, Steven M.
2013-01-01
Continuous fiber unidirectional polymer matrix composites (PMCs) can exhibit significant local variations in fiber volume fraction as a result of processing conditions that can lead to further local differences in material properties and failure behavior. In this work, the coupled effects of both local variations in fiber volume fraction and the empirically-based statistical distribution of fiber strengths on the predicted longitudinal modulus and local tensile strength of a unidirectional AS4 carbon fiber/ Hercules 3502 epoxy composite were investigated using the special purpose NASA Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC); local effective composite properties were obtained by homogenizing the material behavior over repeating units cells (RUCs). The predicted effective longitudinal modulus was relatively insensitive to small (8%) variations in local fiber volume fraction. The composite tensile strength, however, was highly dependent on the local distribution in fiber strengths. The RUC-averaged constitutive response can be used to characterize lower length scale material behavior within a multiscale analysis framework that couples the NASA code FEAMAC and the ABAQUS finite element solver. Such an approach can be effectively used to analyze the progressive failure of PMC structures whose failure initiates at the RUC level. Consideration of the effect of local variations in constituent properties and morphologies on progressive failure of PMCs is a central aspect of the application of Integrated Computational Materials Engineering (ICME) principles for composite materials.
Multiscale Currents Observed by MMS in the Flow Braking Region
Nakamura, Rumi; Varsani, Ali; Genestreti, Kevin J.; Le Contel, Olivier; Nakamura, Takuma; Baumjohann, Wolfgang; Nagai, Tsugunobu; Artemyev, Anton; Birn, Joachim; Sergeev, Victor A.; Apatenkov, Sergey; Ergun, Robert E.; Fuselier, Stephen A.; Gershman, Daniel J.; Giles, Barbara J.; Khotyaintsev, Yuri V.; Lindqvist, Per-Arne; Magnes, Werner; Mauk, Barry; Petrukovich, Anatoli; Russell, Christopher T.; Stawarz, Julia; Strangeway, Robert J.; Anderson, Brian; Burch, James L.; Bromund, Ken R.; Cohen, Ian; Fischer, David; Jaynes, Allison; Kepko, Laurence; Le, Guan; Plaschke, Ferdinand; Reeves, Geoff; Singer, Howard J.; Slavin, James A.; Torbert, Roy B.; Turner, Drew L.
2018-02-01
We present characteristics of current layers in the off-equatorial near-Earth plasma sheet boundary observed with high time-resolution measurements from the Magnetospheric Multiscale mission during an intense substorm associated with multiple dipolarizations. The four Magnetospheric Multiscale spacecraft, separated by distances of about 50 km, were located in the southern hemisphere in the dusk portion of a substorm current wedge. They observed fast flow disturbances (up to about 500 km/s), most intense in the dawn-dusk direction. Field-aligned currents were observed initially within the expanding plasma sheet, where the flow and field disturbances showed the distinct pattern expected in the braking region of localized flows. Subsequently, intense thin field-aligned current layers were detected at the inner boundary of equatorward moving flux tubes together with Earthward streaming hot ions. Intense Hall current layers were found adjacent to the field-aligned currents. In particular, we found a Hall current structure in the vicinity of the Earthward streaming ion jet that consisted of mixed ion components, that is, hot unmagnetized ions, cold E × B drifting ions, and magnetized electrons. Our observations show that both the near-Earth plasma jet diversion and the thin Hall current layers formed around the reconnection jet boundary are the sites where diversion of the perpendicular currents take place that contribute to the observed field-aligned current pattern as predicted by simulations of reconnection jets. Hence, multiscale structure of flow braking is preserved in the field-aligned currents in the off-equatorial plasma sheet and is also translated to ionosphere to become a part of the substorm field-aligned current system.
Asymptotic Expansion Homogenization for Multiscale Nuclear Fuel Analysis
International Nuclear Information System (INIS)
2015-01-01
Engineering scale nuclear fuel performance simulations can benefit by utilizing high-fidelity models running at a lower length scale. Lower length-scale models provide a detailed view of the material behavior that is used to determine the average material response at the macroscale. These lower length-scale calculations may provide insight into material behavior where experimental data is sparse or nonexistent. This multiscale approach is especially useful in the nuclear field, since irradiation experiments are difficult and expensive to conduct. The lower length-scale models complement the experiments by influencing the types of experiments required and by reducing the total number of experiments needed. This multiscale modeling approach is a central motivation in the development of the BISON-MARMOT fuel performance codes at Idaho National Laboratory. These codes seek to provide more accurate and predictive solutions for nuclear fuel behavior. One critical aspect of multiscale modeling is the ability to extract the relevant information from the lower length-scale sim- ulations. One approach, the asymptotic expansion homogenization (AEH) technique, has proven to be an effective method for determining homogenized material parameters. The AEH technique prescribes a system of equations to solve at the microscale that are used to compute homogenized material constants for use at the engineering scale. In this work, we employ AEH to explore the effect of evolving microstructural thermal conductivity and elastic constants on nuclear fuel performance. We show that the AEH approach fits cleanly into the BISON and MARMOT codes and provides a natural, multidimensional homogenization capability.
Multiscale Embedded Gene Co-expression Network Analysis.
Directory of Open Access Journals (Sweden)
Won-Min Song
2015-11-01
Full Text Available Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3, the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA by: i introducing quality control of co-expression similarities, ii parallelizing embedded network construction, and iii developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs. We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA. MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.
Multiscale Embedded Gene Co-expression Network Analysis.
Song, Won-Min; Zhang, Bin
2015-11-01
Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.
The set of prime numbers: Multiscale analysis and numeric accelerators
International Nuclear Information System (INIS)
Iovane, Gerardo
2009-01-01
In this work, we show that the prime numbers follow a multiscale distribution. Indeed they can be classified thanks to tree structures, which are expressed in terms of two maximal subsets of N and using multilayer selection rules, acting on these sets of prime candidates. Consequently, the prime numbers follow a specific deterministic rules. Indeed, a numeric accelerator for generating primes can be realized in terms of the above mentioned specific rules. From the comparison with the Fibonacci numbers a beautiful harmony comes in terms of the Golden Mean which is relevant to high energy physics and E-Infinity theory too.
Growth of nitrogen-doped graphene on copper: Multiscale simulations
Gaillard, P.; Schoenhalz, A. L.; Moskovkin, P.; Lucas, S.; Henrard, L.
2016-02-01
We used multiscale simulations to model the growth of nitrogen-doped graphene on a copper substrate by chemical vapour deposition (CVD). Our simulations are based on ab-initio calculations of energy barriers for surface diffusion, which are complemented by larger scale Kinetic Monte Carlo (KMC) simulations. Our results indicate that the shape of grown doped graphene flakes depends on the temperature and deposition flux they are submitted during the process, but we found no significant effect of nitrogen doping on this shape. However, we show that nitrogen atoms have a preference for pyridine-like sites compared to graphite-like sites, as observed experimentally.
3D Multiscale Modelling of Angiogenesis and Vascular Tumour Growth
Perfahl, H.
2012-11-01
We present a three-dimensional, multiscale model of vascular tumour growth, which couples nutrient/growth factor transport, blood flow, angiogenesis, vascular remodelling, movement of and interactions between normal and tumour cells, and nutrient-dependent cell cycle dynamics within each cell. We present computational simulations which show how a vascular network may evolve and interact with tumour and healthy cells. We also demonstrate how our model may be combined with experimental data, to predict the spatio-temporal evolution of a vascular tumour.
Fast Decentralized Averaging via Multi-scale Gossip
Tsianos, Konstantinos I.; Rabbat, Michael G.
We are interested in the problem of computing the average consensus in a distributed fashion on random geometric graphs. We describe a new algorithm called Multi-scale Gossip which employs a hierarchical decomposition of the graph to partition the computation into tractable sub-problems. Using only pairwise messages of fixed size that travel at most O(n^{1/3}) hops, our algorithm is robust and has communication cost of O(n loglogn logɛ - 1) transmissions, which is order-optimal up to the logarithmic factor in n. Simulated experiments verify the good expected performance on graphs of many thousands of nodes.
Multi-scale structural similarity index for motion detection
Directory of Open Access Journals (Sweden)
M. Abdel-Salam Nasr
2017-07-01
Full Text Available The most recent approach for measuring the image quality is the structural similarity index (SSI. This paper presents a novel algorithm based on the multi-scale structural similarity index for motion detection (MS-SSIM in videos. The MS-SSIM approach is based on modeling of image luminance, contrast and structure at multiple scales. The MS-SSIM has resulted in much better performance than the single scale SSI approach but at the cost of relatively lower processing speed. The major advantages of the presented algorithm are both: the higher detection accuracy and the quasi real-time processing speed.
Multiscale Modeling of Carbon Nanotube-Epoxy Nanocomposites
Fasanella, Nicholas A.
Epoxy-composites are widely used in the aerospace industry. In order to improve upon stiffness and thermal conductivity; carbon nanotube additives to epoxies are being explored. This dissertation presents multiscale modeling techniques to study the engineering properties of single walled carbon nanotube (SWNT)-epoxy nanocomposites, consisting of pristine and covalently functionalized systems. Using Molecular Dynamics (MD), thermomechanical properties were calculated for a representative polymer unit cell. Finite Element (FE) and orientation distribution function (ODF) based methods were used in a multiscale framework to obtain macroscale properties. An epoxy network was built using the dendrimer growth approach. The epoxy model was verified by matching the experimental glass transition temperature, density, and dilatation. MD, via the constant valence force field (CVFF), was used to explore the mechanical and dilatometric effects of adding pristine and functionalized SWNTs to epoxy. Full stiffness matrices and linear coefficient of thermal expansion vectors were obtained. The Green-Kubo method was used to investigate the thermal conductivity as a function of temperature for the various nanocomposites. Inefficient phonon transport at the ends of nanotubes is an important factor in the thermal conductivity of the nanocomposites, and for this reason discontinuous nanotubes were modeled in addition to long nanotubes. To obtain continuum-scale elastic properties from the MD data, multiscale modeling was considered to give better control over the volume fraction of nanotubes, and investigate the effects of nanotube alignment. Two methods were considered; an FE based method, and an ODF based method. The FE method probabilistically assigned elastic properties of elements from the MD lattice results based on the desired volume fraction and alignment of the nanotubes. For the ODF method, a distribution function was generated based on the desired amount of nanotube alignment
3D Multiscale Modelling of Angiogenesis and Vascular Tumour Growth
Perfahl, H.; Byrne, H. M.; Chen, T.; Estrella, V.; Alarcó n, T.; Lapin, A.; Gatenby, R. A.; Gillies, R. J.; Lloyd, M. C.; Maini, P. K.; Reuss, M.; Owen, M. R.
2012-01-01
We present a three-dimensional, multiscale model of vascular tumour growth, which couples nutrient/growth factor transport, blood flow, angiogenesis, vascular remodelling, movement of and interactions between normal and tumour cells, and nutrient-dependent cell cycle dynamics within each cell. We present computational simulations which show how a vascular network may evolve and interact with tumour and healthy cells. We also demonstrate how our model may be combined with experimental data, to predict the spatio-temporal evolution of a vascular tumour.
Gaussian multiscale aggregation applied to segmentation in hand biometrics.
de Santos Sierra, Alberto; Avila, Carmen Sánchez; Casanova, Javier Guerra; del Pozo, Gonzalo Bailador
2011-01-01
This paper presents an image segmentation algorithm based on Gaussian multiscale aggregation oriented to hand biometric applications. The method is able to isolate the hand from a wide variety of background textures such as carpets, fabric, glass, grass, soil or stones. The evaluation was carried out by using a publicly available synthetic database with 408,000 hand images in different backgrounds, comparing the performance in terms of accuracy and computational cost to two competitive segmentation methods existing in literature, namely Lossy Data Compression (LDC) and Normalized Cuts (NCuts). The results highlight that the proposed method outperforms current competitive segmentation methods with regard to computational cost, time performance, accuracy and memory usage.
Multi-scale modeling of spin transport in organic semiconductors
Hemmatiyan, Shayan; Souza, Amaury; Kordt, Pascal; McNellis, Erik; Andrienko, Denis; Sinova, Jairo
In this work, we present our theoretical framework to simulate simultaneously spin and charge transport in amorphous organic semiconductors. By combining several techniques e.g. molecular dynamics, density functional theory and kinetic Monte Carlo, we are be able to study spin transport in the presence of anisotropy, thermal effects, magnetic and electric field effects in a realistic morphologies of amorphous organic systems. We apply our multi-scale approach to investigate the spin transport in amorphous Alq3 (Tris(8-hydroxyquinolinato)aluminum) and address the underlying spin relaxation mechanism in this system as a function of temperature, bias voltage, magnetic field and sample thickness.
An automated vessel segmentation of retinal images using multiscale vesselness
International Nuclear Information System (INIS)
Ben Abdallah, M.; Malek, J.; Tourki, R.; Krissian, K.
2011-01-01
The ocular fundus image can provide information on pathological changes caused by local ocular diseases and early signs of certain systemic diseases, such as diabetes and hypertension. Automated analysis and interpretation of fundus images has become a necessary and important diagnostic procedure in ophthalmology. The extraction of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. In this paper, we introduce an implementation of the anisotropic diffusion which allows reducing the noise and better preserving small structures like vessels in 2D images. A vessel detection filter, based on a multi-scale vesselness function, is then applied to enhance vascular structures.
Multiscale technicolour and the Zbb-bar vertex
International Nuclear Information System (INIS)
Chong-Xing Yue; Yu-Ping Kuang; Gong-Ru Lu
1997-01-01
Correction to the Z→bb-bar branching ratio (R b ) in the multiscale walking technicolour model (MWTCM) is examined. For the original MWTCM, the correction is too large to explain the recent LEP data in most of the parameter space. We show that the branching ratio R b in the topcolour assisted MWTCM can be in agreement with the LEP data for a certain range of the parameters and the flavour diagonal ETC boson exchange gives very small contribution to the parameter T. (author)
Expected Navigation Flight Performance for the Magnetospheric Multiscale (MMS) Mission
Olson, Corwin; Wright, Cinnamon; Long, Anne
2012-01-01
The Magnetospheric Multiscale (MMS) mission consists of four formation-flying spacecraft placed in highly eccentric elliptical orbits about the Earth. The primary scientific mission objective is to study magnetic reconnection within the Earth s magnetosphere. The baseline navigation concept is the independent estimation of each spacecraft state using GPS pseudorange measurements (referenced to an onboard Ultra Stable Oscillator) and accelerometer measurements during maneuvers. State estimation for the MMS spacecraft is performed onboard each vehicle using the Goddard Enhanced Onboard Navigation System, which is embedded in the Navigator GPS receiver. This paper describes the latest efforts to characterize expected navigation flight performance using upgraded simulation models derived from recent analyses.
Multi-Scale Dissemination of Time Series Data
DEFF Research Database (Denmark)
Guo, Qingsong; Zhou, Yongluan; Su, Li
2013-01-01
In this paper, we consider the problem of continuous dissemination of time series data, such as sensor measurements, to a large number of subscribers. These subscribers fall into multiple subscription levels, where each subscription level is specified by the bandwidth constraint of a subscriber......, which is an abstract indicator for both the physical limits and the amount of data that the subscriber would like to handle. To handle this problem, we propose a system framework for multi-scale time series data dissemination that employs a typical tree-based dissemination network and existing time...
Czech Academy of Sciences Publication Activity Database
Rokoš, O.; Peerlings, R. H. J.; Zeman, Jan
2017-01-01
Roč. 320, č. 1 (2017), s. 769-792 ISSN 0045-7825 R&D Projects: GA ČR(CZ) GF16-34894L Institutional support: RVO:67985556 Keywords : Lattice networks * Quasicontinuum method * Damage * Extended finite element method * Multiscale modelling * Variational formulation Subject RIV: JJ - Other Materials OBOR OECD: Materials engineering Impact factor: 3.949, year: 2016 http://library.utia.cas.cz/separaty/2017/AS/zeman-0475349.pdf
Bayesian Uncertainty Quantification for Subsurface Inversion Using a Multiscale Hierarchical Model
Mondal, Anirban
2014-07-03
We consider a Bayesian approach to nonlinear inverse problems in which the unknown quantity is a random field (spatial or temporal). The Bayesian approach contains a natural mechanism for regularization in the form of prior information, can incorporate information from heterogeneous sources and provide a quantitative assessment of uncertainty in the inverse solution. The Bayesian setting casts the inverse solution as a posterior probability distribution over the model parameters. The Karhunen-Loeve expansion is used for dimension reduction of the random field. Furthermore, we use a hierarchical Bayes model to inject multiscale data in the modeling framework. In this Bayesian framework, we show that this inverse problem is well-posed by proving that the posterior measure is Lipschitz continuous with respect to the data in total variation norm. Computational challenges in this construction arise from the need for repeated evaluations of the forward model (e.g., in the context of MCMC) and are compounded by high dimensionality of the posterior. We develop two-stage reversible jump MCMC that has the ability to screen the bad proposals in the first inexpensive stage. Numerical results are presented by analyzing simulated as well as real data from hydrocarbon reservoir. This article has supplementary material available online. © 2014 American Statistical Association and the American Society for Quality.
Directory of Open Access Journals (Sweden)
B. Harris
2012-07-01
Full Text Available Digital Elevation Models (DEMs allow for the efficient and consistent creation of waterways and catchment boundaries over large areas. Studies of waterway delineation from DEMs are usually undertaken over small or single catchment areas due to the nature of the problems being investigated. Improvements in Geographic Information Systems (GIS techniques, software, hardware and data allow for analysis of larger data sets and also facilitate a consistent tool for the creation and analysis of waterways over extensive areas. However, rarely are they developed over large regional areas because of the lack of available raw data sets and the amount of work required to create the underlying DEMs. This paper examines definition of waterways and catchments over an area of approximately 25,000 km2 to establish the optimal DEM scale required for waterway delineation over large regional projects. The comparative study analysed multi-scale DEMs over two test areas (Wivenhoe catchment, 543 km2 and a detailed 13 km2 within the Wivenhoe catchment including various data types, scales, quality, and variable catchment input parameters. Historic and available DEM data was compared to high resolution Lidar based DEMs to assess variations in the formation of stream networks. The results identified that, particularly in areas of high elevation change, DEMs at 20 m cell size created from broad scale 1:25,000 data (combined with more detailed data or manual delineation in flat areas are adequate for the creation of waterways and catchments at a regional scale.
A Multiscale Computational Model of the Response of Swine Epidermis After Acute Irradiation
Hu, Shaowen; Cucinotta, Francis A.
2012-01-01
Radiation exposure from Solar Particle Events can lead to very high skin dose for astronauts on exploration missions outside the protection of the Earth s magnetic field [1]. Assessing the detrimental effects to human skin under such adverse conditions could be predicted by conducting territorial experiments on animal models. In this study we apply a computational approach to simulate the experimental data of the radiation response of swine epidermis, which is closely similar to human epidermis [2]. Incorporating experimentally measured histological and cell kinetic parameters into a multiscale tissue modeling framework, we obtain results of population kinetics and proliferation index comparable to unirradiated and acutely irradiated swine experiments [3]. It is noted the basal cell doubling time is 10 to 16 days in the intact population, but drops to 13.6 hr in the regenerating populations surviving irradiation. This complex 30-fold variation is proposed to be attributed to the shortening of the G1 phase duration. We investigate this radiation induced effect by considering at the sub-cellular level the expression and signaling of TGF-beta, as it is recognized as a key regulatory factor of tissue formation and wound healing [4]. This integrated model will allow us to test the validity of various basic biological rules at the cellular level and sub-cellular mechanisms by qualitatively comparing simulation results with published research, and should lead to a fuller understanding of the pathophysiological effects of ionizing radiation on the skin.
Domain Decomposition Preconditioners for Multiscale Flows in High-Contrast Media
Galvis, Juan; Efendiev, Yalchin
2010-01-01
In this paper, we study domain decomposition preconditioners for multiscale flows in high-contrast media. We consider flow equations governed by elliptic equations in heterogeneous media with a large contrast in the coefficients. Our main goal is to develop domain decomposition preconditioners with the condition number that is independent of the contrast when there are variations within coarse regions. This is accomplished by designing coarse-scale spaces and interpolators that represent important features of the solution within each coarse region. The important features are characterized by the connectivities of high-conductivity regions. To detect these connectivities, we introduce an eigenvalue problem that automatically detects high-conductivity regions via a large gap in the spectrum. A main observation is that this eigenvalue problem has a few small, asymptotically vanishing eigenvalues. The number of these small eigenvalues is the same as the number of connected high-conductivity regions. The coarse spaces are constructed such that they span eigenfunctions corresponding to these small eigenvalues. These spaces are used within two-level additive Schwarz preconditioners as well as overlapping methods for the Schur complement to design preconditioners. We show that the condition number of the preconditioned systems is independent of the contrast. More detailed studies are performed for the case when the high-conductivity region is connected within coarse block neighborhoods. Our numerical experiments confirm the theoretical results presented in this paper. © 2010 Society for Industrial and Applied Mathematics.
Energy Technology Data Exchange (ETDEWEB)
Huang, S. Y.; Yuan, Z. G.; Wang, D. D.; Yu, X. D. [School of Electronic Information, Wuhan University, Wuhan (China); Sahraoui, F.; Contel, O. Le [Laboratoire de Physique des Plasmas, CNRS-Ecole Polytechnique-UPMC, Palaiseau (France); He, J. S. [School of Earth and Space Sciences, Peking University, Beijing (China); Zhao, J. S. [Key Laboratory of Planetary Sciences, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing (China); Deng, X. H.; Pang, Y.; Li, H. M. [Institute of Space Science and Technology, Nanchang University, Nanchang (China); Zhou, M. [Department of Physics and Astronomy, University of California, Los Angeles, CA (United States); Fu, H. S.; Yang, J. [School of Space and Environment, Beihang University, Beijing (China); Shi, Q. Q. [Shandong Provincial Key Laboratory of Optical Astronomy and Solar-Terrestrial Environment, Institute of Space Sciences, Shandong University, Weihai (China); Lavraud, B. [Institut de Recherche and Astrophysique et Planétologie, Université de Toulouse (UPS), Toulouse (France); Pollock, C. J.; Giles, B. L. [NASA, Goddard Space Flight Center, Greenbelt, MD (United States); Torbert, R. B. [University of New Hampshire, Durham, NH (United States); Russell, C. T., E-mail: shiyonghuang@whu.edu.cn [Department of Earth, Planetary and Space Sciences, University of California, Los Angeles, CA (United States); and others
2017-02-20
We report on the observations of an electron vortex magnetic hole corresponding to a new type of coherent structure in the turbulent magnetosheath plasma using the Magnetospheric Multiscale mission data. The magnetic hole is characterized by a magnetic depression, a density peak, a total electron temperature increase (with a parallel temperature decrease but a perpendicular temperature increase), and strong currents carried by the electrons. The current has a dip in the core region and a peak in the outer region of the magnetic hole. The estimated size of the magnetic hole is about 0.23 ρ {sub i} (∼30 ρ {sub e}) in the quasi-circular cross-section perpendicular to its axis, where ρ {sub i} and ρ {sub e} are respectively the proton and electron gyroradius. There are no clear enhancements seen in high-energy electron fluxes. However, there is an enhancement in the perpendicular electron fluxes at 90° pitch angle inside the magnetic hole, implying that the electrons are trapped within it. The variations of the electron velocity components V {sub em} and V {sub en} suggest that an electron vortex is formed by trapping electrons inside the magnetic hole in the cross-section in the M – N plane. These observations demonstrate the existence of a new type of coherent structures behaving as an electron vortex magnetic hole in turbulent space plasmas as predicted by recent kinetic simulations.
Harris, B.; McDougall, K.; Barry, M.
2012-07-01
Digital Elevation Models (DEMs) allow for the efficient and consistent creation of waterways and catchment boundaries over large areas. Studies of waterway delineation from DEMs are usually undertaken over small or single catchment areas due to the nature of the problems being investigated. Improvements in Geographic Information Systems (GIS) techniques, software, hardware and data allow for analysis of larger data sets and also facilitate a consistent tool for the creation and analysis of waterways over extensive areas. However, rarely are they developed over large regional areas because of the lack of available raw data sets and the amount of work required to create the underlying DEMs. This paper examines definition of waterways and catchments over an area of approximately 25,000 km2 to establish the optimal DEM scale required for waterway delineation over large regional projects. The comparative study analysed multi-scale DEMs over two test areas (Wivenhoe catchment, 543 km2 and a detailed 13 km2 within the Wivenhoe catchment) including various data types, scales, quality, and variable catchment input parameters. Historic and available DEM data was compared to high resolution Lidar based DEMs to assess variations in the formation of stream networks. The results identified that, particularly in areas of high elevation change, DEMs at 20 m cell size created from broad scale 1:25,000 data (combined with more detailed data or manual delineation in flat areas) are adequate for the creation of waterways and catchments at a regional scale.
Integrating multi-scale data to create a virtual physiological mouse heart.
Land, Sander; Niederer, Steven A; Louch, William E; Sejersted, Ole M; Smith, Nicolas P
2013-04-06
While the virtual physiological human (VPH) project has made great advances in human modelling, many of the tools and insights developed as part of this initiative are also applicable for facilitating mechanistic understanding of the physiology of a range of other species. This process, in turn, has the potential to provide human relevant insights via a different scientific path. Specifically, the increasing use of mice in experimental research, not yet fully complemented by a similar increase in computational modelling, is currently missing an important opportunity for using and interpreting this growing body of experimental data to improve our understanding of cardiac function. This overview describes our work to address this issue by creating a virtual physiological mouse model of the heart. We describe the similarities between human- and mouse-focused modelling, including the reuse of VPH tools, and the development of methods for investigating parameter sensitivity that are applicable across species. We show how previous results using this approach have already provided important biological insights, and how these can also be used to advance VPH heart models. Finally, we show an example application of this approach to test competing multi-scale hypotheses by investigating variations in length-dependent properties of cardiac muscle.
Yan, Zhifeng; Liu, Chongxuan; Liu, Yuanyuan; Bailey, Vanessa L.
2017-11-01
Biofilms are critical locations for biogeochemical reactions in the subsurface environment. The occurrence and distribution of biofilms at microscale as well as their impacts on macroscopic biogeochemical reaction rates are still poorly understood. This paper investigated the formation and distributions of biofilms in heterogeneous sediments using multiscale models and evaluated the effects of biofilm heterogeneity on local and macroscopic biogeochemical reaction rates. Sediment pore structures derived from X-ray computed tomography were used to simulate the microscale flow dynamics and biofilm distribution in the sediment column. The response of biofilm formation and distribution to the variations in hydraulic and chemical properties was first examined. One representative biofilm distribution was then utilized to evaluate its effects on macroscopic reaction rates using nitrate reduction as an example. The results revealed that microorganisms primarily grew on the surfaces of grains and aggregates near preferential flow paths where both electron donor and acceptor were readily accessible, leading to the heterogeneous distribution of biofilms in the sediments. The heterogeneous biofilm distribution decreased the macroscopic rate of biogeochemical reactions as compared with those in homogeneous cases. Operationally considering the heterogeneous biofilm distribution in macroscopic reactive transport models such as using dual porosity domain concept can significantly improve the prediction of biogeochemical reaction rates. Overall, this study provided important insights into the biofilm formation and distribution in soils and sediments as well as their impacts on the macroscopic manifestation of reaction rates.
Chang, N. B.; Yang, Y. J.; Daranpob, A.
2009-09-01
Recent extreme hydroclimatic events in the United States alone include, but are not limited to, the droughts in Maryland and the Chesapeake Bay area in 2001 through September 2002; Lake Mead in Las Vegas in 2000 through 2004; the Peace River and Lake Okeechobee in South Florida in 2006; and Lake Lanier in Atlanta, Georgia in 2007 that affected the water resources distribution in three states - Alabama, Florida and Georgia. This paper provides evidence from previous work and elaborates on the future perspectives that will collectively employ remote sensing and in-situ observations to support the implementation of the water availability assessment in a metropolitan region. Within the hydrological cycle, precipitation, soil moisture, and evapotranspiration can be monitored by using WSR-88D/NEXRAD data, RADARSAT-1 images, and GEOS images collectively to address the spatiotemporal variations of quantitative availability of waters whereas the MODIS images may be used to track down the qualitative availability of waters in terms of turbidity, Chlorophyll-a and other constitutes of concern. Tampa Bay in Florida was selected as a study site in this analysis, where the water supply infrastructure covers groundwater, desalination plant, and surface water at the same time. Research findings show that through the proper fusion of multi-source and multi-scale remote sensing data for water availability assessment in metropolitan region, a new insight of water infrastructure assessment can be gained to support sustainable planning region wide.
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
A multiscale quantum mechanics/electromagnetics method for device simulations.
Yam, ChiYung; Meng, Lingyi; Zhang, Yu; Chen, GuanHua
2015-04-07
Multiscale modeling has become a popular tool for research applying to different areas including materials science, microelectronics, biology, chemistry, etc. In this tutorial review, we describe a newly developed multiscale computational method, incorporating quantum mechanics into electronic device modeling with the electromagnetic environment included through classical electrodynamics. In the quantum mechanics/electromagnetics (QM/EM) method, the regions of the system where active electron scattering processes take place are treated quantum mechanically, while the surroundings are described by Maxwell's equations and a semiclassical drift-diffusion model. The QM model and the EM model are solved, respectively, in different regions of the system in a self-consistent manner. Potential distributions and current densities at the interface between QM and EM regions are employed as the boundary conditions for the quantum mechanical and electromagnetic simulations, respectively. The method is illustrated in the simulation of several realistic systems. In the case of junctionless field-effect transistors, transfer characteristics are obtained and a good agreement between experiments and simulations is achieved. Optical properties of a tandem photovoltaic cell are studied and the simulations demonstrate that multiple QM regions are coupled through the classical EM model. Finally, the study of a carbon nanotube-based molecular device shows the accuracy and efficiency of the QM/EM method.
Cloud Detection by Fusing Multi-Scale Convolutional Features
Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang
2018-04-01
Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.
Multiscale Morphology of Nanoporous Copper Made from Intermetallic Phases
International Nuclear Information System (INIS)
Egle, Tobias; Harvard University, Cambridge, MA; Barroo, Cédric; Janvelyan, Nare; Baumgaertel, Andreas C.
2017-01-01
Many application-relevant properties of nanoporous metals critically depend on their multiscale architecture. For example, the intrinsically high step-edge density of curved surfaces at the nanoscale provides highly reactive sites for catalysis, whereas the macroscale pore and grain morphology determines the macroscopic properties, such as mass transport, electrical conductivity, or mechanical properties. Here, in this work, we systematically study the effects of alloy composition and dealloying conditions on the multiscale morphology of nanoporous copper (np-Cu) made from various commercial Zn–Cu precursor alloys. Using a combination of X-ray diffraction, electron backscatter diffraction, and focused ion beam cross-sectional analysis, our results reveal that the macroscopic grain structure of the starting alloy surprisingly survives the dealloying process, despite a change in crystal structure from body-centered cubic (Zn–Cu starting alloy) to face-centered cubic (Cu). The nanoscale structure can be controlled by the acid used for dealloying with HCl leading to a larger and more faceted ligament morphology compared to that of H_3PO_4. Finally, anhydrous ethanol dehydrogenation was used as a probe reaction to test the effect of the nanoscale ligament morphology on the apparent activation energy of the reaction.
A wavelet multiscale denoising algorithm for magnetic resonance (MR) images
International Nuclear Information System (INIS)
Yang, Xiaofeng; Fei, Baowei
2011-01-01
Based on the Radon transform, a wavelet multiscale denoising method is proposed for MR images. The approach explicitly accounts for the Rician nature of MR data. Based on noise statistics we apply the Radon transform to the original MR images and use the Gaussian noise model to process the MR sinogram image. A translation invariant wavelet transform is employed to decompose the MR 'sinogram' into multiscales in order to effectively denoise the images. Based on the nature of Rician noise we estimate noise variance in different scales. For the final denoised sinogram we apply the inverse Radon transform in order to reconstruct the original MR images. Phantom, simulation brain MR images, and human brain MR images were used to validate our method. The experiment results show the superiority of the proposed scheme over the traditional methods. Our method can reduce Rician noise while preserving the key image details and features. The wavelet denoising method can have wide applications in MRI as well as other imaging modalities
Multi-scale window specification over streaming trajectories
Directory of Open Access Journals (Sweden)
Kostas Patroumpas
2013-12-01
Full Text Available Enormous amounts of positional information are collected by monitoring applications in domains such as fleet management, cargo transport, wildlife protection, etc. With the advent of modern location-based services, processing such data mostly focuses on providing real-time response to a variety of user requests in continuous and scalable fashion. An important class of such queries concerns evolving trajectories that continuously trace the streaming locations of moving objects, like GPS-equipped vehicles, commodities with RFID's, people with smartphones etc. In this work, we propose an advanced windowing operator that enables online, incremental examination of recent motion paths at multiple resolutions for numerous point entities. When applied against incoming positions, this window can abstract trajectories at coarser representations towards the past, while retaining progressively finer features closer to the present. We explain the semantics of such multi-scale sliding windows through parameterized functions that reflect the sequential nature of trajectories and can effectively capture their spatiotemporal properties. Such window specification goes beyond its usual role for non-blocking processing of multiple concurrent queries. Actually, it can offer concrete subsequences from each trajectory, thus preserving continuity in time and contiguity in space along the respective segments. Further, we suggest language extensions in order to express characteristic spatiotemporal queries using windows. Finally, we discuss algorithms for nested maintenance of multi-scale windows and evaluate their efficiency against streaming positional data, offering empirical evidence of their benefits to online trajectory processing.
Multiscale functions, scale dynamics, and applications to partial differential equations
Cresson, Jacky; Pierret, Frédéric
2016-05-01
Modeling phenomena from experimental data always begins with a choice of hypothesis on the observed dynamics such as determinism, randomness, and differentiability. Depending on these choices, different behaviors can be observed. The natural question associated to the modeling problem is the following: "With a finite set of data concerning a phenomenon, can we recover its underlying nature? From this problem, we introduce in this paper the definition of multi-scale functions, scale calculus, and scale dynamics based on the time scale calculus [see Bohner, M. and Peterson, A., Dynamic Equations on Time Scales: An Introduction with Applications (Springer Science & Business Media, 2001)] which is used to introduce the notion of scale equations. These definitions will be illustrated on the multi-scale Okamoto's functions. Scale equations are analysed using scale regimes and the notion of asymptotic model for a scale equation under a particular scale regime. The introduced formalism explains why a single scale equation can produce distinct continuous models even if the equation is scale invariant. Typical examples of such equations are given by the scale Euler-Lagrange equation. We illustrate our results using the scale Newton's equation which gives rise to a non-linear diffusion equation or a non-linear Schrödinger equation as asymptotic continuous models depending on the particular fractional scale regime which is considered.
Multiscale high-order/low-order (HOLO) algorithms and applications
International Nuclear Information System (INIS)
Chacón, L.; Chen, G.; Knoll, D.A.; Newman, C.; Park, H.; Taitano, W.; Willert, J.A.; Womeldorff, G.
2017-01-01
We review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.
Dynamics of a neural system with a multiscale architecture
Breakspear, Michael; Stam, Cornelis J
2005-01-01
The architecture of the brain is characterized by a modular organization repeated across a hierarchy of spatial scales—neurons, minicolumns, cortical columns, functional brain regions, and so on. It is important to consider that the processes governing neural dynamics at any given scale are not only determined by the behaviour of other neural structures at that scale, but also by the emergent behaviour of smaller scales, and the constraining influence of activity at larger scales. In this paper, we introduce a theoretical framework for neural systems in which the dynamics are nested within a multiscale architecture. In essence, the dynamics at each scale are determined by a coupled ensemble of nonlinear oscillators, which embody the principle scale-specific neurobiological processes. The dynamics at larger scales are ‘slaved’ to the emergent behaviour of smaller scales through a coupling function that depends on a multiscale wavelet decomposition. The approach is first explicated mathematically. Numerical examples are then given to illustrate phenomena such as between-scale bifurcations, and how synchronization in small-scale structures influences the dynamics in larger structures in an intuitive manner that cannot be captured by existing modelling approaches. A framework for relating the dynamical behaviour of the system to measured observables is presented and further extensions to capture wave phenomena and mode coupling are suggested. PMID:16087448
Multiscale Hybrid Nonlocal Means Filtering Using Modified Similarity Measure
Directory of Open Access Journals (Sweden)
Zahid Hussain Shamsi
2015-01-01
Full Text Available A new multiscale implementation of nonlocal means filtering (MHNLM for image denoising is proposed. The proposed algorithm also introduces a modification of the similarity measure for patch comparison. Assuming the patch as an oriented surface, the notion of a normal vectors patch is introduced. The inner product of these normal vectors patches is defined and then used in the weighted Euclidean distance of intensity patches as the weight factor. The algorithm involves two steps: the first step is a multiscale implementation of an accelerated nonlocal means filtering in the discrete stationary wavelet domain to obtain a refined version of the noisy patches for later comparison. The next step is to apply the proposed modification of standard nonlocal means filtering to the noisy image using the reference patches obtained in the first step. These refined patches contain less noise, and consequently the computation of normal vectors and partial derivatives is more precise. Experimental results show equivalent or better performance of the proposed algorithm compared to various state-of-the-art algorithms.
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.
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.
Multi-scale modeling for sustainable chemical production.
Zhuang, Kai; Bakshi, Bhavik R; Herrgård, Markus J
2013-09-01
With recent advances in metabolic engineering, it is now technically possible to produce a wide portfolio of existing petrochemical products from biomass feedstock. In recent years, a number of modeling approaches have been developed to support the engineering and decision-making processes associated with the development and implementation of a sustainable biochemical industry. The temporal and spatial scales of modeling approaches for sustainable chemical production vary greatly, ranging from metabolic models that aid the design of fermentative microbial strains to material and monetary flow models that explore the ecological impacts of all economic activities. Research efforts that attempt to connect the models at different scales have been limited. Here, we review a number of existing modeling approaches and their applications at the scales of metabolism, bioreactor, overall process, chemical industry, economy, and ecosystem. In addition, we propose a multi-scale approach for integrating the existing models into a cohesive framework. The major benefit of this proposed framework is that the design and decision-making at each scale can be informed, guided, and constrained by simulations and predictions at every other scale. In addition, the development of this multi-scale framework would promote cohesive collaborations across multiple traditionally disconnected modeling disciplines to achieve sustainable chemical production. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Refined generalized multiscale entropy analysis for physiological signals
Liu, Yunxiao; Lin, Youfang; Wang, Jing; Shang, Pengjian
2018-01-01
Multiscale entropy analysis has become a prevalent complexity measurement and been successfully applied in various fields. However, it only takes into account the information of mean values (first moment) in coarse-graining procedure. Then generalized multiscale entropy (MSEn) considering higher moments to coarse-grain a time series was proposed and MSEσ2 has been implemented. However, the MSEσ2 sometimes may yield an imprecise estimation of entropy or undefined entropy, and reduce statistical reliability of sample entropy estimation as scale factor increases. For this purpose, we developed the refined model, RMSEσ2, to improve MSEσ2. Simulations on both white noise and 1 / f noise show that RMSEσ2 provides higher entropy reliability and reduces the occurrence of undefined entropy, especially suitable for short time series. Besides, we discuss the effect on RMSEσ2 analysis from outliers, data loss and other concepts in signal processing. We apply the proposed model to evaluate the complexity of heartbeat interval time series derived from healthy young and elderly subjects, patients with congestive heart failure and patients with atrial fibrillation respectively, compared to several popular complexity metrics. The results demonstrate that RMSEσ2 measured complexity (a) decreases with aging and diseases, and (b) gives significant discrimination between different physiological/pathological states, which may facilitate clinical application.
The optimal filtering of a class of dynamic multiscale systems
Institute of Scientific and Technical Information of China (English)
PAN Quan; ZHANG Lei; CUI Peiling; ZHANG Hongcai
2004-01-01
This paper discusses the optimal filtering of a class of dynamic multiscale systems (DMS), which are observed independently by several sensors distributed at different resolution spaces. The system is subject to known dynamic system model. The resolution and sampling frequencies of the sensors are supposed to decrease by a factor of two. By using the Haar wavelet transform to link the state nodes at each of the scales within a time block, a discrete-time model of this class of multiscale systems is given, and the conditions for applying Kalman filtering are proven. Based on the linear time-invariant system, the controllability and observability of the system and the stability of the Kalman filtering is studied, and a theorem is given. It is proved that the Kalman filter is stable if only the system is controllable and observable at the finest scale. Finally, a constant-velocity process is used to obtain insight into the efficiencies offered by our model and algorithm.
Multiscale modelling approaches for assessing cosmetic ingredients safety.
Bois, Frédéric Y; Ochoa, Juan G Diaz; Gajewska, Monika; Kovarich, Simona; Mauch, Klaus; Paini, Alicia; Péry, Alexandre; Benito, Jose Vicente Sala; Teng, Sophie; Worth, Andrew
2017-12-01
The European Union's ban on animal testing for cosmetic ingredients and products has generated a strong momentum for the development of in silico and in vitro alternative methods. One of the focus of the COSMOS project was ab initio prediction of kinetics and toxic effects through multiscale pharmacokinetic modeling and in vitro data integration. In our experience, mathematical or computer modeling and in vitro experiments are complementary. We present here a summary of the main models and results obtained within the framework of the project on these topics. A first section presents our work at the organelle and cellular level. We then go toward modeling cell levels effects (monitored continuously), multiscale physiologically based pharmacokinetic and effect models, and route to route extrapolation. We follow with a short presentation of the automated KNIME workflows developed for dissemination and easy use of the models. We end with a discussion of two challenges to the field: our limited ability to deal with massive data and complex computations. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Multi-scale structural community organisation of the human genome.
Boulos, Rasha E; Tremblay, Nicolas; Arneodo, Alain; Borgnat, Pierre; Audit, Benjamin
2017-04-11
Structural interaction frequency matrices between all genome loci are now experimentally achievable thanks to high-throughput chromosome conformation capture technologies. This ensues a new methodological challenge for computational biology which consists in objectively extracting from these data the structural motifs characteristic of genome organisation. We deployed the fast multi-scale community mining algorithm based on spectral graph wavelets to characterise the networks of intra-chromosomal interactions in human cell lines. We observed that there exist structural domains of all sizes up to chromosome length and demonstrated that the set of structural communities forms a hierarchy of chromosome segments. Hence, at all scales, chromosome folding predominantly involves interactions between neighbouring sites rather than the formation of links between distant loci. Multi-scale structural decomposition of human chromosomes provides an original framework to question structural organisation and its relationship to functional regulation across the scales. By construction the proposed methodology is independent of the precise assembly of the reference genome and is thus directly applicable to genomes whose assembly is not fully determined.
Multiscale high-order/low-order (HOLO) algorithms and applications
Energy Technology Data Exchange (ETDEWEB)
Chacón, L., E-mail: chacon@lanl.gov [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Chen, G.; Knoll, D.A.; Newman, C.; Park, H.; Taitano, W. [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Willert, J.A. [Institute for Defense Analyses, Alexandria, VA 22311 (United States); Womeldorff, G. [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States)
2017-02-01
We review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.
Multiscale CNNs for Brain Tumor Segmentation and Diagnosis
Directory of Open Access Journals (Sweden)
Liya Zhao
2016-01-01
Full Text Available Early brain tumor detection and diagnosis are critical to clinics. Thus segmentation of focused tumor area needs to be accurate, efficient, and robust. In this paper, we propose an automatic brain tumor segmentation method based on Convolutional Neural Networks (CNNs. Traditional CNNs focus only on local features and ignore global region features, which are both important for pixel classification and recognition. Besides, brain tumor can appear in any place of the brain and be any size and shape in patients. We design a three-stream framework named as multiscale CNNs which could automatically detect the optimum top-three scales of the image sizes and combine information from different scales of the regions around that pixel. Datasets provided by Multimodal Brain Tumor Image Segmentation Benchmark (BRATS organized by MICCAI 2013 are utilized for both training and testing. The designed multiscale CNNs framework also combines multimodal features from T1, T1-enhanced, T2, and FLAIR MRI images. By comparison with traditional CNNs and the best two methods in BRATS 2012 and 2013, our framework shows advances in brain tumor segmentation accuracy and robustness.
Multiscale CNNs for Brain Tumor Segmentation and Diagnosis.
Zhao, Liya; Jia, Kebin
2016-01-01
Early brain tumor detection and diagnosis are critical to clinics. Thus segmentation of focused tumor area needs to be accurate, efficient, and robust. In this paper, we propose an automatic brain tumor segmentation method based on Convolutional Neural Networks (CNNs). Traditional CNNs focus only on local features and ignore global region features, which are both important for pixel classification and recognition. Besides, brain tumor can appear in any place of the brain and be any size and shape in patients. We design a three-stream framework named as multiscale CNNs which could automatically detect the optimum top-three scales of the image sizes and combine information from different scales of the regions around that pixel. Datasets provided by Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized by MICCAI 2013 are utilized for both training and testing. The designed multiscale CNNs framework also combines multimodal features from T1, T1-enhanced, T2, and FLAIR MRI images. By comparison with traditional CNNs and the best two methods in BRATS 2012 and 2013, our framework shows advances in brain tumor segmentation accuracy and robustness.
DEFF Research Database (Denmark)
Zhukovsky, Sergei; Orlov, Alexey A.; Babicheva, Viktoriia E.
2014-01-01
) on a larger, wavelength scale, the propagation of volume plasmon polaritons in the resulting multiscale hyperbolic metamaterials is subject to photonic-band-gap phenomena. A great degree of control over such plasmons can be exerted by varying the superstructure geometry. When this geometry is periodic, stop......, fractal Cantor-like multiscale metamaterials are found to exhibit characteristic self-similar spectral signatures in the volume plasmonic band. Multiscale hyperbolic metamaterials are shown to be a promising platform for large-wave-vector bulk plasmonic waves, whether they are considered for use as a kind...
Nakamura, Rumi; Jeszenszky, Harald; Torkar, Klaus; Andriopoulou, Maria; Fremuth, Gerhard; Taijmar, Martin; Scharlemann, Carsten; Svenes, Knut; Escoubet, Philippe; Prattes, Gustav; Laky, Gunter; Giner, Franz; Hoelzl, Bernhard
2015-04-01
The NASA's Magnetospheric Multiscale (MMS) Mission is planned to be launched on March 12, 2015. The scientific objectives of the MMS mission are to explore and understand the fundamental plasma physics processes of magnetic reconnection, particle acceleration and turbulence in the Earth's magnetosphere. The region of scientific interest of MMS is in a tenuous plasma environment where the positive spacecraft potential reaches an equilibrium at several tens of Volts. An Active Spacecraft Potential Control (ASPOC) instrument neutralizes the spacecraft potential by releasing positive charge produced by indium ion emitters. ASPOC thereby reduces the potential in order to improve the electric field and low-energy particle measurement. The method has been successfully applied on other spacecraft such as Cluster and Double Star. Two ASPOC units are present on each of the MMS spacecraft. Each unit contains four ion emitters, whereby one emitter per instrument is operated at a time. ASPOC for MMS includes new developments in the design of the emitters and the electronics enabling lower spacecraft potentials, higher reliability, and a more uniform potential structure in the spacecraft's sheath compared to previous missions. Model calculations confirm the findings from previous applications that the plasma measurements will not be affected by the beam's space charge. A perfectly stable spacecraft potential precludes the utilization of the spacecraft as a plasma probe, which is a conventional technique used to estimate ambient plasma density from the spacecraft potential. The small residual variations of the potential controlled by ASPOC, however, still allow to determine ambient plasma density by comparing two closely separated spacecraft and thereby reconstructing the uncontrolled potential variation from the controlled potential. Regular intercalibration of controlled and uncontrolled potentials is expected to increase the reliability of this new method.
Wilkinson, Mark; Owen, Gareth; Geris, Josie; Soulsby, Chris; Quinn, Paul
2015-04-01
Many communities across the world face the increasing challenge of balancing water quantity and quality issues with accommodating new growth and urban development. Urbanisation is typically associated with detrimental changes in water quality, sediment delivery, and effects on water storage and flow pathways (e.g. increases in flooding). In particular for mixed rural and urban catchments where the spatio-temporal variability of hydrological responses is high, there remains a key research challenge in evaluating the timing and magnitude of storage and flow pathways at multiple scales. This is of crucial importance for appropriate catchment management, for example to aid the design of Green Infrastructure (GI) to mitigate the risk of flooding, among other multiple benefits. The aim of this work was to (i) explore spatio-temporal storm runoff generation characteristics in multi-scale catchment experiments that contain rural and urban land use zones, and (ii) assess the (preliminary) impact of Sustainable Drainage (SuDs) as GI on high flow and flood characteristics. Our key research catchment, the Ouseburn in Northern England (55km2), has rural headwaters (15%) and an urban zone (45%) concentrated in the lower catchment area. There is an intermediate and increasingly expanding peri-urban zone (currently 40%), which is defined here as areas where rural and urban features coexist, alongside GIs. Such a structure is typical for most catchments with urban developments. We monitored spatial precipitation and multiscale nested (five gauges) runoff response, in addition to the storage dynamics in GIs for a period of 6 years (2007-2013). For a range of events, we examined the multiscale nested runoff characteristics (lag time and magnitude) of the rural and urban flow components, assessed how these integrated with changing land use and increasing scale, and discussed the implications for flood management in the catchment. The analyses indicated three distinctly different
Zhou, Zhangjian; Li, Jingfeng; Zhang, Lianmeng; Ge, Changchun
2013-03-01
The 12th International Symposium on Multiscale, Multifunctional and Functionally Graded Materials (FGM-2012) was held in Beijing, China, from 22-36 October 2012. This was part of a series of conferences organized every two years endorsed by International Advisory Committee for FGM's, which serves as a forum for scientists, educators, engineers and young students interested in the development of functionally graded materials (FGM). The series continues from the previous international symposium on FGM held in Sendai, Japan (1990), San Francisco, USA (1992), Lausanne, Switzerland (1994), Tsukuba, Japan (1996), Dresden, Germany (1998), Estes Park, USA (2000), Beijing, China (2002), Leuven, Belgium (2004), Hawaii, USA (2006), Sendai, Japan (2008) and Guimaraes, Portugal (2010). Functionally graded materials are non-uniform materials which are designed with embodied continuous spatial variations in composition and microstructure for the specific purpose of adjusting their thermal, structural, mechanical, biological or functional response to specific application conditions. Such multi-phase materials cover a range of space and time scales, and are best understood by means of a comprehensive multiscale, multiphysics approach. These kinds of materials are presently in the forefront of materials research, receiving worldwide attention. They have a broad range of applications including for example, biomedical, biomechanical, automotive, aerospace, mechanical, civil, nuclear, and naval engineering. New applications are continuously being discovered and developed. The objective of the FGM-2012 intends to provide opportunities for exchanging ideas and discussing state-of-the-art theories, techniques and applications in the fields of multiscale, multifunctional and FGM, through invited lectures, oral and poster presentations. FGM-2012 was organized and hosted by University of Science and Technology Beijing, China, together with Tsing-hua University and Wuhan University of
Zhang, Jun; Gao, Yaozong; Wang, Li; Tang, Zhen; Xia, James J.; Shen, Dinggang
2016-01-01
Objective The goal of this paper is to automatically digitize craniomaxillofacial (CMF) landmarks efficiently and accurately from cone-beam computed tomography (CBCT) images, by addressing the challenge caused by large morphological variations across patients and image artifacts of CBCT images. Methods We propose a Segmentation-guided Partially-joint Regression Forest (S-PRF) model to automatically digitize CMF landmarks. In this model, a regression voting strategy is first adopted to localize each landmark by aggregating evidences from context locations, thus potentially relieving the problem caused by image artifacts near the landmark. Second, CBCT image segmentation is utilized to remove uninformative voxels caused by morphological variations across patients. Third, a partially-joint model is further proposed to separately localize landmarks based on the coherence of landmark positions to improve the digitization reliability. In addition, we propose a fast vector quantization (VQ) method to extract high-level multi-scale statistical features to describe a voxel's appearance, which has low dimensionality, high efficiency, and is also invariant to the local inhomogeneity caused by artifacts. Results Mean digitization errors for 15 landmarks, in comparison to the ground truth, are all less than 2mm. Conclusion Our model has addressed challenges of both inter-patient morphological variations and imaging artifacts. Experiments on a CBCT dataset show that our approach achieves clinically acceptable accuracy for landmark digitalization. Significance Our automatic landmark digitization method can be used clinically to reduce the labor cost and also improve digitalization consistency. PMID:26625402
A multi-scale correlative investigation of ductile fracture
International Nuclear Information System (INIS)
Daly, M.; Burnett, T.L.; Pickering, E.J.; Tuck, O.C.G.; Léonard, F.; Kelley, R.; Withers, P.J.; Sherry, A.H.
2017-01-01
The use of novel multi-scale correlative methods, which involve the coordinated characterisation of matter across a range of length scales, are becoming of increasing value to materials scientists. Here, we describe for the first time how a multi-scale correlative approach can be used to investigate the nature of ductile fracture in metals. Specimens of a nuclear pressure vessel steel, SA508 Grade 3, are examined following ductile fracture using medium and high-resolution 3D X-ray computed tomography (CT) analyses, and a site-specific analysis using a dual beam plasma focused ion beam scanning electron microscope (PFIB-SEM). The methods are employed sequentially to characterise damage by void nucleation and growth in one volume of interest, allowing for the imaging of voids that ranged in size from less than 100 nm to over 100 μm. This enables the examination of voids initiated at carbide particles to be detected, as well as the large voids initiated at inclusions. We demonstrate that this multi-scale correlative approach is a powerful tool, which not only enhances our understanding of ductile failure through detailed characterisation of microstructure, but also provides quantitative information about the size, volume fractions and spatial distributions of voids that can be used to inform models of failure. It is found that the vast majority of large voids nucleated at MnS inclusions, and that the volume of a void varied according to the volume of its initiating inclusion raised to the power 3/2. The most severe voiding was concentrated within 500 μm of the fracture surface, but measurable damage was found to extend to a depth of at least 3 mm. Microvoids associated with carbides (carbide-initiated voids) were found to be concentrated around larger inclusion-initiated voids at depths of at least 400 μm. Methods for quantifying X-ray CT void data are discussed, and a procedure for using this data to calibrate parameters in the Gurson-Tvergaard Needleman (GTN
Predictive Multiscale Modeling of Nanocellulose Based Materials and Systems
International Nuclear Information System (INIS)
Kovalenko, Andriy
2014-01-01
Cellulose Nanocrysals (CNC) is a renewable biodegradable biopolymer with outstanding mechanical properties made from highly abundant natural source, and therefore is very attractive as reinforcing additive to replace petroleum-based plastics in biocomposite materials, foams, and gels. Large-scale applications of CNC are currently limited due to its low solubility in non-polar organic solvents used in existing polymerization technologies. The solvation properties of CNC can be improved by chemical modification of its surface. Development of effective surface modifications has been rather slow because extensive chemical modifications destabilize the hydrogen bonding network of cellulose and deteriorate the mechanical properties of CNC. We employ predictive multiscale theory, modeling, and simulation to gain a fundamental insight into the effect of CNC surface modifications on hydrogen bonding, CNC crystallinity, solvation thermodynamics, and CNC compatibilization with the existing polymerization technologies, so as to rationally design green nanomaterials with improved solubility in non-polar solvents, controlled liquid crystal ordering and optimized extrusion properties. An essential part of this multiscale modeling approach is the statistical- mechanical 3D-RISM-KH molecular theory of solvation, coupled with quantum mechanics, molecular mechanics, and multistep molecular dynamics simulation. The 3D-RISM-KH theory provides predictive modeling of both polar and non-polar solvents, solvent mixtures, and electrolyte solutions in a wide range of concentrations and thermodynamic states. It properly accounts for effective interactions in solution such as steric effects, hydrophobicity and hydrophilicity, hydrogen bonding, salt bridges, buffer, co-solvent, and successfully predicts solvation effects and processes in bulk liquids, solvation layers at solid surface, and in pockets and other inner spaces of macromolecules and supramolecular assemblies. This methodology
Predictive Multiscale Modeling of Nanocellulose Based Materials and Systems
Kovalenko, Andriy
2014-08-01
Cellulose Nanocrysals (CNC) is a renewable biodegradable biopolymer with outstanding mechanical properties made from highly abundant natural source, and therefore is very attractive as reinforcing additive to replace petroleum-based plastics in biocomposite materials, foams, and gels. Large-scale applications of CNC are currently limited due to its low solubility in non-polar organic solvents used in existing polymerization technologies. The solvation properties of CNC can be improved by chemical modification of its surface. Development of effective surface modifications has been rather slow because extensive chemical modifications destabilize the hydrogen bonding network of cellulose and deteriorate the mechanical properties of CNC. We employ predictive multiscale theory, modeling, and simulation to gain a fundamental insight into the effect of CNC surface modifications on hydrogen bonding, CNC crystallinity, solvation thermodynamics, and CNC compatibilization with the existing polymerization technologies, so as to rationally design green nanomaterials with improved solubility in non-polar solvents, controlled liquid crystal ordering and optimized extrusion properties. An essential part of this multiscale modeling approach is the statistical- mechanical 3D-RISM-KH molecular theory of solvation, coupled with quantum mechanics, molecular mechanics, and multistep molecular dynamics simulation. The 3D-RISM-KH theory provides predictive modeling of both polar and non-polar solvents, solvent mixtures, and electrolyte solutions in a wide range of concentrations and thermodynamic states. It properly accounts for effective interactions in solution such as steric effects, hydrophobicity and hydrophilicity, hydrogen bonding, salt bridges, buffer, co-solvent, and successfully predicts solvation effects and processes in bulk liquids, solvation layers at solid surface, and in pockets and other inner spaces of macromolecules and supramolecular assemblies. This methodology
A bidirectional coupling procedure applied to multiscale respiratory modeling
Energy Technology Data Exchange (ETDEWEB)
Kuprat, A.P., E-mail: andrew.kuprat@pnnl.gov [Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA (United States); Kabilan, S., E-mail: senthil.kabilan@pnnl.gov [Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA (United States); Carson, J.P., E-mail: james.carson@pnnl.gov [Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA (United States); Corley, R.A., E-mail: rick.corley@pnnl.gov [Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA (United States); Einstein, D.R., E-mail: daniel.einstein@pnnl.gov [Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA (United States)
2013-07-01
In this study, we present a novel multiscale computational framework for efficiently linking multiple lower-dimensional models describing the distal lung mechanics to imaging-based 3D computational fluid dynamics (CFDs) models of the upper pulmonary airways in order to incorporate physiologically appropriate outlet boundary conditions. The framework is an extension of the modified Newton’s method with nonlinear Krylov accelerator developed by Carlson and Miller [1], Miller [2] and Scott and Fenves [3]. Our extensions include the retention of subspace information over multiple timesteps, and a special correction at the end of a timestep that allows for corrections to be accepted with verified low residual with as little as a single residual evaluation per timestep on average. In the case of a single residual evaluation per timestep, the method has zero additional computational cost compared to uncoupled or unidirectionally coupled simulations. We expect these enhancements to be generally applicable to other multiscale coupling applications where timestepping occurs. In addition we have developed a “pressure-drop” residual which allows for stable coupling of flows between a 3D incompressible CFD application and another (lower-dimensional) fluid system. We expect this residual to also be useful for coupling non-respiratory incompressible fluid applications, such as multiscale simulations involving blood flow. The lower-dimensional models that are considered in this study are sets of simple ordinary differential equations (ODEs) representing the compliant mechanics of symmetric human pulmonary airway trees. To validate the method, we compare the predictions of hybrid CFD–ODE models against an ODE-only model of pulmonary airflow in an idealized geometry. Subsequently, we couple multiple sets of ODEs describing the distal lung to an imaging-based human lung geometry. Boundary conditions in these models consist of atmospheric pressure at the mouth and intrapleural
Multiscale study on stochastic reconstructions of shale samples
Lili, J.; Lin, M.; Jiang, W. B.
2016-12-01
Shales are known to have multiscale pore systems, composed of macroscale fractures, micropores, and nanoscale pores within gas or oil-producing organic material. Also, shales are fissile and laminated, and the heterogeneity in horizontal is quite different from that in vertical. Stochastic reconstructions are extremely useful in situations where three-dimensional information is costly and time consuming. Thus the purpose of our paper is to reconstruct stochastically equiprobable 3D models containing information from several scales. In this paper, macroscale and microscale images of shale structure in the Lower Silurian Longmaxi are obtained by X-ray microtomography and nanoscale images are obtained by scanning electron microscopy. Each image is representative for all given scales and phases. Especially, the macroscale is four times coarser than the microscale, which in turn is four times lower in resolution than the nanoscale image. Secondly, the cross correlation-based simulation method (CCSIM) and the three-step sampling method are combined together to generate stochastic reconstructions for each scale. It is important to point out that the boundary points of pore and matrix are selected based on multiple-point connectivity function in the sampling process, and thus the characteristics of the reconstructed image can be controlled indirectly. Thirdly, all images with the same resolution are developed through downscaling and upscaling by interpolation, and then we merge multiscale categorical spatial data into a single 3D image with predefined resolution (the microscale image). 30 realizations using the given images and the proposed method are generated. The result reveals that the proposed method is capable of preserving the multiscale pore structure, both vertically and horizontally, which is necessary for accurate permeability prediction. The variogram curves and pore-size distribution for both original 3D sample and the generated 3D realizations are compared
A bidirectional coupling procedure applied to multiscale respiratory modeling
Kuprat, A. P.; Kabilan, S.; Carson, J. P.; Corley, R. A.; Einstein, D. R.
2013-07-01
In this study, we present a novel multiscale computational framework for efficiently linking multiple lower-dimensional models describing the distal lung mechanics to imaging-based 3D computational fluid dynamics (CFDs) models of the upper pulmonary airways in order to incorporate physiologically appropriate outlet boundary conditions. The framework is an extension of the modified Newton's method with nonlinear Krylov accelerator developed by Carlson and Miller [1], Miller [2] and Scott and Fenves [3]. Our extensions include the retention of subspace information over multiple timesteps, and a special correction at the end of a timestep that allows for corrections to be accepted with verified low residual with as little as a single residual evaluation per timestep on average. In the case of a single residual evaluation per timestep, the method has zero additional computational cost compared to uncoupled or unidirectionally coupled simulations. We expect these enhancements to be generally applicable to other multiscale coupling applications where timestepping occurs. In addition we have developed a "pressure-drop" residual which allows for stable coupling of flows between a 3D incompressible CFD application and another (lower-dimensional) fluid system. We expect this residual to also be useful for coupling non-respiratory incompressible fluid applications, such as multiscale simulations involving blood flow. The lower-dimensional models that are considered in this study are sets of simple ordinary differential equations (ODEs) representing the compliant mechanics of symmetric human pulmonary airway trees. To validate the method, we compare the predictions of hybrid CFD-ODE models against an ODE-only model of pulmonary airflow in an idealized geometry. Subsequently, we couple multiple sets of ODEs describing the distal lung to an imaging-based human lung geometry. Boundary conditions in these models consist of atmospheric pressure at the mouth and intrapleural
Adaptive Multiscale Modeling of Geochemical Impacts on Fracture Evolution
Molins, S.; Trebotich, D.; Steefel, C. I.; Deng, H.
2016-12-01
Understanding fracture evolution is essential for many subsurface energy applications, including subsurface storage, shale gas production, fracking, CO2 sequestration, and geothermal energy extraction. Geochemical processes in particular play a significant role in the evolution of fractures through dissolution-driven widening, fines migration, and/or fracture sealing due to precipitation. One obstacle to understanding and exploiting geochemical fracture evolution is that it is a multiscale process. However, current geochemical modeling of fractures cannot capture this multi-scale nature of geochemical and mechanical impacts on fracture evolution, and is limited to either a continuum or pore-scale representation. Conventional continuum-scale models treat fractures as preferential flow paths, with their permeability evolving as a function (often, a cubic law) of the fracture aperture. This approach has the limitation that it oversimplifies flow within the fracture in its omission of pore scale effects while also assuming well-mixed conditions. More recently, pore-scale models along with advanced characterization techniques have allowed for accurate simulations of flow and reactive transport within the pore space (Molins et al., 2014, 2015). However, these models, even with high performance computing, are currently limited in their ability to treat tractable domain sizes (Steefel et al., 2013). Thus, there is a critical need to develop an adaptive modeling capability that can account for separate properties and processes, emergent and otherwise, in the fracture and the rock matrix at different spatial scales. Here we present an adaptive modeling capability that treats geochemical impacts on fracture evolution within a single multiscale framework. Model development makes use of the high performance simulation capability, Chombo-Crunch, leveraged by high resolution characterization and experiments. The modeling framework is based on the adaptive capability in Chombo
A bidirectional coupling procedure applied to multiscale respiratory modeling
International Nuclear Information System (INIS)
Kuprat, A.P.; Kabilan, S.; Carson, J.P.; Corley, R.A.; Einstein, D.R.
2013-01-01
In this study, we present a novel multiscale computational framework for efficiently linking multiple lower-dimensional models describing the distal lung mechanics to imaging-based 3D computational fluid dynamics (CFDs) models of the upper pulmonary airways in order to incorporate physiologically appropriate outlet boundary conditions. The framework is an extension of the modified Newton’s method with nonlinear Krylov accelerator developed by Carlson and Miller [1], Miller [2] and Scott and Fenves [3]. Our extensions include the retention of subspace information over multiple timesteps, and a special correction at the end of a timestep that allows for corrections to be accepted with verified low residual with as little as a single residual evaluation per timestep on average. In the case of a single residual evaluation per timestep, the method has zero additional computational cost compared to uncoupled or unidirectionally coupled simulations. We expect these enhancements to be generally applicable to other multiscale coupling applications where timestepping occurs. In addition we have developed a “pressure-drop” residual which allows for stable coupling of flows between a 3D incompressible CFD application and another (lower-dimensional) fluid system. We expect this residual to also be useful for coupling non-respiratory incompressible fluid applications, such as multiscale simulations involving blood flow. The lower-dimensional models that are considered in this study are sets of simple ordinary differential equations (ODEs) representing the compliant mechanics of symmetric human pulmonary airway trees. To validate the method, we compare the predictions of hybrid CFD–ODE models against an ODE-only model of pulmonary airflow in an idealized geometry. Subsequently, we couple multiple sets of ODEs describing the distal lung to an imaging-based human lung geometry. Boundary conditions in these models consist of atmospheric pressure at the mouth and intrapleural
Heat and mass transfer intensification and shape optimization a multi-scale approach
2013-01-01
Is the heat and mass transfer intensification defined as a new paradigm of process engineering, or is it just a common and old idea, renamed and given the current taste? Where might intensification occur? How to achieve intensification? How the shape optimization of thermal and fluidic devices leads to intensified heat and mass transfers? To answer these questions, Heat & Mass Transfer Intensification and Shape Optimization: A Multi-scale Approach clarifies the definition of the intensification by highlighting the potential role of the multi-scale structures, the specific interfacial area, the distribution of driving force, the modes of energy supply and the temporal aspects of processes. A reflection on the methods of process intensification or heat and mass transfer enhancement in multi-scale structures is provided, including porous media, heat exchangers, fluid distributors, mixers and reactors. A multi-scale approach to achieve intensification and shape optimization is developed and clearly expla...
Adjoint Based A Posteriori Analysis of Multiscale Mortar Discretizations with Multinumerics
Tavener, Simon; Wildey, Tim
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
Multiscale Lattice Boltzmann method for flow simulations in highly heterogenous porous media
Li, Jun; Brown, Donald; Calo, Victor M.; Efendiev, Yalchin R.; Illiev, Oleg
2013-01-01
.g., water and oil) are modeled using cohesive or repulsive forces, respectively. The relative permeability can be computed using pore-scale simulations and seamlessly applied for intermediate and Darcy-scale simulations. A multiscale LBM that can reduce
Jiang, Lijian; Efendiev, Yalchin; Mishev, IIya
2009-01-01
The use of limited global information in multiscale simulations is needed when there is no scale separation. Previous approaches entail fine-scale simulations in the computation of the global information. The computation of the global information
Multiscale integration of -omic, imaging, and clinical data in biomedical informatics.
Phan, John H; Quo, Chang F; Cheng, Chihwen; Wang, May Dongmei
2012-01-01
This paper reviews challenges and opportunities in multiscale data integration for biomedical informatics. Biomedical data can come from different biological origins, data acquisition technologies, and clinical applications. Integrating such data across multiple scales (e.g., molecular, cellular/tissue, and patient) can lead to more informed decisions for personalized, predictive, and preventive medicine. However, data heterogeneity, community standards in data acquisition, and computational complexity are big challenges for such decision making. This review describes genomic and proteomic (i.e., molecular), histopathological imaging (i.e., cellular/tissue), and clinical (i.e., patient) data; it includes case studies for single-scale (e.g., combining genomic or histopathological image data), multiscale (e.g., combining histopathological image and clinical data), and multiscale and multiplatform (e.g., the Human Protein Atlas and The Cancer Genome Atlas) data integration. Numerous opportunities exist in biomedical informatics research focusing on integration of multiscale and multiplatform data.
Energy Technology Data Exchange (ETDEWEB)
Dorland, William [University of Maryland
2014-11-18
The Center for Multiscale Plasma Dynamics (CMPD) was a five-year Fusion Science Center. The University of Maryland (UMD) and UCLA were the host universities. This final technical report describes the physics results from the UMD CMPD.
Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network.
Du, Xiaofeng; Qu, Xiaobo; He, Yifan; Guo, Di
2018-03-06
Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods.
A constrained approach to multiscale stochastic simulation of chemically reacting systems
Cotter, Simon L.; Zygalakis, Konstantinos C.; Kevrekidis, Ioannis G.; Erban, Radek
2011-01-01
Stochastic simulation of coupled chemical reactions is often computationally intensive, especially if a chemical system contains reactions occurring on different time scales. In this paper, we introduce a multiscale methodology suitable to address
Multi-scale graphene patterns on arbitrary substrates via laser-assisted transfer-printing process
Park, J. B.; Yoo, J.-H.; Grigoropoulos, C. P.
2012-01-01
A laser-assisted transfer-printing process is developed for multi-scale graphene patterns on arbitrary substrates using femtosecond laser scanning on a graphene/metal substrate and transfer techniques without using multi-step patterning processes
A spectral multiscale hybridizable discontinuous Galerkin method for second order elliptic problems
Efendiev, Yalchin R.
2015-08-01
We design a multiscale model reduction framework within the hybridizable discontinuous Galerkin finite element method. Our approach uses local snapshot spaces and local spectral decomposition following the concept of Generalized Multiscale Finite Element Methods. We propose several multiscale finite element spaces on the coarse edges that provide a reduced dimensional approximation for numerical traces within the HDG framework. We provide a general framework for systematic construction of multiscale trace spaces. Using local snapshots, we avoid high dimensional representation of trace spaces and use some local features of the solution space in constructing a low dimensional trace space. We investigate the solvability and numerically study the performance of the proposed method on a representative number of numerical examples.
A spectral multiscale hybridizable discontinuous Galerkin method for second order elliptic problems
Efendiev, Yalchin R.; Lazarov, Raytcho D.; Moon, Minam; Shi, Ke
2015-01-01
of multiscale trace spaces. Using local snapshots, we avoid high dimensional representation of trace spaces and use some local features of the solution space in constructing a low dimensional trace space. We investigate the solvability and numerically study
The Feasibility of Multiscale Modeling of Tunnel Fires Using FDS 6
DEFF Research Database (Denmark)
Vermesi, Izabella; Colella, Francesco; Rein, Guillermo
2014-01-01
The HVAC component of FDS 6 was used to divide a 1.2km tunnel into a 3D near fire area and a 1D area further away from the fire in order to investigate the feasibility of multiscale modeling of tunnel fires with this new feature in FDS. The two sub-models were coupled directly. The results were...... compared with reference works on multiscale modeling and the outcome is considered positive, with a deviation of less than 5% in magnitude of relevant parameters, yet with a significant reduction of the simulation runtime. As such, the multiscale method is deemed feasible for simulating tunnel fires in FDS......6. However, the simplifications that are made in this work require further investigation in order to take full advantage of the potential of this computational method. INTRODUCTION Multiscale modeling for tunnel flows and fires has previously been studied using RANS general purpose CFD software...
Multiscale aspects of the visual system and their use for scale invariant object recognition
Petkov, N; vanDeemter, J; Karsch, F; Monien, B; Satz, H
1997-01-01
Psychophysical, neuroanatomical and neurophysiological evidence for multiscale aspects of the visual system is considered. The stack model and its relation to the image pyramid are discussed. The results of a straightforward implementation on a parallel supercomputer are presented. The high
Definability and stability of multiscale decompositions for manifold-valued data
Grohs, Philipp; Wallner, Johannes
2012-01-01
are based on upscaling operators which are either interpolating or midpoint-interpolating. For definable multiscale decompositions we obtain a stability result. © 2012 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Farrell, Patricio; Pestana, Jennifer
2015-01-01
. However, the benefit of a guaranteed symmetric positive definite block system comes at a high computational cost. This cost can be alleviated somewhat by considering compactly supported RBFs and a multiscale technique. But the condition number and sparsity
Li, Dengwang; Li, Hongsheng; Wan, Honglin; Chen, Jinhu; Gong, Guanzhong; Wang, Hongjun; Wang, Liming; Yin, Yong
2012-08-01
Mutual information (MI) is a well-accepted similarity measure for image registration in medical systems. However, MI-based registration faces the challenges of high computational complexity and a high likelihood of being trapped into local optima due to an absence of spatial information. In order to solve these problems, multi-scale frameworks can be used to accelerate registration and improve robustness. Traditional Gaussian pyramid representation is one such technique but it suffers from contour diffusion at coarse levels which may lead to unsatisfactory registration results. In this work, a new multi-scale registration framework called edge preserving multiscale registration (EPMR) was proposed based upon an edge preserving total variation L1 norm (TV-L1) scale space representation. TV-L1 scale space is constructed by selecting edges and contours of images according to their size rather than the intensity values of the image features. This ensures more meaningful spatial information with an EPMR framework for MI-based registration. Furthermore, we design an optimal estimation of the TV-L1 parameter in the EPMR framework by training and minimizing the transformation offset between the registered pairs for automated registration in medical systems. We validated our EPMR method on both simulated mono- and multi-modal medical datasets with ground truth and clinical studies from a combined positron emission tomography/computed tomography (PET/CT) scanner. We compared our registration framework with other traditional registration approaches. Our experimental results demonstrated that our method outperformed other methods in terms of the accuracy and robustness for medical images. EPMR can always achieve a small offset value, which is closer to the ground truth both for mono-modality and multi-modality, and the speed can be increased 5-8% for mono-modality and 10-14% for multi-modality registration under the same condition. Furthermore, clinical application by adaptive
International Nuclear Information System (INIS)
Li Dengwang; Wan Honglin; Li Hongsheng; Chen Jinhu; Gong Guanzhong; Yin Yong; Wang Hongjun; Wang Liming
2012-01-01
Mutual information (MI) is a well-accepted similarity measure for image registration in medical systems. However, MI-based registration faces the challenges of high computational complexity and a high likelihood of being trapped into local optima due to an absence of spatial information. In order to solve these problems, multi-scale frameworks can be used to accelerate registration and improve robustness. Traditional Gaussian pyramid representation is one such technique but it suffers from contour diffusion at coarse levels which may lead to unsatisfactory registration results. In this work, a new multi-scale registration framework called edge preserving multiscale registration (EPMR) was proposed based upon an edge preserving total variation L1 norm (TV-L1) scale space representation. TV-L1 scale space is constructed by selecting edges and contours of images according to their size rather than the intensity values of the image features. This ensures more meaningful spatial information with an EPMR framework for MI-based registration. Furthermore, we design an optimal estimation of the TV-L1 parameter in the EPMR framework by training and minimizing the transformation offset between the registered pairs for automated registration in medical systems. We validated our EPMR method on both simulated mono- and multi-modal medical datasets with ground truth and clinical studies from a combined positron emission tomography/computed tomography (PET/CT) scanner. We compared our registration framework with other traditional registration approaches. Our experimental results demonstrated that our method outperformed other methods in terms of the accuracy and robustness for medical images. EPMR can always achieve a small offset value, which is closer to the ground truth both for mono-modality and multi-modality, and the speed can be increased 5–8% for mono-modality and 10–14% for multi-modality registration under the same condition. Furthermore, clinical application by
Multiscale modeling of nerve agent hydrolysis mechanisms: a tale of two Nobel Prizes
Field, Martin J.; Wymore, Troy W.
2014-10-01
The 2013 Nobel Prize in Chemistry was awarded for the development of multiscale models for complex chemical systems, whereas the 2013 Peace Prize was given to the Organisation for the Prohibition of Chemical Weapons for their efforts to eliminate chemical warfare agents. This review relates the two by introducing the field of multiscale modeling and highlighting its application to the study of the biological mechanisms by which selected chemical weapon agents exert their effects at an atomic level.
A Generalized Hybrid Multiscale Modeling Approach for Flow and Reactive Transport in Porous Media
Yang, X.; Meng, X.; Tang, Y. H.; Guo, Z.; Karniadakis, G. E.
2017-12-01
Using emerging understanding of biological and environmental processes at fundamental scales to advance predictions of the larger system behavior requires the development of multiscale approaches, and there is strong interest in coupling models at different scales together in a hybrid multiscale simulation framework. A limited number of hybrid multiscale simulation methods have been developed for subsurface applications, mostly using application-specific approaches for model coupling. The proposed generalized hybrid multiscale approach is designed with minimal intrusiveness to the at-scale simulators (pre-selected) and provides a set of lightweight C++ scripts to manage a complex multiscale workflow utilizing a concurrent coupling approach. The workflow includes at-scale simulators (using the lattice-Boltzmann method, LBM, at the pore and Darcy scale, respectively), scripts for boundary treatment (coupling and kriging), and a multiscale universal interface (MUI) for data exchange. The current study aims to apply the generalized hybrid multiscale modeling approach to couple pore- and Darcy-scale models for flow and mixing-controlled reaction with precipitation/dissolution in heterogeneous porous media. The model domain is packed heterogeneously that the mixing front geometry is more complex and not known a priori. To address those challenges, the generalized hybrid multiscale modeling approach is further developed to 1) adaptively define the locations of pore-scale subdomains, 2) provide a suite of physical boundary coupling schemes and 3) consider the dynamic change of the pore structures due to mineral precipitation/dissolution. The results are validated and evaluated by comparing with single-scale simulations in terms of velocities, reactive concentrations and computing cost.
Multiscale Space-Time Computational Methods for Fluid-Structure Interactions
2015-09-13
thermo-fluid analysis of a ground vehicle and its tires ST-SI Computational Analysis of a Vertical - Axis Wind Turbine We have successfully...of a vertical - axis wind turbine . Multiscale Compressible-Flow Computation with Particle Tracking We have successfully tested the multiscale...Tezduyar, Spenser McIntyre, Nikolay Kostov, Ryan Kolesar, Casey Habluetzel. Space–time VMS computation of wind - turbine rotor and tower aerodynamics
Multiscale Stochastic Fracture Mechanics of Composites Informed by In-situ XCT Tests
2016-02-02
interfacial fracture ) in CFRP was recently found in the fuselages of Dreamliner 787, and two types of cracks were found in the rib feet brackets...AFRL-AFOSR-UK-TR-2016-0003 Multiscale Stochastic Fracture Mechanics of Composites Informed by In-situ XCT Tests Zhenjun Yang UNIVERSITY OF MANCHESTER...Multiscale Stochastic Fracture Mechanics of Composites Informed by In-situ XCT Tests 5a. CONTRACT NUMBER EOARD 12-2100 5b. GRANT NUMBER F8655-12-1
Definability and stability of multiscale decompositions for manifold-valued data
Grohs, Philipp
2012-06-01
We discuss multiscale representations of discrete manifold-valued data. As it turns out that we cannot expect general manifold analogs of biorthogonal wavelets to possess perfect reconstruction, we focus our attention on those constructions which are based on upscaling operators which are either interpolating or midpoint-interpolating. For definable multiscale decompositions we obtain a stability result. © 2012 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Multi-Scale Models for the Scale Interaction of Organized Tropical Convection
Yang, Qiu
Assessing the upscale impact of organized tropical convection from small spatial and temporal scales is a research imperative, not only for having a better understanding of the multi-scale structures of dynamical and convective fields in the tropics, but also for eventually helping in the design of new parameterization strategies to improve the next-generation global climate models. Here self-consistent multi-scale models are derived systematically by following the multi-scale asymptotic methods and used to describe the hierarchical structures of tropical atmospheric flows. The advantages of using these multi-scale models lie in isolating the essential components of multi-scale interaction and providing assessment of the upscale impact of the small-scale fluctuations onto the large-scale mean flow through eddy flux divergences of momentum and temperature in a transparent fashion. Specifically, this thesis includes three research projects about multi-scale interaction of organized tropical convection, involving tropical flows at different scaling regimes and utilizing different multi-scale models correspondingly. Inspired by the observed variability of tropical convection on multiple temporal scales, including daily and intraseasonal time scales, the goal of the first project is to assess the intraseasonal impact of the diurnal cycle on the planetary-scale circulation such as the Hadley cell. As an extension of the first project, the goal of the second project is to assess the intraseasonal impact of the diurnal cycle over the Maritime Continent on the Madden-Julian Oscillation. In the third project, the goals are to simulate the baroclinic aspects of the ITCZ breakdown and assess its upscale impact on the planetary-scale circulation over the eastern Pacific. These simple multi-scale models should be useful to understand the scale interaction of organized tropical convection and help improve the parameterization of unresolved processes in global climate models.
Multiscale vision model for event detection and reconstruction in two-photon imaging data
DEFF Research Database (Denmark)
Brazhe, Alexey; Mathiesen, Claus; Lind, Barbara Lykke
2014-01-01
on a modified multiscale vision model, an object detection framework based on the thresholding of wavelet coefficients and hierarchical trees of significant coefficients followed by nonlinear iterative partial object reconstruction, for the analysis of two-photon calcium imaging data. The framework is discussed...... of the multiscale vision model is similar in the denoising, but provides a better segmenation of the image into meaningful objects, whereas other methods need to be combined with dedicated thresholding and segmentation utilities....
Multiscale 3D characterization with dark-field x-ray microscopy
DEFF Research Database (Denmark)
Simons, Hugh; Jakobsen, Anders Clemen; Ahl, Sonja Rosenlund
2016-01-01
Dark-field x-ray microscopy is a new way to three-dimensionally map lattice strain and orientation in crystalline matter. It is analogous to dark-field electron microscopy in that an objective lens magnifies diffracting features of the sample; however, the use of high-energy synchrotron x-rays me......, multiscale phenomena in situ is a key step toward formulating and validating multiscale models that account for the entire heterogeneity of materials....
Multiscale Multiphysics Developments for Accident Tolerant Fuel Concepts
International Nuclear Information System (INIS)
Gamble, K. A.; Hales, J. D.; Yu, J.; Zhang, Y.; Bai, X.; Andersson, D.; Patra, A.; Wen, W.; Tome, C.; Baskes, M.; Martinez, E.; Stanek, C. R.; Miao, Y.; Ye, B.; Hofman, G. L.; Yacout, A. M.; Liu, W.
2015-01-01
U 3 Si 2 and iron-chromium-aluminum (Fe-Cr-Al) alloys are two of many proposed accident-tolerant fuel concepts for the fuel and cladding, respectively. The behavior of these materials under normal operating and accident reactor conditions is not well known. As part of the Department of Energy's Accident Tolerant Fuel High Impact Problem program significant work has been conducted to investigate the U 3 Si 2 and FeCrAl behavior under reactor conditions. This report presents the multiscale and multiphysics effort completed in fiscal year 2015. The report is split into four major categories including Density Functional Theory Developments, Molecular Dynamics Developments, Mesoscale Developments, and Engineering Scale Developments. The work shown here is a compilation of a collaborative effort between Idaho National Laboratory, Los Alamos National Laboratory, Argonne National Laboratory and Anatech Corp.
Cellular potts models multiscale extensions and biological applications
Scianna, Marco
2013-01-01
A flexible, cell-level, and lattice-based technique, the cellular Potts model accurately describes the phenomenological mechanisms involved in many biological processes. Cellular Potts Models: Multiscale Extensions and Biological Applications gives an interdisciplinary, accessible treatment of these models, from the original methodologies to the latest developments. The book first explains the biophysical bases, main merits, and limitations of the cellular Potts model. It then proposes several innovative extensions, focusing on ways to integrate and interface the basic cellular Potts model at the mesoscopic scale with approaches that accurately model microscopic dynamics. These extensions are designed to create a nested and hybrid environment, where the evolution of a biological system is realistically driven by the constant interplay and flux of information between the different levels of description. Through several biological examples, the authors demonstrate a qualitative and quantitative agreement with t...
A Multi-Scale Settlement Matching Algorithm Based on ARG
Yue, Han; Zhu, Xinyan; Chen, Di; Liu, Lingjia
2016-06-01
Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG) is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.
Critical behavior of the contact process in a multiscale network
Ferreira, Silvio C.; Martins, Marcelo L.
2007-09-01
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 Barabási-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.
Detecting fine scratches on smooth surfaces with multiscale wavelet representation
International Nuclear Information System (INIS)
Yao, Li; Wan, Yan; Yao, Ming; Xu, Bugao
2012-01-01
This paper presents a set of image-processing algorithms for automatic detection of fine scratches on smooth surfaces, such as automobile paint surfaces. The scratches to be detected have random directions, inconspicuous gray levels and background noise. The multiscale wavelet transform was used to extract texture features, and a controlled edge fusion model was employed to merge the detailed (horizontal, vertical and diagonal) wavelet coefficient maps. Based on the fused detail map, multivariate statistics were applied to synthesize features in multiple scales and directions, and an optimal threshold was set to separate scratches from the background. The experimental results of 24 automobile paint surface showed that the presented algorithms can effectively suppress background noise and detect scratches accurately. (paper)
Gaussian Multiscale Aggregation Applied to Segmentation in Hand Biometrics
Directory of Open Access Journals (Sweden)
Gonzalo Bailador del Pozo
2011-11-01
Full Text Available This paper presents an image segmentation algorithm based on Gaussian multiscale aggregation oriented to hand biometric applications. The method is able to isolate the hand from a wide variety of background textures such as carpets, fabric, glass, grass, soil or stones. The evaluation was carried out by using a publicly available synthetic database with 408,000 hand images in different backgrounds, comparing the performance in terms of accuracy and computational cost to two competitive segmentation methods existing in literature, namely Lossy Data Compression (LDC and Normalized Cuts (NCuts. The results highlight that the proposed method outperforms current competitive segmentation methods with regard to computational cost, time performance, accuracy and memory usage.
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.
Generalized multiscale finite element methods. nonlinear elliptic equations
Efendiev, Yalchin R.; Galvis, Juan; Li, Guanglian; Presho, Michael
2013-01-01
In this paper we use the Generalized Multiscale Finite Element Method (GMsFEM) framework, introduced in [26], in order to solve nonlinear elliptic equations with high-contrast coefficients. The proposed solution method involves linearizing the equation so that coarse-grid quantities of previous solution iterates can be regarded as auxiliary parameters within the problem formulation. With this convention, we systematically construct respective coarse solution spaces that lend themselves to either continuous Galerkin (CG) or discontinuous Galerkin (DG) global formulations. Here, we use Symmetric Interior Penalty Discontinuous Galerkin approach. Both methods yield a predictable error decline that depends on the respective coarse space dimension, and we illustrate the effectiveness of the CG and DG formulations by offering a variety of numerical examples. © 2014 Global-Science Press.
An augmented Lagrangian multi-scale dictionary learning algorithm
Directory of Open Access Journals (Sweden)
Ye Meng
2011-01-01
Full Text Available Abstract Learning overcomplete dictionaries for sparse signal representation has become a hot topic fascinated by many researchers in the recent years, while most of the existing approaches have a serious problem that they always lead to local minima. In this article, we present a novel augmented Lagrangian multi-scale dictionary learning algorithm (ALM-DL, which is achieved by first recasting the constrained dictionary learning problem into an AL scheme, and then updating the dictionary after each inner iteration of the scheme during which majorization-minimization technique is employed for solving the inner subproblem. Refining the dictionary from low scale to high makes the proposed method less dependent on the initial dictionary hence avoiding local optima. Numerical tests for synthetic data and denoising applications on real images demonstrate the superior performance of the proposed approach.
Multi-scale Dynamical Processes in Space and Astrophysical Plasmas
Vörös, Zoltán; IAFA 2011 - International Astrophysics Forum 2011 : Frontiers in Space Environment Research
2012-01-01
Magnetized plasmas in the universe exhibit complex dynamical behavior over a huge range of scales. The fundamental mechanisms of energy transport, redistribution and conversion occur at multiple scales. The driving mechanisms often include energy accumulation, free-energy-excited relaxation processes, dissipation and self-organization. The plasma processes associated with energy conversion, transport and self-organization, such as magnetic reconnection, instabilities, linear and nonlinear waves, wave-particle interactions, dynamo processes, turbulence, heating, diffusion and convection represent fundamental physical effects. They demonstrate similar dynamical behavior in near-Earth space, on the Sun, in the heliosphere and in astrophysical environments. 'Multi-scale Dynamical Processes in Space and Astrophysical Plasmas' presents the proceedings of the International Astrophysics Forum Alpbach 2011. The contributions discuss the latest advances in the exploration of dynamical behavior in space plasmas environm...
Multiscale deep features learning for land-use scene recognition
Yuan, Baohua; Li, Shijin; Li, Ning
2018-01-01
The features extracted from deep convolutional neural networks (CNNs) have shown their promise as generic descriptors for land-use scene recognition. However, most of the work directly adopts the deep features for the classification of remote sensing images, and does not encode the deep features for improving their discriminative power, which can affect the performance of deep feature representations. To address this issue, we propose an effective framework, LASC-CNN, obtained by locality-constrained affine subspace coding (LASC) pooling of a CNN filter bank. LASC-CNN obtains more discriminative deep features than directly extracted from CNNs. Furthermore, LASC-CNN builds on the top convolutional layers of CNNs, which can incorporate multiscale information and regions of arbitrary resolution and sizes. Our experiments have been conducted using two widely used remote sensing image databases, and the results show that the proposed method significantly improves the performance when compared to other state-of-the-art methods.
Multiscale modelling of hydrogen behaviour on beryllium (0001 surface
Directory of Open Access Journals (Sweden)
Ch. Stihl
2016-12-01
Full Text Available Beryllium is proposed to be a neutron multiplier and plasma facing material in future fusion devices. Therefore, it is crucial to acquire an understanding of the microscopic mechanisms of tritium accumulation and release as a result of transmutation processes that Be undergoes under neutron irradiation. A multiscale simulation of ad- and desorption of hydrogen isotopes on the beryllium (0001 surface is developed. It consists of ab initio calculations of certain H adsorption configurations, a suitable cluster expansion approximating the energies of arbitrary configurations, and a kinetic Monte Carlo method for dynamic simulations of adsorption and desorption. The processes implemented in the kinetic Monte Carlo simulation are deduced from further ab initio calculations comprising both, static relaxation as well as molecular dynamics runs. The simulation is used to reproduce experimental data and the results are compared and discussed. Based on the observed results, proposals for a refined model are made.
Model-to-model interface for multiscale materials modeling
Energy Technology Data Exchange (ETDEWEB)
Antonelli, Perry Edward [Iowa State Univ., Ames, IA (United States)
2017-12-17
A low-level model-to-model interface is presented that will enable independent models to be linked into an integrated system of models. The interface is based on a standard set of functions that contain appropriate export and import schemas that enable models to be linked with no changes to the models themselves. These ideas are presented in the context of a specific multiscale material problem that couples atomistic-based molecular dynamics calculations to continuum calculations of fluid ow. These simulations will be used to examine the influence of interactions of the fluid with an adjacent solid on the fluid ow. The interface will also be examined by adding it to an already existing modeling code, Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and comparing it with our own molecular dynamics code.
All-Particle Multiscale Computation of Hypersonic Rarefied Flow
Jun, E.; Burt, J. M.; Boyd, I. D.
2011-05-01
This study examines a new hybrid particle scheme used as an alternative means of multiscale flow simulation. The hybrid particle scheme employs the direct simulation Monte Carlo (DSMC) method in rarefied flow regions and the low diffusion (LD) particle method in continuum flow regions. The numerical procedures of the low diffusion particle method are implemented within an existing DSMC algorithm. The performance of the LD-DSMC approach is assessed by studying Mach 10 nitrogen flow over a sphere with a global Knudsen number of 0.002. The hybrid scheme results show good overall agreement with results from standard DSMC and CFD computation. Subcell procedures are utilized to improve computational efficiency and reduce sensitivity to DSMC cell size in the hybrid scheme. This makes it possible to perform the LD-DSMC simulation on a much coarser mesh that leads to a significant reduction in computation time.
HAM-Based Adaptive Multiscale Meshless Method for Burgers Equation
Directory of Open Access Journals (Sweden)
Shu-Li Mei
2013-01-01
Full Text Available Based on the multilevel interpolation theory, we constructed a meshless adaptive multiscale interpolation operator (MAMIO with the radial basis function. Using this operator, any nonlinear partial differential equations such as Burgers equation can be discretized adaptively in physical spaces as a nonlinear matrix ordinary differential equation. In order to obtain the analytical solution of the system of ODEs, the homotopy analysis method (HAM proposed by Shijun Liao was developed to solve the system of ODEs by combining the precise integration method (PIM which can be employed to get the analytical solution of linear system of ODEs. The numerical experiences show that HAM is not sensitive to the time step, and so the arithmetic error is mainly derived from the discrete in physical space.
Multiscale Computation. Needs and Opportunities for BER Science
Energy Technology Data Exchange (ETDEWEB)
Scheibe, Timothy D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Smith, Jeremy C. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2015-01-01
The Environmental Molecular Sciences Laboratory (EMSL), a scientific user facility managed by Pacific Northwest National Laboratory for the U.S. Department of Energy, Office of Biological and Environmental Research (BER), conducted a one-day workshop on August 26, 2014 on the topic of “Multiscale Computation: Needs and Opportunities for BER Science.” Twenty invited participants, from various computational disciplines within the BER program research areas, were charged with the following objectives; Identify BER-relevant models and their potential cross-scale linkages that could be exploited to better connect molecular-scale research to BER research at larger scales and; Identify critical science directions that will motivate EMSL decisions regarding future computational (hardware and software) architectures.
Multi-scale evaluations of submarine groundwater discharge
Directory of Open Access Journals (Sweden)
M. Taniguchi
2015-03-01
Full Text Available Multi-scale evaluations of submarine groundwater discharge (SGD have been made in Saijo, Ehime Prefecture, Shikoku Island, Japan, by using seepage meters for point scale, 222Rn tracer for point and coastal scales, and a numerical groundwater model (SEAWAT for coastal and basin scales. Daily basis temporal changes in SGD are evaluated by continuous seepage meter and 222Rn mooring measurements, and depend on sea level changes. Spatial evaluations of SGD were also made by 222Rn along the coast in July 2010 and November 2011. The area with larger 222Rn concentration during both seasons agreed well with the area with larger SGD calculated by 3D groundwater numerical simulations.
A Multi-Scale Settlement Matching Algorithm Based on ARG
Directory of Open Access Journals (Sweden)
H. Yue
2016-06-01
Full Text Available Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.
Pricing perpetual American options under multiscale stochastic elasticity of variance
International Nuclear Information System (INIS)
Yoon, Ji-Hun
2015-01-01
Highlights: • We study the effects of the stochastic elasticity of variance on perpetual American option. • Our SEV model consists of a fast mean-reverting factor and a slow mean-revering factor. • A slow scale factor has a very significant impact on the option price. • We analyze option price structures through the market prices of elasticity risk. - Abstract: This paper studies pricing the perpetual American options under a constant elasticity of variance type of underlying asset price model where the constant elasticity is replaced by a fast mean-reverting Ornstein–Ulenbeck process and a slowly varying diffusion process. By using a multiscale asymptotic analysis, we find the impact of the stochastic elasticity of variance on the option prices and the optimal exercise prices with respect to model parameters. Our results enhance the existing option price structures in view of flexibility and applicability through the market prices of elasticity risk
Stochastic scalar mixing models accounting for turbulent frequency multiscale fluctuations
International Nuclear Information System (INIS)
Soulard, Olivier; Sabel'nikov, Vladimir; Gorokhovski, Michael
2004-01-01
Two new scalar micromixing models accounting for a turbulent frequency scale distribution are investigated. These models were derived by Sabel'nikov and Gorokhovski [Second International Symposium on Turbulence and Shear FLow Phenomena, Royal Institute of technology (KTH), Stockholm, Sweden, June 27-29, 2001] using a multiscale extension of the classical interaction by exchange with the mean (IEM) and Langevin models. They are, respectively, called Extended IEM (EIEM) and Extended Langevin (ELM) models. The EIEM and ELM models are tested against DNS results in the case of the decay of a homogeneous scalar field in homogeneous turbulence. This comparison leads to a reformulation of the law governing the mixing frequency distribution. Finally, the asymptotic behaviour of the modeled PDF is discussed
Energy Technology Data Exchange (ETDEWEB)
Thelin, Gunnar (EkoBalans Fenix AB, Malmoe (Sweden))
2009-03-15
Sewage sludge and wood ashes could be used as fertilizers in order to increase forest tree production. In southern Sweden forest growth normally increases with approximately 10 % after ash recycling due to increased N and/or P availability. P is added with the ashes and the pH-increasing effect of the wood ash can lead to increased N net mineralization. Other positive effects of wood ash recycling are improved nutrient sustainability and less acid run-off water. Possible negative effects are heavy metal accumulation, if the content of one or more heavy metals of the recycled ash exceeds the heavy metal content of the harvested biomass, and nitrate leaching if the vegetation cannot take up nitrified N. It is important to evaluate the sustainability of fertilization systems based on residues such as sludge and wood ash. Wood ash does not contain N and the P concentration often is too low for the ashes to function as an NP fertilizer. Thus N and sometimes P must be added. Sludge is an interesting alternative. The main purpose of the project is to study sustainable production of forest bio energy in intensively cultivated birch and hybrid aspen stands. Another purpose is to establish experiments that can be used for long term studies and as demonstration objects. In the first few years the goal is to study the short term effects of residue based fertilization compared to conventional NPK fertilization on tree nutrient uptake, nutrient leaching, sustainability and economy. In the long term the goal is to design appropriate fertilization strategies in a residue based fertilization system for the intensive cultivation of birch and hybrid aspen without negative side effects such as large scale nutrient leaching. Four field experiments were established in 2008 and one additional experiment in hybrid aspen will be established in the spring of 2009. Elevated bud N and P concentrations after fertilization with both Ashes+N and NPK means good possibilities for future growth
Bai, Ling; Chen, Zhongsheng; Xu, Jianhua; Li, Weihong
2016-08-01
Based on the hydrological and meteorological data in the headwater region of the Kaidu River during 1960-2009, the multi-scale characteristics of runoff variability were analyzed using the ensemble empirical mode decomposition method (EEMD), and the aim is to investigate the oscillation mode structure characteristics of runoff change and its response to climate fluctuation at different time scales. Results indicated that in the past 50 years, the overall runoff of Kaidu River in Xinjiang has showed a significant nonlinear upward trend, and its changes have obviously exhibited an inter-annual scale (quasi-3 and quasi-6-year) and inter-decadal scale (quasi-10 and quasi-25-year). Variance contribution rates of each component manifested that the inter-decadal change had been playing a more important role in the overall runoff change for Kaidu River, and the reconstructed inter-annual variation trend could describe the fluctuation state of the original runoff anomaly during the study period. The reconstructed inter-decadal variability effectively revealed that the runoff for Kaidu River changed over the years, namely the states of abundance and low water period appear alternately. In addition, we found that runoff has a positive correlation to precipitation and temperature at different time scales, but they are most significant and relevant at inter-decadal scale, indicating the inter-decadal scale is most suitable for investigating the responses of runoff dynamics to climate fluctuation. At the same time, the results also suggested that EEMD is an effective method to analyze the multi-scale characteristics of nonlinear and non-stationary signal.
Multiscale experimental mechanics of hierarchical carbon-based materials.
Espinosa, Horacio D; Filleter, Tobin; Naraghi, Mohammad
2012-06-05
Investigation of the mechanics of natural materials, such as spider silk, abalone shells, and bone, has provided great insight into the design of materials that can simultaneously achieve high specific strength and toughness. Research has shown that their emergent mechanical properties are owed in part to their specific self-organization in hierarchical molecular structures, from nanoscale to macroscale, as well as their mixing and bonding. To apply these findings to manmade materials, researchers have devoted significant efforts in developing a fundamental understanding of multiscale mechanics of materials and its application to the design of novel materials with superior mechanical performance. These efforts included the utilization of some of the most promising carbon-based nanomaterials, such as carbon nanotubes, carbon nanofibers, and graphene, together with a variety of matrix materials. At the core of these efforts lies the need to characterize material mechanical behavior across multiple length scales starting from nanoscale characterization of constituents and their interactions to emerging micro- and macroscale properties. In this report, progress made in experimental tools and methods currently used for material characterization across multiple length scales is reviewed, as well as a discussion of how they have impacted our current understanding of the mechanics of hierarchical carbon-based materials. In addition, insight is provided into strategies for bridging experiments across length scales, which are essential in establishing a multiscale characterization approach. While the focus of this progress report is in experimental methods, their concerted use with theoretical-computational approaches towards the establishment of a robust material by design methodology is also discussed, which can pave the way for the development of novel materials possessing unprecedented mechanical properties. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Multiscale estimation of excess mass from gravity data
Castaldo, Raffaele; Fedi, Maurizio; Florio, Giovanni
2014-06-01
We describe a multiscale method to estimate the excess mass of gravity anomaly sources, based on the theory of source moments. Using a multipole expansion of the potential field and considering only the data along the vertical direction, a system of linear equations is obtained. The choice of inverting data along a vertical profile can help us to reduce the interference effects due to nearby anomalies and will allow a local estimate of the source parameters. A criterion is established allowing the selection of the optimal highest altitude of the vertical profile data and truncation order of the series expansion. The inversion provides an estimate of the total anomalous mass and of the depth to the centre of mass. The method has several advantages with respect to classical methods, such as the Gauss' method: (i) we need just a 1-D inversion to obtain our estimates, being the inverted data sampled along a single vertical profile; (ii) the resolution may be straightforward enhanced by using vertical derivatives; (iii) the centre of mass is also estimated, besides the excess mass; (iv) the method is very robust versus noise; (v) the profile may be chosen in such a way to minimize the effects from interfering anomalies or from side effects due to the a limited area extension. The multiscale estimation of excess mass method can be successfully used in various fields of application. Here, we analyse the gravity anomaly generated by a sulphide body in the Skelleftea ore district, North Sweden, obtaining source mass and volume estimates in agreement with the known information. We show also that these estimates are substantially improved with respect to those obtained with the classical approach.
Multiscale modeling of alloy solidification using a database approach
Tan, Lijian; Zabaras, Nicholas
2007-11-01
sample problems. The efficiency of the proposed multiscale framework is demonstrated with numerical examples that consider a large number of crystals. A computationally intensive fully-resolved microscale analysis is also performed to evaluate the accuracy of the multiscale framework.
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.
What is at stake in multi-scale approaches
International Nuclear Information System (INIS)
Jamet, Didier
2008-01-01
Full text of publication follows: Multi-scale approaches amount to analyzing physical phenomena at small space and time scales in order to model their effects at larger scales. This approach is very general in physics and engineering; one of the best examples of success of this approach is certainly statistical physics that allows to recover classical thermodynamics and to determine the limits of application of classical thermodynamics. Getting access to small scale information aims at reducing the models' uncertainty but it has a cost: fine scale models may be more complex than larger scale models and their resolution may require the development of specific and possibly expensive methods, numerical simulation techniques and experiments. For instance, in applications related to nuclear engineering, the application of computational fluid dynamics instead of cruder models is a formidable engineering challenge because it requires resorting to high performance computing. Likewise, in two-phase flow modeling, the techniques of direct numerical simulation, where all the interfaces are tracked individually and where all turbulence scales are captured, are getting mature enough to be considered for averaged modeling purposes. However, resolving small scale problems is a necessary step but it is not sufficient in a multi-scale approach. An important modeling challenge is to determine how to treat small scale data in order to get relevant information for larger scale models. For some applications, such as single-phase turbulence or transfers in porous media, this up-scaling approach is known and is now used rather routinely. However, in two-phase flow modeling, the up-scaling approach is not as mature and specific issues must be addressed that raise fundamental questions. This will be discussed and illustrated. (author)
Toward a global multi-scale heliophysics observatory
Semeter, J. L.
2017-12-01
We live within the only known stellar-planetary system that supports life. What we learn about this system is not only relevant to human society and its expanding reach beyond Earth's surface, but also to our understanding of the origins and evolution of life in the universe. Heliophysics is focused on solar-terrestrial interactions mediated by the magnetic and plasma environment surrounding the planet. A defining feature of energy flow through this environment is interaction across physical scales. A solar disturbance aimed at Earth can excite geospace variability on scales ranging from thousands of kilometers (e.g., global convection, region 1 and 2 currents, electrojet intensifications) to 10's of meters (e.g., equatorial spread-F, dispersive Alfven waves, plasma instabilities). Most "geospace observatory" concepts are focused on a single modality (e.g., HF/UHF radar, magnetometer, optical) providing a limited parameter set over a particular spatiotemporal resolution. Data assimilation methods have been developed to couple heterogeneous and distributed observations, but resolution has typically been prescribed a-priori and according to physical assumptions. This paper develops a conceptual framework for the next generation multi-scale heliophysics observatory, capable of revealing and quantifying the complete spectrum of cross-scale interactions occurring globally within the geospace system. The envisioned concept leverages existing assets, enlists citizen scientists, and exploits low-cost access to the geospace environment. Examples are presented where distributed multi-scale observations have resulted in substantial new insight into the inner workings of our stellar-planetary system.
ANALYSIS/MODEL COVER SHEET, MULTISCALE THERMOHYDROLOGIC MODEL
International Nuclear Information System (INIS)
Buscheck, T.A.
2001-01-01
The purpose of the Multiscale Thermohydrologic Model (MSTHM) is to describe the thermohydrologic evolution of the near-field environment (NFE) and engineered barrier system (EBS) throughout the potential high-level nuclear waste repository at Yucca Mountain for a particular engineering design (CRWMS M andO 2000c). The process-level model will provide thermohydrologic (TH) information and data (such as in-drift temperature, relative humidity, liquid saturation, etc.) for use in other technical products. This data is provided throughout the entire repository area as a function of time. The MSTHM couples the Smeared-heat-source Drift-scale Thermal-conduction (SDT), Line-average-heat-source Drift-scale Thermohydrologic (LDTH), Discrete-heat-source Drift-scale Thermal-conduction (DDT), and Smeared-heat-source Mountain-scale Thermal-conduction (SMT) submodels such that the flow of water and water vapor through partially-saturated fractured rock is considered. The MSTHM accounts for 3-D drift-scale and mountain-scale heat flow, repository-scale variability of stratigraphy and infiltration flux, and waste package (WP)-to-WP variability in heat output from WPs. All submodels use the nonisothermal unsaturated-saturated flow and transport (NUFT) simulation code. The MSTHM is implemented in several data-processing steps. The four major steps are: (1) submodel input-file preparation, (2) execution of the four submodel families with the use of the NUFT code, (3) execution of the multiscale thermohydrologic abstraction code (MSTHAC), and (4) binning and post-processing (i.e., graphics preparation) of the output from MSTHAC. Section 6 describes the MSTHM in detail. The objectives of this Analyses and Model Report (AMR) are to investigate near field (NF) and EBS thermohydrologic environments throughout the repository area at various evolution periods, and to provide TH data that may be used in other process model reports
Multiscale impact of fuel consumption on air quality
Energy Technology Data Exchange (ETDEWEB)
Hidy, G.M. [Envair/Aerochem, Placitas, NM (USA)
2002-04-01
Energy production from combustion of fossil fuels tends to dominate the emissions of criteria pollutants. Emissions derive both from large stationary sources with tall stacks such as fossil-fuelled power plants, and from the ground level use of fuels in transportation. Management of these sources presents a challenge in the light of multi-scale processes that influence ambient concentration and exposure patterns. Directly emitted pollutants and those resulting from atmospheric chemistry, like O{sub 3} and sulfate, nitrate and some organic material in fine particles, are affected by phenomena extending over a range of less than a meter to 10{sup 7} meters in spatial scale, and minutes to many years in temporal scale. Their environmental effects have an analogous wide range of descriptive spatial and temporal scale. Pollution phenomena can be thought of in terms of three major groupings: neighbourhood - urban, regional, and continental - global. Currently, decision-makers are developing emission reduction strategies that conceptually integrate considerations over this entire range of scales. In keeping with conceptual integration, recent studies and analyses are bridging different spatial and temporal scales in observations and in mathematical descriptions. Some examples of contemporary issues falling within different scales are described that illustrate approaches to add insight for developing regulatory strategies. A key element in the technical approaches is the application of air quality and exposure modeling using spatially nested descriptions of atmospheric phenomena. The reliability of multi-scale models remains a concern so that analyses for US regulatory applications combine the results of modeling with observations, and knowledge of spatially and temporally differentiated emissions. 32 refs., 3 tabs.
Fast Multiscale Reservoir Simulations using POD-DEIM Model Reduction
Ghasemi, Mohammadreza
2015-02-23
In this paper, we present a global-local model reduction for fast multiscale reservoir simulations in highly heterogeneous porous media with applications to optimization and history matching. Our proposed approach identifies a low dimensional structure of the solution space. We introduce an auxiliary variable (the velocity field) in our model reduction that allows achieving a high degree of model reduction. The latter is due to the fact that the velocity field is conservative for any low-order reduced model in our framework. Because a typical global model reduction based on POD is a Galerkin finite element method, and thus it can not guarantee local mass conservation. This can be observed in numerical simulations that use finite volume based approaches. Discrete Empirical Interpolation Method (DEIM) is used to approximate the nonlinear functions of fine-grid functions in Newton iterations. This approach allows achieving the computational cost that is independent of the fine grid dimension. POD snapshots are inexpensively computed using local model reduction techniques based on Generalized Multiscale Finite Element Method (GMsFEM) which provides (1) a hierarchical approximation of snapshot vectors (2) adaptive computations by using coarse grids (3) inexpensive global POD operations in a small dimensional spaces on a coarse grid. By balancing the errors of the global and local reduced-order models, our new methodology can provide an error bound in simulations. Our numerical results, utilizing a two-phase immiscible flow, show a substantial speed-up and we compare our results to the standard POD-DEIM in finite volume setup.
Hybrid numerical methods for multiscale simulations of subsurface biogeochemical processes
International Nuclear Information System (INIS)
Scheibe, T D; Tartakovsky, A M; Tartakovsky, D M; Redden, G D; Meakin, P
2007-01-01
Many subsurface flow and transport problems of importance today involve coupled non-linear flow, transport, and reaction in media exhibiting complex heterogeneity. In particular, problems involving biological mediation of reactions fall into this class of problems. Recent experimental research has revealed important details about the physical, chemical, and biological mechanisms involved in these processes at a variety of scales ranging from molecular to laboratory scales. However, it has not been practical or possible to translate detailed knowledge at small scales into reliable predictions of field-scale phenomena important for environmental management applications. A large assortment of numerical simulation tools have been developed, each with its own characteristic scale. Important examples include 1. molecular simulations (e.g., molecular dynamics); 2. simulation of microbial processes at the cell level (e.g., cellular automata or particle individual-based models); 3. pore-scale simulations (e.g., lattice-Boltzmann, pore network models, and discrete particle methods such as smoothed particle hydrodynamics); and 4. macroscopic continuum-scale simulations (e.g., traditional partial differential equations solved by finite difference or finite element methods). While many problems can be effectively addressed by one of these models at a single scale, some problems may require explicit integration of models across multiple scales. We are developing a hybrid multi-scale subsurface reactive transport modeling framework that integrates models with diverse representations of physics, chemistry and biology at different scales (sub-pore, pore and continuum). The modeling framework is being designed to take advantage of advanced computational technologies including parallel code components using the Common Component Architecture, parallel solvers, gridding, data and workflow management, and visualization. This paper describes the specific methods/codes being used at each
Yin, Yi; Shang, Pengjian
2013-12-01
We use multiscale detrended fluctuation analysis (MSDFA) and multiscale detrended cross-correlation analysis (MSDCCA) to investigate auto-correlation (AC) and cross-correlation (CC) in the US and Chinese stock markets during 1997-2012. The results show that US and Chinese stock indices differ in terms of their multiscale AC structures. Stock indices in the same region also differ with regard to their multiscale AC structures. We analyze AC and CC behaviors among indices for the same region to determine similarity among six stock indices and divide them into four groups accordingly. We choose S&P500, NQCI, HSI, and the Shanghai Composite Index as representative samples for simplicity. MSDFA and MSDCCA results and average MSDFA spectra for local scaling exponents (LSEs) for individual series are presented. We find that the MSDCCA spectrum for LSE CC between two time series generally tends to be greater than the average MSDFA LSE spectrum for individual series. We obtain detailed multiscale structures and relations for CC between the four representatives. MSDFA and MSDCCA with secant rolling windows of different sizes are then applied to reanalyze the AC and CC. Vertical and horizontal comparisons of different window sizes are made. The MSDFA and MSDCCA results for the original window size are confirmed and some new interesting characteristics and conclusions regarding multiscale correlation structures are obtained.
Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J
2014-01-01
The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. © 2014 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc.
Physics-based hybrid method for multiscale transport in porous media
Yousefzadeh, Mehrdad; Battiato, Ilenia
2017-09-01
Despite advancements in the development of multiscale models for flow and reactive transport in porous media, the accurate, efficient and physics-based coupling of multiple scales in hybrid models remains a major theoretical and computational challenge. Improving the predictivity of macroscale predictions by means of multiscale algorithms relative to classical at-scale models is the primary motivation for the development of multiscale simulators. Yet, very few are the quantitative studies that explicitly address the predictive capability of multiscale coupling algorithms as it is still generally not possible to have a priori estimates of the errors that are present when complex flow processes are modeled. We develop a nonintrusive pore-/continuum-scale hybrid model whose coupling error is bounded by the upscaling error, i.e. we build a predictive tightly coupled multiscale scheme. This is accomplished by slightly enlarging the subdomain where continuum-scale equations are locally invalid and analytically defining physics-based coupling conditions at the interfaces separating the two computational sub-domains, while enforcing state variable and flux continuity. The proposed multiscale coupling approach retains the advantages of domain decomposition approaches, including the use of existing solvers for each subdomain, while it gains flexibility in the choice of the numerical discretization method and maintains the coupling errors bounded by the upscaling error. We implement the coupling in finite volumes and test the proposed method by modeling flow and transport through a reactive channel and past an array of heterogeneously reactive cylinders.
Zhang, Xueliang; Xiao, Pengfeng; Feng, Xuezhi
2017-09-01
It has been a common idea to produce multiscale segmentations to represent the various geographic objects in high-spatial resolution remote sensing (HR) images. However, it remains a great challenge to automatically select the proper segmentation scale(s) just according to the image information. In this study, we propose a novel way of information fusion at object level by combining hierarchical multiscale segmentations with existed thematic information produced by classification or recognition. The tree Markov random field (T-MRF) model is designed for the multiscale combination framework, through which the object type is determined as close as the existed thematic information. At the same time, the object boundary is jointly determined by the thematic labels and the multiscale segments through the minimization of the energy function. The benefits of the proposed T-MRF combination model include: (1) reducing the dependence of segmentation scale selection when utilizing multiscale segmentations; (2) exploring the hierarchical context naturally imbedded in the multiscale segmentations. The HR images in both urban and rural areas are used in the experiments to show the effectiveness of the proposed combination framework on these two aspects.
DEFF Research Database (Denmark)
Zhukovsky, Sergei; Lavrinenko, Andrei; Sipe, J. E.
2013-01-01
, wavelength scale, the propagation of bulk plasmon polaritons in the resulting multiscale HMM is subject to photonic band gap phenomena. A great degree of control over such plasmons can be exerted by varying the superstructure geometry. As an example, Bragg reflection and Fabry-Pérot resonances...... are demonstrated in multiscale HMMs with periodic superstructures. More complicated, aperiodically ordered superstructures are also considered, with fractal Cantor-like multiscale HMMs exhibiting characteristic self-similar spectral signatures in the high-k band. The multiscale HMM concept is shown...
Patterns and multi-scale drivers of phytoplankton species richness in temperate peri-urban lakes
Energy Technology Data Exchange (ETDEWEB)
Catherine, Arnaud, E-mail: arnocat@mnhn.fr [UMR7245 MCAM MNHN-CNRS, Muséum National d' Histoire Naturelle, CC 39, 12 rue Buffon, F-75231 Paris, Cedex 05 (France); Selma, Maloufi, E-mail: maloufi@mnhn.fr [UMR7245 MCAM MNHN-CNRS, Muséum National d' Histoire Naturelle, CC 39, 12 rue Buffon, F-75231 Paris, Cedex 05 (France); Mouillot, David, E-mail: david.mouillot@univ-montp2.fr [UMR 9190 MARBEC UM2-CNRS-IRD-UM1-IFREMER, CC 93, Place Eugène Bataillon, Université de Montpellier 2, F-34095 Montpellier (France); Troussellier, Marc, E-mail: troussel@univ-montp2.fr [UMR 9190 MARBEC UM2-CNRS-IRD-UM1-IFREMER, CC 93, Place Eugène Bataillon, Université de Montpellier 2, F-34095 Montpellier (France); Bernard, Cécile, E-mail: cbernard@mnhn.fr [UMR7245 MCAM MNHN-CNRS, Muséum National d' Histoire Naturelle, CC 39, 12 rue Buffon, F-75231 Paris, Cedex 05 (France)
2016-07-15
species richness in temperate lakes. This approach may prove useful and cost-effective for the management and conservation of aquatic ecosystems. - Highlights: • We studied phytoplankton communities in 50 peri-urban lakes. • We assessed the impact of multi-scale drivers of phytoplankton richness. • Local- and catchment-scale predictive models performed similarly. • Seasonal temperature variation and resource availability strongly modulate species richness. • This approach may be used for the management and conservation of aquatic ecosystems.
Patterns and multi-scale drivers of phytoplankton species richness in temperate peri-urban lakes
International Nuclear Information System (INIS)
Catherine, Arnaud; Selma, Maloufi; Mouillot, David; Troussellier, Marc; Bernard, Cécile
2016-01-01
species richness in temperate lakes. This approach may prove useful and cost-effective for the management and conservation of aquatic ecosystems. - Highlights: • We studied phytoplankton communities in 50 peri-urban lakes. • We assessed the impact of multi-scale drivers of phytoplankton richness. • Local- and catchment-scale predictive models performed similarly. • Seasonal temperature variation and resource availability strongly modulate species richness. • This approach may be used for the management and conservation of aquatic ecosystems.
Niu, Meng; Zhang, Binjia; Jia, Caihua; Zhao, Siming
2017-11-01
The multi-scale structures and pasting properties of starch in WWF were investigated after superfine grinding. Five particle size distributions of WWF and their corresponding starch were obtained. The grinding process reduced the particle size of WWF and starch. However, a slight increase of fragments from starch granules was observed with enhanced grinding strength because of the small decrease in starch particle size and the existence of other WWF components that undertook some of shearing force and friction during grinding. A prominent reduction in starch crystallinity was resulted due to the destruction of crystalline structure by grinding. Small-angle X-ray scattering analyses indicated the disordering in starch semi-crystalline lamellae with thinner lamellae thickness. Additionally, the 13 C Nuclear Magnetic Resonance spectra demonstrated the alterations in starch chain conformation by varying peak areas of starch carbons (C1 and C4). Along with these structural changes, Starch pasting characteristics showed substantial variations, indicating decreased viscosities and higher pasting stability. The results suggest that the grinding treatments influenced the structures and pasting properties of starch even at a non-separated state, the changes in starch structures were related to the variations in starch gelatinization characteristics. Copyright © 2017 Elsevier B.V. All rights reserved.
Multiscale Analysis of Nanocomposites and Their Use in Structural Level Applications
Hasan, Zeaid
This research focuses on the benefits of using nanocomposites in aerospace structural components to prevent or delay the onset of unique composite failure modes, such as delamination. Analytical, numerical, and experimental analyses were conducted to provide a comprehensive understanding of how carbon nanotubes (CNTs) can provide additional structural integrity when they are used in specific hot spots within a structure. A multiscale approach was implemented to determine the mechanical and thermal properties of the nanocomposites, which were used in detailed finite element models (FEMs) to analyze interlaminar failures in T and Hat section stringers. The delamination that first occurs between the tow filler and the bondline between the stringer and skin was of particular interest. Both locations are considered to be hot spots in such structural components, and failures tend to initiate from these areas. In this research, nanocomposite use was investigated as an alternative to traditional methods of suppressing delamination. The stringer was analyzed under different loading conditions and assuming different structural defects. Initial damage, defined as the first drop in the load displacement curve was considered to be a useful variable to compare the different behaviors in this study and was detected via the virtual crack closure technique (VCCT) implemented in the FE analysis. Experiments were conducted to test T section skin/stringer specimens under pull-off loading, replicating those used in composite panels as stiffeners. Two types of designs were considered: one using pure epoxy to fill the tow region and another that used nanocomposite with 5 wt. % CNTs. The response variable in the tests was the initial damage. Detailed analyses were conducted using FEMs to correlate with the experimental data. The correlation between both the experiment and model was satisfactory. Finally, the effects of thermal cure and temperature variation on nanocomposite structure
Multi-scale Gaussian representation and outline-learning based cell image segmentation
2013-01-01
Background High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. Methods We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. Results and conclusions We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks. PMID:24267488
Multiscale mapping of species diversity under changed land use using imaging spectroscopy.
Paz-Kagan, Tarin; Caras, Tamir; Herrmann, Ittai; Shachak, Moshe; Karnieli, Arnon
2017-07-01
Land use changes are one of the most important factors causing environmental transformations and species diversity alterations. The aim of the current study was to develop a geoinformatics-based framework to quantify alpha and beta diversity indices in two sites in Israel with different land uses, i.e., an agricultural system of fruit orchards, an afforestation system of planted groves, and an unmanaged system of groves. The framework comprises four scaling steps: (1) classification of a tree species distribution (SD) map using imaging spectroscopy (IS) at a pixel size of 1 m; (2) estimation of local species richness by calculating the alpha diversity index for 30-m grid cells; (3) calculation of beta diversity for different land use categories and sub-categories at different sizes; and (4) calculation of the beta diversity difference between the two sites. The SD was classified based on a hyperspectral image with 448 bands within the 380-2500 nm spectral range and a spatial resolution of 1 m. Twenty-three tree species were classified with high overall accuracy values of 82.57% and 86.93% for the two sites. Significantly high values of the alpha index characterize the unmanaged land use, and the lowest values were calculated for the agricultural land use. In addition, high values of alpha indices were found at the borders between the polygons related to the "edge-effect" phenomenon, whereas low alpha indices were found in areas with high invasion species rates. The beta index value, calculated for 58 polygons, was significantly lower in the agricultural land use. The suggested framework of this study succeeded in quantifying land use effects on tree species distribution, evenness, and richness. IS and spatial statistics techniques offer an opportunity to study woody plant species variation with a multiscale approach that is useful for managing land use, especially under increasing environmental changes. © 2017 by the Ecological Society of America.
Multiscale empirical modeling of the geomagnetic field: From storms to substorms
Stephens, G. K.; Sitnov, M. I.; Korth, H.; Gkioulidou, M.; Ukhorskiy, A. Y.; Merkin, V. G.
2017-12-01
An advanced version of the TS07D empirical geomagnetic field model, herein called SST17, is used to model the global picture of the geomagnetic field and its characteristic variations on both storm and substorm scales. The new SST17 model uses two regular expansions describing the equatorial currents with each having distinctly different scales, one corresponding to a thick and one to a thin current sheet relative to the thermal ion gyroradius. These expansions have an arbitrary distribution of currents in the equatorial plane that is constrained only by magnetometer data. This multi-scale description allows one to reproduce the current sheet thinning during the growth phase. Additionaly, the model uses a flexible description of field-aligned currents that reproduces their spiral structure at low altitudes and provides a continuous transition from region 1 to region 2 current systems. The empirical picture of substorms is obtained by combining magnetometer data from Geotail, THEMIS, Van Allen Probes, Cluster II, Polar, IMP-8, GOES 8, 9, 10 and 12 and then binning this data based on similar values of the auroral index AL, its time derivative and the integral of the solar wind electric field parameter (from ACE, Wind, and IMP-8) in time over substorm scales. The performance of the model is demonstrated for several events, including the 3 July 2012 substorm, which had multi-probe coverage and a series of substorms during the March 2008 storm. It is shown that the AL binning helps reproduce dipolarization signatures in the northward magnetic field Bz, while the solar wind electric field integral allows one to capture the current sheet thinning during the growth phase. The model allows one to trace the substorm dipolarization from the tail to the inner magnetosphere where the dipolarization of strongly stretched tail field lines causes a redistribution of the tail current resulting in an enhancement of the partial ring current in the premidnight sector.
Hu, Q.; Vidal, G.
2017-07-01
The generalization of the multiscale entanglement renormalization ansatz (MERA) to continuous systems, or cMERA [Haegeman et al., Phys. Rev. Lett. 110, 100402 (2013), 10.1103/PhysRevLett.110.100402], is expected to become a powerful variational ansatz for the ground state of strongly interacting quantum field theories. In this Letter, we investigate, in the simpler context of Gaussian cMERA for free theories, the extent to which the cMERA state |ΨΛ⟩ with finite UV cutoff Λ can capture the spacetime symmetries of the ground state |Ψ ⟩. For a free boson conformal field theory (CFT) in 1 +1 dimensions, as a concrete example, we build a quasilocal unitary transformation V that maps |Ψ ⟩ into |ΨΛ⟩ and show two main results. (i) Any spacetime symmetry of the ground state |Ψ ⟩ is also mapped by V into a spacetime symmetry of the cMERA |ΨΛ⟩. However, while in the CFT, the stress-energy tensor Tμ ν(x ) (in terms of which all the spacetime symmetry generators are expressed) is local, and the corresponding cMERA stress-energy tensor Tμν Λ(x )=V Tμ ν(x )V† is quasilocal. (ii) From the cMERA, we can extract quasilocal scaling operators OαΛ(x ) characterized by the exact same scaling dimensions Δα, conformal spins sα, operator product expansion coefficients Cα β γ, and central charge c as the original CFT. Finally, we argue that these results should also apply to interacting theories.
Source-to-exposure assessment with the Pangea multi-scale framework - case study in Australia.
Wannaz, Cedric; Fantke, Peter; Lane, Joe; Jolliet, Olivier
2018-01-24
Effective planning of airshed pollution mitigation is often constrained by a lack of integrative analysis able to relate the relevant emitters to the receptor populations at risk. Both emitter and receptor perspectives are therefore needed to consistently inform emission and exposure reduction measures. This paper aims to extend the Pangea spatial multi-scale multimedia framework to evaluate source-to-receptor relationships of industrial sources of organic pollutants in Australia. Pangea solves a large compartmental system in parallel by block to determine arrays of masses at steady-state for 100 000+ compartments and 4000+ emission scenarios, and further computes population exposure by inhalation and ingestion. From an emitter perspective, radial spatial distributions of population intakes show high spatial variation in intake fractions from 0.68 to 33 ppm for benzene, and from 0.006 to 9.5 ppm for formaldehyde, contrasting urban, rural, desert, and sea source locations. Extending analyses to the receptor perspective, population exposures from the combined emissions of 4101 Australian point sources are more extended for benzene that travels over longer distances, versus formaldehyde that has a more local impact. Decomposing exposure per industrial sector shows petroleum and steel industry as the highest contributing industrial sectors for benzene, whereas the electricity sector and petroleum refining contribute most to formaldehyde exposures. The source apportionment identifies the main sources contributing to exposure at five locations. Overall, this paper demonstrates high interest in addressing exposures from both an emitter perspective well-suited to inform product oriented approaches such as LCA, and from a receptor perspective for health risk mitigation.
Nematzadeh, Nasim; Powers, David M W; Lewis, Trent W
2017-12-01
Why does our visual system fail to reconstruct reality, when we look at certain patterns? Where do Geometrical illusions start to emerge in the visual pathway? How far should we take computational models of vision with the same visual ability to detect illusions as we do? This study addresses these questions, by focusing on a specific underlying neural mechanism involved in our visual experiences that affects our final perception. Among many types of visual illusion, 'Geometrical' and, in particular, 'Tilt Illusions' are rather important, being characterized by misperception of geometric patterns involving lines and tiles in combination with contrasting orientation, size or position. Over the last decade, many new neurophysiological experiments have led to new insights as to how, when and where retinal processing takes place, and the encoding nature of the retinal representation that is sent to the cortex for further processing. Based on these neurobiological discoveries, we provide computer simulation evidence from modelling retinal ganglion cells responses to some complex Tilt Illusions, suggesting that the emergence of tilt in these illusions is partially related to the interaction of multiscale visual processing performed in the retina. The output of our low-level filtering model is presented for several types of Tilt Illusion, predicting that the final tilt percept arises from multiple-scale processing of the Differences of Gaussians and the perceptual interaction of foreground and background elements. The model is a variation of classical receptive field implementation for simple cells in early stages of vision with the scales tuned to the object/texture sizes in the pattern. Our results suggest that this model has a high potential in revealing the underlying mechanism connecting low-level filtering approaches to mid- and high-level explanations such as 'Anchoring theory' and 'Perceptual grouping'.