An Efficient Multiscale Finite-Element Method for Frequency-Domain Seismic Wave Propagation

DOE PAGES

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

2018-02-13

The frequency-domain seismic-wave equation, that is, the Helmholtz equation, has many important applications in seismological studies, yet is very challenging to solve, particularly for large geological models. Iterative solvers, domain decomposition, or parallel strategies can partially alleviate the computational burden, but these approaches may still encounter nontrivial difficulties in complex geological models where a sufficiently fine mesh is required to represent the fine-scale heterogeneities. We develop a novel numerical method to solve the frequency-domain acoustic wave equation on the basis of the multiscale finite-element theory. We discretize a heterogeneous model with a coarse mesh and employ carefully constructed high-order multiscalemore » basis functions to form the basis space for the coarse mesh. Solved from medium- and frequency-dependent local problems, these multiscale basis functions can effectively capture themedium’s fine-scale heterogeneity and the source’s frequency information, leading to a discrete system matrix with a much smaller dimension compared with those from conventional methods.We then obtain an accurate solution to the acoustic Helmholtz equation by solving only a small linear system instead of a large linear system constructed on the fine mesh in conventional methods.We verify our new method using several models of complicated heterogeneities, and the results show that our new multiscale method can solve the Helmholtz equation in complex models with high accuracy and extremely low computational costs.« less

An Efficient Multiscale Finite-Element Method for Frequency-Domain Seismic Wave Propagation

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

The frequency-domain seismic-wave equation, that is, the Helmholtz equation, has many important applications in seismological studies, yet is very challenging to solve, particularly for large geological models. Iterative solvers, domain decomposition, or parallel strategies can partially alleviate the computational burden, but these approaches may still encounter nontrivial difficulties in complex geological models where a sufficiently fine mesh is required to represent the fine-scale heterogeneities. We develop a novel numerical method to solve the frequency-domain acoustic wave equation on the basis of the multiscale finite-element theory. We discretize a heterogeneous model with a coarse mesh and employ carefully constructed high-order multiscalemore » basis functions to form the basis space for the coarse mesh. Solved from medium- and frequency-dependent local problems, these multiscale basis functions can effectively capture themedium’s fine-scale heterogeneity and the source’s frequency information, leading to a discrete system matrix with a much smaller dimension compared with those from conventional methods.We then obtain an accurate solution to the acoustic Helmholtz equation by solving only a small linear system instead of a large linear system constructed on the fine mesh in conventional methods.We verify our new method using several models of complicated heterogeneities, and the results show that our new multiscale method can solve the Helmholtz equation in complex models with high accuracy and extremely low computational costs.« less

Hybrid Parallelization of Adaptive MHD-Kinetic Module in Multi-Scale Fluid-Kinetic Simulation Suite

DOE PAGES

Borovikov, Sergey; Heerikhuisen, Jacob; Pogorelov, Nikolai

2013-04-01

The Multi-Scale Fluid-Kinetic Simulation Suite has a computational tool set for solving partially ionized flows. In this paper we focus on recent developments of the kinetic module which solves the Boltzmann equation using the Monte-Carlo method. The module has been recently redesigned to utilize intra-node hybrid parallelization. We describe in detail the redesign process, implementation issues, and modifications made to the code. Finally, we conduct a performance analysis.

Moose: An Open-Source Framework to Enable Rapid Development of Collaborative, Multi-Scale, Multi-Physics Simulation Tools

NASA Astrophysics Data System (ADS)

Slaughter, A. E.; Permann, C.; Peterson, J. W.; Gaston, D.; Andrs, D.; Miller, J.

2014-12-01

The Idaho National Laboratory (INL)-developed Multiphysics Object Oriented Simulation Environment (MOOSE; www.mooseframework.org), is an open-source, parallel computational framework for enabling the solution of complex, fully implicit multiphysics systems. MOOSE provides a set of computational tools that scientists and engineers can use to create sophisticated multiphysics simulations. Applications built using MOOSE have computed solutions for chemical reaction and transport equations, computational fluid dynamics, solid mechanics, heat conduction, mesoscale materials modeling, geomechanics, and others. To facilitate the coupling of diverse and highly-coupled physical systems, MOOSE employs the Jacobian-free Newton-Krylov (JFNK) method when solving the coupled nonlinear systems of equations arising in multiphysics applications. The MOOSE framework is written in C++, and leverages other high-quality, open-source scientific software packages such as LibMesh, Hypre, and PETSc. MOOSE uses a "hybrid parallel" model which combines both shared memory (thread-based) and distributed memory (MPI-based) parallelism to ensure efficient resource utilization on a wide range of computational hardware. MOOSE-based applications are inherently modular, which allows for simulation expansion (via coupling of additional physics modules) and the creation of multi-scale simulations. Any application developed with MOOSE supports running (in parallel) any other MOOSE-based application. Each application can be developed independently, yet easily communicate with other applications (e.g., conductivity in a slope-scale model could be a constant input, or a complete phase-field micro-structure simulation) without additional code being written. This method of development has proven effective at INL and expedites the development of sophisticated, sustainable, and collaborative simulation tools.

Magnetospheric Multiscale Observations of the Electron Diffusion Region of Large Guide Field Magnetic Reconnection

NASA Technical Reports Server (NTRS)

Eriksson, S.; Wilder, F. D.; Ergun, R. E.; Schwartz, S. J.; Cassak, P. A.; Burch, J. L.; Chen, Li-Jen; Torbert, R. B.; Phan, T. D.; Lavraud, B.;

Multiscale Multilevel Approach to Solution of Nanotechnology Problems

NASA Astrophysics Data System (ADS)

Polyakov, Sergey; Podryga, Viktoriia

2018-02-01

The paper is devoted to a multiscale multilevel approach for the solution of nanotechnology problems on supercomputer systems. The approach uses the combination of continuum mechanics models and the Newton dynamics for individual particles. This combination includes three scale levels: macroscopic, mesoscopic and microscopic. For gas-metal technical systems the following models are used. The quasihydrodynamic system of equations is used as a mathematical model at the macrolevel for gas and solid states. The system of Newton equations is used as a mathematical model at the mesoand microlevels; it is written for nanoparticles of the medium and larger particles moving in the medium. The numerical implementation of the approach is based on the method of splitting into physical processes. The quasihydrodynamic equations are solved by the finite volume method on grids of different types. The Newton equations of motion are solved by Verlet integration in each cell of the grid independently or in groups of connected cells. In the framework of the general methodology, four classes of algorithms and methods of their parallelization are provided. The parallelization uses the principles of geometric parallelism and the efficient partitioning of the computational domain. A special dynamic algorithm is used for load balancing the solvers. The testing of the developed approach was made by the example of the nitrogen outflow from a balloon with high pressure to a vacuum chamber through a micronozzle and a microchannel. The obtained results confirm the high efficiency of the developed methodology.

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

NASA Astrophysics Data System (ADS)

Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt; Stuehn, Torsten

2017-11-01

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach, the theoretical modeling and scaling laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. These two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.

A Parallel, Multi-Scale Watershed-Hydrologic-Inundation Model with Adaptively Switching Mesh for Capturing Flooding and Lake Dynamics

NASA Astrophysics Data System (ADS)

Ji, X.; Shen, C.

2017-12-01

Flood inundation presents substantial societal hazards and also changes biogeochemistry for systems like the Amazon. It is often expensive to simulate high-resolution flood inundation and propagation in a long-term watershed-scale model. Due to the Courant-Friedrichs-Lewy (CFL) restriction, high resolution and large local flow velocity both demand prohibitively small time steps even for parallel codes. Here we develop a parallel surface-subsurface process-based model enhanced by multi-resolution meshes that are adaptively switched on or off. The high-resolution overland flow meshes are enabled only when the flood wave invades to floodplains. This model applies semi-implicit, semi-Lagrangian (SISL) scheme in solving dynamic wave equations, and with the assistant of the multi-mesh method, it also adaptively chooses the dynamic wave equation only in the area of deep inundation. Therefore, the model achieves a balance between accuracy and computational cost.

Multiscale analysis of structure development in expanded starch snacks

NASA Astrophysics Data System (ADS)

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.

Magnetospheric Multiscale Satellites Observations of Parallel Electric Fields Associated with Magnetic Reconnection

NASA Technical Reports Server (NTRS)

Ergun, R. E.; Goodrich, K. A.; Wilder, F. D.; Holmes, J. C.; Stawarz, J. E.; Eriksson, S.; Sturner, A. P.; Malaspina, D. M.; Usanova, M. E.; Torbert, R. B.;

Multiscale Modeling of Hall Thrusters. Chapter 7: Plume Modeling

DTIC Science & Technology

2012-03-06

Quasineutral Potential Fix Finally, a ”quasi-neutral” switch has been implemented in the Draco Gauss - Seidel Solver. Implementation in the PCG solver is...unlimited. 4 (a) (b) Figure 7.2: Potential solution obtained for a single and multiple (16) zones Hence, part of the development effort went into...be seen from this plot, the two solutions are identical. The division of mesh into multiple zones had another benefit for parallel compu- tations

Multiscale Support Vector Learning With Projection Operator Wavelet Kernel for Nonlinear Dynamical System Identification.

PubMed

Lu, Zhao; Sun, Jing; Butts, Kenneth

2016-02-03

A giant leap has been made in the past couple of decades with the introduction of kernel-based learning as a mainstay for designing effective nonlinear computational learning algorithms. In view of the geometric interpretation of conditional expectation and the ubiquity of multiscale characteristics in highly complex nonlinear dynamic systems [1]-[3], this paper presents a new orthogonal projection operator wavelet kernel, aiming at developing an efficient computational learning approach for nonlinear dynamical system identification. In the framework of multiresolution analysis, the proposed projection operator wavelet kernel can fulfill the multiscale, multidimensional learning to estimate complex dependencies. The special advantage of the projection operator wavelet kernel developed in this paper lies in the fact that it has a closed-form expression, which greatly facilitates its application in kernel learning. To the best of our knowledge, it is the first closed-form orthogonal projection wavelet kernel reported in the literature. It provides a link between grid-based wavelets and mesh-free kernel-based methods. Simulation studies for identifying the parallel models of two benchmark nonlinear dynamical systems confirm its superiority in model accuracy and sparsity.

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach and paper, the theoretical modeling and scalingmore » laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. Finally, these two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.« less

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

DOE PAGES

Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt; ...

2017-11-27

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach and paper, the theoretical modeling and scalingmore » laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. Finally, these two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.« less

Magnetospheric Multiscale Observations of Large-Amplitude Parallel, Electrostatic Waves Associated with Magnetic Reconnection at the Magnetopause

NASA Technical Reports Server (NTRS)

Ergun, R. E.; Holmes, J. C.; Goodrich, K. A.; Wilder, F. D.; Stawarz, J. E.; Eriksson, S.; Newman, D. L.; Schwartz, S. J.; Goldman, M. V.; Sturner, A. P.;

Hybrid Multiscale Finite Volume method for multiresolution simulations of flow and reactive transport in porous media

NASA Astrophysics Data System (ADS)

Barajas-Solano, D. A.; Tartakovsky, A. M.

2017-12-01

We present a multiresolution method for the numerical simulation of flow and reactive transport in porous, heterogeneous media, based on the hybrid Multiscale Finite Volume (h-MsFV) algorithm. The h-MsFV algorithm allows us to couple high-resolution (fine scale) flow and transport models with lower resolution (coarse) models to locally refine both spatial resolution and transport models. The fine scale problem is decomposed into various "local'' problems solved independently in parallel and coordinated via a "global'' problem. This global problem is then coupled with the coarse model to strictly ensure domain-wide coarse-scale mass conservation. The proposed method provides an alternative to adaptive mesh refinement (AMR), due to its capacity to rapidly refine spatial resolution beyond what's possible with state-of-the-art AMR techniques, and the capability to locally swap transport models. We illustrate our method by applying it to groundwater flow and reactive transport of multiple species.

Multiscale Simulations of Magnetic Island Coalescence

NASA Technical Reports Server (NTRS)

Dorelli, John C.

2010-01-01

We describe a new interactive parallel Adaptive Mesh Refinement (AMR) framework written in the Python programming language. This new framework, PyAMR, hides the details of parallel AMR data structures and algorithms (e.g., domain decomposition, grid partition, and inter-process communication), allowing the user to focus on the development of algorithms for advancing the solution of a systems of partial differential equations on a single uniform mesh. We demonstrate the use of PyAMR by simulating the pairwise coalescence of magnetic islands using the resistive Hall MHD equations. Techniques for coupling different physics models on different levels of the AMR grid hierarchy are discussed.

Peridynamic Multiscale Finite Element Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Costa, Timothy; Bond, Stephen D.; Littlewood, David John

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 andmore » 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 art of local models with the flexibility and accuracy of the nonlocal peridynamic model. In the mixed locality method this coupling occurs across scales, so that the nonlocal model can be used to communicate material heterogeneity at scales inappropriate to local partial differential equation models. Additionally, the computational burden of the weak form of the peridynamic model is reduced dramatically by only requiring that the model be solved on local patches of the simulation domain which may be computed in parallel, taking advantage of the heterogeneous nature of next generation computing platforms. Addition- ally, we present a novel Galerkin framework, the 'Ambulant Galerkin Method', which represents a first step towards a unified mathematical analysis of local and nonlocal multiscale finite element methods, and whose future extension will allow the analysis of multiscale finite element methods that mix models across scales under certain assumptions of the consistency of those models.« less

Coupling of ab initio density functional theory and molecular dynamics for the multiscale modeling of carbon nanotubes

NASA Astrophysics Data System (ADS)

Ng, T. Y.; Yeak, S. H.; Liew, K. M.

2008-02-01

A multiscale technique is developed that couples empirical molecular dynamics (MD) and ab initio density functional theory (DFT). An overlap handshaking region between the empirical MD and ab initio DFT regions is formulated and the interaction forces between the carbon atoms are calculated based on the second-generation reactive empirical bond order potential, the long-range Lennard-Jones potential as well as the quantum-mechanical DFT derived forces. A density of point algorithm is also developed to track all interatomic distances in the system, and to activate and establish the DFT and handshaking regions. Through parallel computing, this multiscale method is used here to study the dynamic behavior of single-walled carbon nanotubes (SWCNTs) under asymmetrical axial compression. The detection of sideways buckling due to the asymmetrical axial compression is reported and discussed. It is noted from this study on SWCNTs that the MD results may be stiffer compared to those with electron density considerations, i.e. first-principle ab initio methods.

Accelerating Electrostatic Surface Potential Calculation with Multiscale Approximation on Graphics Processing Units

PubMed Central

Anandakrishnan, Ramu; Scogland, Tom R. W.; Fenley, Andrew T.; Gordon, John C.; Feng, Wu-chun; Onufriev, Alexey V.

2010-01-01

Tools that compute and visualize biomolecular electrostatic surface potential have been used extensively for studying biomolecular function. However, determining the surface potential for large biomolecules on a typical desktop computer can take days or longer using currently available tools and methods. Two commonly used techniques to speed up these types of electrostatic computations are approximations based on multi-scale coarse-graining and parallelization across multiple processors. This paper demonstrates that for the computation of electrostatic surface potential, these two techniques can be combined to deliver significantly greater speed-up than either one separately, something that is in general not always possible. Specifically, the electrostatic potential computation, using an analytical linearized Poisson Boltzmann (ALPB) method, is approximated using the hierarchical charge partitioning (HCP) multiscale method, and parallelized on an ATI Radeon 4870 graphical processing unit (GPU). The implementation delivers a combined 934-fold speed-up for a 476,040 atom viral capsid, compared to an equivalent non-parallel implementation on an Intel E6550 CPU without the approximation. This speed-up is significantly greater than the 42-fold speed-up for the HCP approximation alone or the 182-fold speed-up for the GPU alone. PMID:20452792

Using CellML with OpenCMISS to Simulate Multi-Scale Physiology

PubMed Central

Nickerson, David P.; Ladd, David; Hussan, Jagir R.; Safaei, Soroush; Suresh, Vinod; Hunter, Peter J.; Bradley, Christopher P.

2014-01-01

OpenCMISS is an open-source modeling environment aimed, in particular, at the solution of bioengineering problems. OpenCMISS consists of two main parts: a computational library (OpenCMISS-Iron) and a field manipulation and visualization library (OpenCMISS-Zinc). OpenCMISS is designed for the solution of coupled multi-scale, multi-physics problems in a general-purpose parallel environment. CellML is an XML format designed to encode biophysically based systems of ordinary differential equations and both linear and non-linear algebraic equations. A primary design goal of CellML is to allow mathematical models to be encoded in a modular and reusable format to aid reproducibility and interoperability of modeling studies. In OpenCMISS, we make use of CellML models to enable users to configure various aspects of their multi-scale physiological models. This avoids the need for users to be familiar with the OpenCMISS internal code in order to perform customized computational experiments. Examples of this are: cellular electrophysiology models embedded in tissue electrical propagation models; material constitutive relationships for mechanical growth and deformation simulations; time-varying boundary conditions for various problem domains; and fluid constitutive relationships and lumped-parameter models. In this paper, we provide implementation details describing how CellML models are integrated into multi-scale physiological models in OpenCMISS. The external interface OpenCMISS presents to users is also described, including specific examples exemplifying the extensibility and usability these tools provide the physiological modeling and simulation community. We conclude with some thoughts on future extension of OpenCMISS to make use of other community developed information standards, such as FieldML, SED-ML, and BioSignalML. Plans for the integration of accelerator code (graphical processing unit and field programmable gate array) generated from CellML models is also discussed. PMID:25601911

A mixed parallel strategy for the solution of coupled multi-scale problems at finite strains

NASA Astrophysics Data System (ADS)

Lopes, I. A. Rodrigues; Pires, F. M. Andrade; Reis, F. J. P.

2018-02-01

A mixed parallel strategy for the solution of homogenization-based multi-scale constitutive problems undergoing finite strains is proposed. The approach aims to reduce the computational time and memory requirements of non-linear coupled simulations that use finite element discretization at both scales (FE^2). In the first level of the algorithm, a non-conforming domain decomposition technique, based on the FETI method combined with a mortar discretization at the interface of macroscopic subdomains, is employed. A master-slave scheme, which distributes tasks by macroscopic element and adopts dynamic scheduling, is then used for each macroscopic subdomain composing the second level of the algorithm. This strategy allows the parallelization of FE^2 simulations in computers with either shared memory or distributed memory architectures. The proposed strategy preserves the quadratic rates of asymptotic convergence that characterize the Newton-Raphson scheme. Several examples are presented to demonstrate the robustness and efficiency of the proposed parallel strategy.

Modelling strategies to predict the multi-scale effects of rural land management change

NASA Astrophysics Data System (ADS)

Bulygina, N.; Ballard, C. E.; Jackson, B. M.; McIntyre, N.; Marshall, M.; Reynolds, B.; Wheater, H. S.

2011-12-01

Changes to the rural landscape due to agricultural land management are ubiquitous, yet predicting the multi-scale effects of land management change on hydrological response remains an important scientific challenge. Much empirical research has been of little generic value due to inadequate design and funding of monitoring programmes, while the modelling issues challenge the capability of data-based, conceptual and physics-based modelling approaches. In this paper we report on a major UK research programme, motivated by a national need to quantify effects of agricultural intensification on flood risk. Working with a consortium of farmers in upland Wales, a multi-scale experimental programme (from experimental plots to 2nd order catchments) was developed to address issues of upland agricultural intensification. This provided data support for a multi-scale modelling programme, in which highly detailed physics-based models were conditioned on the experimental data and used to explore effects of potential field-scale interventions. A meta-modelling strategy was developed to represent detailed modelling in a computationally-efficient manner for catchment-scale simulation; this allowed catchment-scale quantification of potential management options. For more general application to data-sparse areas, alternative approaches were needed. Physics-based models were developed for a range of upland management problems, including the restoration of drained peatlands, afforestation, and changing grazing practices. Their performance was explored using literature and surrogate data; although subject to high levels of uncertainty, important insights were obtained, of practical relevance to management decisions. In parallel, regionalised conceptual modelling was used to explore the potential of indices of catchment response, conditioned on readily-available catchment characteristics, to represent ungauged catchments subject to land management change. Although based in part on speculative relationships, significant predictive power was derived from this approach. Finally, using a formal Bayesian procedure, these different sources of information were combined with local flow data in a catchment-scale conceptual model application , i.e. using small-scale physical properties, regionalised signatures of flow and available flow measurements.

Magnetospheric Multiscale observations of large-amplitude, parallel, electrostatic waves associated with magnetic reconnection at the magnetopause

NASA Astrophysics Data System (ADS)

Ergun, R. E.; Holmes, J. C.; Goodrich, K. A.; Wilder, F. D.; Stawarz, J. E.; Eriksson, S.; Newman, D. L.; Schwartz, S. J.; Goldman, M. V.; Sturner, A. P.; Malaspina, D. M.; Usanova, M. E.; Torbert, R. B.; Argall, M.; Lindqvist, P.-A.; Khotyaintsev, Y.; Burch, J. L.; Strangeway, R. J.; Russell, C. T.; Pollock, C. J.; Giles, B. L.; Dorelli, J. J. C.; Avanov, L.; Hesse, M.; Chen, L. J.; Lavraud, B.; Le Contel, O.; Retino, A.; Phan, T. D.; Eastwood, J. P.; Oieroset, M.; Drake, J.; Shay, M. A.; Cassak, P. A.; Nakamura, R.; Zhou, M.; Ashour-Abdalla, M.; André, M.

2016-06-01

We report observations from the Magnetospheric Multiscale satellites of large-amplitude, parallel, electrostatic waves associated with magnetic reconnection at the Earth's magnetopause. The observed waves have parallel electric fields (E||) with amplitudes on the order of 100 mV/m and display nonlinear characteristics that suggest a possible net E||. These waves are observed within the ion diffusion region and adjacent to (within several electron skin depths) the electron diffusion region. They are in or near the magnetosphere side current layer. Simulation results support that the strong electrostatic linear and nonlinear wave activities appear to be driven by a two stream instability, which is a consequence of mixing cold (<10 eV) plasma in the magnetosphere with warm (~100 eV) plasma from the magnetosheath on a freshly reconnected magnetic field line. The frequent observation of these waves suggests that cold plasma is often present near the magnetopause.

Accelerating electrostatic surface potential calculation with multi-scale approximation on graphics processing units.

PubMed

Anandakrishnan, Ramu; Scogland, Tom R W; Fenley, Andrew T; Gordon, John C; Feng, Wu-chun; Onufriev, Alexey V

2010-06-01

Tools that compute and visualize biomolecular electrostatic surface potential have been used extensively for studying biomolecular function. However, determining the surface potential for large biomolecules on a typical desktop computer can take days or longer using currently available tools and methods. Two commonly used techniques to speed-up these types of electrostatic computations are approximations based on multi-scale coarse-graining and parallelization across multiple processors. This paper demonstrates that for the computation of electrostatic surface potential, these two techniques can be combined to deliver significantly greater speed-up than either one separately, something that is in general not always possible. Specifically, the electrostatic potential computation, using an analytical linearized Poisson-Boltzmann (ALPB) method, is approximated using the hierarchical charge partitioning (HCP) multi-scale method, and parallelized on an ATI Radeon 4870 graphical processing unit (GPU). The implementation delivers a combined 934-fold speed-up for a 476,040 atom viral capsid, compared to an equivalent non-parallel implementation on an Intel E6550 CPU without the approximation. This speed-up is significantly greater than the 42-fold speed-up for the HCP approximation alone or the 182-fold speed-up for the GPU alone. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Fast Particle Methods for Multiscale Phenomena Simulations

NASA Technical Reports Server (NTRS)

Koumoutsakos, P.; Wray, A.; Shariff, K.; Pohorille, Andrew

2000-01-01

We are developing particle methods oriented at improving computational modeling capabilities of multiscale physical phenomena in : (i) high Reynolds number unsteady vortical flows, (ii) particle laden and interfacial flows, (iii)molecular dynamics studies of nanoscale droplets and studies of the structure, functions, and evolution of the earliest living cell. The unifying computational approach involves particle methods implemented in parallel computer architectures. The inherent adaptivity, robustness and efficiency of particle methods makes them a multidisciplinary computational tool capable of bridging the gap of micro-scale and continuum flow simulations. Using efficient tree data structures, multipole expansion algorithms, and improved particle-grid interpolation, particle methods allow for simulations using millions of computational elements, making possible the resolution of a wide range of length and time scales of these important physical phenomena.The current challenges in these simulations are in : [i] the proper formulation of particle methods in the molecular and continuous level for the discretization of the governing equations [ii] the resolution of the wide range of time and length scales governing the phenomena under investigation. [iii] the minimization of numerical artifacts that may interfere with the physics of the systems under consideration. [iv] the parallelization of processes such as tree traversal and grid-particle interpolations We are conducting simulations using vortex methods, molecular dynamics and smooth particle hydrodynamics, exploiting their unifying concepts such as : the solution of the N-body problem in parallel computers, highly accurate particle-particle and grid-particle interpolations, parallel FFT's and the formulation of processes such as diffusion in the context of particle methods. This approach enables us to transcend among seemingly unrelated areas of research.

Overcoming Challenges in Kinetic Modeling of Magnetized Plasmas and Vacuum Electronic Devices

NASA Astrophysics Data System (ADS)

Omelchenko, Yuri; Na, Dong-Yeop; Teixeira, Fernando

2017-10-01

We transform the state-of-the art of plasma modeling by taking advantage of novel computational techniques for fast and robust integration of multiscale hybrid (full particle ions, fluid electrons, no displacement current) and full-PIC models. These models are implemented in 3D HYPERS and axisymmetric full-PIC CONPIC codes. HYPERS is a massively parallel, asynchronous code. The HYPERS solver does not step fields and particles synchronously in time but instead executes local variable updates (events) at their self-adaptive rates while preserving fundamental conservation laws. The charge-conserving CONPIC code has a matrix-free explicit finite-element (FE) solver based on a sparse-approximate inverse (SPAI) algorithm. This explicit solver approximates the inverse FE system matrix (``mass'' matrix) using successive sparsity pattern orders of the original matrix. It does not reduce the set of Maxwell's equations to a vector-wave (curl-curl) equation of second order but instead utilizes the standard coupled first-order Maxwell's system. We discuss the ability of our codes to accurately and efficiently account for multiscale physical phenomena in 3D magnetized space and laboratory plasmas and axisymmetric vacuum electronic devices.

Tinker-HP: a massively parallel molecular dynamics package for multiscale simulations of large complex systems with advanced point dipole polarizable force fields.

PubMed

Lagardère, Louis; Jolly, Luc-Henri; Lipparini, Filippo; Aviat, Félix; Stamm, Benjamin; Jing, Zhifeng F; Harger, Matthew; Torabifard, Hedieh; Cisneros, G Andrés; Schnieders, Michael J; Gresh, Nohad; Maday, Yvon; Ren, Pengyu Y; Ponder, Jay W; Piquemal, Jean-Philip

2018-01-28

We present Tinker-HP, a massively MPI parallel package dedicated to classical molecular dynamics (MD) and to multiscale simulations, using advanced polarizable force fields (PFF) encompassing distributed multipoles electrostatics. Tinker-HP is an evolution of the popular Tinker package code that conserves its simplicity of use and its reference double precision implementation for CPUs. Grounded on interdisciplinary efforts with applied mathematics, Tinker-HP allows for long polarizable MD simulations on large systems up to millions of atoms. We detail in the paper the newly developed extension of massively parallel 3D spatial decomposition to point dipole polarizable models as well as their coupling to efficient Krylov iterative and non-iterative polarization solvers. The design of the code allows the use of various computer systems ranging from laboratory workstations to modern petascale supercomputers with thousands of cores. Tinker-HP proposes therefore the first high-performance scalable CPU computing environment for the development of next generation point dipole PFFs and for production simulations. Strategies linking Tinker-HP to Quantum Mechanics (QM) in the framework of multiscale polarizable self-consistent QM/MD simulations are also provided. The possibilities, performances and scalability of the software are demonstrated via benchmarks calculations using the polarizable AMOEBA force field on systems ranging from large water boxes of increasing size and ionic liquids to (very) large biosystems encompassing several proteins as well as the complete satellite tobacco mosaic virus and ribosome structures. For small systems, Tinker-HP appears to be competitive with the Tinker-OpenMM GPU implementation of Tinker. As the system size grows, Tinker-HP remains operational thanks to its access to distributed memory and takes advantage of its new algorithmic enabling for stable long timescale polarizable simulations. Overall, a several thousand-fold acceleration over a single-core computation is observed for the largest systems. The extension of the present CPU implementation of Tinker-HP to other computational platforms is discussed.

Observations of Large-Amplitude, Parallel, Electrostatic Waves Associated with the Kelvin-Helmholtz Instability by the Magnetospheric Multiscale Mission

NASA Technical Reports Server (NTRS)

Wilder, F. D.; Ergun, R. E.; Schwartz, S. J.; Newman, D. L.; Eriksson, S.; Stawarz, J. E.; Goldman, M. V.; Goodrich, K. A.; Gershman, D. J.; Malaspina, D.;

Global Environmental Multiscale model - a platform for integrated environmental predictions

NASA Astrophysics Data System (ADS)

Kaminski, Jacek W.; Struzewska, Joanna; Neary, Lori; Dearden, Frank

2017-04-01

The Global Environmental Multiscale model was developed by the Government of Canada as an operational weather prediction model in the mid-1990s. Subsequently, it was used as the host meteorological model for an on-line implementation of air quality chemistry and aerosols from global to the meso-gamma scale. Further model developments led to the vertical extension of the modelling domain to include stratospheric chemistry, aerosols, and formation of polar stratospheric clouds. In parallel, the modelling platform was used for planetary applications where dynamical, radiative transfer and chemical processes in the atmosphere of Mars were successfully simulated. Undoubtedly, the developed modelling platform can be classified as an example capable of the seamless and coupled modelling of the dynamics and chemistry of planetary atmospheres. We will present modelling results for global, regional, and local air quality episodes and the long-term air quality trends. Upper troposphere and lower stratosphere modelling results will be presented in terms of climate change and subsonic aviation emissions modelling. Model results for the atmosphere of Mars will be presented in the context of the 2016 ExoMars mission and the anticipated observations from the NOMAD instrument. Also, we will present plans and the design to extend the GEM model to the F region with further coupling with a magnetospheric model that extends to 15 Re.

A Novel Multi-scale Simulation Strategy for Turbulent Reacting Flows

DOE Office of Scientific and Technical Information (OSTI.GOV)

James, Sutherland C.

In this project, a new methodology was proposed to bridge the gap between Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES). This novel methodology, titled Lattice-Based Multiscale Simulation (LBMS), creates a lattice structure of One-Dimensional Turbulence (ODT) models. This model has been shown to capture turbulent combustion with high fidelity by fully resolving interactions between turbulence and diffusion. By creating a lattice of ODT models, which are then coupled, LBMS overcomes the shortcomings of ODT, which are its inability to capture large scale three dimensional flow structures. However, by spacing these lattices significantly apart, LBMS can avoid the cursemore » of dimensionality that creates untenable computational costs associated with DNS. This project has shown that LBMS is capable of reproducing statistics of isotropic turbulent flows while coarsening the spacing between lines significantly. It also investigates and resolves issues that arise when coupling ODT lines, such as flux reconstruction perpendicular to a given ODT line, preservation of conserved quantities when eddies cross a course cell volume and boundary condition application. Robust parallelization is also investigated.« less

Anti-parallel versus Component Reconnection at the Earth Magnetopause

NASA Astrophysics Data System (ADS)

Trattner, K. J.; Burch, J. L.; Ergun, R.; Eriksson, S.; Fuselier, S. A.; Gomez, R. G.; Giles, B. L.; Steven, P. M.; Strangeway, R. J.; Wilder, F. D.

2017-12-01

Magnetic reconnection at the Earth's magnetopause is discussed and has been observed as anti-parallel and component reconnection. While anti-parallel reconnection occurs between magnetic field lines of (ideally) exactly opposite polarity, component reconnection (also known as the tilted X-line model) predicts the location of the reconnection line to be anchored at the sub-solar point and extend continuously along the dayside magnetopause, while the ratio of the IMF By/Bz component determines the tilt of the X-line relative to the equatorial plane.A reconnection location prediction model known as the Maximum Magnetic Shear Model combines these two scenarios. The model predicts that during dominant IMF By conditions, magnetic reconnection occurs along an extended line across the dayside magnetopause but generally not through the sub-solar point (as predicted in the original tilted X-line model). Rather, the line follows the ridge of maximum magnetic shear across the dayside magnetopause. In contrast, for dominant IMF Bz (155° < tan-1(By/Bz) < 205°) or dominant Bx (|Bx|/B > 0.7) conditions, the reconnection location bifurcates and traces to high-latitudes, in close agreement with the anti-parallel reconnection scenario, and does not cross the dayside magnetopause as a single tilted reconnection line. Using observations from the Magnetospheric MultiScale missions during a magnetopause crossing when the IMF rotated from an dominate IMF BZ to a dominant IMF BY field we will investigate when the transition between the anti-parallel and tilted X-line scenarios occurs.

Multiscale simulation of DC corona discharge and ozone generation from nanostructures

NASA Astrophysics Data System (ADS)

Wang, Pengxiang

Atmospheric direct current (dc) corona discharge from micro-sized objects has been widely used as an ion source in many devices, such as photocopiers, laser printers, and electronic air cleaners. Shrinking the size of the discharge electrode to the nanometer range (e.g., through the use of carbon nanotubes or CNTs) is expected to lead to a significant reduction in power consumption and detrimental ozone production in these devices. The objectives of this study are to unveil the fundamental physics of the nanoscale corona discharge and to evaluate its performance and ozone production through numerical models. The extremely small size of CNTs presents considerable complexity and challenges in modeling CNT corona discharges. A hybrid multiscale model, which combines a kinetic particle-in-cell plus Monte Carlo collision (PIC-MCC) model and a continuum model, is developed to simulate the corona discharge from nanostructures. The multiscale model is developed in several steps. First, a pure PIC-MCC model is developed and PIC-MCC simulations of corona plasma from micro-sized electrode with same boundary conditions as prior model are performed to validate the PIC-MCC scheme. The agreement between the PIC-MCC model and the prior continuum model indicates the validity of the PIC-MCC scheme. The validated PIC-MCC scheme is then coupled with a continuum model to simulate the corona discharge from a micro-sized electrode. Unlike the prior continuum model which only predicts the corona plasma region, the hybrid model successfully predicts the self-consistent discharge process in the entire corona discharge gap that includes both corona plasma region and unipolar ion region. The voltage-current density curves obtained by the hybrid model agree well with analytical prediction and experimental results. The hybrid modeling approach, which combines the accuracy of a kinetic model and the efficiency of a continuum model, is thus validated for modeling dc corona discharges. For simulation of corona discharges from nanostructures, a one-dimensional (1-D) multiscale model is used due to the prohibitive computational expense associated with two-dimensional (2-D) modeling. Near the nanoscale discharge electrode surface, a kinetic model based on PIC-MCC is used due to a relatively large Knudsen number in this region. Far away from the nanoscale discharge electrode, a continuum model is used since the Knudsen number is very small there. The multiscale modeling results are compared with experimental data. The quantitative agreement in positive discharges and qualitative agreement in negative discharges validate the modeling approach. The mechanism of sustaining the discharge process from nanostructures is revealed and is found to be different from that of discharge from micro- or macro-sized electrodes. Finally, the corona plasma model is combined with a plasma chemistry model and a transport model to predict the ozone production from the nanoscale corona. The dependence of ozone production on the applied potential and air velocity is studied. The electric field distribution in a 2-D multiscale domain (from nanoscale to microscale) is predicted by solving the Poisson's equation using a finite difference scheme. The discretized linear equations are solved using a multigrid method under the framework of PETSc on a paralleled supercomputer. Although the Poisson solver is able to resolve the multiscale field, the prohibitively long computation time limits the use of a 2-D solver in the current PIC-MCC scheme.

Engineering Digestion: Multiscale Processes of Food Digestion.

PubMed

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®

Highly efficient spatial data filtering in parallel using the opensource library CPPPO

NASA Astrophysics Data System (ADS)

Municchi, Federico; Goniva, Christoph; Radl, Stefan

2016-10-01

CPPPO is a compilation of parallel data processing routines developed with the aim to create a library for "scale bridging" (i.e. connecting different scales by mean of closure models) in a multi-scale approach. CPPPO features a number of parallel filtering algorithms designed for use with structured and unstructured Eulerian meshes, as well as Lagrangian data sets. In addition, data can be processed on the fly, allowing the collection of relevant statistics without saving individual snapshots of the simulation state. Our library is provided with an interface to the widely-used CFD solver OpenFOAM®, and can be easily connected to any other software package via interface modules. Also, we introduce a novel, extremely efficient approach to parallel data filtering, and show that our algorithms scale super-linearly on multi-core clusters. Furthermore, we provide a guideline for choosing the optimal Eulerian cell selection algorithm depending on the number of CPU cores used. Finally, we demonstrate the accuracy and the parallel scalability of CPPPO in a showcase focusing on heat and mass transfer from a dense bed of particles.

Development of mpi_EPIC model for global agroecosystem modeling

DOE PAGES

Kang, Shujiang; Wang, Dali; Jeff A. Nichols; ...

2014-12-31

Models that address policy-maker concerns about multi-scale effects of food and bioenergy production systems are computationally demanding. We integrated the message passing interface algorithm into the process-based EPIC model to accelerate computation of ecosystem effects. Simulation performance was further enhanced by applying the Vampir framework. When this enhanced mpi_EPIC model was tested, total execution time for a global 30-year simulation of a switchgrass cropping system was shortened to less than 0.5 hours on a supercomputer. The results illustrate that mpi_EPIC using parallel design can balance simulation workloads and facilitate large-scale, high-resolution analysis of agricultural production systems, management alternatives and environmentalmore » effects.« less

Development of Semantic Description for Multiscale Models of Thermo-Mechanical Treatment of Metal Alloys

NASA Astrophysics Data System (ADS)

Macioł, Piotr; Regulski, Krzysztof

2016-08-01

We present a process of semantic meta-model development for data management in an adaptable multiscale modeling framework. The main problems in ontology design are discussed, and a solution achieved as a result of the research is presented. The main concepts concerning the application and data management background for multiscale modeling were derived from the AM3 approach—object-oriented Agile multiscale modeling methodology. The ontological description of multiscale models enables validation of semantic correctness of data interchange between submodels. We also present a possibility of using the ontological model as a supervisor in conjunction with a multiscale model controller and a knowledge base system. Multiscale modeling formal ontology (MMFO), designed for describing multiscale models' data and structures, is presented. A need for applying meta-ontology in the MMFO development process is discussed. Examples of MMFO application in describing thermo-mechanical treatment of metal alloys are discussed. Present and future applications of MMFO are described.

Comparison of Multiscale Method of Cells-Based Models for Predicting Elastic Properties of Filament Wound C/C-SiC

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Fassin, Marek; Bednarcyk, Brett A.; Reese, Stefanie; Simon, Jaan-Willem

2017-01-01

Three different multiscale models, based on the method of cells (generalized and high fidelity) micromechanics models were developed and used to predict the elastic properties of C/C-SiC composites. In particular, the following multiscale modeling strategies were employed: Concurrent multiscale modeling of all phases using the generalized method of cells, synergistic (two-way coupling in space) multiscale modeling with the generalized method of cells, and hierarchical (one-way coupling in space) multiscale modeling with the high fidelity generalized method of cells. The three models are validated against data from a hierarchical multiscale finite element model in the literature for a repeating unit cell of C/C-SiC. Furthermore, the multiscale models are used in conjunction with classical lamination theory to predict the stiffness of C/C-SiC plates manufactured via a wet filament winding and liquid silicon infiltration process recently developed by the German Aerospace Institute.

Strategies for Large Scale Implementation of a Multiscale, Multiprocess Integrated Hydrologic Model

NASA Astrophysics Data System (ADS)

Kumar, M.; Duffy, C.

2006-05-01

Distributed models simulate hydrologic state variables in space and time while taking into account the heterogeneities in terrain, surface, subsurface properties and meteorological forcings. Computational cost and complexity associated with these model increases with its tendency to accurately simulate the large number of interacting physical processes at fine spatio-temporal resolution in a large basin. A hydrologic model run on a coarse spatial discretization of the watershed with limited number of physical processes needs lesser computational load. But this negatively affects the accuracy of model results and restricts physical realization of the problem. So it is imperative to have an integrated modeling strategy (a) which can be universally applied at various scales in order to study the tradeoffs between computational complexity (determined by spatio- temporal resolution), accuracy and predictive uncertainty in relation to various approximations of physical processes (b) which can be applied at adaptively different spatial scales in the same domain by taking into account the local heterogeneity of topography and hydrogeologic variables c) which is flexible enough to incorporate different number and approximation of process equations depending on model purpose and computational constraint. An efficient implementation of this strategy becomes all the more important for Great Salt Lake river basin which is relatively large (~89000 sq. km) and complex in terms of hydrologic and geomorphic conditions. Also the types and the time scales of hydrologic processes which are dominant in different parts of basin are different. Part of snow melt runoff generated in the Uinta Mountains infiltrates and contributes as base flow to the Great Salt Lake over a time scale of decades to centuries. The adaptive strategy helps capture the steep topographic and climatic gradient along the Wasatch front. Here we present the aforesaid modeling strategy along with an associated hydrologic modeling framework which facilitates a seamless, computationally efficient and accurate integration of the process model with the data model. The flexibility of this framework leads to implementation of multiscale, multiresolution, adaptive refinement/de-refinement and nested modeling simulations with least computational burden. However, performing these simulations and related calibration of these models over a large basin at higher spatio- temporal resolutions is computationally intensive and requires use of increasing computing power. With the advent of parallel processing architectures, high computing performance can be achieved by parallelization of existing serial integrated-hydrologic-model code. This translates to running the same model simulation on a network of large number of processors thereby reducing the time needed to obtain solution. The paper also discusses the implementation of the integrated model on parallel processors. Also will be discussed the mapping of the problem on multi-processor environment, method to incorporate coupling between hydrologic processes using interprocessor communication models, model data structure and parallel numerical algorithms to obtain high performance.

Multiscale Monte Carlo equilibration: Pure Yang-Mills theory

DOE PAGES

Endres, Michael G.; Brower, Richard C.; Orginos, Kostas; ...

2015-12-29

In this study, we present a multiscale thermalization algorithm for lattice gauge theory, which enables efficient parallel generation of uncorrelated gauge field configurations. The algorithm combines standard Monte Carlo techniques with ideas drawn from real space renormalization group and multigrid methods. We demonstrate the viability of the algorithm for pure Yang-Mills gauge theory for both heat bath and hybrid Monte Carlo evolution, and show that it ameliorates the problem of topological freezing up to controllable lattice spacing artifacts.

CCMC Modeling of Magnetic Reconnection in Electron Diffusion Region Events

NASA Astrophysics Data System (ADS)

Marshall, A.; Reiff, P. H.; Daou, A.; Webster, J.; Sazykin, S. Y.; Kuznetsova, M.; Grocer, A.; Rastaetter, L.; Welling, D. T.; DeZeeuw, D.; Russell, C. T.

2017-12-01

We use the unprecedented spatial and temporal cadence of the Magnetospheric Multiscale Mission to study four electron diffusion events, and infer important physical properties of their respective magnetic reconnection processes. We couple these observations with numerical simulations using tools such as SWMF with RCM, and RECON-X, from the Coordinated Community Modeling Center, to provide, for a first time, a coherent temporal description of the magnetic reconnection process through tracing the coupling of IMF and closed Earth magnetic field lines, leading to the corresponding polar cap open field lines. We note that the reconnection geometry is far from slab-like: the IMF field lines drape over the magnetopause, lending to a stretching of the field lines. The stretched field lines become parallel to, and merge with the dayside separator. Surprisingly, the inner closed field lines also distort to become parallel to the separator. This parallel geometry allows a very sharp boundary between open and closed field lines. In three of the events, the MMS location was near the predicted separator location; in the fourth it was near the outflow region.

Materials integrity in microsystems: a framework for a petascale predictive-science-based multiscale modeling and simulation system

NASA Astrophysics Data System (ADS)

To, Albert C.; Liu, Wing Kam; Olson, Gregory B.; Belytschko, Ted; Chen, Wei; Shephard, Mark S.; Chung, Yip-Wah; Ghanem, Roger; Voorhees, Peter W.; Seidman, David N.; Wolverton, Chris; Chen, J. S.; Moran, Brian; Freeman, Arthur J.; Tian, Rong; Luo, Xiaojuan; Lautenschlager, Eric; Challoner, A. Dorian

2008-09-01

Microsystems have become an integral part of our lives and can be found in homeland security, medical science, aerospace applications and beyond. Many critical microsystem applications are in harsh environments, in which long-term reliability needs to be guaranteed and repair is not feasible. For example, gyroscope microsystems on satellites need to function for over 20 years under severe radiation, thermal cycling, and shock loading. Hence a predictive-science-based, verified and validated computational models and algorithms to predict the performance and materials integrity of microsystems in these situations is needed. Confidence in these predictions is improved by quantifying uncertainties and approximation errors. With no full system testing and limited sub-system testings, petascale computing is certainly necessary to span both time and space scales and to reduce the uncertainty in the prediction of long-term reliability. This paper presents the necessary steps to develop predictive-science-based multiscale modeling and simulation system. The development of this system will be focused on the prediction of the long-term performance of a gyroscope microsystem. The environmental effects to be considered include radiation, thermo-mechanical cycling and shock. Since there will be many material performance issues, attention is restricted to creep resulting from thermal aging and radiation-enhanced mass diffusion, material instability due to radiation and thermo-mechanical cycling and damage and fracture due to shock. To meet these challenges, we aim to develop an integrated multiscale software analysis system that spans the length scales from the atomistic scale to the scale of the device. The proposed software system will include molecular mechanics, phase field evolution, micromechanics and continuum mechanics software, and the state-of-the-art model identification strategies where atomistic properties are calibrated by quantum calculations. We aim to predict the long-term (in excess of 20 years) integrity of the resonator, electrode base, multilayer metallic bonding pads, and vacuum seals in a prescribed mission. Although multiscale simulations are efficient in the sense that they focus the most computationally intensive models and methods on only the portions of the space time domain needed, the execution of the multiscale simulations associated with evaluating materials and device integrity for aerospace microsystems will require the application of petascale computing. A component-based software strategy will be used in the development of our massively parallel multiscale simulation system. This approach will allow us to take full advantage of existing single scale modeling components. An extensive, pervasive thrust in the software system development is verification, validation, and uncertainty quantification (UQ). Each component and the integrated software system need to be carefully verified. An UQ methodology that determines the quality of predictive information available from experimental measurements and packages the information in a form suitable for UQ at various scales needs to be developed. Experiments to validate the model at the nanoscale, microscale, and macroscale are proposed. The development of a petascale predictive-science-based multiscale modeling and simulation system will advance the field of predictive multiscale science so that it can be used to reliably analyze problems of unprecedented complexity, where limited testing resources can be adequately replaced by petascale computational power, advanced verification, validation, and UQ methodologies.

Progress in fast, accurate multi-scale climate simulations

DOE PAGES

Collins, W. D.; Johansen, H.; Evans, K. J.; ...

2015-06-01

We present a survey of physical and computational techniques that have the potential to contribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth with these computational improvements include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enablingmore » improved accuracy and fidelity in simulation of dynamics and allowing more complete representations of climate features at the global scale. At the same time, partnerships with computer science teams have focused on taking advantage of evolving computer architectures such as many-core processors and GPUs. As a result, approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.« less

Multiscale Electrodynamics/Time-Dependent Density Functional Theory Modeling of Coupled Plasmon/Molecule Excitations

NASA Astrophysics Data System (ADS)

Lopata, Kenneth; Smith, Holden

The coupled dynamics of molecular chromophores and plasmons at surface of metal nanostructures are important for a range of processes such as molecular sensing, light harvesting, and near-field photochemistry. Modeling these dynamics from first principles, however, is challenging, as the large system sizes precludes a purely quantum mechanical treatment. In this talk I will present an approach based on propagating the plasmonic currents and fields using electrodynamics (finite-difference time-domain) with each chromophore described using an isolated quantum sub-region embedded in the overall classical background. This approach can be readily parallelized over these quantum regions, which enables large multiscale simulations of tens or hundreds of dyes, each of which is described individually by real-time time-dependent density functional theory. Application to gold nanoparticles coated with malachite green and rhodamine 6G monolayers shows good agreement with experimentally measured coupling spectra, including the polariton peaks, as well as the plasmon and molecular depletions. This research was supported by the Louisiana Board of Regents Research Competitiveness Subprogram under Contract Number LEQSF(2014-17)-RD-A-0.

Tinker-HP: a massively parallel molecular dynamics package for multiscale simulations of large complex systems with advanced point dipole polarizable force fields† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc04531j

PubMed Central

Lagardère, Louis; Jolly, Luc-Henri; Lipparini, Filippo; Aviat, Félix; Stamm, Benjamin; Jing, Zhifeng F.; Harger, Matthew; Torabifard, Hedieh; Cisneros, G. Andrés; Schnieders, Michael J.; Gresh, Nohad; Maday, Yvon; Ren, Pengyu Y.; Ponder, Jay W.

2017-01-01

We present Tinker-HP, a massively MPI parallel package dedicated to classical molecular dynamics (MD) and to multiscale simulations, using advanced polarizable force fields (PFF) encompassing distributed multipoles electrostatics. Tinker-HP is an evolution of the popular Tinker package code that conserves its simplicity of use and its reference double precision implementation for CPUs. Grounded on interdisciplinary efforts with applied mathematics, Tinker-HP allows for long polarizable MD simulations on large systems up to millions of atoms. We detail in the paper the newly developed extension of massively parallel 3D spatial decomposition to point dipole polarizable models as well as their coupling to efficient Krylov iterative and non-iterative polarization solvers. The design of the code allows the use of various computer systems ranging from laboratory workstations to modern petascale supercomputers with thousands of cores. Tinker-HP proposes therefore the first high-performance scalable CPU computing environment for the development of next generation point dipole PFFs and for production simulations. Strategies linking Tinker-HP to Quantum Mechanics (QM) in the framework of multiscale polarizable self-consistent QM/MD simulations are also provided. The possibilities, performances and scalability of the software are demonstrated via benchmarks calculations using the polarizable AMOEBA force field on systems ranging from large water boxes of increasing size and ionic liquids to (very) large biosystems encompassing several proteins as well as the complete satellite tobacco mosaic virus and ribosome structures. For small systems, Tinker-HP appears to be competitive with the Tinker-OpenMM GPU implementation of Tinker. As the system size grows, Tinker-HP remains operational thanks to its access to distributed memory and takes advantage of its new algorithmic enabling for stable long timescale polarizable simulations. Overall, a several thousand-fold acceleration over a single-core computation is observed for the largest systems. The extension of the present CPU implementation of Tinker-HP to other computational platforms is discussed. PMID:29732110

Improving NASA's Multiscale Modeling Framework for Tropical Cyclone Climate Study

NASA Technical Reports Server (NTRS)

Shen, Bo-Wen; Nelson, Bron; Cheung, Samson; Tao, Wei-Kuo

2013-01-01

One of the current challenges in tropical cyclone (TC) research is how to improve our understanding of TC interannual variability and the impact of climate change on TCs. Recent advances in global modeling, visualization, and supercomputing technologies at NASA show potential for such studies. In this article, the authors discuss recent scalability improvement to the multiscale modeling framework (MMF) that makes it feasible to perform long-term TC-resolving simulations. The MMF consists of the finite-volume general circulation model (fvGCM), supplemented by a copy of the Goddard cumulus ensemble model (GCE) at each of the fvGCM grid points, giving 13,104 GCE copies. The original fvGCM implementation has a 1D data decomposition; the revised MMF implementation retains the 1D decomposition for most of the code, but uses a 2D decomposition for the massive copies of GCEs. Because the vast majority of computation time in the MMF is spent computing the GCEs, this approach can achieve excellent speedup without incurring the cost of modifying the entire code. Intelligent process mapping allows differing numbers of processes to be assigned to each domain for load balancing. The revised parallel implementation shows highly promising scalability, obtaining a nearly 80-fold speedup by increasing the number of cores from 30 to 3,335.

Tensor Arithmetic, Geometric and Mathematic Principles of Fluid Mechanics in Implementation of Direct Computational Experiments

NASA Astrophysics Data System (ADS)

Bogdanov, Alexander; Khramushin, Vasily

2016-02-01

The architecture of a digital computing system determines the technical foundation of a unified mathematical language for exact arithmetic-logical description of phenomena and laws of continuum mechanics for applications in fluid mechanics and theoretical physics. The deep parallelization of the computing processes results in functional programming at a new technological level, providing traceability of the computing processes with automatic application of multiscale hybrid circuits and adaptive mathematical models for the true reproduction of the fundamental laws of physics and continuum mechanics.

Exploiting multi-scale parallelism for large scale numerical modelling of laser wakefield accelerators

NASA Astrophysics Data System (ADS)

Fonseca, R. A.; Vieira, J.; Fiuza, F.; Davidson, A.; Tsung, F. S.; Mori, W. B.; Silva, L. O.

2013-12-01

A new generation of laser wakefield accelerators (LWFA), supported by the extreme accelerating fields generated in the interaction of PW-Class lasers and underdense targets, promises the production of high quality electron beams in short distances for multiple applications. Achieving this goal will rely heavily on numerical modelling to further understand the underlying physics and identify optimal regimes, but large scale modelling of these scenarios is computationally heavy and requires the efficient use of state-of-the-art petascale supercomputing systems. We discuss the main difficulties involved in running these simulations and the new developments implemented in the OSIRIS framework to address these issues, ranging from multi-dimensional dynamic load balancing and hybrid distributed/shared memory parallelism to the vectorization of the PIC algorithm. We present the results of the OASCR Joule Metric program on the issue of large scale modelling of LWFA, demonstrating speedups of over 1 order of magnitude on the same hardware. Finally, scalability to over ˜106 cores and sustained performance over ˜2 P Flops is demonstrated, opening the way for large scale modelling of LWFA scenarios.

The self-assembly of particles with isotropic interactions: Using DNA coated colloids to create designer nanomaterials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, R. B.; Dion, S.; Konigslow, K. von

Self-consistent field theory equations are presented that are suitable for use as a coarse-grained model for DNA coated colloids, polymer-grafted nanoparticles and other systems with approximately isotropic interactions. The equations are generalized for arbitrary numbers of chemically distinct colloids. The advantages and limitations of such a coarse-grained approach for DNA coated colloids are discussed, as are similarities with block copolymer self-assembly. In particular, preliminary results for three species self-assembly are presented that parallel results from a two dimensional ABC triblock copolymer phase. The possibility of incorporating crystallization, dynamics, inverse statistical mechanics and multiscale modelling techniques are discussed.

Multiscale measurement error models for aggregated small area health data.

PubMed

Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin

2016-08-01

Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates. © The Author(s) 2016.

GENESIS: a hybrid-parallel and multi-scale molecular dynamics simulator with enhanced sampling algorithms for biomolecular and cellular simulations.

PubMed

Jung, Jaewoon; Mori, Takaharu; Kobayashi, Chigusa; Matsunaga, Yasuhiro; Yoda, Takao; Feig, Michael; Sugita, Yuji

2015-07-01

GENESIS (Generalized-Ensemble Simulation System) is a new software package for molecular dynamics (MD) simulations of macromolecules. It has two MD simulators, called ATDYN and SPDYN. ATDYN is parallelized based on an atomic decomposition algorithm for the simulations of all-atom force-field models as well as coarse-grained Go-like models. SPDYN is highly parallelized based on a domain decomposition scheme, allowing large-scale MD simulations on supercomputers. Hybrid schemes combining OpenMP and MPI are used in both simulators to target modern multicore computer architectures. Key advantages of GENESIS are (1) the highly parallel performance of SPDYN for very large biological systems consisting of more than one million atoms and (2) the availability of various REMD algorithms (T-REMD, REUS, multi-dimensional REMD for both all-atom and Go-like models under the NVT, NPT, NPAT, and NPγT ensembles). The former is achieved by a combination of the midpoint cell method and the efficient three-dimensional Fast Fourier Transform algorithm, where the domain decomposition space is shared in real-space and reciprocal-space calculations. Other features in SPDYN, such as avoiding concurrent memory access, reducing communication times, and usage of parallel input/output files, also contribute to the performance. We show the REMD simulation results of a mixed (POPC/DMPC) lipid bilayer as a real application using GENESIS. GENESIS is released as free software under the GPLv2 licence and can be easily modified for the development of new algorithms and molecular models. WIREs Comput Mol Sci 2015, 5:310-323. doi: 10.1002/wcms.1220.

Multi-thread parallel algorithm for reconstructing 3D large-scale porous structures

NASA Astrophysics Data System (ADS)

Ju, Yang; Huang, Yaohui; Zheng, Jiangtao; Qian, Xu; Xie, Heping; Zhao, Xi

2017-04-01

Geomaterials inherently contain many discontinuous, multi-scale, geometrically irregular pores, forming a complex porous structure that governs their mechanical and transport properties. The development of an efficient reconstruction method for representing porous structures can significantly contribute toward providing a better understanding of the governing effects of porous structures on the properties of porous materials. In order to improve the efficiency of reconstructing large-scale porous structures, a multi-thread parallel scheme was incorporated into the simulated annealing reconstruction method. In the method, four correlation functions, which include the two-point probability function, the linear-path functions for the pore phase and the solid phase, and the fractal system function for the solid phase, were employed for better reproduction of the complex well-connected porous structures. In addition, a random sphere packing method and a self-developed pre-conditioning method were incorporated to cast the initial reconstructed model and select independent interchanging pairs for parallel multi-thread calculation, respectively. The accuracy of the proposed algorithm was evaluated by examining the similarity between the reconstructed structure and a prototype in terms of their geometrical, topological, and mechanical properties. Comparisons of the reconstruction efficiency of porous models with various scales indicated that the parallel multi-thread scheme significantly shortened the execution time for reconstruction of a large-scale well-connected porous model compared to a sequential single-thread procedure.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Antonelli, Perry Edward

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 willmore » 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.« less

Multiscale Modeling in Computational Biomechanics: Determining Computational Priorities and Addressing Current Challenges

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tawhai, Merryn; Bischoff, Jeff; Einstein, Daniel R.

2009-05-01

Abstract In this article, we describe some current multiscale modeling issues in computational biomechanics from the perspective of the musculoskeletal and respiratory systems and mechanotransduction. First, we outline the necessity of multiscale simulations in these biological systems. Then we summarize challenges inherent to multiscale biomechanics modeling, regardless of the subdiscipline, followed by computational challenges that are system-specific. We discuss some of the current tools that have been utilized to aid research in multiscale mechanics simulations, and the priorities to further the field of multiscale biomechanics computation.

A complete categorization of multiscale models of infectious disease systems.

PubMed

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.

Spatial adaptive sampling in multiscale simulation

NASA Astrophysics Data System (ADS)

Rouet-Leduc, Bertrand; Barros, Kipton; Cieren, Emmanuel; Elango, Venmugil; Junghans, Christoph; Lookman, Turab; Mohd-Yusof, Jamaludin; Pavel, Robert S.; Rivera, Axel Y.; Roehm, Dominic; McPherson, Allen L.; Germann, Timothy C.

2014-07-01

In a common approach to multiscale simulation, an incomplete set of macroscale equations must be supplemented with constitutive data provided by fine-scale simulation. Collecting statistics from these fine-scale simulations is typically the overwhelming computational cost. We reduce this cost by interpolating the results of fine-scale simulation over the spatial domain of the macro-solver. Unlike previous adaptive sampling strategies, we do not interpolate on the potentially very high dimensional space of inputs to the fine-scale simulation. Our approach is local in space and time, avoids the need for a central database, and is designed to parallelize well on large computer clusters. To demonstrate our method, we simulate one-dimensional elastodynamic shock propagation using the Heterogeneous Multiscale Method (HMM); we find that spatial adaptive sampling requires only ≈ 50 ×N0.14 fine-scale simulations to reconstruct the stress field at all N grid points. Related multiscale approaches, such as Equation Free methods, may also benefit from spatial adaptive sampling.

Development and parallelization of a direct numerical simulation to study the formation and transport of nanoparticle clusters in a viscous fluid

NASA Astrophysics Data System (ADS)

Sloan, Gregory James

The direct numerical simulation (DNS) offers the most accurate approach to modeling the behavior of a physical system, but carries an enormous computation cost. There exists a need for an accurate DNS to model the coupled solid-fluid system seen in targeted drug delivery (TDD), nanofluid thermal energy storage (TES), as well as other fields where experiments are necessary, but experiment design may be costly. A parallel DNS can greatly reduce the large computation times required, while providing the same results and functionality of the serial counterpart. A D2Q9 lattice Boltzmann method approach was implemented to solve the fluid phase. The use of domain decomposition with message passing interface (MPI) parallelism resulted in an algorithm that exhibits super-linear scaling in testing, which may be attributed to the caching effect. Decreased performance on a per-node basis for a fixed number of processes confirms this observation. A multiscale approach was implemented to model the behavior of nanoparticles submerged in a viscous fluid, and used to examine the mechanisms that promote or inhibit clustering. Parallelization of this model using a masterworker algorithm with MPI gives less-than-linear speedup for a fixed number of particles and varying number of processes. This is due to the inherent inefficiency of the master-worker approach. Lastly, these separate simulations are combined, and two-way coupling is implemented between the solid and fluid.

Modeling the nanoscale viscoelasticity of fluids by bridging non-Markovian fluctuating hydrodynamics and molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Voulgarakis, Nikolaos K.; Satish, Siddarth; Chu, Jhih-Wei

2009-12-01

A multiscale computational method is developed to model the nanoscale viscoelasticity of fluids by bridging non-Markovian fluctuating hydrodynamics (FHD) and molecular dynamics (MD) simulations. To capture the elastic responses that emerge at small length scales, we attach an additional rheological model parallel to the macroscopic constitutive equation of a fluid. The widely used linear Maxwell model is employed as a working choice; other models can be used as well. For a fluid that is Newtonian in the macroscopic limit, this approach results in a parallel Newtonian-Maxwell model. For water, argon, and an ionic liquid, the power spectrum of momentum field autocorrelation functions of the parallel Newtonian-Maxwell model agrees very well with those calculated from all-atom MD simulations. To incorporate thermal fluctuations, we generalize the equations of FHD to work with non-Markovian rheological models and colored noise. The fluctuating stress tensor (white noise) is integrated in time in the same manner as its dissipative counterpart and numerical simulations indicate that this approach accurately preserves the set temperature in a FHD simulation. By mapping position and velocity vectors in the molecular representation onto field variables, we bridge the non-Markovian FHD with atomistic MD simulations. Through this mapping, we quantitatively determine the transport coefficients of the parallel Newtonian-Maxwell model for water and argon from all-atom MD simulations. For both fluids, a significant enhancement in elastic responses is observed as the wave number of hydrodynamic modes is reduced to a few nanometers. The mapping from particle to field representations and the perturbative strategy of developing constitutive equations provide a useful framework for modeling the nanoscale viscoelasticity of fluids.

Microphysics in Multi-scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

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.

Energy limits of electron acceleration in the plasma sheet during substorms: A case study with the Magnetospheric Multiscale (MMS) mission

NASA Astrophysics Data System (ADS)

Turner, D. L.; Fennell, J. F.; Blake, J. B.; Clemmons, J. H.; Mauk, B. H.; Cohen, I. J.; Jaynes, A. N.; Craft, J. V.; Wilder, F. D.; Baker, D. N.; Reeves, G. D.; Gershman, D. J.; Avanov, L. A.; Dorelli, J. C.; Giles, B. L.; Pollock, C. J.; Schmid, D.; Nakamura, R.; Strangeway, R. J.; Russell, C. T.; Artemyev, A. V.; Runov, A.; Angelopoulos, V.; Spence, H. E.; Torbert, R. B.; Burch, J. L.

2016-08-01

We present multipoint observations of earthward moving dipolarization fronts and energetic particle injections from NASA's Magnetospheric Multiscale mission with a focus on electron acceleration. From a case study during a substorm on 02 August 2015, we find that electrons are only accelerated over a finite energy range, from a lower energy threshold at 7-9 keV up to an upper energy cutoff in the hundreds of keV range. At energies lower than the threshold energy, electron fluxes decrease, potentially due to precipitation by strong parallel electrostatic wavefields or initial sources in the lobes. Electrons at energies higher than the threshold are accelerated cumulatively by a series of impulsive magnetic dipolarization events. This case demonstrates how the upper energy cutoff increases, in this case from 130 keV to >500 keV, with each dipolarization/injection during sustained activity. We also present a simple model accounting for these energy limits that reveals that electron energization is dominated by betatron acceleration.

Energy Limits of Electron Acceleration in the Plasma Sheet During Substorms: A Case Study with the Magnetospheric Multiscale (MMS) Mission

NASA Technical Reports Server (NTRS)

Turner, D. L.; Fennell, J. F.; Blake, J. B.; Clemmons, J. H.; Mauk, B. H.; Cohen, I. J.; Jaynes, A. N.; Craft, J. V.; Wilder, F. D.; Baker, D. N.;

Community Multiscale Air Quality Model

EPA Science Inventory

The U.S. EPA developed the Community Multiscale Air Quality (CMAQ) system to apply a “one atmosphere” multiscale and multi-pollutant modeling approach based mainly on the “first principles” description of the atmosphere. The multiscale capability is supported by the governing di...

Anisotropic transverse mixing and its effect on reaction rates in multi-scale, 3D heterogeneous porous media

NASA Astrophysics Data System (ADS)

Engdahl, N. B.

2016-12-01

Mixing rates in porous media have been a heavily research topic in recent years covering analytic, random, and structured fields. However, there are some persistent assumptions and common features to these models that raise some questions about the generality of the results. One of these commonalities is the orientation of the flow field with respect to the heterogeneity structure, which are almost always defined to be parallel each other if there is an elongated axis of permeability correlation. Given the vastly different tortuosities for flow parallel to bedding and flow transverse to bedding, this assumption of parallel orientation may have significant effects on reaction rates when natural flows deviate from this assumed setting. This study investigates the role of orientation on mixing and reaction rates in multi-scale, 3D heterogeneous porous media with varying degrees of anisotropy in the correlation structure. Ten realizations of a small flow field, with three anisotropy levels, were simulated for flow parallel and transverse to bedding. Transport was simulated in each model with an advective-diffusive random walk and reactions were simulated using the chemical Langevin equation. The reaction system is a vertically segregated, transverse mixing problem between two mobile reactants. The results show that different transport behaviors and reaction rates are obtained by simply rotating the direction of flow relative to bedding, even when the net flux in both directions is the same. This kind of behavior was observed for three different weightings of the initial condition: 1) uniform, 2) flux-based, and 3) travel time based. The different schemes resulted in 20-50% more mass formation in the transverse direction than the longitudinal. The greatest variability in mass was observed for the flux weights and these were proportionate to the level of anisotropy. The implications of this study are that flux or travel time weights do not provide any guarantee of a fair comparison in this kind of a mixing scenario and that the role of directional tendencies on reaction rates can be significant. Further, it may be necessary to include anisotropy in future upscaled models to create robust methods that give representative reaction rates for any flow direction relative to geologic bedding.

Novel Multiscale Modeling Tool Applied to Pseudomonas aeruginosa Biofilm Formation

PubMed Central

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. PMID:24147108

Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.

PubMed

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.

Advanced Technology and Mitigation (ATDM) SPARC Re-Entry Code Fiscal Year 2017 Progress and Accomplishments for ECP.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crozier, Paul; Howard, Micah; Rider, William J.

The SPARC (Sandia Parallel Aerodynamics and Reentry Code) will provide nuclear weapon qualification evidence for the random vibration and thermal environments created by re-entry of a warhead into the earth’s atmosphere. SPARC incorporates the innovative approaches of ATDM projects on several fronts including: effective harnessing of heterogeneous compute nodes using Kokkos, exascale-ready parallel scalability through asynchronous multi-tasking, uncertainty quantification through Sacado integration, implementation of state-of-the-art reentry physics and multiscale models, use of advanced verification and validation methods, and enabling of improved workflows for users. SPARC is being developed primarily for the Department of Energy nuclear weapon program, with additional developmentmore » and use of the code is being supported by the Department of Defense for conventional weapons programs.« less

An approach to multiscale modelling with graph grammars.

PubMed

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.

An approach to multiscale modelling with graph grammars

PubMed Central

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

2014-01-01

Background and Aims 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. Methods 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. Key Results 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. Conclusions 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. PMID:25134929

Towards a Multiscale Approach to Cybersecurity Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hogan, Emilie A.; Hui, Peter SY; Choudhury, Sutanay

2013-11-12

We propose a multiscale approach to modeling cyber networks, with the goal of capturing a view of the network and overall situational awareness with respect to a few key properties--- connectivity, distance, and centrality--- for a system under an active attack. We focus on theoretical and algorithmic foundations of multiscale graphs, coming from an algorithmic perspective, with the goal of modeling cyber system defense as a specific use case scenario. We first define a notion of \\emph{multiscale} graphs, in contrast with their well-studied single-scale counterparts. We develop multiscale analogs of paths and distance metrics. As a simple, motivating example ofmore » a common metric, we present a multiscale analog of the all-pairs shortest-path problem, along with a multiscale analog of a well-known algorithm which solves it. From a cyber defense perspective, this metric might be used to model the distance from an attacker's position in the network to a sensitive machine. In addition, we investigate probabilistic models of connectivity. These models exploit the hierarchy to quantify the likelihood that sensitive targets might be reachable from compromised nodes. We believe that our novel multiscale approach to modeling cyber-physical systems will advance several aspects of cyber defense, specifically allowing for a more efficient and agile approach to defending these systems.« less

Filters for Improvement of Multiscale Data from Atomistic Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gardner, David J.; Reynolds, Daniel R.

Multiscale computational models strive to produce accurate and efficient numerical simulations of systems involving interactions across multiple spatial and temporal scales that typically differ by several orders of magnitude. Some such models utilize a hybrid continuum-atomistic approach combining continuum approximations with first-principles-based atomistic models to capture multiscale behavior. By following the heterogeneous multiscale method framework for developing multiscale computational models, unknown continuum scale data can be computed from an atomistic model. Concurrently coupling the two models requires performing numerous atomistic simulations which can dominate the computational cost of the method. Furthermore, when the resulting continuum data is noisy due tomore » sampling error, stochasticity in the model, or randomness in the initial conditions, filtering can result in significant accuracy gains in the computed multiscale data without increasing the size or duration of the atomistic simulations. In this work, we demonstrate the effectiveness of spectral filtering for increasing the accuracy of noisy multiscale data obtained from atomistic simulations. Moreover, we present a robust and automatic method for closely approximating the optimum level of filtering in the case of additive white noise. By improving the accuracy of this filtered simulation data, it leads to a dramatic computational savings by allowing for shorter and smaller atomistic simulations to achieve the same desired multiscale simulation precision.« less

Filters for Improvement of Multiscale Data from Atomistic Simulations

DOE PAGES

Gardner, David J.; Reynolds, Daniel R.

2017-01-05

Multiscale computational models strive to produce accurate and efficient numerical simulations of systems involving interactions across multiple spatial and temporal scales that typically differ by several orders of magnitude. Some such models utilize a hybrid continuum-atomistic approach combining continuum approximations with first-principles-based atomistic models to capture multiscale behavior. By following the heterogeneous multiscale method framework for developing multiscale computational models, unknown continuum scale data can be computed from an atomistic model. Concurrently coupling the two models requires performing numerous atomistic simulations which can dominate the computational cost of the method. Furthermore, when the resulting continuum data is noisy due tomore » sampling error, stochasticity in the model, or randomness in the initial conditions, filtering can result in significant accuracy gains in the computed multiscale data without increasing the size or duration of the atomistic simulations. In this work, we demonstrate the effectiveness of spectral filtering for increasing the accuracy of noisy multiscale data obtained from atomistic simulations. Moreover, we present a robust and automatic method for closely approximating the optimum level of filtering in the case of additive white noise. By improving the accuracy of this filtered simulation data, it leads to a dramatic computational savings by allowing for shorter and smaller atomistic simulations to achieve the same desired multiscale simulation precision.« less

GENESIS: a hybrid-parallel and multi-scale molecular dynamics simulator with enhanced sampling algorithms for biomolecular and cellular simulations

PubMed Central

Jung, Jaewoon; Mori, Takaharu; Kobayashi, Chigusa; Matsunaga, Yasuhiro; Yoda, Takao; Feig, Michael; Sugita, Yuji

2015-01-01

GENESIS (Generalized-Ensemble Simulation System) is a new software package for molecular dynamics (MD) simulations of macromolecules. It has two MD simulators, called ATDYN and SPDYN. ATDYN is parallelized based on an atomic decomposition algorithm for the simulations of all-atom force-field models as well as coarse-grained Go-like models. SPDYN is highly parallelized based on a domain decomposition scheme, allowing large-scale MD simulations on supercomputers. Hybrid schemes combining OpenMP and MPI are used in both simulators to target modern multicore computer architectures. Key advantages of GENESIS are (1) the highly parallel performance of SPDYN for very large biological systems consisting of more than one million atoms and (2) the availability of various REMD algorithms (T-REMD, REUS, multi-dimensional REMD for both all-atom and Go-like models under the NVT, NPT, NPAT, and NPγT ensembles). The former is achieved by a combination of the midpoint cell method and the efficient three-dimensional Fast Fourier Transform algorithm, where the domain decomposition space is shared in real-space and reciprocal-space calculations. Other features in SPDYN, such as avoiding concurrent memory access, reducing communication times, and usage of parallel input/output files, also contribute to the performance. We show the REMD simulation results of a mixed (POPC/DMPC) lipid bilayer as a real application using GENESIS. GENESIS is released as free software under the GPLv2 licence and can be easily modified for the development of new algorithms and molecular models. WIREs Comput Mol Sci 2015, 5:310–323. doi: 10.1002/wcms.1220 PMID:26753008

Facing the challenges of multiscale modelling of bacterial and fungal pathogen–host interactions

PubMed Central

Schleicher, Jana; Conrad, Theresia; Gustafsson, Mika; Cedersund, Gunnar; Guthke, Reinhard

2017-01-01

Abstract Recent and rapidly evolving progress on high-throughput measurement techniques and computational performance has led to the emergence of new disciplines, such as systems medicine and translational systems biology. At the core of these disciplines lies the desire to produce multiscale models: mathematical models that integrate multiple scales of biological organization, ranging from molecular, cellular and tissue models to organ, whole-organism and population scale models. Using such models, hypotheses can systematically be tested. In this review, we present state-of-the-art multiscale modelling of bacterial and fungal infections, considering both the pathogen and host as well as their interaction. Multiscale modelling of the interactions of bacteria, especially Mycobacterium tuberculosis, with the human host is quite advanced. In contrast, models for fungal infections are still in their infancy, in particular regarding infections with the most important human pathogenic fungi, Candida albicans and Aspergillus fumigatus. We reflect on the current availability of computational approaches for multiscale modelling of host–pathogen interactions and point out current challenges. Finally, we provide an outlook for future requirements of multiscale modelling. PMID:26857943

ONE-ATMOSPHERE DYNAMICS DESCRIPTION IN THE MODELS-3 COMMUNITY MULTI-SCALE QUALITY (CMAQ) MODELING SYSTEM

EPA Science Inventory

This paper proposes a general procedure to link meteorological data with air quality models, such as U.S. EPA's Models-3 Community Multi-scale Air Quality (CMAQ) modeling system. CMAQ is intended to be used for studying multi-scale (urban and regional) and multi-pollutant (ozon...

Integrating Multiscale Modeling with Drug Effects for Cancer Treatment.

PubMed

Li, Xiangfang L; Oduola, Wasiu O; Qian, Lijun; Dougherty, Edward R

2015-01-01

In this paper, we review multiscale modeling for cancer treatment with the incorporation of drug effects from an applied system's pharmacology perspective. Both the classical pharmacology and systems biology are inherently quantitative; however, systems biology focuses more on networks and multi factorial controls over biological processes rather than on drugs and targets in isolation, whereas systems pharmacology has a strong focus on studying drugs with regard to the pharmacokinetic (PK) and pharmacodynamic (PD) relations accompanying drug interactions with multiscale physiology as well as the prediction of dosage-exposure responses and economic potentials of drugs. Thus, it requires multiscale methods to address the need for integrating models from the molecular levels to the cellular, tissue, and organism levels. It is a common belief that tumorigenesis and tumor growth can be best understood and tackled by employing and integrating a multifaceted approach that includes in vivo and in vitro experiments, in silico models, multiscale tumor modeling, continuous/discrete modeling, agent-based modeling, and multiscale modeling with PK/PD drug effect inputs. We provide an example application of multiscale modeling employing stochastic hybrid system for a colon cancer cell line HCT-116 with the application of Lapatinib drug. It is observed that the simulation results are similar to those observed from the setup of the wet-lab experiments at the Translational Genomics Research Institute.

Combinatorial Algorithms to Enable Computational Science and Engineering: Work from the CSCAPES Institute

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boman, Erik G.; Catalyurek, Umit V.; Chevalier, Cedric

2015-01-16

This final progress report summarizes the work accomplished at the Combinatorial Scientific Computing and Petascale Simulations Institute. We developed Zoltan, a parallel mesh partitioning library that made use of accurate hypergraph models to provide load balancing in mesh-based computations. We developed several graph coloring algorithms for computing Jacobian and Hessian matrices and organized them into a software package called ColPack. We developed parallel algorithms for graph coloring and graph matching problems, and also designed multi-scale graph algorithms. Three PhD students graduated, six more are continuing their PhD studies, and four postdoctoral scholars were advised. Six of these students and Fellowsmore » have joined DOE Labs (Sandia, Berkeley), as staff scientists or as postdoctoral scientists. We also organized the SIAM Workshop on Combinatorial Scientific Computing (CSC) in 2007, 2009, and 2011 to continue to foster the CSC community.« less

Magnetospheric Multiscale Satellites Observations of Parallel Electric Fields Associated with Magnetic Reconnection.

PubMed

Ergun, R E; Goodrich, K A; Wilder, F D; Holmes, J C; Stawarz, J E; Eriksson, S; Sturner, A P; Malaspina, D M; Usanova, M E; Torbert, R B; Lindqvist, P-A; Khotyaintsev, Y; Burch, J L; Strangeway, R J; Russell, C T; Pollock, C J; Giles, B L; Hesse, M; Chen, L J; Lapenta, G; Goldman, M V; Newman, D L; Schwartz, S J; Eastwood, J P; Phan, T D; Mozer, F S; Drake, J; Shay, M A; Cassak, P A; Nakamura, R; Marklund, G

2016-06-10

We report observations from the Magnetospheric Multiscale satellites of parallel electric fields (E_{∥}) associated with magnetic reconnection in the subsolar region of the Earth's magnetopause. E_{∥} events near the electron diffusion region have amplitudes on the order of 100  mV/m, which are significantly larger than those predicted for an antiparallel reconnection electric field. This Letter addresses specific types of E_{∥} events, which appear as large-amplitude, near unipolar spikes that are associated with tangled, reconnected magnetic fields. These E_{∥} events are primarily in or near a current layer near the separatrix and are interpreted to be double layers that may be responsible for secondary reconnection in tangled magnetic fields or flux ropes. These results are telling of the three-dimensional nature of magnetopause reconnection and indicate that magnetopause reconnection may be often patchy and/or drive turbulence along the separatrix that results in flux ropes and/or tangled magnetic fields.

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

NASA Astrophysics Data System (ADS)

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.

A real-time multi-scale 2D Gaussian filter based on FPGA

NASA Astrophysics Data System (ADS)

Luo, Haibo; Gai, Xingqin; Chang, Zheng; Hui, Bin

2014-11-01

Multi-scale 2-D Gaussian filter has been widely used in feature extraction (e.g. SIFT, edge etc.), image segmentation, image enhancement, image noise removing, multi-scale shape description etc. However, their computational complexity remains an issue for real-time image processing systems. Aimed at this problem, we propose a framework of multi-scale 2-D Gaussian filter based on FPGA in this paper. Firstly, a full-hardware architecture based on parallel pipeline was designed to achieve high throughput rate. Secondly, in order to save some multiplier, the 2-D convolution is separated into two 1-D convolutions. Thirdly, a dedicate first in first out memory named as CAFIFO (Column Addressing FIFO) was designed to avoid the error propagating induced by spark on clock. Finally, a shared memory framework was designed to reduce memory costs. As a demonstration, we realized a 3 scales 2-D Gaussian filter on a single ALTERA Cyclone III FPGA chip. Experimental results show that, the proposed framework can computing a Multi-scales 2-D Gaussian filtering within one pixel clock period, is further suitable for real-time image processing. Moreover, the main principle can be popularized to the other operators based on convolution, such as Gabor filter, Sobel operator and so on.

Petascale computation performance of lightweight multiscale cardiac models using hybrid programming models.

PubMed

Pope, Bernard J; Fitch, Blake G; Pitman, Michael C; Rice, John J; Reumann, Matthias

2011-01-01

Future multiscale and multiphysics models must use the power of high performance computing (HPC) systems to enable research into human disease, translational medical science, and treatment. Previously we showed that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message passing processes (e.g. the message passing interface (MPI)) with multithreading (e.g. OpenMP, POSIX pthreads). The objective of this work is to compare the performance of such hybrid programming models when applied to the simulation of a lightweight multiscale cardiac model. Our results show that the hybrid models do not perform favourably when compared to an implementation using only MPI which is in contrast to our results using complex physiological models. Thus, with regards to lightweight multiscale cardiac models, the user may not need to increase programming complexity by using a hybrid programming approach. However, considering that model complexity will increase as well as the HPC system size in both node count and number of cores per node, it is still foreseeable that we will achieve faster than real time multiscale cardiac simulations on these systems using hybrid programming models.

Collaborative Simulation Grid: Multiscale Quantum-Mechanical/Classical Atomistic Simulations on Distributed PC Clusters in the US and Japan

NASA Technical Reports Server (NTRS)

Kikuchi, Hideaki; Kalia, Rajiv; Nakano, Aiichiro; Vashishta, Priya; Iyetomi, Hiroshi; Ogata, Shuji; Kouno, Takahisa; Shimojo, Fuyuki; Tsuruta, Kanji; Saini, Subhash;

Vehicle track segmentation using higher order random fields

DOE PAGES

Quach, Tu -Thach

2017-01-09

Here, we present an approach to segment vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times. The approach uses multiscale higher order random field models to capture track statistics, such as curvatures and their parallel nature, that are not currently utilized in existing methods. These statistics are encoded as 3-by-3 patterns at different scales. The model can complete disconnected tracks often caused by sensor noise and various environmental effects. Coupling the model with a simple classifier, our approach is effective at segmenting salient tracks. We improve the F-measure onmore » a standard vehicle track data set to 0.963, up from 0.897 obtained by the current state-of-the-art method.« less

Vehicle track segmentation using higher order random fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quach, Tu -Thach

Here, we present an approach to segment vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times. The approach uses multiscale higher order random field models to capture track statistics, such as curvatures and their parallel nature, that are not currently utilized in existing methods. These statistics are encoded as 3-by-3 patterns at different scales. The model can complete disconnected tracks often caused by sensor noise and various environmental effects. Coupling the model with a simple classifier, our approach is effective at segmenting salient tracks. We improve the F-measure onmore » a standard vehicle track data set to 0.963, up from 0.897 obtained by the current state-of-the-art method.« less

Multiscale Materials Modeling Workshop Summary

DOT National Transportation Integrated Search

2013-12-01

This report summarizes a 2-day workshop held to share information on multiscale material modeling. The aim was to gain expert feedback on the state of the art and identify Exploratory Advanced Research (EAR) Program opportunities for multiscale mater...

Multiscale molecular dynamics/hydrodynamics implementation of two dimensional "Mercedes Benz" water model

NASA Astrophysics Data System (ADS)

Scukins, A.; Nerukh, D.; Pavlov, E.; Karabasov, S.; Markesteijn, A.

2015-09-01

A multiscale Molecular Dynamics/Hydrodynamics implementation of the 2D Mercedes Benz (MB or BN2D) [1] water model is developed and investigated. The concept and the governing equations of multiscale coupling together with the results of the two-way coupling implementation are reported. The sensitivity of the multiscale model for obtaining macroscopic and microscopic parameters of the system, such as macroscopic density and velocity fluctuations, radial distribution and velocity autocorrelation functions of MB particles, is evaluated. Critical issues for extending the current model to large systems are discussed.

Multiscale Cancer Modeling

PubMed Central

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

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

NASA Astrophysics Data System (ADS)

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.

Energy limits of electron acceleration in the plasma sheet during substorms: A case study with the Magnetospheric Multiscale (MMS) mission

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turner, Drew Lawson; Fennell, J. F.; Blake, J. B.

Here, we present multipoint observations of earthward moving dipolarization fronts and energetic particle injections from NASA's Magnetospheric Multiscale mission with a focus on electron acceleration. From a case study during a substorm on 02 August 2015, we find that electrons are only accelerated over a finite energy range, from a lower energy threshold at ~7–9 keV up to an upper energy cutoff in the hundreds of keV range. At energies lower than the threshold energy, electron fluxes decrease, potentially due to precipitation by strong parallel electrostatic wavefields or initial sources in the lobes. Electrons at energies higher than the thresholdmore » are accelerated cumulatively by a series of impulsive magnetic dipolarization events. This case demonstrates how the upper energy cutoff increases, in this case from ~130 keV to >500 keV, with each dipolarization/injection during sustained activity. We also present a simple model accounting for these energy limits that reveals that electron energization is dominated by betatron acceleration.« less

Energy limits of electron acceleration in the plasma sheet during substorms: A case study with the Magnetospheric Multiscale (MMS) mission

DOE PAGES

Turner, Drew Lawson; Fennell, J. F.; Blake, J. B.; ...

2016-08-01

Here, we present multipoint observations of earthward moving dipolarization fronts and energetic particle injections from NASA's Magnetospheric Multiscale mission with a focus on electron acceleration. From a case study during a substorm on 02 August 2015, we find that electrons are only accelerated over a finite energy range, from a lower energy threshold at ~7–9 keV up to an upper energy cutoff in the hundreds of keV range. At energies lower than the threshold energy, electron fluxes decrease, potentially due to precipitation by strong parallel electrostatic wavefields or initial sources in the lobes. Electrons at energies higher than the thresholdmore » are accelerated cumulatively by a series of impulsive magnetic dipolarization events. This case demonstrates how the upper energy cutoff increases, in this case from ~130 keV to >500 keV, with each dipolarization/injection during sustained activity. We also present a simple model accounting for these energy limits that reveals that electron energization is dominated by betatron acceleration.« less

An analysis platform for multiscale hydrogeologic modeling with emphasis on hybrid multiscale methods.

PubMed

Scheibe, Timothy D; Murphy, Ellyn M; Chen, Xingyuan; Rice, Amy K; Carroll, Kenneth C; Palmer, Bruce J; Tartakovsky, Alexandre M; Battiato, Ilenia; Wood, Brian D

2015-01-01

One of the most significant challenges faced by hydrogeologic modelers is the disparity between the spatial and temporal scales at which fundamental flow, transport, and reaction processes can best be understood and quantified (e.g., microscopic to pore scales and seconds to days) and at which practical model predictions are needed (e.g., plume to aquifer scales and years to centuries). While the multiscale nature of hydrogeologic problems is widely recognized, technological limitations in computation and characterization restrict most practical modeling efforts to fairly coarse representations of heterogeneous properties and processes. For some modern problems, the necessary level of simplification is such that model parameters may lose physical meaning and model predictive ability is questionable for any conditions other than those to which the model was calibrated. Recently, there has been broad interest across a wide range of scientific and engineering disciplines in simulation approaches that more rigorously account for the multiscale nature of systems of interest. In this article, we review a number of such approaches and propose a classification scheme for defining different types of multiscale simulation methods and those classes of problems to which they are most applicable. Our classification scheme is presented in terms of a flowchart (Multiscale Analysis Platform), and defines several different motifs of multiscale simulation. Within each motif, the member methods are reviewed and example applications are discussed. We focus attention on hybrid multiscale methods, in which two or more models with different physics described at fundamentally different scales are directly coupled within a single simulation. Very recently these methods have begun to be applied to groundwater flow and transport simulations, and we discuss these applications in the context of our classification scheme. As computational and characterization capabilities continue to improve, we envision that hybrid multiscale modeling will become more common and also a viable alternative to conventional single-scale models in the near future. © 2014, National Ground Water Association.

Kinetic-scale fluctuations resolved with the Fast Plasma Investigation on NASA's Magnetospheric Multiscale mission.

NASA Astrophysics Data System (ADS)

Gershman, D. J.; Figueroa-Vinas, A.; Dorelli, J.; Goldstein, M. L.; Shuster, J. R.; Avanov, L. A.; Boardsen, S. A.; Stawarz, J. E.; Schwartz, S. J.; Schiff, C.; Lavraud, B.; Saito, Y.; Paterson, W. R.; Giles, B. L.; Pollock, C. J.; Strangeway, R. J.; Russell, C. T.; Torbert, R. B.; Moore, T. E.; Burch, J. L.

2017-12-01

Measurements from the Fast Plasma Investigation (FPI) on NASA's Magnetospheric Multiscale (MMS) mission have enabled unprecedented analyses of kinetic-scale plasma physics. FPI regularly provides estimates of current density and pressure gradients of sufficient accuracy to evaluate the relative contribution of terms in plasma equations of motion. In addition, high-resolution three-dimensional velocity distribution functions of both ions and electrons provide new insights into kinetic-scale processes. As an example, for a monochromatic kinetic Alfven wave (KAW) we find non-zero, but out-of-phase parallel current density and electric field fluctuations, providing direct confirmation of the conservative energy exchange between the wave field and particles. In addition, we use fluctuations in current density and magnetic field to calculate the perpendicular and parallel wavelengths of the KAW. Furthermore, examination of the electron velocity distribution inside the KAW reveals a population of electrons non-linearly trapped in the kinetic-scale magnetic mirror formed between successive wave peaks. These electrons not only contribute to the wave's parallel electric field but also account for over half of the density fluctuations within the wave, supplying an unexpected mechanism for maintaining quasi-neutrality in a KAW. Finally, we demonstrate that the employed wave vector determination technique is also applicable to broadband fluctuations found in Earth's turbulent magnetosheath.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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

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

DOE PAGES

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

2018-02-04

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

An Analysis Platform for Multiscale Hydrogeologic Modeling with Emphasis on Hybrid Multiscale Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scheibe, Timothy D.; Murphy, Ellyn M.; Chen, Xingyuan

2015-01-01

One of the most significant challenges facing hydrogeologic modelers is the disparity between those spatial and temporal scales at which fundamental flow, transport and reaction processes can best be understood and quantified (e.g., microscopic to pore scales, seconds to days) and those at which practical model predictions are needed (e.g., plume to aquifer scales, years to centuries). While the multiscale nature of hydrogeologic problems is widely recognized, technological limitations in computational and characterization restrict most practical modeling efforts to fairly coarse representations of heterogeneous properties and processes. For some modern problems, the necessary level of simplification is such that modelmore » parameters may lose physical meaning and model predictive ability is questionable for any conditions other than those to which the model was calibrated. Recently, there has been broad interest across a wide range of scientific and engineering disciplines in simulation approaches that more rigorously account for the multiscale nature of systems of interest. In this paper, we review a number of such approaches and propose a classification scheme for defining different types of multiscale simulation methods and those classes of problems to which they are most applicable. Our classification scheme is presented in terms of a flow chart (Multiscale Analysis Platform or MAP), and defines several different motifs of multiscale simulation. Within each motif, the member methods are reviewed and example applications are discussed. We focus attention on hybrid multiscale methods, in which two or more models with different physics described at fundamentally different scales are directly coupled within a single simulation. Very recently these methods have begun to be applied to groundwater flow and transport simulations, and we discuss these applications in the context of our classification scheme. As computational and characterization capabilities continue to improve, we envision that hybrid multiscale modeling will become more common and may become a viable alternative to conventional single-scale models in the near future.« less

Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

PubMed Central

Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.

2015-01-01

Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

Multiscale hidden Markov models for photon-limited imaging

NASA Astrophysics Data System (ADS)

Nowak, Robert D.

1999-06-01

Photon-limited image analysis is often hindered by low signal-to-noise ratios. A novel Bayesian multiscale modeling and analysis method is developed in this paper to assist in these challenging situations. In addition to providing a very natural and useful framework for modeling an d processing images, Bayesian multiscale analysis is often much less computationally demanding compared to classical Markov random field models. This paper focuses on a probabilistic graph model called the multiscale hidden Markov model (MHMM), which captures the key inter-scale dependencies present in natural image intensities. The MHMM framework presented here is specifically designed for photon-limited imagin applications involving Poisson statistics, and applications to image intensity analysis are examined.

Multiscale modelling in immunology: a review.

PubMed

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.

PFLOTRAN User Manual: A Massively Parallel Reactive Flow and Transport Model for Describing Surface and Subsurface Processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lichtner, Peter C.; Hammond, Glenn E.; Lu, Chuan

PFLOTRAN solves a system of generally nonlinear partial differential equations describing multi-phase, multicomponent and multiscale reactive flow and transport in porous materials. The code is designed to run on massively parallel computing architectures as well as workstations and laptops (e.g. Hammond et al., 2011). Parallelization is achieved through domain decomposition using the PETSc (Portable Extensible Toolkit for Scientific Computation) libraries for the parallelization framework (Balay et al., 1997). PFLOTRAN has been developed from the ground up for parallel scalability and has been run on up to 218 processor cores with problem sizes up to 2 billion degrees of freedom. Writtenmore » in object oriented Fortran 90, the code requires the latest compilers compatible with Fortran 2003. At the time of this writing this requires gcc 4.7.x, Intel 12.1.x and PGC compilers. As a requirement of running problems with a large number of degrees of freedom, PFLOTRAN allows reading input data that is too large to fit into memory allotted to a single processor core. The current limitation to the problem size PFLOTRAN can handle is the limitation of the HDF5 file format used for parallel IO to 32 bit integers. Noting that 2 32 = 4; 294; 967; 296, this gives an estimate of the maximum problem size that can be currently run with PFLOTRAN. Hopefully this limitation will be remedied in the near future.« less

Performance of distributed multiscale simulations

PubMed Central

Borgdorff, J.; Ben Belgacem, M.; Bona-Casas, C.; Fazendeiro, L.; Groen, D.; Hoenen, O.; Mizeranschi, A.; Suter, J. L.; Coster, D.; Coveney, P. V.; Dubitzky, W.; Hoekstra, A. G.; Strand, P.; Chopard, B.

2014-01-01

Multiscale simulations model phenomena across natural scales using monolithic or component-based code, running on local or distributed resources. In this work, we investigate the performance of distributed multiscale computing of component-based models, guided by six multiscale applications with different characteristics and from several disciplines. Three modes of distributed multiscale computing are identified: supplementing local dependencies with large-scale resources, load distribution over multiple resources, and load balancing of small- and large-scale resources. We find that the first mode has the apparent benefit of increasing simulation speed, and the second mode can increase simulation speed if local resources are limited. Depending on resource reservation and model coupling topology, the third mode may result in a reduction of resource consumption. PMID:24982258

Coarse-grained component concurrency in Earth system modeling: parallelizing atmospheric radiative transfer in the GFDL AM3 model using the Flexible Modeling System coupling framework

NASA Astrophysics Data System (ADS)

Balaji, V.; Benson, Rusty; Wyman, Bruce; Held, Isaac

2016-10-01

Climate models represent a large variety of processes on a variety of timescales and space scales, a canonical example of multi-physics multi-scale modeling. Current hardware trends, such as Graphical Processing Units (GPUs) and Many Integrated Core (MIC) chips, are based on, at best, marginal increases in clock speed, coupled with vast increases in concurrency, particularly at the fine grain. Multi-physics codes face particular challenges in achieving fine-grained concurrency, as different physics and dynamics components have different computational profiles, and universal solutions are hard to come by. We propose here one approach for multi-physics codes. These codes are typically structured as components interacting via software frameworks. The component structure of a typical Earth system model consists of a hierarchical and recursive tree of components, each representing a different climate process or dynamical system. This recursive structure generally encompasses a modest level of concurrency at the highest level (e.g., atmosphere and ocean on different processor sets) with serial organization underneath. We propose to extend concurrency much further by running more and more lower- and higher-level components in parallel with each other. Each component can further be parallelized on the fine grain, potentially offering a major increase in the scalability of Earth system models. We present here first results from this approach, called coarse-grained component concurrency, or CCC. Within the Geophysical Fluid Dynamics Laboratory (GFDL) Flexible Modeling System (FMS), the atmospheric radiative transfer component has been configured to run in parallel with a composite component consisting of every other atmospheric component, including the atmospheric dynamics and all other atmospheric physics components. We will explore the algorithmic challenges involved in such an approach, and present results from such simulations. Plans to achieve even greater levels of coarse-grained concurrency by extending this approach within other components, such as the ocean, will be discussed.

Multiscale Modeling in the Clinic: Drug Design and Development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clancy, Colleen E.; An, Gary; Cannon, William R.

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 tomore » 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.« less

The fusion code XGC: Enabling kinetic study of multi-scale edge turbulent transport in ITER [Book Chapter

DOE Office of Scientific and Technical Information (OSTI.GOV)

D'Azevedo, Eduardo; Abbott, Stephen; Koskela, Tuomas

The XGC fusion gyrokinetic code combines state-of-the-art, portable computational and algorithmic technologies to enable complicated multiscale simulations of turbulence and transport dynamics in ITER edge plasma on the largest US open-science computer, the CRAY XK7 Titan, at its maximal heterogeneous capability, which have not been possible before due to a factor of over 10 shortage in the time-to-solution for less than 5 days of wall-clock time for one physics case. Frontier techniques such as nested OpenMP parallelism, adaptive parallel I/O, staging I/O and data reduction using dynamic and asynchronous applications interactions, dynamic repartitioning for balancing computational work in pushing particlesmore » and in grid related work, scalable and accurate discretization algorithms for non-linear Coulomb collisions, and communication-avoiding subcycling technology for pushing particles on both CPUs and GPUs are also utilized to dramatically improve the scalability and time-to-solution, hence enabling the difficult kinetic ITER edge simulation on a present-day leadership class computer.« less

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

PubMed

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

2017-11-01

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

Characterization of Cyclohexanone Inclusions in Class 1 RDX

DTIC Science & Technology

2014-06-01

characterized with respect to solvent inclusions in support of a U.S. Army Research Laboratory (ARL) program to model Multiscale Response of Energetic...pertinent to their modeling effort under the Multiscale Response of Energetic Materials (MREM) program, and the Weapons and Materials Research...support of a U.S. Army Research Laboratory (ARL) initiative called “ Multiscale Modeling of Energetic Materials” (MREM). The MREM program aims, for

Structural and Practical Identifiability Issues of Immuno-Epidemiological Vector-Host Models with Application to Rift Valley Fever.

PubMed

Tuncer, Necibe; Gulbudak, Hayriye; Cannataro, Vincent L; Martcheva, Maia

2016-09-01

In this article, we discuss the structural and practical identifiability of a nested immuno-epidemiological model of arbovirus diseases, where host-vector transmission rate, host recovery, and disease-induced death rates are governed by the within-host immune system. We incorporate the newest ideas and the most up-to-date features of numerical methods to fit multi-scale models to multi-scale data. For an immunological model, we use Rift Valley Fever Virus (RVFV) time-series data obtained from livestock under laboratory experiments, and for an epidemiological model we incorporate a human compartment to the nested model and use the number of human RVFV cases reported by the CDC during the 2006-2007 Kenya outbreak. We show that the immunological model is not structurally identifiable for the measurements of time-series viremia concentrations in the host. Thus, we study the non-dimensionalized and scaled versions of the immunological model and prove that both are structurally globally identifiable. After fixing estimated parameter values for the immunological model derived from the scaled model, we develop a numerical method to fit observable RVFV epidemiological data to the nested model for the remaining parameter values of the multi-scale system. For the given (CDC) data set, Monte Carlo simulations indicate that only three parameters of the epidemiological model are practically identifiable when the immune model parameters are fixed. Alternatively, we fit the multi-scale data to the multi-scale model simultaneously. Monte Carlo simulations for the simultaneous fitting suggest that the parameters of the immunological model and the parameters of the immuno-epidemiological model are practically identifiable. We suggest that analytic approaches for studying the structural identifiability of nested models are a necessity, so that identifiable parameter combinations can be derived to reparameterize the nested model to obtain an identifiable one. This is a crucial step in developing multi-scale models which explain multi-scale data.

Multiscale Models in the Biomechanics of Plant Growth

PubMed Central

Fozard, John A.

2015-01-01

Plant growth occurs through the coordinated expansion of tightly adherent cells, driven by regulated softening of cell walls. It is an intrinsically multiscale process, with the integrated properties of multiple cell walls shaping the whole tissue. Multiscale models encode physical relationships to bring new understanding to plant physiology and development. PMID:25729061

New Insights into the Nature of Turbulence in the Earth's Magnetosheath Using Magnetospheric MultiScale Mission Data

NASA Astrophysics Data System (ADS)

Breuillard, H.; Matteini, L.; Argall, M. R.; Sahraoui, F.; Andriopoulou, M.; Le Contel, O.; Retinò, A.; Mirioni, L.; Huang, S. Y.; Gershman, D. J.; Ergun, R. E.; Wilder, F. D.; Goodrich, K. A.; Ahmadi, N.; Yordanova, E.; Vaivads, A.; Turner, D. L.; Khotyaintsev, Yu. V.; Graham, D. B.; Lindqvist, P.-A.; Chasapis, A.; Burch, J. L.; Torbert, R. B.; Russell, C. T.; Magnes, W.; Strangeway, R. J.; Plaschke, F.; Moore, T. E.; Giles, B. L.; Paterson, W. R.; Pollock, C. J.; Lavraud, B.; Fuselier, S. A.; Cohen, I. J.

2018-06-01

The Earth’s magnetosheath, which is characterized by highly turbulent fluctuations, is usually divided into two regions of different properties as a function of the angle between the interplanetary magnetic field and the shock normal. In this study, we make use of high-time resolution instruments on board the Magnetospheric MultiScale spacecraft to determine and compare the properties of subsolar magnetosheath turbulence in both regions, i.e., downstream of the quasi-parallel and quasi-perpendicular bow shocks. In particular, we take advantage of the unprecedented temporal resolution of the Fast Plasma Investigation instrument to show the density fluctuations down to sub-ion scales for the first time. We show that the nature of turbulence is highly compressible down to electron scales, particularly in the quasi-parallel magnetosheath. In this region, the magnetic turbulence also shows an inertial (Kolmogorov-like) range, indicating that the fluctuations are not formed locally, in contrast with the quasi-perpendicular magnetosheath. We also show that the electromagnetic turbulence is dominated by electric fluctuations at sub-ion scales (f > 1 Hz) and that magnetic and electric spectra steepen at the largest-electron scale. The latter indicates a change in the nature of turbulence at electron scales. Finally, we show that the electric fluctuations around the electron gyrofrequency are mostly parallel in the quasi-perpendicular magnetosheath, where intense whistlers are observed. This result suggests that energy dissipation, plasma heating, and acceleration might be driven by intense electrostatic parallel structures/waves, which can be linked to whistler waves.

Systems oncology: towards patient-specific treatment regimes informed by multiscale mathematical modelling.

PubMed

Powathil, Gibin G; Swat, Maciej; Chaplain, Mark A J

2015-02-01

The multiscale complexity of cancer as a disease necessitates a corresponding multiscale modelling approach to produce truly predictive mathematical models capable of improving existing treatment protocols. To capture all the dynamics of solid tumour growth and its progression, mathematical modellers need to couple biological processes occurring at various spatial and temporal scales (from genes to tissues). Because effectiveness of cancer therapy is considerably affected by intracellular and extracellular heterogeneities as well as by the dynamical changes in the tissue microenvironment, any model attempt to optimise existing protocols must consider these factors ultimately leading to improved multimodal treatment regimes. By improving existing and building new mathematical models of cancer, modellers can play important role in preventing the use of potentially sub-optimal treatment combinations. In this paper, we analyse a multiscale computational mathematical model for cancer growth and spread, incorporating the multiple effects of radiation therapy and chemotherapy in the patient survival probability and implement the model using two different cell based modelling techniques. We show that the insights provided by such multiscale modelling approaches can ultimately help in designing optimal patient-specific multi-modality treatment protocols that may increase patients quality of life. Copyright © 2014 Elsevier Ltd. All rights reserved.

Towards anatomic scale agent-based modeling with a massively parallel spatially explicit general-purpose model of enteric tissue (SEGMEnT_HPC).

PubMed

Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary

2015-01-01

Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis.

Rigorous vector wave propagation for arbitrary flat media

NASA Astrophysics Data System (ADS)

Bos, Steven P.; Haffert, Sebastiaan Y.; Keller, Christoph U.

2017-08-01

Precise modelling of the (off-axis) point spread function (PSF) to identify geometrical and polarization aberrations is important for many optical systems. In order to characterise the PSF of the system in all Stokes parameters, an end-to-end simulation of the system has to be performed in which Maxwell's equations are rigorously solved. We present the first results of a python code that we are developing to perform multiscale end-to-end wave propagation simulations that include all relevant physics. Currently we can handle plane-parallel near- and far-field vector diffraction effects of propagating waves in homogeneous isotropic and anisotropic materials, refraction and reflection of flat parallel surfaces, interference effects in thin films and unpolarized light. We show that the code has a numerical precision on the order of 10-16 for non-absorbing isotropic and anisotropic materials. For absorbing materials the precision is on the order of 10-8. The capabilities of the code are demonstrated by simulating a converging beam reflecting from a flat aluminium mirror at normal incidence.

Multi-scale Modeling in Clinical Oncology: Opportunities and Barriers to Success.

PubMed

Yankeelov, Thomas E; An, Gary; Saut, Oliver; Luebeck, E Georg; Popel, Aleksander S; Ribba, Benjamin; Vicini, Paolo; Zhou, Xiaobo; Weis, Jared A; Ye, Kaiming; Genin, Guy M

2016-09-01

Hierarchical processes spanning several orders of magnitude of both space and time underlie nearly all cancers. Multi-scale statistical, mathematical, and computational modeling methods are central to designing, implementing and assessing treatment strategies that account for these hierarchies. The basic science underlying these modeling efforts is maturing into a new discipline that is close to influencing and facilitating clinical successes. The purpose of this review is to capture the state-of-the-art as well as the key barriers to success for multi-scale modeling in clinical oncology. We begin with a summary of the long-envisioned promise of multi-scale modeling in clinical oncology, including the synthesis of disparate data types into models that reveal underlying mechanisms and allow for experimental testing of hypotheses. We then evaluate the mathematical techniques employed most widely and present several examples illustrating their application as well as the current gap between pre-clinical and clinical applications. We conclude with a discussion of what we view to be the key challenges and opportunities for multi-scale modeling in clinical oncology.

Multi-scale Modeling in Clinical Oncology: Opportunities and Barriers to Success

PubMed Central

Yankeelov, Thomas E.; An, Gary; Saut, Oliver; Luebeck, E. Georg; Popel, Aleksander S.; Ribba, Benjamin; Vicini, Paolo; Zhou, Xiaobo; Weis, Jared A.; Ye, Kaiming; Genin, Guy M.

2016-01-01

Hierarchical processes spanning several orders of magnitude of both space and time underlie nearly all cancers. Multi-scale statistical, mathematical, and computational modeling methods are central to designing, implementing and assessing treatment strategies that account for these hierarchies. The basic science underlying these modeling efforts is maturing into a new discipline that is close to influencing and facilitating clinical successes. The purpose of this review is to capture the state-of-the-art as well as the key barriers to success for multi-scale modeling in clinical oncology. We begin with a summary of the long-envisioned promise of multi-scale modeling in clinical oncology, including the synthesis of disparate data types into models that reveal underlying mechanisms and allow for experimental testing of hypotheses. We then evaluate the mathematical techniques employed most widely and present several examples illustrating their application as well as the current gap between pre-clinical and clinical applications. We conclude with a discussion of what we view to be the key challenges and opportunities for multi-scale modeling in clinical oncology. PMID:27384942

Modeling Framework for Fracture in Multiscale Cement-Based Material Structures

PubMed Central

Qian, Zhiwei; Schlangen, Erik; Ye, Guang; van Breugel, Klaas

2017-01-01

Multiscale modeling for cement-based materials, such as concrete, is a relatively young subject, but there are already a number of different approaches to study different aspects of these classical materials. In this paper, the parameter-passing multiscale modeling scheme is established and applied to address the multiscale modeling problem for the integrated system of cement paste, mortar, and concrete. The block-by-block technique is employed to solve the length scale overlap challenge between the mortar level (0.1–10 mm) and the concrete level (1–40 mm). The microstructures of cement paste are simulated by the HYMOSTRUC3D model, and the material structures of mortar and concrete are simulated by the Anm material model. Afterwards the 3D lattice fracture model is used to evaluate their mechanical performance by simulating a uniaxial tensile test. The simulated output properties at a lower scale are passed to the next higher scale to serve as input local properties. A three-level multiscale lattice fracture analysis is demonstrated, including cement paste at the micrometer scale, mortar at the millimeter scale, and concrete at centimeter scale. PMID:28772948

Multiscale modeling and simulation of brain blood flow

NASA Astrophysics Data System (ADS)

Perdikaris, Paris; Grinberg, Leopold; Karniadakis, George Em

2016-02-01

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.

Generalized multiscale finite-element method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Kai; Fu, Shubin; Gibson, Richard L.

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 mediummore » 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.« less

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Kai, E-mail: kaigao87@gmail.com; Fu, Shubin, E-mail: shubinfu89@gmail.com; Gibson, Richard L., E-mail: gibson@tamu.edu

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 mediummore » 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.« less

Generalized multiscale finite-element method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media

DOE PAGES

Gao, Kai; Fu, Shubin; Gibson, Richard L.; ...

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 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 mediummore » 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.« less

Shaken but not stirred: Multiscale habitat suitability modeling of sympatric marten species (Martes martes and Martes foina) in the northern Iberian Peninsula

Treesearch

Maria Vergara; Samuel A. Cushman; Fermin Urra; Aritz Ruiz-Gonzalez

2016-01-01

Multispecies and multiscale habitat suitability models (HSM) are important to identify the environmental variables and scales influencing habitat selection and facilitate the comparison of closely related species with different ecological requirements. Objectives This study explores the multiscale relationships of habitat suitability for the pine (Martes...

Microphysics in the Multi-Scale Modeling Systems with Unified Physics

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

A Liver-centric Multiscale Modeling Framework for Xenobiotics ...

EPA Pesticide Factsheets

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 focuses on developing a multi-scale computational model to characterize both phase I and phase II metabolism of acetaminophen, by bridging Physiologically Based Pharmacokinetic (PBPK) modeling at the whole body level, cell movement and blood flow at the tissue level and cell signaling and drug metabolism at the sub-cellular level. To validate the model, we estimated our model parameters by fi?tting serum concentrations of acetaminophen and its glucuronide and sulfate metabolites to experiments, and carried out sensitivity analysis on 35 parameters selected from three modules. Our study focuses on developing a multi-scale computational model to characterize both phase I and phase II metabolism of acetaminophen, by bridging Physiologically Based Pharmacokinetic (PBPK) modeling at the whole body level, cell movement and blood flow at the tissue level and cell signaling and drug metabolism at the sub-cellular level. This multiscale model bridges the CompuCell3D tool used by the Virtual Tissue project with the httk tool developed by the Rapid Exposure and Dosimetry project.

Shock waves simulated using the dual domain material point method combined with molecular dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Duan Z.; Dhakal, Tilak Raj

Here in this work we combine the dual domain material point method with molecular dynamics in an attempt to create a multiscale numerical method to simulate materials undergoing large deformations with high strain rates. In these types of problems, the material is often in a thermodynamically nonequilibrium state, and conventional constitutive relations or equations of state are often not available. In this method, the closure quantities, such as stress, at each material point are calculated from a molecular dynamics simulation of a group of atoms surrounding the material point. Rather than restricting the multiscale simulation in a small spatial region,more » such as phase interfaces, or crack tips, this multiscale method can be used to consider nonequilibrium thermodynamic effects in a macroscopic domain. This method takes the advantage that the material points only communicate with mesh nodes, not among themselves; therefore molecular dynamics simulations for material points can be performed independently in parallel. The dual domain material point method is chosen for this multiscale method because it can be used in history dependent problems with large deformation without generating numerical noise as material points move across cells, and also because of its convergence and conservation properties. In conclusion, to demonstrate the feasibility and accuracy of this method, we compare the results of a shock wave propagation in a cerium crystal calculated using the direct molecular dynamics simulation with the results from this combined multiscale calculation.« less

Shock waves simulated using the dual domain material point method combined with molecular dynamics

DOE PAGES

Zhang, Duan Z.; Dhakal, Tilak Raj

2017-01-17

Here in this work we combine the dual domain material point method with molecular dynamics in an attempt to create a multiscale numerical method to simulate materials undergoing large deformations with high strain rates. In these types of problems, the material is often in a thermodynamically nonequilibrium state, and conventional constitutive relations or equations of state are often not available. In this method, the closure quantities, such as stress, at each material point are calculated from a molecular dynamics simulation of a group of atoms surrounding the material point. Rather than restricting the multiscale simulation in a small spatial region,more » such as phase interfaces, or crack tips, this multiscale method can be used to consider nonequilibrium thermodynamic effects in a macroscopic domain. This method takes the advantage that the material points only communicate with mesh nodes, not among themselves; therefore molecular dynamics simulations for material points can be performed independently in parallel. The dual domain material point method is chosen for this multiscale method because it can be used in history dependent problems with large deformation without generating numerical noise as material points move across cells, and also because of its convergence and conservation properties. In conclusion, to demonstrate the feasibility and accuracy of this method, we compare the results of a shock wave propagation in a cerium crystal calculated using the direct molecular dynamics simulation with the results from this combined multiscale calculation.« less

Multiscale and Multiphysics Modeling of Additive Manufacturing of Advanced Materials

NASA Technical Reports Server (NTRS)

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

2015-01-01

The objective of this proposed project is to research and develop a prediction tool for advanced additive manufacturing (AAM) processes for advanced materials and develop experimental methods to provide fundamental properties and establish validation data. Aircraft structures and engines demand materials that are stronger, useable at much higher temperatures, provide less acoustic transmission, and enable more aeroelastic tailoring than those currently used. Significant improvements in properties can only be achieved by processing the materials under nonequilibrium conditions, such as AAM processes. AAM processes encompass a class of processes that use a focused heat source to create a melt pool on a substrate. Examples include Electron Beam Freeform Fabrication and Direct Metal Deposition. These types of additive processes enable fabrication of parts directly from CAD drawings. To achieve the desired material properties and geometries of the final structure, assessing the impact of process parameters and predicting optimized conditions with numerical modeling as an effective prediction tool is necessary. The targets for the processing are multiple and at different spatial scales, and the physical phenomena associated occur in multiphysics and multiscale. In this project, the research work has been developed to model AAM processes in a multiscale and multiphysics approach. A macroscale model was developed to investigate the residual stresses and distortion in AAM processes. A sequentially coupled, thermomechanical, finite element model was developed and validated experimentally. The results showed the temperature distribution, residual stress, and deformation within the formed deposits and substrates. A mesoscale model was developed to include heat transfer, phase change with mushy zone, incompressible free surface flow, solute redistribution, and surface tension. Because of excessive computing time needed, a parallel computing approach was also tested. In addition, after investigating various methods, a Smoothed Particle Hydrodynamics Model (SPH Model) was developed to model wire feeding process. Its computational efficiency and simple architecture makes it more robust and flexible than other models. More research on material properties may be needed to realistically model the AAM processes. A microscale model was developed to investigate heterogeneous nucleation, dendritic grain growth, epitaxial growth of columnar grains, columnar-to-equiaxed transition, grain transport in melt, and other properties. The orientations of the columnar grains were almost perpendicular to the laser motion's direction. Compared to the similar studies in the literature, the multiple grain morphology modeling result is in the same order of magnitude as optical morphologies in the experiment. Experimental work was conducted to validate different models. An infrared camera was incorporated as a process monitoring and validating tool to identify the solidus and mushy zones during deposition. The images were successfully processed to identify these regions. This research project has investigated multiscale and multiphysics of the complex AAM processes thus leading to advanced understanding of these processes. The project has also developed several modeling tools and experimental validation tools that will be very critical in the future of AAM process qualification and certification.

Multiscale Modeling of PEEK Using Reactive Molecular Dynamics Modeling and Micromechanics

NASA Technical Reports Server (NTRS)

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

2018-01-01

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

The structure of the electron diffusion region during asymmetric anti-parallel magnetic reconnection

NASA Astrophysics Data System (ADS)

Swisdak, M.; Drake, J. F.; Price, L.; Burch, J. L.; Cassak, P.

2017-12-01

The structure of the electron diffusion region during asymmetric magnetic reconnection is ex- plored with high-resolution particle-in-cell simulations that focus on an magnetopause event ob- served by the Magnetospheric Multiscale Mission (MMS). A major surprise is the development of a standing, oblique whistler-like structure with regions of intense positive and negative dissipation. This structure arises from high-speed electrons that flow along the magnetosheath magnetic sepa- ratrices, converge in the dissipation region and jet across the x-line into the magnetosphere. The jet produces a region of negative charge and generates intense parallel electric fields that eject the electrons downstream along the magnetospheric separatrices. The ejected electrons produce the parallel velocity-space crescents documented by MMS.

High-performance parallel analysis of coupled problems for aircraft propulsion

NASA Technical Reports Server (NTRS)

Felippa, C. A.; Farhat, C.; Lanteri, S.; Gumaste, U.; Ronaghi, M.

1994-01-01

Applications are described of high-performance parallel, computation for the analysis of complete jet engines, considering its multi-discipline coupled problem. The coupled problem involves interaction of structures with gas dynamics, heat conduction and heat transfer in aircraft engines. The methodology issues addressed include: consistent discrete formulation of coupled problems with emphasis on coupling phenomena; effect of partitioning strategies, augmentation and temporal solution procedures; sensitivity of response to problem parameters; and methods for interfacing multiscale discretizations in different single fields. The computer implementation issues addressed include: parallel treatment of coupled systems; domain decomposition and mesh partitioning strategies; data representation in object-oriented form and mapping to hardware driven representation, and tradeoff studies between partitioning schemes and fully coupled treatment.

Snow Micro-Structure Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Micah Johnson, Andrew Slaughter

PIKA is a MOOSE-based application for modeling micro-structure evolution of seasonal snow. The model will be useful for environmental, atmospheric, and climate scientists. Possible applications include application to energy balance models, ice sheet modeling, and avalanche forecasting. The model implements physics from published, peer-reviewed articles. The main purpose is to foster university and laboratory collaboration to build a larger multi-scale snow model using MOOSE. The main feature of the code is that it is implemented using the MOOSE framework, thus making features such as multiphysics coupling, adaptive mesh refinement, and parallel scalability native to the application. PIKA implements three equations:more » the phase-field equation for tracking the evolution of the ice-air interface within seasonal snow at the grain-scale; the heat equation for computing the temperature of both the ice and air within the snow; and the mass transport equation for monitoring the diffusion of water vapor in the pore space of the snow.« less

Integrated multiscale biomaterials experiment and modelling: a perspective

PubMed Central

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

D'Azevedo, Eduardo; Abbott, Stephen; Koskela, Tuomas

The XGC fusion gyrokinetic code combines state-of-the-art, portable computational and algorithmic technologies to enable complicated multiscale simulations of turbulence and transport dynamics in ITER edge plasma on the largest US open-science computer, the CRAY XK7 Titan, at its maximal heterogeneous capability, which have not been possible before due to a factor of over 10 shortage in the time-to-solution for less than 5 days of wall-clock time for one physics case. Frontier techniques such as nested OpenMP parallelism, adaptive parallel I/O, staging I/O and data reduction using dynamic and asynchronous applications interactions, dynamic repartitioning.

Nonlocal and Mixed-Locality Multiscale Finite Element Methods

DOE PAGES

Costa, Timothy B.; Bond, Stephen D.; Littlewood, David J.

2018-03-27

In many applications the resolution of small-scale heterogeneities remains a significant hurdle to robust and reliable predictive simulations. In particular, while material variability at the mesoscale plays a fundamental role in processes such as material failure, the resolution required to capture mechanisms at this scale is often computationally intractable. Multiscale methods aim to overcome this difficulty through judicious choice of a subscale problem and a robust manner of passing information between scales. One promising approach is the multiscale finite element method, which increases the fidelity of macroscale simulations by solving lower-scale problems that produce enriched multiscale basis functions. Here, inmore » this study, we present the first work toward application of the multiscale finite element method to the nonlocal peridynamic theory of solid mechanics. This is achieved within the context of a discontinuous Galerkin framework that facilitates the description of material discontinuities and does not assume the existence of spatial derivatives. Analysis of the resulting nonlocal multiscale finite element method is achieved using the ambulant Galerkin method, developed here with sufficient generality to allow for application to multiscale finite element methods for both local and nonlocal models that satisfy minimal assumptions. Finally, we conclude with preliminary results on a mixed-locality multiscale finite element method in which a nonlocal model is applied at the fine scale and a local model at the coarse scale.« less

Nonlocal and Mixed-Locality Multiscale Finite Element Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Costa, Timothy B.; Bond, Stephen D.; Littlewood, David J.

In many applications the resolution of small-scale heterogeneities remains a significant hurdle to robust and reliable predictive simulations. In particular, while material variability at the mesoscale plays a fundamental role in processes such as material failure, the resolution required to capture mechanisms at this scale is often computationally intractable. Multiscale methods aim to overcome this difficulty through judicious choice of a subscale problem and a robust manner of passing information between scales. One promising approach is the multiscale finite element method, which increases the fidelity of macroscale simulations by solving lower-scale problems that produce enriched multiscale basis functions. Here, inmore » this study, we present the first work toward application of the multiscale finite element method to the nonlocal peridynamic theory of solid mechanics. This is achieved within the context of a discontinuous Galerkin framework that facilitates the description of material discontinuities and does not assume the existence of spatial derivatives. Analysis of the resulting nonlocal multiscale finite element method is achieved using the ambulant Galerkin method, developed here with sufficient generality to allow for application to multiscale finite element methods for both local and nonlocal models that satisfy minimal assumptions. Finally, we conclude with preliminary results on a mixed-locality multiscale finite element method in which a nonlocal model is applied at the fine scale and a local model at the coarse scale.« less

FWT2D: A massively parallel program for frequency-domain full-waveform tomography of wide-aperture seismic data—Part 1: Algorithm

NASA Astrophysics Data System (ADS)

Sourbier, Florent; Operto, Stéphane; Virieux, Jean; Amestoy, Patrick; L'Excellent, Jean-Yves

2009-03-01

This is the first paper in a two-part series that describes a massively parallel code that performs 2D frequency-domain full-waveform inversion of wide-aperture seismic data for imaging complex structures. Full-waveform inversion methods, namely quantitative seismic imaging methods based on the resolution of the full wave equation, are computationally expensive. Therefore, designing efficient algorithms which take advantage of parallel computing facilities is critical for the appraisal of these approaches when applied to representative case studies and for further improvements. Full-waveform modelling requires the resolution of a large sparse system of linear equations which is performed with the massively parallel direct solver MUMPS for efficient multiple-shot simulations. Efficiency of the multiple-shot solution phase (forward/backward substitutions) is improved by using the BLAS3 library. The inverse problem relies on a classic local optimization approach implemented with a gradient method. The direct solver returns the multiple-shot wavefield solutions distributed over the processors according to a domain decomposition driven by the distribution of the LU factors. The domain decomposition of the wavefield solutions is used to compute in parallel the gradient of the objective function and the diagonal Hessian, this latter providing a suitable scaling of the gradient. The algorithm allows one to test different strategies for multiscale frequency inversion ranging from successive mono-frequency inversion to simultaneous multifrequency inversion. These different inversion strategies will be illustrated in the following companion paper. The parallel efficiency and the scalability of the code will also be quantified.

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

PubMed

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.

Multi-element least square HDMR methods and their applications for stochastic multiscale model reduction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn; Li, Xinping, E-mail: exping@126.com

Stochastic multiscale modeling has become a necessary approach to quantify uncertainty and characterize multiscale phenomena for many practical problems such as flows in stochastic porous media. The numerical treatment of the stochastic multiscale models can be very challengeable as the existence of complex uncertainty and multiple physical scales in the models. To efficiently take care of the difficulty, we construct a computational reduced model. To this end, we propose a multi-element least square high-dimensional model representation (HDMR) method, through which the random domain is adaptively decomposed into a few subdomains, and a local least square HDMR is constructed in eachmore » subdomain. These local HDMRs are represented by a finite number of orthogonal basis functions defined in low-dimensional random spaces. The coefficients in the local HDMRs are determined using least square methods. We paste all the local HDMR approximations together to form a global HDMR approximation. To further reduce computational cost, we present a multi-element reduced least-square HDMR, which improves both efficiency and approximation accuracy in certain conditions. To effectively treat heterogeneity properties and multiscale features in the models, we integrate multiscale finite element methods with multi-element least-square HDMR for stochastic multiscale model reduction. This approach significantly reduces the original model's complexity in both the resolution of the physical space and the high-dimensional stochastic space. We analyze the proposed approach, and provide a set of numerical experiments to demonstrate the performance of the presented model reduction techniques. - Highlights: • Multi-element least square HDMR is proposed to treat stochastic models. • Random domain is adaptively decomposed into some subdomains to obtain adaptive multi-element HDMR. • Least-square reduced HDMR is proposed to enhance computation efficiency and approximation accuracy in certain conditions. • Integrating MsFEM and multi-element least square HDMR can significantly reduce computation complexity.« less

Identity in agent-based models : modeling dynamic multiscale social processes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ozik, J.; Sallach, D. L.; Macal, C. M.

Identity-related issues play central roles in many current events, including those involving factional politics, sectarianism, and tribal conflicts. Two popular models from the computational-social-science (CSS) literature - the Threat Anticipation Program and SharedID models - incorporate notions of identity (individual and collective) and processes of identity formation. A multiscale conceptual framework that extends some ideas presented in these models and draws other capabilities from the broader CSS literature is useful in modeling the formation of political identities. The dynamic, multiscale processes that constitute and transform social identities can be mapped to expressive structures of the framework

Performance of hybrid programming models for multiscale cardiac simulations: preparing for petascale computation.

PubMed

Pope, Bernard J; Fitch, Blake G; Pitman, Michael C; Rice, John J; Reumann, Matthias

2011-10-01

Future multiscale and multiphysics models that support research into human disease, translational medical science, and treatment can utilize the power of high-performance computing (HPC) systems. We anticipate that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message-passing processes [e.g., the message-passing interface (MPI)] with multithreading (e.g., OpenMP, Pthreads). The objective of this study is to compare the performance of such hybrid programming models when applied to the simulation of a realistic physiological multiscale model of the heart. Our results show that the hybrid models perform favorably when compared to an implementation using only the MPI and, furthermore, that OpenMP in combination with the MPI provides a satisfactory compromise between performance and code complexity. Having the ability to use threads within MPI processes enables the sophisticated use of all processor cores for both computation and communication phases. Considering that HPC systems in 2012 will have two orders of magnitude more cores than what was used in this study, we believe that faster than real-time multiscale cardiac simulations can be achieved on these systems.

Multi-scale signed envelope inversion

NASA Astrophysics Data System (ADS)

Chen, Guo-Xin; Wu, Ru-Shan; Wang, Yu-Qing; Chen, Sheng-Chang

2018-06-01

Envelope inversion based on modulation signal mode was proposed to reconstruct large-scale structures of underground media. In order to solve the shortcomings of conventional envelope inversion, multi-scale envelope inversion was proposed using new envelope Fréchet derivative and multi-scale inversion strategy to invert strong contrast models. In multi-scale envelope inversion, amplitude demodulation was used to extract the low frequency information from envelope data. However, only to use amplitude demodulation method will cause the loss of wavefield polarity information, thus increasing the possibility of inversion to obtain multiple solutions. In this paper we proposed a new demodulation method which can contain both the amplitude and polarity information of the envelope data. Then we introduced this demodulation method into multi-scale envelope inversion, and proposed a new misfit functional: multi-scale signed envelope inversion. In the numerical tests, we applied the new inversion method to the salt layer model and SEG/EAGE 2-D Salt model using low-cut source (frequency components below 4 Hz were truncated). The results of numerical test demonstrated the effectiveness of this method.

An automatic generation of non-uniform mesh for CFD analyses of image-based multiscale human airway models

NASA Astrophysics Data System (ADS)

Miyawaki, Shinjiro; Tawhai, Merryn H.; Hoffman, Eric A.; Lin, Ching-Long

2014-11-01

The authors have developed a method to automatically generate non-uniform CFD mesh for image-based human airway models. The sizes of generated tetrahedral elements vary in both radial and longitudinal directions to account for boundary layer and multiscale nature of pulmonary airflow. The proposed method takes advantage of our previously developed centerline-based geometry reconstruction method. In order to generate the mesh branch by branch in parallel, we used the open-source programs Gmsh and TetGen for surface and volume meshes, respectively. Both programs can specify element sizes by means of background mesh. The size of an arbitrary element in the domain is a function of wall distance, element size on the wall, and element size at the center of airway lumen. The element sizes on the wall are computed based on local flow rate and airway diameter. The total number of elements in the non-uniform mesh (10 M) was about half of that in the uniform mesh, although the computational time for the non-uniform mesh was about twice longer (170 min). The proposed method generates CFD meshes with fine elements near the wall and smooth variation of element size in longitudinal direction, which are required, e.g., for simulations with high flow rate. NIH Grants R01-HL094315, U01-HL114494, and S10-RR022421. Computer time provided by XSEDE.

An approach to enhance pnetCDF performance in ...

EPA Pesticide Factsheets

Data intensive simulations are often limited by their I/O (input/output) performance, and "novel" techniques need to be developed in order to overcome this limitation. The software package pnetCDF (parallel network Common Data Form), which works with parallel file systems, was developed to address this issue by providing parallel I/O capability. This study examines the performance of an application-level data aggregation approach which performs data aggregation along either row or column dimension of MPI (Message Passing Interface) processes on a spatially decomposed domain, and then applies the pnetCDF parallel I/O paradigm. The test was done with three different domain sizes which represent small, moderately large, and large data domains, using a small-scale Community Multiscale Air Quality model (CMAQ) mock-up code. The examination includes comparing I/O performance with traditional serial I/O technique, straight application of pnetCDF, and the data aggregation along row and column dimension before applying pnetCDF. After the comparison, "optimal" I/O configurations of this application-level data aggregation approach were quantified. Data aggregation along the row dimension (pnetCDFcr) works better than along the column dimension (pnetCDFcc) although it may perform slightly worse than the straight pnetCDF method with a small number of processors. When the number of processors becomes larger, pnetCDFcr outperforms pnetCDF significantly. If the number of proces

A dynamic multi-scale Markov model based methodology for remaining life prediction

NASA Astrophysics Data System (ADS)

Yan, Jihong; Guo, Chaozhong; Wang, Xing

2011-05-01

The ability to accurately predict the remaining life of partially degraded components is crucial in prognostics. In this paper, a performance degradation index is designed using multi-feature fusion techniques to represent deterioration severities of facilities. Based on this indicator, an improved Markov model is proposed for remaining life prediction. Fuzzy C-Means (FCM) algorithm is employed to perform state division for Markov model in order to avoid the uncertainty of state division caused by the hard division approach. Considering the influence of both historical and real time data, a dynamic prediction method is introduced into Markov model by a weighted coefficient. Multi-scale theory is employed to solve the state division problem of multi-sample prediction. Consequently, a dynamic multi-scale Markov model is constructed. An experiment is designed based on a Bently-RK4 rotor testbed to validate the dynamic multi-scale Markov model, experimental results illustrate the effectiveness of the methodology.

Influence of additive laser manufacturing parameters on surface using density of partially melted particles

NASA Astrophysics Data System (ADS)

Rosa, Benoit; Brient, Antoine; Samper, Serge; Hascoët, Jean-Yves

2016-12-01

Mastering the additive laser manufacturing surface is a real challenge and would allow functional surfaces to be obtained without finishing. Direct Metal Deposition (DMD) surfaces are composed by directional and chaotic textures that are directly linked to the process principles. The aim of this work is to obtain surface topographies by mastering the operating process parameters. Based on experimental investigation, the influence of operating parameters on the surface finish has been modeled. Topography parameters and multi-scale analysis have been used in order to characterize the DMD obtained surfaces. This study also proposes a methodology to characterize DMD chaotic texture through topography filtering and 3D image treatment. In parallel, a new parameter is proposed: density of particles (D p). Finally, this study proposes a regression modeling between process parameters and density of particles parameter.

Multi-scale Mexican spotted owl (Strix occidentalis lucida) nest/roost habitat selection in Arizona and a comparison with single-scale modeling results

Treesearch

Brad C. Timm; Kevin McGarigal; Samuel A. Cushman; Joseph L. Ganey

2016-01-01

Efficacy of future habitat selection studies will benefit by taking a multi-scale approach. In addition to potentially providing increased explanatory power and predictive capacity, multi-scale habitat models enhance our understanding of the scales at which species respond to their environment, which is critical knowledge required to implement effective...

Multiscale Modeling of Damage Processes in fcc Aluminum: From Atoms to Grains

NASA Technical Reports Server (NTRS)

Glaessgen, E. H.; Saether, E.; Yamakov, V.

2008-01-01

Molecular dynamics (MD) methods are opening new opportunities for simulating the fundamental processes of material behavior at the atomistic level. However, current analysis is limited to small domains and increasing the size of the MD domain quickly presents intractable computational demands. A preferred approach to surmount this computational limitation has been to combine continuum mechanics-based modeling procedures, such as the finite element method (FEM), with MD analyses thereby reducing the region of atomic scale refinement. Such multiscale modeling strategies can be divided into two broad classifications: concurrent multiscale methods that directly incorporate an atomistic domain within a continuum domain and sequential multiscale methods that extract an averaged response from the atomistic simulation for later use as a constitutive model in a continuum analysis.

Towards the virtual artery: a multiscale model for vascular physiology at the physics-chemistry-biology interface.

PubMed

Hoekstra, Alfons G; Alowayyed, Saad; Lorenz, Eric; Melnikova, Natalia; Mountrakis, Lampros; van Rooij, Britt; Svitenkov, Andrew; Závodszky, Gábor; Zun, Pavel

2016-11-13

This discussion paper introduces the concept of the Virtual Artery as a multiscale model for arterial physiology and pathologies at the physics-chemistry-biology (PCB) interface. The cellular level is identified as the mesoscopic level, and we argue that by coupling cell-based models with other relevant models on the macro- and microscale, a versatile model of arterial health and disease can be composed. We review the necessary ingredients, both models of arteries at many different scales, as well as generic methods to compose multiscale models. Next, we discuss how this can be combined into the virtual artery. Finally, we argue that the concept of models at the PCB interface could or perhaps should become a powerful paradigm, not only as in our case for studying physiology, but also for many other systems that have such PCB interfaces.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2016 The Authors.

Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen

DOE Office of Scientific and Technical Information (OSTI.GOV)

Plechac, Petr

2016-03-01

The overall objective of this project was 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 and developing rigorous mathematical techniques and computational algorithms to study such models. 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.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zabaras, Nicolas J.

2016-11-08

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

Report of the proceedings of the Colloquium and Workshop on Multiscale Coupled Modeling

NASA Technical Reports Server (NTRS)

Koch, Steven E. (Editor)

1993-01-01

The Colloquium and Workshop on Multiscale Coupled Modeling was held for the purpose of addressing modeling issues of importance to planning for the Cooperative Multiscale Experiment (CME). The colloquium presentations attempted to assess the current ability of numerical models to accurately simulate the development and evolution of mesoscale cloud and precipitation systems and their cycling of water substance, energy, and trace species. The primary purpose of the workshop was to make specific recommendations for the improvement of mesoscale models prior to the CME, their coupling with cloud, cumulus ensemble, hydrology, air chemistry models, and the observational requirements to initialize and verify these models.

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

NASA Astrophysics Data System (ADS)

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.

Multiscale Micromechanical Modeling of Polymer/Clay Nanocomposites and the Effective Clay Particle

NASA Astrophysics Data System (ADS)

Sheng, Nuo; Boyce, Mary C.; Parks, David M.; Manovitch, Oleg; Rutledge, Gregory C.; Lee, Hojun; McKinley, Gareth H.

2003-03-01

Polymer/clay nanocomposites have been observed to exhibit enhanced mechanical properties at low weight fractions (Wp) of clay. Continuum-based composite modeling reveals that the enhanced properties are strongly dependent on particular features of the second-phase ¡°particles¡+/-; in particular, the particle volume fraction (fp), the particle aspect ratio (L/t), and the ratio of particle mechanical properties to those of the matrix. However, these important aspects of as-processed nanoclay composites have yet to be consistently and accurately defined. A multiscale modeling strategy was developed to account for the hierarchical morphology of the nanocomposite: at a lengthscale of thousands of microns, the structure is one of high aspect ratio particles within a matrix; at the lengthscale of microns, the clay particle structure is either (a) exfoliated clay sheets of nanometer level thickness or (b) stacks of parallel clay sheets separated from one another by interlayer galleries of nanometer level height. Here, quantitative structural parameters extracted from XRD patterns and TEM micrographs are used to determine geometric features of the as-processed clay ¡°particles¡+/-, including L/t and the ratio of fp to Wp. These geometric features, together with estimates of silicate lamina stiffness obtained from molecular dynamics simulations, provide a basis for modeling effective mechanical properties of the clay particle. The structure-based predictions of the macroscopic elastic modulus of the nanocomposite as a function of clay weight fraction are in excellent agreement with experimental data. The adopted methodology offers promise for study of related properties in polymer/clay nanocomposites.

Understanding DNA under oxidative stress and sensitization: the role of molecular modeling

PubMed Central

Dumont, Elise; Monari, Antonio

2015-01-01

DNA is constantly exposed to damaging threats coming from oxidative stress, i.e., from the presence of free radicals and reactive oxygen species. Sensitization from exogenous and endogenous compounds that strongly enhance the frequency of light-induced lesions also plays an important role. The experimental determination of DNA lesions, though a difficult subject, is somehow well established and allows to elucidate even extremely rare DNA lesions. In parallel, molecular modeling has become fundamental to clearly understand the fine mechanisms related to DNA defects induction. Indeed, it offers an unprecedented possibility to get access to an atomistic or even electronic resolution. Ab initio molecular dynamics may also describe the time-evolution of the molecular system and its reactivity. Yet the modeling of DNA (photo-)reactions does necessitate elaborate multi-scale methodologies to tackle a damage induction reactivity that takes place in a complex environment. The double-stranded DNA environment is first characterized by a very high flexibility, but also a strongly inhomogeneous electrostatic embedding. Additionally, one aims at capturing more subtle effects, such as the sequence selectivity which is of critical important for DNA damage. The structure and dynamics of the DNA/sensitizers complexes, as well as the photo-induced electron- and energy-transfer phenomena taking place upon sensitization, should be carefully modeled. Finally the factors inducing different repair ratios for different lesions should also be rationalized. In this review we will critically analyze the different computational strategies used to model DNA lesions. A clear picture of the complex interplay between reactivity and structural factors will be sketched. The use of proper multi-scale modeling leads to the in-depth comprehension of DNA lesions mechanisms and also to the rational design of new chemo-therapeutic agents. PMID:26236706

Crops in silico: A community wide multi-scale computational modeling framework of plant canopies

NASA Astrophysics Data System (ADS)

Srinivasan, V.; Christensen, A.; Borkiewic, K.; Yiwen, X.; Ellis, A.; Panneerselvam, B.; Kannan, K.; Shrivastava, S.; Cox, D.; Hart, J.; Marshall-Colon, A.; Long, S.

2016-12-01

Current crop models predict a looming gap between supply and demand for primary foodstuffs over the next 100 years. While significant yield increases were achieved in major food crops during the early years of the green revolution, the current rates of yield increases are insufficient to meet future projected food demand. Furthermore, with projected reduction in arable land, decrease in water availability, and increasing impacts of climate change on future food production, innovative technologies are required to sustainably improve crop yield. To meet these challenges, we are developing Crops in silico (Cis), a biologically informed, multi-scale, computational modeling framework that can facilitate whole plant simulations of crop systems. The Cis framework is capable of linking models of gene networks, protein synthesis, metabolic pathways, physiology, growth, and development in order to investigate crop response to different climate scenarios and resource constraints. This modeling framework will provide the mechanistic details to generate testable hypotheses toward accelerating directed breeding and engineering efforts to increase future food security. A primary objective for building such a framework is to create synergy among an inter-connected community of biologists and modelers to create a realistic virtual plant. This framework advantageously casts the detailed mechanistic understanding of individual plant processes across various scales in a common scalable framework that makes use of current advances in high performance and parallel computing. We are currently designing a user friendly interface that will make this tool equally accessible to biologists and computer scientists. Critically, this framework will provide the community with much needed tools for guiding future crop breeding and engineering, understanding the emergent implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment.

Multiscale analysis of neural spike trains.

PubMed

Ramezan, Reza; Marriott, Paul; Chenouri, Shojaeddin

2014-01-30

This paper studies the multiscale analysis of neural spike trains, through both graphical and Poisson process approaches. We introduce the interspike interval plot, which simultaneously visualizes characteristics of neural spiking activity at different time scales. Using an inhomogeneous Poisson process framework, we discuss multiscale estimates of the intensity functions of spike trains. We also introduce the windowing effect for two multiscale methods. Using quasi-likelihood, we develop bootstrap confidence intervals for the multiscale intensity function. We provide a cross-validation scheme, to choose the tuning parameters, and study its unbiasedness. Studying the relationship between the spike rate and the stimulus signal, we observe that adjusting for the first spike latency is important in cross-validation. We show, through examples, that the correlation between spike trains and spike count variability can be multiscale phenomena. Furthermore, we address the modeling of the periodicity of the spike trains caused by a stimulus signal or by brain rhythms. Within the multiscale framework, we introduce intensity functions for spike trains with multiplicative and additive periodic components. Analyzing a dataset from the retinogeniculate synapse, we compare the fit of these models with the Bayesian adaptive regression splines method and discuss the limitations of the methodology. Computational efficiency, which is usually a challenge in the analysis of spike trains, is one of the highlights of these new models. In an example, we show that the reconstruction quality of a complex intensity function demonstrates the ability of the multiscale methodology to crack the neural code. Copyright © 2013 John Wiley & Sons, Ltd.

Multiscale recurrence analysis of spatio-temporal data

NASA Astrophysics Data System (ADS)

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.

Multiscale recurrence analysis of spatio-temporal data.

PubMed

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.

Flexible feature-space-construction architecture and its VLSI implementation for multi-scale object detection

NASA Astrophysics Data System (ADS)

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.

Adaptation of a Fast Optimal Interpolation Algorithm to the Mapping of Oceangraphic Data

NASA Technical Reports Server (NTRS)

Menemenlis, Dimitris; Fieguth, Paul; Wunsch, Carl; Willsky, Alan

1997-01-01

A fast, recently developed, multiscale optimal interpolation algorithm has been adapted to the mapping of hydrographic and other oceanographic data. This algorithm produces solution and error estimates which are consistent with those obtained from exact least squares methods, but at a small fraction of the computational cost. Problems whose solution would be completely impractical using exact least squares, that is, problems with tens or hundreds of thousands of measurements and estimation grid points, can easily be solved on a small workstation using the multiscale algorithm. In contrast to methods previously proposed for solving large least squares problems, our approach provides estimation error statistics while permitting long-range correlations, using all measurements, and permitting arbitrary measurement locations. The multiscale algorithm itself, published elsewhere, is not the focus of this paper. However, the algorithm requires statistical models having a very particular multiscale structure; it is the development of a class of multiscale statistical models, appropriate for oceanographic mapping problems, with which we concern ourselves in this paper. The approach is illustrated by mapping temperature in the northeastern Pacific. The number of hydrographic stations is kept deliberately small to show that multiscale and exact least squares results are comparable. A portion of the data were not used in the analysis; these data serve to test the multiscale estimates. A major advantage of the present approach is the ability to repeat the estimation procedure a large number of times for sensitivity studies, parameter estimation, and model testing. We have made available by anonymous Ftp a set of MATLAB-callable routines which implement the multiscale algorithm and the statistical models developed in this paper.

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

NASA Astrophysics Data System (ADS)

Tao, W. K.

2017-12-01

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

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

In recent years, exponentially increasing computer power extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale models can be run in grid size similar to cloud resolving models through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model). (2) a regional scale model (a NASA unified weather research and forecast, W8F). (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 results from using multi-scale modeling systems to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use the multi-satellite simulator to improve precipitation processes will be discussed.

Using Multi-Scale Modeling Systems to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2010-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (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 results from using multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

Wavelet-based multiscale performance analysis: An approach to assess and improve hydrological models

NASA Astrophysics Data System (ADS)

Rathinasamy, Maheswaran; Khosa, Rakesh; Adamowski, Jan; ch, Sudheer; Partheepan, G.; Anand, Jatin; Narsimlu, Boini

2014-12-01

The temporal dynamics of hydrological processes are spread across different time scales and, as such, the performance of hydrological models cannot be estimated reliably from global performance measures that assign a single number to the fit of a simulated time series to an observed reference series. Accordingly, it is important to analyze model performance at different time scales. Wavelets have been used extensively in the area of hydrological modeling for multiscale analysis, and have been shown to be very reliable and useful in understanding dynamics across time scales and as these evolve in time. In this paper, a wavelet-based multiscale performance measure for hydrological models is proposed and tested (i.e., Multiscale Nash-Sutcliffe Criteria and Multiscale Normalized Root Mean Square Error). The main advantage of this method is that it provides a quantitative measure of model performance across different time scales. In the proposed approach, model and observed time series are decomposed using the Discrete Wavelet Transform (known as the à trous wavelet transform), and performance measures of the model are obtained at each time scale. The applicability of the proposed method was explored using various case studies-both real as well as synthetic. The synthetic case studies included various kinds of errors (e.g., timing error, under and over prediction of high and low flows) in outputs from a hydrologic model. The real time case studies investigated in this study included simulation results of both the process-based Soil Water Assessment Tool (SWAT) model, as well as statistical models, namely the Coupled Wavelet-Volterra (WVC), Artificial Neural Network (ANN), and Auto Regressive Moving Average (ARMA) methods. For the SWAT model, data from Wainganga and Sind Basin (India) were used, while for the Wavelet Volterra, ANN and ARMA models, data from the Cauvery River Basin (India) and Fraser River (Canada) were used. The study also explored the effect of the choice of the wavelets in multiscale model evaluation. It was found that the proposed wavelet-based performance measures, namely the MNSC (Multiscale Nash-Sutcliffe Criteria) and MNRMSE (Multiscale Normalized Root Mean Square Error), are a more reliable measure than traditional performance measures such as the Nash-Sutcliffe Criteria (NSC), Root Mean Square Error (RMSE), and Normalized Root Mean Square Error (NRMSE). Further, the proposed methodology can be used to: i) compare different hydrological models (both physical and statistical models), and ii) help in model calibration.

MODELS-3 COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL AEROSOL COMPONENT 1: MODEL DESCRIPTION

EPA Science Inventory

The aerosol component of the Community Multiscale Air Quality (CMAQ) model is designed to be an efficient and economical depiction of aerosol dynamics in the atmosphere. The approach taken represents the particle size distribution as the superposition of three lognormal subdis...

Evaluation of the Community Multiscale Air Quality model version 5.1

EPA Science Inventory

The Community Multiscale Air Quality model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Atmospheric Modeling and Analysis Division (AMAD) of the U.S. Environment...

Multi-scale calculation based on dual domain material point method combined with molecular dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dhakal, Tilak Raj

This dissertation combines the dual domain material point method (DDMP) with molecular dynamics (MD) in an attempt to create a multi-scale numerical method to simulate materials undergoing large deformations with high strain rates. In these types of problems, the material is often in a thermodynamically non-equilibrium state, and conventional constitutive relations are often not available. In this method, the closure quantities, such as stress, at each material point are calculated from a MD simulation of a group of atoms surrounding the material point. Rather than restricting the multi-scale simulation in a small spatial region, such as phase interfaces, or crackmore » tips, this multi-scale method can be used to consider non-equilibrium thermodynamic e ects in a macroscopic domain. This method takes advantage that the material points only communicate with mesh nodes, not among themselves; therefore MD simulations for material points can be performed independently in parallel. First, using a one-dimensional shock problem as an example, the numerical properties of the original material point method (MPM), the generalized interpolation material point (GIMP) method, the convected particle domain interpolation (CPDI) method, and the DDMP method are investigated. Among these methods, only the DDMP method converges as the number of particles increases, but the large number of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the computation. The numerical properties of the multiscale method are investigated as well as the results from this multi-scale calculation are compared of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the computation. The numerical properties of the multiscale method are investigated as well as the results from this multi-scale calculation are compared with direct MD simulation results to demonstrate the feasibility of the method. Also, the multi-scale method is applied for a two dimensional problem of jet formation around copper notch under a strong impact.« less

Towards Anatomic Scale Agent-Based Modeling with a Massively Parallel Spatially Explicit General-Purpose Model of Enteric Tissue (SEGMEnT_HPC)

PubMed Central

Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary

2015-01-01

Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis. PMID:25806784

Towards Personalized Cardiology: Multi-Scale Modeling of the Failing Heart

PubMed Central

Amr, Ali; Neumann, Dominik; Georgescu, Bogdan; Seegerer, Philipp; Kamen, Ali; Haas, Jan; Frese, Karen S.; Irawati, Maria; Wirsz, Emil; King, Vanessa; Buss, Sebastian; Mereles, Derliz; Zitron, Edgar; Keller, Andreas; Katus, Hugo A.; Comaniciu, Dorin; Meder, Benjamin

2015-01-01

Background Despite modern pharmacotherapy and advanced implantable cardiac devices, overall prognosis and quality of life of HF patients remain poor. This is in part due to insufficient patient stratification and lack of individualized therapy planning, resulting in less effective treatments and a significant number of non-responders. Methods and Results State-of-the-art clinical phenotyping was acquired, including magnetic resonance imaging (MRI) and biomarker assessment. An individualized, multi-scale model of heart function covering cardiac anatomy, electrophysiology, biomechanics and hemodynamics was estimated using a robust framework. The model was computed on n=46 HF patients, showing for the first time that advanced multi-scale models can be fitted consistently on large cohorts. Novel multi-scale parameters derived from the model of all cases were analyzed and compared against clinical parameters, cardiac imaging, lab tests and survival scores to evaluate the explicative power of the model and its potential for better patient stratification. Model validation was pursued by comparing clinical parameters that were not used in the fitting process against model parameters. Conclusion This paper illustrates how advanced multi-scale models can complement cardiovascular imaging and how they could be applied in patient care. Based on obtained results, it becomes conceivable that, after thorough validation, such heart failure models could be applied for patient management and therapy planning in the future, as we illustrate in one patient of our cohort who received CRT-D implantation. PMID:26230546

COMMUNITY MULTISCALE AIR QUALITY MODELING SYSTEM (ONE ATMOSPHERE)

EPA Science Inventory

This task supports ORD's strategy by providing responsive technical support of EPA's mission and provides credible state of the art air quality models and guidance. This research effort is to develop and improve the Community Multiscale Air Quality (CMAQ) modeling system, a mu...

Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was ...

Multiscale modeling methods in biomechanics.

PubMed

Bhattacharya, Pinaki; Viceconti, Marco

2017-05-01

More and more frequently, computational biomechanics deals with problems where the portion of physical reality to be modeled spans over such a large range of spatial and temporal dimensions, that it is impossible to represent it as a single space-time continuum. We are forced to consider multiple space-time continua, each representing the phenomenon of interest at a characteristic space-time scale. Multiscale models describe a complex process across multiple scales, and account for how quantities transform as we move from one scale to another. This review offers a set of definitions for this emerging field, and provides a brief summary of the most recent developments on multiscale modeling in biomechanics. Of all possible perspectives, we chose that of the modeling intent, which vastly affect the nature and the structure of each research activity. To the purpose we organized all papers reviewed in three categories: 'causal confirmation,' where multiscale models are used as materializations of the causation theories; 'predictive accuracy,' where multiscale modeling is aimed to improve the predictive accuracy; and 'determination of effect,' where multiscale modeling is used to model how a change at one scale manifests in an effect at another radically different space-time scale. Consistent with how the volume of computational biomechanics research is distributed across application targets, we extensively reviewed papers targeting the musculoskeletal and the cardiovascular systems, and covered only a few exemplary papers targeting other organ systems. The review shows a research subdomain still in its infancy, where causal confirmation papers remain the most common. WIREs Syst Biol Med 2017, 9:e1375. doi: 10.1002/wsbm.1375 For further resources related to this article, please visit the WIREs website. © 2017 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc.

Multiscale Modeling and Simulation of Material Processing

DTIC Science & Technology

2006-07-01

As a re- GIMP simulations . Fig. 2 illustrates the contact algo- suit, MPM using a single mesh tends to induce early con- rithm for the contact pair ...21-07-2006 Final Performance Report 05-01-2003 - 04-30-2006 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Multiscale Modeling and Simulation of Material...development of scaling laws for multiscale simulations from atomistic to continuum using material testing techniques, such as tension and indentation

Multi-scale heat and mass transfer modelling of cell and tissue cryopreservation

PubMed Central

Xu, Feng; Moon, Sangjun; Zhang, Xiaohui; Shao, Lei; Song, Young Seok; Demirci, Utkan

2010-01-01

Cells and tissues undergo complex physical processes during cryopreservation. Understanding the underlying physical phenomena is critical to improve current cryopreservation methods and to develop new techniques. Here, we describe multi-scale approaches for modelling cell and tissue cryopreservation including heat transfer at macroscale level, crystallization, cell volume change and mass transport across cell membranes at microscale level. These multi-scale approaches allow us to study cell and tissue cryopreservation. PMID:20047939

Multi-scale modelling of rubber-like materials and soft tissues: an appraisal

PubMed Central

Puglisi, G.

2016-01-01

We survey, in a partial way, multi-scale approaches for the modelling of rubber-like and soft tissues and compare them with classical macroscopic phenomenological models. Our aim is to show how it is possible to obtain practical mathematical models for the mechanical behaviour of these materials incorporating mesoscopic (network scale) information. Multi-scale approaches are crucial for the theoretical comprehension and prediction of the complex mechanical response of these materials. Moreover, such models are fundamental in the perspective of the design, through manipulation at the micro- and nano-scales, of new polymeric and bioinspired materials with exceptional macroscopic properties. PMID:27118927

Multi-Scale Validation of a Nanodiamond Drug Delivery System and Multi-Scale Engineering Education

ERIC Educational Resources Information Center

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…

COMMUNITY MULTISCALE AIR QUALITY ( CMAQ ) MODEL - QUALITY ASSURANCE AND VERSION CONTROL

EPA Science Inventory

This presentation will be given to the EPA Exposure Modeling Workgroup on January 24, 2006. The quality assurance and version control procedures for the Community Multiscale Air Quality (CMAQ) Model are presented. A brief background of CMAQ is given, then issues related to qual...

Evaluation of the Community Multiscale Air Quality (CMAQ) Model Version 5.2

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

Evaluation of the Community Multi-scale Air Quality Model Version 5.2

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

A review on battery thermal management in electric vehicle application

NASA Astrophysics Data System (ADS)

Xia, Guodong; Cao, Lei; Bi, Guanglong

2017-11-01

The global issues of energy crisis and air pollution have offered a great opportunity to develop electric vehicles. However, so far, cycle life of power battery, environment adaptability, driving range and charging time seems far to compare with the level of traditional vehicles with internal combustion engine. Effective battery thermal management (BTM) is absolutely essential to relieve this situation. This paper reviews the existing literature from two levels that are cell level and battery module level. For single battery, specific attention is paid to three important processes which are heat generation, heat transport, and heat dissipation. For large format cell, multi-scale multi-dimensional coupled models have been developed. This will facilitate the investigation on factors, such as local irreversible heat generation, thermal resistance, current distribution, etc., that account for intrinsic temperature gradients existing in cell. For battery module based on air and liquid cooling, series, series-parallel and parallel cooling configurations are discussed. Liquid cooling strategies, especially direct liquid cooling strategies, are reviewed and they may advance the battery thermal management system to a new generation.

Multiscale Simulation Framework for Coupled Fluid Flow and Mechanical Deformation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hou, Thomas; Efendiev, Yalchin; Tchelepi, Hamdi

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-scalemore » 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.« less

Multiscale analysis and computation for flows in heterogeneous media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Efendiev, Yalchin; Hou, T. Y.; Durlofsky, L. J.

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-scalemore » 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.« less

DEVELOPMENT OF AN AGGREGATION AND EPISODE SELECTION SCHEME TO SUPPORT THE MODELS-3 COMMUNITY MULTISCALE AIR QUALITY MODEL

EPA Science Inventory

The development of an episode selection and aggregation approach, designed to support distributional estimation of use with the Models-3 Community Multiscale Air Quality (CMAQ) model, is described. The approach utilized cluster analysis of the 700-hPa east-west and north-south...

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

EPA Science Inventory

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

Lattice Boltzmann modeling of transport phenomena in fuel cells and flow batteries

NASA Astrophysics Data System (ADS)

Xu, Ao; Shyy, Wei; Zhao, Tianshou

2017-06-01

Fuel cells and flow batteries are promising technologies to address climate change and air pollution problems. An understanding of the complex multiscale and multiphysics transport phenomena occurring in these electrochemical systems requires powerful numerical tools. Over the past decades, the lattice Boltzmann (LB) method has attracted broad interest in the computational fluid dynamics and the numerical heat transfer communities, primarily due to its kinetic nature making it appropriate for modeling complex multiphase transport phenomena. More importantly, the LB method fits well with parallel computing due to its locality feature, which is required for large-scale engineering applications. In this article, we review the LB method for gas-liquid two-phase flows, coupled fluid flow and mass transport in porous media, and particulate flows. Examples of applications are provided in fuel cells and flow batteries. Further developments of the LB method are also outlined.

Multi-Scale Computational Models for Electrical Brain Stimulation

PubMed Central

Seo, Hyeon; Jun, Sung C.

2017-01-01

Electrical brain stimulation (EBS) is an appealing method to treat neurological disorders. To achieve optimal stimulation effects and a better understanding of the underlying brain mechanisms, neuroscientists have proposed computational modeling studies for a decade. Recently, multi-scale models that combine a volume conductor head model and multi-compartmental models of cortical neurons have been developed to predict stimulation effects on the macroscopic and microscopic levels more precisely. As the need for better computational models continues to increase, we overview here recent multi-scale modeling studies; we focused on approaches that coupled a simplified or high-resolution volume conductor head model and multi-compartmental models of cortical neurons, and constructed realistic fiber models using diffusion tensor imaging (DTI). Further implications for achieving better precision in estimating cellular responses are discussed. PMID:29123476

Transition between inverse and direct energy cascades in multiscale optical turbulence

DOE PAGES

Malkin, V. M.; Fisch, N. J.

2018-03-06

Transition between inverse and direct energy cascades in multiscale optical turbulence. Multiscale turbulence naturally develops and plays an important role in many fluid, gas, and plasma phenomena. Statistical models of multiscale turbulence usually employ Kolmogorov hypotheses of spectral locality of interactions (meaning that interactions primarily occur between pulsations of comparable scales) and scale-invariance of turbulent pulsations. However, optical turbulence described by the nonlinear Schrodinger equation exhibits breaking of both the Kolmogorov locality and scale-invariance. A weaker form of spectral locality that holds for multi-scale optical turbulence enables a derivation of simplified evolution equations that reduce the problem to a singlemore » scale modeling. We present the derivation of these equations for Kerr media with random inhomogeneities. Then, we find the analytical solution that exhibits a transition between inverse and direct energy cascades in optical turbulence.« less

Magnetospheric Multiscale Mission Examination of Stress Balance in FTE-Type Flux Ropes at the Earth's Magnetopause

NASA Astrophysics Data System (ADS)

Akhavan-Tafti, M.; Slavin, J. A.; Le, G.; Eastwood, J. P.; Strangeway, R. J.; Russell, C. T.; Nakamura, R.; Baumjohann, W.; Torbert, R. B.; Giles, B. L.; Gershman, D. J.; Burch, J. L.

2016-12-01

Determining the magnetic field structure, electric currents, and plasma distribution within flux transfer event (FTE)-type flux ropes is critical to the understanding of their origin, evolution, and dynamics. We analyze FTEs observed by the Magnetospheric Multiscale (MMS) mission in the vicinity of the sub-solar magnetopause, i.e. 12 ± 22.5' Local Time and XGSM > 7 RE. High-resolution data from the Fluxgate Magnetometer (FGM) and Fast Plasma Investigation (FPI) are used to determine and compare the extent to which large (> 1 RE) and small (ion scale) diameter FTEs are force-free, i.e. J×B=0, or non-force-free, i.e. J×B= gradP. Three independent methods are used: i) current density parallel and perpendicular to the magnetic field derived from the plasma measurements or magnetic field using the curlometer technique; ii) direct measurement of the plasma pressure gradient by FPI; and iii) fitting magnetic field to force-free (J=αB) flux rope models. Our initial results indicate that the plasma content of the ion-scale FTEs often exceeds that of larger FTEs. This results in higher plasma pressure gradients inside smaller FTEs and a magnetic field that is less force-free than the larger flux ropes.

Construction of multi-scale consistent brain networks: methods and applications.

PubMed

Ge, Bao; Tian, Yin; Hu, Xintao; Chen, Hanbo; Zhu, Dajiang; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

Mapping human brain networks provides a basis for studying brain function and dysfunction, and thus has gained significant interest in recent years. However, modeling human brain networks still faces several challenges including constructing networks at multiple spatial scales and finding common corresponding networks across individuals. As a consequence, many previous methods were designed for a single resolution or scale of brain network, though the brain networks are multi-scale in nature. To address this problem, this paper presents a novel approach to constructing multi-scale common structural brain networks from DTI data via an improved multi-scale spectral clustering applied on our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess intrinsic structural correspondences across individuals and populations, we employed the multi-scale spectral clustering algorithm to group the DICCCOL landmarks and their connections into sub-networks, meanwhile preserving the intrinsically-established correspondences across multiple scales. Experimental results demonstrated that the proposed method can generate multi-scale consistent and common structural brain networks across subjects, and its reproducibility has been verified by multiple independent datasets. As an application, these multi-scale networks were used to guide the clustering of multi-scale fiber bundles and to compare the fiber integrity in schizophrenia and healthy controls. In general, our methods offer a novel and effective framework for brain network modeling and tract-based analysis of DTI data.

A Multiscale Parallel Computing Architecture for Automated Segmentation of the Brain Connectome

PubMed Central

Knobe, Kathleen; Newton, Ryan R.; Schlimbach, Frank; Blower, Melanie; Reid, R. Clay

2015-01-01

Several groups in neurobiology have embarked into deciphering the brain circuitry using large-scale imaging of a mouse brain and manual tracing of the connections between neurons. Creating a graph of the brain circuitry, also called a connectome, could have a huge impact on the understanding of neurodegenerative diseases such as Alzheimer’s disease. Although considerably smaller than a human brain, a mouse brain already exhibits one billion connections and manually tracing the connectome of a mouse brain can only be achieved partially. This paper proposes to scale up the tracing by using automated image segmentation and a parallel computing approach designed for domain experts. We explain the design decisions behind our parallel approach and we present our results for the segmentation of the vasculature and the cell nuclei, which have been obtained without any manual intervention. PMID:21926011

A perspective on modeling the multiscale response of energetic materials

NASA Astrophysics Data System (ADS)

Rice, Betsy M.

2017-01-01

The response of an energetic material to insult is perhaps one of the most difficult processes to model due to concurrent chemical and physical phenomena occurring over scales ranging from atomistic to continuum. Unraveling the interdependencies of these complex processes across the scales through modeling can only be done within a multiscale framework. In this paper, I will describe progress in the development of a predictive, experimentally validated multiscale reactive modeling capability for energetic materials at the Army Research Laboratory. I will also describe new challenges and research opportunities that have arisen in the course of our development which should be pursued in the future.

Evaluation of the Community Multi-scale Air Quality (CMAQ) Model Version 5.1

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

Overview and Evaluation of the Community Multiscale Air Quality Model Version 5.2

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

Evaluation of the Community Multi-scale Air Quality (CMAQ) Model Version 5.2

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

Incremental Testing of the Community Multiscale Air Quality (CMAQ) Modeling System Version 4.7

EPA Science Inventory

This paper describes the scientific and structural updates to the latest release of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7 (v4.7) and points the reader to additional resources for further details. The model updates were evaluated relative to obse...

Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) modeling system is extended to simulate ozone, particulate matter, and related precursor distributions throughout the Northern Hemisphere. Modeled processes were examined and enhanced to suitably represent the extended space and timesca...

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

High-resolution time-frequency representation of EEG data using multi-scale wavelets

NASA Astrophysics Data System (ADS)

Li, Yang; Cui, Wei-Gang; Luo, Mei-Lin; Li, Ke; Wang, Lina

2017-09-01

An efficient time-varying autoregressive (TVAR) modelling scheme that expands the time-varying parameters onto the multi-scale wavelet basis functions is presented for modelling nonstationary signals and with applications to time-frequency analysis (TFA) of electroencephalogram (EEG) signals. In the new parametric modelling framework, the time-dependent parameters of the TVAR model are locally represented by using a novel multi-scale wavelet decomposition scheme, which can allow the capability to capture the smooth trends as well as track the abrupt changes of time-varying parameters simultaneously. A forward orthogonal least square (FOLS) algorithm aided by mutual information criteria are then applied for sparse model term selection and parameter estimation. Two simulation examples illustrate that the performance of the proposed multi-scale wavelet basis functions outperforms the only single-scale wavelet basis functions or Kalman filter algorithm for many nonstationary processes. Furthermore, an application of the proposed method to a real EEG signal demonstrates the new approach can provide highly time-dependent spectral resolution capability.

A multiscale, model-based analysis of the multi-tissue interplay underlying blood glucose regulation in type I diabetes.

PubMed

Wadehn, Federico; Schaller, Stephan; Eissing, Thomas; Krauss, Markus; Kupfer, Lars

2016-08-01

A multiscale model for blood glucose regulation in diabetes type I patients is constructed by integrating detailed metabolic network models for fat, liver and muscle cells into a whole body physiologically-based pharmacokinetic/pharmacodynamic (pBPK/PD) model. The blood glucose regulation PBPK/PD model simulates the distribution and metabolization of glucose, insulin and glucagon on an organ and whole body level. The genome-scale metabolic networks in contrast describe intracellular reactions. The developed multiscale model is fitted to insulin, glucagon and glucose measurements of a 48h clinical trial featuring 6 subjects and is subsequently used to simulate (in silico) the influence of geneknockouts and drug-induced enzyme inhibitions on whole body blood glucose levels. Simulations of diabetes associated gene knockouts and impaired cellular glucose metabolism, resulted in elevated whole body blood-glucose levels, but also in a metabolic shift within the cell's reaction network. Such multiscale models have the potential to be employed in the exploration of novel drug-targets or to be integrated into control algorithms for artificial pancreas systems.

Magnetospheric Multiscale Satellite Observations of Parallel Electron Acceleration in Magnetic Field Reconnection by Fermi Reflection from Time Domain Structures

NASA Technical Reports Server (NTRS)

Mozer, F. S.; Agapitov, O. A.; Artemyev, A.; Burch, J. L.; Ergun, R. E.; Giles, B. L.; Mourenas, D.; Torbert, R. B.; Phan, T. D.; Vasko, I.

2016-01-01

The same time domain structures (TDS) have been observed on two Magnetospheric Multiscale Satellites near Earth's dayside magnetopause. These TDS, traveling away from the X line along the magnetic field at 4000 km/s, accelerated field-aligned approx. 5 eV electrons to approx. 200 eV by a single Fermi reflection of the electrons by these overtaking barriers. Additionally, the TDS contained both positive and negative potentials, so they were a mixture of electron holes and double layers. They evolve in approx.10 km of space or 7 ms of time and their spatial scale size is 10-20 km, which is much larger than the electron gyroradius (less than1km) or the electron inertial length (4 km at the observation point, less nearer the X line).

A Liver-centric Multiscale Modeling Framework for Xenobiotics

EPA Science Inventory

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...

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mehrez, Loujaine; Ghanem, Roger; McAuliffe, Colin

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stander, Nielen; Basudhar, Anirban; Basu, Ushnish

2015-09-14

Ever-tightening regulations on fuel economy, and the likely future regulation of carbon emissions, demand persistent innovation in vehicle design to reduce vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials, by adding material diversity and composite materials, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing plate thickness while retaining sufficient strength and ductility required for durability and safety. A project tomore » develop computational material models for advanced high strength steel is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the US Department of Energy. Under this program, new Third Generation Advanced High Strength Steel (i.e., 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. The objectives of the project are to integrate atomistic, microstructural, forming and performance models to create an integrated computational materials engineering (ICME) toolkit for 3GAHSS. The mechanical properties of Advanced High Strength Steels (AHSS) are controlled by many factors, including phase composition and distribution in the overall microstructure, volume fraction, size and morphology of phase constituents as well as stability of the metastable retained austenite phase. The complex phase transformation and deformation mechanisms in these steels make the well-established traditional techniques obsolete, and a multi-scale microstructure-based modeling approach following the ICME [0]strategy was therefore chosen in this project. Multi-scale modeling as a major area of research and development is an outgrowth of the Comprehensive Test Ban Treaty of 1996 which banned surface testing of nuclear devices [1]. This had the effect that experimental work was reduced from large scale tests to multiscale experiments to provide material models with validation at different length scales. In the subsequent years industry realized that multi-scale modeling and simulation-based design were transferable to the design optimization of any structural system. Horstemeyer [1] lists a number of advantages of the use of multiscale modeling. Among these are: the reduction of product development time by alleviating costly trial-and-error iterations as well as the reduction of product costs through innovations in material, product and process designs. Multi-scale modeling can reduce the number of costly large scale experiments and can increase product quality by providing more accurate predictions. Research tends to be focussed on each particular length scale, which enhances accuracy in the long term. This paper serves as an introduction to the LS-OPT and LS-DYNA methodology for multi-scale modeling. It mainly focuses on an approach to integrate material identification using material models of different length scales. As an example, a multi-scale material identification strategy, consisting of a Crystal Plasticity (CP) material model and a homogenized State Variable (SV) model, is discussed and the parameter identification of the individual material models of different length scales is demonstrated. The paper concludes with thoughts on integrating the multi-scale methodology into the overall vehicle design.« less

FIRST RESULTS FROM OPERATIONAL TESTING OF THE U.S. EPA MODELS-3 COMMUNITY MULTISCALE MODEL FOR AIR QUALITY (CMAQ)

EPA Science Inventory

The Models 3 / Community Multiscale Model for Air Quality (CMAQ) has been designed for one-atmosphere assessments for multiple pollutants including ozone (O3), particulate matter (PM10, PM2.5), and acid / nutrient deposition. In this paper we report initial results of our evalu...

EVALUATION OF THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL VERSION 4.5: UNCERTAINTIES AND SENSITIVITIES IMPACTING MODEL PERFORMANCE: PART I - OZONE

EPA Science Inventory

This study examines ozone (O₃) predictions from the Community Multiscale Air Quality (CMAQ) model version 4.5 and discusses potential factors influencing the model results. Daily maximum 8-hr average O₃ levels are largely underpredicted when observed O_...

Overview and Evaluation of the Community Multiscale Air Quality (CMAQ) Modeling System Version 5.2

EPA Science Inventory

A new version of the Community Multiscale Air Quality (CMAQ) model, version 5.2 (CMAQv5.2), is currently being developed, with a planned release date in 2017. The new model includes numerous updates from the previous version of the model (CMAQv5.1). Specific updates include a new...

Multi-scale modeling in cell biology

PubMed Central

Meier-Schellersheim, Martin; Fraser, Iain D. C.; Klauschen, Frederick

2009-01-01

Biomedical research frequently involves performing experiments and developing hypotheses that link different scales of biological systems such as, for instance, the scales of intracellular molecular interactions to the scale of cellular behavior and beyond to the behavior of cell populations. Computational modeling efforts that aim at exploring such multi-scale systems quantitatively with the help of simulations have to incorporate several different simulation techniques due to the different time and space scales involved. Here, we provide a non-technical overview of how different scales of experimental research can be combined with the appropriate computational modeling techniques. We also show that current modeling software permits building and simulating multi-scale models without having to become involved with the underlying technical details of computational modeling. PMID:20448808

MMS Observations of Parallel Electric Fields During a Quasi-Perpendicular Bow Shock Crossing

NASA Astrophysics Data System (ADS)

Goodrich, K.; Schwartz, S. J.; Ergun, R.; Wilder, F. D.; Holmes, J.; Burch, J. L.; Gershman, D. J.; Giles, B. L.; Khotyaintsev, Y. V.; Le Contel, O.; Lindqvist, P. A.; Strangeway, R. J.; Russell, C.; Torbert, R. B.

2016-12-01

Previous observations of the terrestrial bow shock have frequently shown large-amplitude fluctuations in the parallel electric field. These parallel electric fields are seen as both nonlinear solitary structures, such as double layers and electron phase-space holes, and short-wavelength waves, which can reach amplitudes greater than 100 mV/m. The Magnetospheric Multi-Scale (MMS) Mission has crossed the Earth's bow shock more than 200 times. The parallel electric field signatures observed in these crossings are seen in very discrete packets and evolve over time scales of less than a second, indicating the presence of a wealth of kinetic-scale activity. The high time resolution of the Fast Particle Instrument (FPI) available on MMS offers greater detail of the kinetic-scale physics that occur at bow shocks than ever before, allowing greater insight into the overall effect of these observed electric fields. We present a characterization of these parallel electric fields found in a single bow shock event and how it reflects the kinetic-scale activity that can occur at the terrestrial bow shock.

Scaling of Electron Heating During Magnetic Reconnection

NASA Astrophysics Data System (ADS)

Ohia, O.; Le, A.; Daughton, W. S.; Egedal, J.

2016-12-01

While magnetic reconnection plays a major role in accelerating and heating magnetospheric plasma, it remains poorly understood how the level of particle energization depends on the plasma conditions. Meanwhile, a recent survey of THEMIS magnetopause reconnection observations [Phan et al. GRL 2013] and a numerical study [Shay et al. PoP 2014] found empirically that the electron heating scales with the square of the upstream Alfven speed. Equivalently for weak guide fields, the fractional electron temperature increase is inversely proportional to the upstream electron beta (ratio of electron to magnetic pressure). We present models for symmetric reconnection with moderate [Ohia et al., GRL 2015] or zero guide field that predict the electron bulk heating. In the models, adiabatically trapped electrons gain energy from parallel electric fields in the inflowing region. For purely anti-parallel reconnection, meandering electrons receive additional energy from the reconnection electric field. The predicted scalings are in quantitative agreement with fluid and kinetic simulations, as well as spacecraft observations. Using kinetic simulations, we extend this work to explore how the layer dynamics and electron bulk heating vary as functions of the magnetic shear and plasma and magnetic pressure asymmetry across the reconnection layer. These results are pertinent to recent Magnetospheric Multiscale (MMS) Mission measurements of electron dynamics during dayside magnetopause reconnection.

Multiscale geometric modeling of macromolecules II: Lagrangian representation

PubMed Central

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

Widespread mechanosensing controls the structure behind the architecture in plants.

PubMed

Hamant, Olivier

2013-10-01

Mechanical forces play an instructing role for many aspects of animal cell biology, such as division, polarity and fate. Although the associated mechanoperception pathways still remain largely elusive in plants, physical cues have long been thought to guide development in parallel to biochemical factors. With the development of new imaging techniques, micromechanics tools and modeling approaches, the role of mechanical signals in plant development is now re-examined and fully integrated with modern cell biology. Using recent examples from the literature, I propose to use a multiscale perspective, from the whole plant down to the cell wall, to fully appreciate the diversity of developmental processes that depend on mechanical signals. Incidentally, this also illustrates how conceptually rich this field is. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

EPA Science Inventory

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

Models, Databases, and Simulation Tools Needed for the Realization of Integrated Computational Materials Engineering. Proceedings of the Symposium Held at Materials Science and Technology 2010

NASA Technical Reports Server (NTRS)

Arnold, Steven M. (Editor); Wong, Terry T. (Editor)

2011-01-01

Topics covered include: An Annotative Review of Multiscale Modeling and its Application to Scales Inherent in the Field of ICME; and A Multiscale, Nonlinear, Modeling Framework Enabling the Design and Analysis of Composite Materials and Structures.

Evaluation of the Community Multiscale Air Quality Model for Simulating Winter Ozone Formation in the Uinta Basin.

EPA Science Inventory

The Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models were used to simulate a 10 day high‐ozone episode observed during the 2013 Uinta Basin Winter Ozone Study (UBWOS). The baseline model had a large negative bias when compared to ozo...

Prediction of failure in notched carbon-fibre-reinforced-polymer laminates under multi-axial loading.

PubMed

Tan, J L Y; Deshpande, V S; Fleck, N A

2016-07-13

A damage-based finite-element model is used to predict the fracture behaviour of centre-notched quasi-isotropic carbon-fibre-reinforced-polymer laminates under multi-axial loading. Damage within each ply is associated with fibre tension, fibre compression, matrix tension and matrix compression. Inter-ply delamination is modelled by cohesive interfaces using a traction-separation law. Failure envelopes for a notch and a circular hole are predicted for in-plane multi-axial loading and are in good agreement with the observed failure envelopes from a parallel experimental study. The ply-by-ply (and inter-ply) damage evolution and the critical mechanisms of ultimate failure also agree with the observed damage evolution. It is demonstrated that accurate predictions of notched compressive strength are obtained upon employing the band broadening stress for microbuckling, highlighting the importance of this damage mode in compression. This article is part of the themed issue 'Multiscale modelling of the structural integrity of composite materials'. © 2016 The Author(s).

Multiscale modeling of mucosal immune responses

PubMed Central

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 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. PMID:26329787

Multiscale modeling of mucosal immune responses.

PubMed

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 cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM.

Recent Enhancements to the Community Multiscale Air Quality Modeling System (CMAQ)

EPA Science Inventory

EPA’s Office of Research and Development, Computational Exposure Division held a webinar on January 31, 2017 to present the recent scientific and computational updates made by EPA to the Community Multi-Scale Air Quality Model (CMAQ). Topics covered included: (1) Improveme...

Sensitivity of the Community Multiscale Air Quality (CMAQ) Model v4.7 Results for the Eastern United States to MM5 and WRF Meteorological Drivers

EPA Science Inventory

This paper presents a comparison of the operational performance of two Community Multiscale Air Quality (CMAQ) model v4.7 simulations that utilize input data from the 5th generation Mesoscale Model MM5 and the Weather Research and Forecasting (WRF) meteorological models.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perdikaris, Paris, E-mail: parisp@mit.edu; Grinberg, Leopold, E-mail: leopoldgrinberg@us.ibm.com; Karniadakis, George Em, E-mail: george-karniadakis@brown.edu

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 takingmore » 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.« less

eDNAoccupancy: An R package for multi-scale occupancy modeling of environmental DNA data

USGS Publications Warehouse

Dorazio, Robert; Erickson, Richard A.

2017-01-01

In this article we describe eDNAoccupancy, an R package for fitting Bayesian, multi-scale occupancy models. These models are appropriate for occupancy surveys that include three, nested levels of sampling: primary sample units within a study area, secondary sample units collected from each primary unit, and replicates of each secondary sample unit. This design is commonly used in occupancy surveys of environmental DNA (eDNA). eDNAoccupancy allows users to specify and fit multi-scale occupancy models with or without covariates, to estimate posterior summaries of occurrence and detection probabilities, and to compare different models using Bayesian model-selection criteria. We illustrate these features by analyzing two published data sets: eDNA surveys of a fungal pathogen of amphibians and eDNA surveys of an endangered fish species.

Multiscale Modeling and Uncertainty Quantification for Nuclear Fuel Performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Estep, Donald; El-Azab, Anter; Pernice, Michael

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 formore » 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.« less

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

PubMed

Xia, Kelin

2017-12-20

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

Multiscale Modeling of Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

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.

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model

EPA Science Inventory

Sea spray aerosols (SSA) impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. In this study, the Community Multiscale Air Quality (CMAQ) model is updated to enhance fine mode SSA emissions,...

Industrial process system assessment: bridging process engineering and life cycle assessment through multiscale modeling.

EPA Science Inventory

The Industrial Process System Assessment (IPSA) methodology is a multiple step allocation approach for connecting information from the production line level up to the facility level and vice versa using a multiscale model of process systems. The allocation procedure assigns inpu...

Cloud processing of gases and aerosols in the Community Multiscale Air Quality (CMAQ) model: Impacts of extended chemistry

EPA Science Inventory

Clouds and fogs can significantly impact the concentration and distribution of atmospheric gases and aerosols through chemistry, scavenging, and transport. This presentation summarizes the representation of cloud processes in the Community Multiscale Air Quality (CMAQ) modeling ...

Multi-scale habitat selection modeling: A review and outlook

Treesearch

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

2016-01-01

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

A Multi-Resolution Assessment of the Community Multiscale Air Quality (CMAQ) Model v4.7 Wet Deposition Estimates for 2002 - 2006

EPA Science Inventory

This paper examines the operational performance of the Community Multiscale Air Quality (CMAQ) model simulations for 2002 - 2006 using both 36-km and 12-km horizontal grid spacing, with a primary focus on the performance of the CMAQ model in predicting wet deposition of sulfate (...

A new hybrid code (CHIEF) implementing the inertial electron fluid equation without approximation

NASA Astrophysics Data System (ADS)

Muñoz, P. A.; Jain, N.; Kilian, P.; Büchner, J.

2018-03-01

We present a new hybrid algorithm implemented in the code CHIEF (Code Hybrid with Inertial Electron Fluid) for simulations of electron-ion plasmas. The algorithm treats the ions kinetically, modeled by the Particle-in-Cell (PiC) method, and electrons as an inertial fluid, modeled by electron fluid equations without any of the approximations used in most of the other hybrid codes with an inertial electron fluid. This kind of code is appropriate to model a large variety of quasineutral plasma phenomena where the electron inertia and/or ion kinetic effects are relevant. We present here the governing equations of the model, how these are discretized and implemented numerically, as well as six test problems to validate our numerical approach. Our chosen test problems, where the electron inertia and ion kinetic effects play the essential role, are: 0) Excitation of parallel eigenmodes to check numerical convergence and stability, 1) parallel (to a background magnetic field) propagating electromagnetic waves, 2) perpendicular propagating electrostatic waves (ion Bernstein modes), 3) ion beam right-hand instability (resonant and non-resonant), 4) ion Landau damping, 5) ion firehose instability, and 6) 2D oblique ion firehose instability. Our results reproduce successfully the predictions of linear and non-linear theory for all these problems, validating our code. All properties of this hybrid code make it ideal to study multi-scale phenomena between electron and ion scales such as collisionless shocks, magnetic reconnection and kinetic plasma turbulence in the dissipation range above the electron scales.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Emery, John M.; Coffin, Peter; Robbins, Brian A.

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

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matouš, Karel, E-mail: kmatous@nd.edu; Geers, Marc G.D.; Kouznetsova, Varvara G.

2017-02-01

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

MMS Observations and Hybrid Simulations of Surface Ripples at a Marginally Quasi-Parallel Shock

NASA Astrophysics Data System (ADS)

Gingell, Imogen; Schwartz, Steven J.; Burgess, David; Johlander, Andreas; Russell, Christopher T.; Burch, James L.; Ergun, Robert E.; Fuselier, Stephen; Gershman, Daniel J.; Giles, Barbara L.; Goodrich, Katherine A.; Khotyaintsev, Yuri V.; Lavraud, Benoit; Lindqvist, Per-Arne; Strangeway, Robert J.; Trattner, Karlheinz; Torbert, Roy B.; Wei, Hanying; Wilder, Frederick

2017-11-01

Simulations and observations of collisionless shocks have shown that deviations of the nominal local shock normal orientation, that is, surface waves or ripples, are expected to propagate in the ramp and overshoot of quasi-perpendicular shocks. Here we identify signatures of a surface ripple propagating during a crossing of Earth's marginally quasi-parallel (θBn˜45∘) or quasi-parallel bow shock on 27 November 2015 06:01:44 UTC by the Magnetospheric Multiscale (MMS) mission and determine the ripple's properties using multispacecraft methods. Using two-dimensional hybrid simulations, we confirm that surface ripples are a feature of marginally quasi-parallel and quasi-parallel shocks under the observed solar wind conditions. In addition, since these marginally quasi-parallel and quasi-parallel shocks are expected to undergo a cyclic reformation of the shock front, we discuss the impact of multiple sources of nonstationarity on shock structure. Importantly, ripples are shown to be transient phenomena, developing faster than an ion gyroperiod and only during the period of the reformation cycle when a newly developed shock ramp is unaffected by turbulence in the foot. We conclude that the change in properties of the ripple observed by MMS is consistent with the reformation of the shock front over a time scale of an ion gyroperiod.

Beyond Low Rank + Sparse: Multi-scale Low Rank Matrix Decomposition

PubMed Central

Ong, Frank; Lustig, Michael

2016-01-01

We present a natural generalization of the recent low rank + sparse matrix decomposition and consider the decomposition of matrices into components of multiple scales. Such decomposition is well motivated in practice as data matrices often exhibit local correlations in multiple scales. Concretely, we propose a multi-scale low rank modeling that represents a data matrix as a sum of block-wise low rank matrices with increasing scales of block sizes. We then consider the inverse problem of decomposing the data matrix into its multi-scale low rank components and approach the problem via a convex formulation. Theoretically, we show that under various incoherence conditions, the convex program recovers the multi-scale low rank components either exactly or approximately. Practically, we provide guidance on selecting the regularization parameters and incorporate cycle spinning to reduce blocking artifacts. Experimentally, we show that the multi-scale low rank decomposition provides a more intuitive decomposition than conventional low rank methods and demonstrate its effectiveness in four applications, including illumination normalization for face images, motion separation for surveillance videos, multi-scale modeling of the dynamic contrast enhanced magnetic resonance imaging and collaborative filtering exploiting age information. PMID:28450978

Transition between inverse and direct energy cascades in multiscale optical turbulence.

PubMed

Malkin, V M; Fisch, N J

2018-03-01

Multiscale turbulence naturally develops and plays an important role in many fluid, gas, and plasma phenomena. Statistical models of multiscale turbulence usually employ Kolmogorov hypotheses of spectral locality of interactions (meaning that interactions primarily occur between pulsations of comparable scales) and scale-invariance of turbulent pulsations. However, optical turbulence described by the nonlinear Schrodinger equation exhibits breaking of both the Kolmogorov locality and scale-invariance. A weaker form of spectral locality that holds for multi-scale optical turbulence enables a derivation of simplified evolution equations that reduce the problem to a single scale modeling. We present the derivation of these equations for Kerr media with random inhomogeneities. Then, we find the analytical solution that exhibits a transition between inverse and direct energy cascades in optical turbulence.

Transition between inverse and direct energy cascades in multiscale optical turbulence

NASA Astrophysics Data System (ADS)

Malkin, V. M.; Fisch, N. J.

2018-03-01

Multiscale turbulence naturally develops and plays an important role in many fluid, gas, and plasma phenomena. Statistical models of multiscale turbulence usually employ Kolmogorov hypotheses of spectral locality of interactions (meaning that interactions primarily occur between pulsations of comparable scales) and scale-invariance of turbulent pulsations. However, optical turbulence described by the nonlinear Schrodinger equation exhibits breaking of both the Kolmogorov locality and scale-invariance. A weaker form of spectral locality that holds for multi-scale optical turbulence enables a derivation of simplified evolution equations that reduce the problem to a single scale modeling. We present the derivation of these equations for Kerr media with random inhomogeneities. Then, we find the analytical solution that exhibits a transition between inverse and direct energy cascades in optical turbulence.

Hybrid multiscale modeling and prediction of cancer cell behavior

PubMed Central

Habibi, Jafar

2017-01-01

Background Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. Methods In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for prediction of cell phenotypes. By using a proposed Q-learning based on SVR-NSGA-II method, the cells have the capability to predict their phenotypes autonomously that is, to act on its own without external direction in response to situations it encounters. Results Computational simulations of the model were performed in order to analyze its performance. The most striking feature of our results is that each cell can select its phenotype at each time step according to its condition. We provide evidence that the prediction of cell phenotypes is reliable. Conclusion Our proposed model, which we term a hybrid multiscale modeling of cancer cell behavior, has the potential to combine the best features of both continuum and discrete models. The in silico results indicate that the 3D model can represent key features of cancer growth, angiogenesis, and its related micro-environment and show that the findings are in good agreement with biological tumor behavior. To the best of our knowledge, this paper is the first hybrid vascular multiscale modeling of cancer cell behavior that has the capability to predict cell phenotypes individually by a self-generated dataset. PMID:28846712

Hybrid multiscale modeling and prediction of cancer cell behavior.

PubMed

Zangooei, Mohammad Hossein; Habibi, Jafar

2017-01-01

Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for prediction of cell phenotypes. By using a proposed Q-learning based on SVR-NSGA-II method, the cells have the capability to predict their phenotypes autonomously that is, to act on its own without external direction in response to situations it encounters. Computational simulations of the model were performed in order to analyze its performance. The most striking feature of our results is that each cell can select its phenotype at each time step according to its condition. We provide evidence that the prediction of cell phenotypes is reliable. Our proposed model, which we term a hybrid multiscale modeling of cancer cell behavior, has the potential to combine the best features of both continuum and discrete models. The in silico results indicate that the 3D model can represent key features of cancer growth, angiogenesis, and its related micro-environment and show that the findings are in good agreement with biological tumor behavior. To the best of our knowledge, this paper is the first hybrid vascular multiscale modeling of cancer cell behavior that has the capability to predict cell phenotypes individually by a self-generated dataset.

Evolution of Tides and Tidal Dissipation Over the Past 26,000 Years Using a Multi-Scale Model of Global Barotropic Tides

NASA Astrophysics Data System (ADS)

Salehipour, H.; Peltier, W. R.

2014-12-01

In this paper we will describe the results obtained through integration of a further refined version of the truly global barotropic tidal model of Salehipour et al. (Ocean Modell., 69, 2013) using the most recent reconstruction of ice-age bathymetric conditions as embodied in the recently constructed ICE-6G_C (VM5a) model of Peltier et al. (JGR-Solid Earth, in press, 2014). Our interest is in the spatial and temporal evolution of tidal amplitude, phase and dissipation from the Last Glacial Maximum (LGM) 26,000 years ago until the present. The state-of-the-art higher order nonlinear tidal model of Salehipour et al. (2013) includes a highly parallelized multi-scale framework in which an unstructured tessellation of the global ocean enables extensive local refinement around regions of interest such as the Hawaiian Ridge, the Brazil Basin and the Southern Ocean. At LGM, features such as the Patagonian Shelf were fully exposed land which during the deglaciation process would have been flooded leading to significant changes of tidal range along the evolving coastline. In the further development of this model we have included the fully iterated treatment of the influence of gravitational self-attraction and loading as in, e.g. Egbert et al. (JGR-Oceans, 109, 2004). The treatment of the dissipation of the barotropic tide through dissipation of the internal tide has also been significantly improved. Our paleobathymetry and coastline data sets extend from LGM to present at 500 year intervals and constitute a significant refinement of the widely employed ICE-5G (VM2) model of Peltier (Annu. Rev. Earth Planet. Sci., 32, 2004). Our results will be compared with those recently published by Green & Nycander (JPO, 43, 2013) and Wilmes & Green (JGR-Oceans, 119, 2014) as well as with the earlier results of Griffiths & Peltier (GRL, 35, 2008; J. Clim., 22, 2009).

Electron Pressure Anisotropy in the Terrestrial Reconnection Experiment and the Magnetospheric Multiscale Mission

NASA Astrophysics Data System (ADS)

Myers, Rachel; Egedal, Jan; Olson, Joseph; Greess, Samuel; Millet-Ayala, Alexander; Clark, Michael; Nonn, Paul; Wallace, John; Forest, Cary

2017-10-01

The NASA Magnetospheric Multiscale (MMS) Mission seeks to measure heating and motion of charged particles from reconnection events in the magnetotail and dayside magnetopause. MMS is paralleled by the Terrestrial Reconnection Experiment (TREX) at the Wisconsin Plasma Astrophysics Laboratory (WiPAL) in its study of collisionless magnetic reconnection. In the regimes seen by TREX and MMS, electron pressure anisotropy should develop, driving large-scale current layer formation. MMS has witnessed anisotropy, but the spatial coverage of the data is too limited to determine how the pressure anisotropy affects jet and current layer creation. Measurements of pressure anisotropy on TREX will be presented, and implications for reconnecting current layer structure in the magnetosphere, as measured by MMS, will be discussed. This research was conducted with support from a UW-Madison University Fellowship as well as the NSF/DOE award DE-SC0013032.

SHORT RANGE ENSEMBLE Products

Science.gov Websites

- CONUS Double Resolution (Lambert Conformal - 40km) NEMS Non-hydrostatic Multiscale Model on the B grid AWIPS grid 212 Regional - CONUS Double Resolution (Lambert Conformal - 40km) NEMS Non-hydrostatic 132 - Double Resolution (Lambert Conformal - 16km) NEMS Non-hydrostatic Multiscale Model on the B grid

Extending the Applicability of the Community Multiscale Air Quality Model to Hemispheric Scales: Motivation, Challenges, and Progress

EPA Science Inventory

The adaptation of the Community Multiscale Air Quality (CMAQ) modeling system to simulate O₃, particulate matter, and related precursor distributions over the northern hemisphere is presented. Hemispheric simulations with CMAQ and the Weather Research and Forecasting (...

A Goddard Multi-Scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, W.K.; Anderson, D.; Atlas, R.; Chern, J.; Houser, P.; Hou, A.; Lang, S.; Lau, W.; Peters-Lidard, C.; Kakar, R.;

Towards multiscale modeling of influenza infection

PubMed Central

Murillo, Lisa N.; Murillo, Michael S.; Perelson, Alan S.

2013-01-01

Aided by recent advances in computational power, algorithms, and higher fidelity data, increasingly detailed theoretical models of infection with influenza A virus are being developed. We review single scale models as they describe influenza infection from intracellular to global scales, and, in particular, we consider those models that capture details specific to influenza and can be used to link different scales. We discuss the few multiscale models of influenza infection that have been developed in this emerging field. In addition to discussing modeling approaches, we also survey biological data on influenza infection and transmission that is relevant for constructing influenza infection models. We envision that, in the future, multiscale models that capitalize on technical advances in experimental biology and high performance computing could be used to describe the large spatial scale epidemiology of influenza infection, evolution of the virus, and transmission between hosts more accurately. PMID:23608630

Hybrid methods for simulating hydrodynamics and heat transfer in multiscale (1D-3D) models

NASA Astrophysics Data System (ADS)

Filimonov, S. A.; Mikhienkova, E. I.; Dekterev, A. A.; Boykov, D. V.

2017-09-01

The work is devoted to application of different-scale models in the simulation of hydrodynamics and heat transfer of large and/or complex systems, which can be considered as a combination of extended and “compact” elements. The model consisting of simultaneously existing three-dimensional and network (one-dimensional) elements is called multiscale. The paper examines the relevance of building such models and considers three main options for their implementation: the spatial and the network parts of the model are calculated separately; spatial and network parts are calculated simultaneously (hydraulically unified model); network elements “penetrate” the spatial part and are connected through the integral characteristics at the tube/channel walls (hydraulically disconnected model). Each proposed method is analyzed in terms of advantages and disadvantages. The paper presents a number of practical examples demonstrating the application of multiscale models.

Versatile Micromechanics Model for Multiscale Analysis of Composite Structures

NASA Astrophysics Data System (ADS)

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.

Multiscale Modeling of Multiphase Fluid Flow

DTIC Science & Technology

2016-08-01

the disparate time and length scales involved in modeling fluid flow and heat transfer. Molecular dynamics simulations were carried out to provide a...fluid dynamics methods were used to investigate the heat transfer process in open-cell micro-foam with phase change material; enhancement of natural...Computational fluid dynamics, Heat transfer, Phase change material in Micro-foam, Molecular Dynamics, Multiphase flow, Multiscale modeling, Natural

Multi-Scale Characterization of Orthotropic Microstructures

DTIC Science & Technology

2008-04-01

D. Valiveti, S. J. Harris, J. Boileau, A domain partitioning based pre-processor for multi-scale modelling of cast aluminium alloys , Modelling and...SUPPLEMENTARY NOTES Journal article submitted to Modeling and Simulation in Materials Science and Engineering. PAO Case Number: WPAFB 08-3362...element for charac- terization or simulation to avoid misleading predictions of macroscopic defor- mation, fracture, or transport behavior. Likewise

Simulations of Tornadoes, Tropical Cyclones, MJOs, and QBOs, using GFDL's multi-scale global climate modeling system

NASA Astrophysics Data System (ADS)

Lin, Shian-Jiann; Harris, Lucas; Chen, Jan-Huey; Zhao, Ming

2014-05-01

A multi-scale High-Resolution Atmosphere Model (HiRAM) is being developed at NOAA/Geophysical Fluid Dynamics Laboratory. The model's dynamical framework is the non-hydrostatic extension of the vertically Lagrangian finite-volume dynamical core (Lin 2004, Monthly Wea. Rev.) constructed on a stretchable (via Schmidt transformation) cubed-sphere grid. Physical parametrizations originally designed for IPCC-type climate predictions are in the process of being modified and made more "scale-aware", in an effort to make the model suitable for multi-scale weather-climate applications, with horizontal resolution ranging from 1 km (near the target high-resolution region) to as low as 400 km (near the antipodal point). One of the main goals of this development is to enable simulation of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously thought impossible. We will present preliminary results, covering a very wide spectrum of temporal-spatial scales, ranging from simulation of tornado genesis (hours), Madden-Julian Oscillations (intra-seasonal), topical cyclones (seasonal), to Quasi Biennial Oscillations (intra-decadal), using the same global multi-scale modeling system.

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

PubMed

Lefkimmiatis, Stamatios; Maragos, Petros; Papandreou, George

2009-08-01

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

Scale effect challenges in urban hydrology highlighted with a Fully Distributed Model and High-resolution rainfall data

NASA Astrophysics Data System (ADS)

Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe; Ten Veldhuis, Marie-Claire

2017-04-01

Nowadays, there is a growing interest on small-scale rainfall information, provided by weather radars, to be used in urban water management and decision-making. Therefore, an increasing interest is in parallel devoted to the development of fully distributed and grid-based models following the increase of computation capabilities, the availability of high-resolution GIS information needed for such models implementation. However, the choice of an appropriate implementation scale to integrate the catchment heterogeneity and the whole measured rainfall variability provided by High-resolution radar technologies still issues. This work proposes a two steps investigation of scale effects in urban hydrology and its effects on modeling works. In the first step fractal tools are used to highlight the scale dependency observed within distributed data used to describe the catchment heterogeneity, both the structure of the sewer network and the distribution of impervious areas are analyzed. Then an intensive multi-scale modeling work is carried out to understand scaling effects on hydrological model performance. Investigations were conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model was implemented at 17 spatial resolutions ranging from 100 m to 5 m and modeling investigations were performed using both rain gauge rainfall information as well as high resolution X band radar data in order to assess the sensitivity of the model to small scale rainfall variability. Results coming out from this work demonstrate scale effect challenges in urban hydrology modeling. In fact, fractal concept highlights the scale dependency observed within distributed data used to implement hydrological models. Patterns of geophysical data change when we change the observation pixel size. The multi-scale modeling investigation performed with Multi-Hydro model at 17 spatial resolutions confirms scaling effect on hydrological model performance. Results were analyzed at three ranges of scales identified in the fractal analysis and confirmed in the modeling work. The sensitivity of the model to small-scale rainfall variability was discussed as well.

Voluntary EMG-to-force estimation with a multi-scale physiological muscle model

PubMed Central

2013-01-01

Background EMG-to-force estimation based on muscle models, for voluntary contraction has many applications in human motion analysis. The so-called Hill model is recognized as a standard model for this practical use. However, it is a phenomenological model whereby muscle activation, force-length and force-velocity properties are considered independently. Perreault reported Hill modeling errors were large for different firing frequencies, level of activation and speed of contraction. It may be due to the lack of coupling between activation and force-velocity properties. In this paper, we discuss EMG-force estimation with a multi-scale physiology based model, which has a link to underlying crossbridge dynamics. Differently from the Hill model, the proposed method provides dual dynamics of recruitment and calcium activation. Methods The ankle torque was measured for the plantar flexion along with EMG measurements of the medial gastrocnemius (GAS) and soleus (SOL). In addition to Hill representation of the passive elements, three models of the contractile parts have been compared. Using common EMG signals during isometric contraction in four able-bodied subjects, torque was estimated by the linear Hill model, the nonlinear Hill model and the multi-scale physiological model that refers to Huxley theory. The comparison was made in normalized scale versus the case in maximum voluntary contraction. Results The estimation results obtained with the multi-scale model showed the best performances both in fast-short and slow-long term contraction in randomized tests for all the four subjects. The RMS errors were improved with the nonlinear Hill model compared to linear Hill, however it showed limitations to account for the different speed of contractions. Average error was 16.9% with the linear Hill model, 9.3% with the modified Hill model. In contrast, the error in the multi-scale model was 6.1% while maintaining a uniform estimation performance in both fast and slow contractions schemes. Conclusions We introduced a novel approach that allows EMG-force estimation based on a multi-scale physiology model integrating Hill approach for the passive elements and microscopic cross-bridge representations for the contractile element. The experimental evaluation highlights estimation improvements especially a larger range of contraction conditions with integration of the neural activation frequency property and force-velocity relationship through cross-bridge dynamics consideration. PMID:24007560

Statistical Field Estimation for Complex Coastal Regions and Archipelagos (PREPRINT)

DTIC Science & Technology

2011-04-09

and study the computational properties of these schemes. Specifically, we extend a multiscale Objective Analysis (OA) approach to complex coastal...computational properties of these schemes. Specifically, we extend a multiscale Objective Analysis (OA) approach to complex coastal regions and... multiscale free-surface code builds on the primitive-equation model of the Harvard Ocean Predic- tion System (HOPS, Haley et al. (2009)). Additionally

Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing

DTIC Science & Technology

2016-07-15

AFRL-AFOSR-JP-TR-2016-0068 Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing Hean-Teik...SUBTITLE Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER... electromagnetics to the application in microwave remote sensing as well as extension of modelling capability with computational flexibility to study

Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing

DTIC Science & Technology

2016-07-15

AFRL-AFOSR-JP-TR-2016-0068 Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing Hean-Teik...SUBTITLE Multi-scale Computational Electromagnetics for Phenomenology and Saliency Characterization in Remote Sensing 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER...electromagnetics to the application in microwave remote sensing as well as extension of modelling capability with computational flexibility to study

Radiomics Evaluation of Histological Heterogeneity Using Multiscale Textures Derived From 3D Wavelet Transformation of Multispectral Images.

PubMed

Chaddad, Ahmad; Daniel, Paul; Niazi, Tamim

2018-01-01

Colorectal cancer (CRC) is markedly heterogeneous and develops progressively toward malignancy through several stages which include stroma (ST), benign hyperplasia (BH), intraepithelial neoplasia (IN) or precursor cancerous lesion, and carcinoma (CA). Identification of the malignancy stage of CRC pathology tissues (PT) allows the most appropriate therapeutic intervention. This study investigates multiscale texture features extracted from CRC pathology sections using 3D wavelet transform (3D-WT) filter. Multiscale features were extracted from digital whole slide images of 39 patients that were segmented in a pre-processing step using an active contour model. The capacity for multiscale texture to compare and classify between PTs was investigated using ANOVA significance test and random forest classifier models, respectively. 12 significant features derived from the multiscale texture (i.e., variance, entropy, and energy) were found to discriminate between CRC grades at a significance value of p  < 0.01 after correction. Combining multiscale texture features lead to a better predictive capacity compared to prediction models based on individual scale features with an average (±SD) classification accuracy of 93.33 (±3.52)%, sensitivity of 88.33 (± 4.12)%, and specificity of 96.89 (± 3.88)%. Entropy was found to be the best classifier feature across all the PT grades with an average of the area under the curve (AUC) value of 91.17, 94.21, 97.70, 100% for ST, BH, IN, and CA, respectively. Our results suggest that multiscale texture features based on 3D-WT are sensitive enough to discriminate between CRC grades with the entropy feature, the best predictor of pathology grade.

Integrating Intracellular Dynamics Using CompuCell3D and Bionetsolver: Applications to Multiscale Modelling of Cancer Cell Growth and Invasion

PubMed Central

Andasari, Vivi; Roper, Ryan T.; Swat, Maciej H.; Chaplain, Mark A. J.

2012-01-01

In this paper we present a multiscale, individual-based simulation environment that integrates CompuCell3D for lattice-based modelling on the cellular level and Bionetsolver for intracellular modelling. CompuCell3D or CC3D provides an implementation of the lattice-based Cellular Potts Model or CPM (also known as the Glazier-Graner-Hogeweg or GGH model) and a Monte Carlo method based on the metropolis algorithm for system evolution. The integration of CC3D for cellular systems with Bionetsolver for subcellular systems enables us to develop a multiscale mathematical model and to study the evolution of cell behaviour due to the dynamics inside of the cells, capturing aspects of cell behaviour and interaction that is not possible using continuum approaches. We then apply this multiscale modelling technique to a model of cancer growth and invasion, based on a previously published model of Ramis-Conde et al. (2008) where individual cell behaviour is driven by a molecular network describing the dynamics of E-cadherin and -catenin. In this model, which we refer to as the centre-based model, an alternative individual-based modelling technique was used, namely, a lattice-free approach. In many respects, the GGH or CPM methodology and the approach of the centre-based model have the same overall goal, that is to mimic behaviours and interactions of biological cells. Although the mathematical foundations and computational implementations of the two approaches are very different, the results of the presented simulations are compatible with each other, suggesting that by using individual-based approaches we can formulate a natural way of describing complex multi-cell, multiscale models. The ability to easily reproduce results of one modelling approach using an alternative approach is also essential from a model cross-validation standpoint and also helps to identify any modelling artefacts specific to a given computational approach. PMID:22461894

Parallel Multiscale Algorithms for Astrophysical Fluid Dynamics Simulations

NASA Technical Reports Server (NTRS)

Norman, Michael L.

1997-01-01

Our goal is to develop software libraries and applications for astrophysical fluid dynamics simulations in multidimensions that will enable us to resolve the large spatial and temporal variations that inevitably arise due to gravity, fronts and microphysical phenomena. The software must run efficiently on parallel computers and be general enough to allow the incorporation of a wide variety of physics. Cosmological structure formation with realistic gas physics is the primary application driver in this work. Accurate simulations of e.g. galaxy formation require a spatial dynamic range (i.e., ratio of system scale to smallest resolved feature) of 104 or more in three dimensions in arbitrary topologies. We take this as our technical requirement. We have achieved, and in fact, surpassed these goals.

Multiscale Modeling of Virus Entry via Receptor-Mediated Endocytosis

NASA Astrophysics Data System (ADS)

Liu, Jin

2012-11-01

Virus infections are ubiquitous and remain major threats to human health worldwide. Viruses are intracellular parasites and must enter host cells to initiate infection. Receptor-mediated endocytosis is the most common entry pathway taken by viruses, the whole process is highly complex and dictated by various events, such as virus motions, membrane deformations, receptor diffusion and ligand-receptor reactions, occurring at multiple length and time scales. We develop a multiscale model for virus entry through receptor-mediated endocytosis. The binding of virus to cell surface is based on a mesoscale three dimensional stochastic adhesion model, the internalization (endocytosis) of virus and cellular membrane deformation is based on the discretization of Helfrich Hamiltonian in a curvilinear space using Monte Carlo method. The multiscale model is based on the combination of these two models. We will implement this model to study the herpes simplex virus entry into B78 cells and compare the model predictions with experimental measurements.

Modeling crack propagation in polycrystalline microstructure using variational multiscale method

DOE PAGES

Sun, Shang; Sundararaghavan, Veera

2016-01-01

Crack propagation in a polycrystalline microstructure is analyzed using a novel multiscale model. The model includes an explicit microstructural representation at critical regions (stress concentrators such as notches and cracks) and a reduced order model that statistically captures the microstructure at regions far away from stress concentrations. Crack propagation is modeled in these critical regions using the variational multiscale method. In this approach, a discontinuous displacement field is added to elements that exceed the critical values of normal or tangential tractions during loading. Compared to traditional cohesive zone modeling approaches, the method does not require the use of any specialmore » interface elements in the microstructure and thus can model arbitrary crack paths. As a result, the capability of the method in predicting both intergranular and transgranular failure modes in an elastoplastic polycrystal is demonstrated under tensile and three-point bending loads.« less

A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

EPA Science Inventory

This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM − KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used t...

Observations and modeling of air quality trends over 1990-2010 across the northern hemisphere: China, the United States and Europe

EPA Science Inventory

Trends in air quality across the Northern Hemisphere over a 21-year period (1990–2010) were simulated using the Community Multiscale Air Quality (CMAQ) multiscale chemical transport model driven by meteorology from Weather Research and Forecasting WRF) simulations and internally ...

Comparing AMSR-E soil moisture estimates to the extended record of the U.S. Climate Reference Network (USCRN)

USDA-ARS?s Scientific Manuscript database

Soil moisture plays an integral role in various aspects ranging from multi-scale hydrologic modeling to agricultural decision analysis to multi-scale hydrologic modeling, from climate change assessments to drought prediction and prevention. The broad availability of soil moisture estimates has only...

Evaluation of the Community Multiscale Air Quality (CMAQ) modeling system against size-resolved measurements of inorganic particle composition across sites in North America

EPA Science Inventory

This work evaluates particle size-composition distributions simulated by the Community Multiscale Air Quality (CMAQ) model using Micro-Orifice Uniform Deposit Impactor (MOUDI) measurements at 18 sites across North America. Size-resolved measurements of particulate SO₄<...

Numerical Simulations of a Multiscale Model of Stratified Langmuir Circulation

NASA Astrophysics Data System (ADS)

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.

Large scale cardiac modeling on the Blue Gene supercomputer.

PubMed

Reumann, Matthias; Fitch, Blake G; Rayshubskiy, Aleksandr; Keller, David U; Weiss, Daniel L; Seemann, Gunnar; Dössel, Olaf; Pitman, Michael C; Rice, John J

2008-01-01

Multi-scale, multi-physical heart models have not yet been able to include a high degree of accuracy and resolution with respect to model detail and spatial resolution due to computational limitations of current systems. We propose a framework to compute large scale cardiac models. Decomposition of anatomical data in segments to be distributed on a parallel computer is carried out by optimal recursive bisection (ORB). The algorithm takes into account a computational load parameter which has to be adjusted according to the cell models used. The diffusion term is realized by the monodomain equations. The anatomical data-set was given by both ventricles of the Visible Female data-set in a 0.2 mm resolution. Heterogeneous anisotropy was included in the computation. Model weights as input for the decomposition and load balancing were set to (a) 1 for tissue and 0 for non-tissue elements; (b) 10 for tissue and 1 for non-tissue elements. Scaling results for 512, 1024, 2048, 4096 and 8192 computational nodes were obtained for 10 ms simulation time. The simulations were carried out on an IBM Blue Gene/L parallel computer. A 1 s simulation was then carried out on 2048 nodes for the optimal model load. Load balances did not differ significantly across computational nodes even if the number of data elements distributed to each node differed greatly. Since the ORB algorithm did not take into account computational load due to communication cycles, the speedup is close to optimal for the computation time but not optimal overall due to the communication overhead. However, the simulation times were reduced form 87 minutes on 512 to 11 minutes on 8192 nodes. This work demonstrates that it is possible to run simulations of the presented detailed cardiac model within hours for the simulation of a heart beat.

GNAQPMS v1.1: accelerating the Global Nested Air Quality Prediction Modeling System (GNAQPMS) on Intel Xeon Phi processors

NASA Astrophysics Data System (ADS)

Wang, Hui; Chen, Huansheng; Wu, Qizhong; Lin, Junmin; Chen, Xueshun; Xie, Xinwei; Wang, Rongrong; Tang, Xiao; Wang, Zifa

2017-08-01

The Global Nested Air Quality Prediction Modeling System (GNAQPMS) is the global version of the Nested Air Quality Prediction Modeling System (NAQPMS), which is a multi-scale chemical transport model used for air quality forecast and atmospheric environmental research. In this study, we present the porting and optimisation of GNAQPMS on a second-generation Intel Xeon Phi processor, codenamed Knights Landing (KNL). Compared with the first-generation Xeon Phi coprocessor (codenamed Knights Corner, KNC), KNL has many new hardware features such as a bootable processor, high-performance in-package memory and ISA compatibility with Intel Xeon processors. In particular, we describe the five optimisations we applied to the key modules of GNAQPMS, including the CBM-Z gas-phase chemistry, advection, convection and wet deposition modules. These optimisations work well on both the KNL 7250 processor and the Intel Xeon E5-2697 V4 processor. They include (1) updating the pure Message Passing Interface (MPI) parallel mode to the hybrid parallel mode with MPI and OpenMP in the emission, advection, convection and gas-phase chemistry modules; (2) fully employing the 512 bit wide vector processing units (VPUs) on the KNL platform; (3) reducing unnecessary memory access to improve cache efficiency; (4) reducing the thread local storage (TLS) in the CBM-Z gas-phase chemistry module to improve its OpenMP performance; and (5) changing the global communication from writing/reading interface files to MPI functions to improve the performance and the parallel scalability. These optimisations greatly improved the GNAQPMS performance. The same optimisations also work well for the Intel Xeon Broadwell processor, specifically E5-2697 v4. Compared with the baseline version of GNAQPMS, the optimised version was 3.51 × faster on KNL and 2.77 × faster on the CPU. Moreover, the optimised version ran at 26 % lower average power on KNL than on the CPU. With the combined performance and energy improvement, the KNL platform was 37.5 % more efficient on power consumption compared with the CPU platform. The optimisations also enabled much further parallel scalability on both the CPU cluster and the KNL cluster scaled to 40 CPU nodes and 30 KNL nodes, with a parallel efficiency of 70.4 and 42.2 %, respectively.

A general CFD framework for fault-resilient simulations based on multi-resolution information fusion

NASA Astrophysics Data System (ADS)

Lee, Seungjoon; Kevrekidis, Ioannis G.; Karniadakis, George Em

2017-10-01

We develop a general CFD framework for multi-resolution simulations to target multiscale problems but also resilience in exascale simulations, where faulty processors may lead to gappy, in space-time, simulated fields. We combine approximation theory and domain decomposition together with statistical learning techniques, e.g. coKriging, to estimate boundary conditions and minimize communications by performing independent parallel runs. To demonstrate this new simulation approach, we consider two benchmark problems. First, we solve the heat equation (a) on a small number of spatial "patches" distributed across the domain, simulated by finite differences at fine resolution and (b) on the entire domain simulated at very low resolution, thus fusing multi-resolution models to obtain the final answer. Second, we simulate the flow in a lid-driven cavity in an analogous fashion, by fusing finite difference solutions obtained with fine and low resolution assuming gappy data sets. We investigate the influence of various parameters for this framework, including the correlation kernel, the size of a buffer employed in estimating boundary conditions, the coarseness of the resolution of auxiliary data, and the communication frequency across different patches in fusing the information at different resolution levels. In addition to its robustness and resilience, the new framework can be employed to generalize previous multiscale approaches involving heterogeneous discretizations or even fundamentally different flow descriptions, e.g. in continuum-atomistic simulations.

Networked high-speed auroral observations combined with radar measurements for multi-scale insights

NASA Astrophysics Data System (ADS)

Hirsch, M.; Semeter, J. L.

2015-12-01

Networks of ground-based instruments to study terrestrial aurora for the purpose of analyzing particle precipitation characteristics driving the aurora have been established. Additional funding is pouring into future ground-based auroral observation networks consisting of combinations of tossable, portable, and fixed installation ground-based legacy equipment. Our approach to this problem using the High Speed Tomography (HiST) system combines tightly-synchronized filtered auroral optical observations capturing temporal features of order 10 ms with supporting measurements from incoherent scatter radar (ISR). ISR provides a broader spatial context up to order 100 km laterally on one minute time scales, while our camera field of view (FOV) is chosen to be order 10 km at auroral altitudes in order to capture 100 m scale lateral auroral features. The dual-scale observations of ISR and HiST fine-scale optical observations may be coupled through a physical model using linear basis functions to estimate important ionospheric quantities such as electron number density in 3-D (time, perpendicular and parallel to the geomagnetic field).Field measurements and analysis using HiST and PFISR are presented from experiments conducted at the Poker Flat Research Range in central Alaska. Other multiscale configuration candidates include supplementing networks of all-sky cameras such as THEMIS with co-locations of HiST-like instruments to fuse wide FOV measurements with the fine-scale HiST precipitation characteristic estimates. Candidate models for this coupling include GLOW and TRANSCAR. Future extensions of this work may include incorporating line of sight total electron count estimates from ground-based networks of GPS receivers in a sensor fusion problem.

Computational Chemistry Toolkit for Energetic Materials Design

DTIC Science & Technology

2006-11-01

industry are aggressively engaged in efforts to develop multiscale modeling and simulation methodologies to model and analyze complex phenomena across...energetic materials design. It is hoped that this toolkit will evolve into a collection of well-integrated multiscale modeling methodologies...Experimenta Theoreticala This Work 1-5-Diamino-4- methyl- tetrazolium nitrate 8.4 41.7 47.5 1-5-Diamino-4- methyl- tetrazolium azide 138.1 161.6

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed Central

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

2014-01-01

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

Multiscale implementation of infinite-swap replica exchange molecular dynamics.

PubMed

Yu, Tang-Qing; Lu, Jianfeng; Abrams, Cameron F; Vanden-Eijnden, Eric

2016-10-18

Replica exchange molecular dynamics (REMD) is a popular method to accelerate conformational sampling of complex molecular systems. The idea is to run several replicas of the system in parallel at different temperatures that are swapped periodically. These swaps are typically attempted every few MD steps and accepted or rejected according to a Metropolis-Hastings criterion. This guarantees that the joint distribution of the composite system of replicas is the normalized sum of the symmetrized product of the canonical distributions of these replicas at the different temperatures. Here we propose a different implementation of REMD in which (i) the swaps obey a continuous-time Markov jump process implemented via Gillespie's stochastic simulation algorithm (SSA), which also samples exactly the aforementioned joint distribution and has the advantage of being rejection free, and (ii) this REMD-SSA is combined with the heterogeneous multiscale method to accelerate the rate of the swaps and reach the so-called infinite-swap limit that is known to optimize sampling efficiency. The method is easy to implement and can be trivially parallelized. Here we illustrate its accuracy and efficiency on the examples of alanine dipeptide in vacuum and C-terminal β-hairpin of protein G in explicit solvent. In this latter example, our results indicate that the landscape of the protein is a triple funnel with two folded structures and one misfolded structure that are stabilized by H-bonds.

Multiscale turbulence models based on convected fluid microstructure

NASA Astrophysics Data System (ADS)

Holm, Darryl D.; Tronci, Cesare

2012-11-01

The Euler-Poincaré approach to complex fluids is used to derive multiscale equations for computationally modeling Euler flows as a basis for modeling turbulence. The model is based on a kinematic sweeping ansatz (KSA) which assumes that the mean fluid flow serves as a Lagrangian frame of motion for the fluctuation dynamics. Thus, we regard the motion of a fluid parcel on the computationally resolvable length scales as a moving Lagrange coordinate for the fluctuating (zero-mean) motion of fluid parcels at the unresolved scales. Even in the simplest two-scale version on which we concentrate here, the contributions of the fluctuating motion under the KSA to the mean motion yields a system of equations that extends known results and appears to be suitable for modeling nonlinear backscatter (energy transfer from smaller to larger scales) in turbulence using multiscale methods.

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

PubMed

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

2016-01-01

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

Multiscale Modeling, Simulation and Visualization and Their Potential for Future Aerospace Systems

NASA Technical Reports Server (NTRS)

Noor, Ahmed K. (Compiler)

2002-01-01

This document contains the proceedings of the Training Workshop on Multiscale Modeling, Simulation and Visualization and Their Potential for Future Aerospace Systems held at NASA Langley Research Center, Hampton, Virginia, March 5 - 6, 2002. The workshop was jointly sponsored by Old Dominion University's Center for Advanced Engineering Environments and NASA. Workshop attendees were from NASA, other government agencies, industry, and universities. The objectives of the workshop were to give overviews of the diverse activities in hierarchical approach to material modeling from continuum to atomistics; applications of multiscale modeling to advanced and improved material synthesis; defects, dislocations, and material deformation; fracture and friction; thin-film growth; characterization at nano and micro scales; and, verification and validation of numerical simulations, and to identify their potential for future aerospace systems.

On a sparse pressure-flow rate condensation of rigid circulation models

PubMed Central

Schiavazzi, D. E.; Hsia, T. Y.; Marsden, A. L.

2015-01-01

Cardiovascular simulation has shown potential value in clinical decision-making, providing a framework to assess changes in hemodynamics produced by physiological and surgical alterations. State-of-the-art predictions are provided by deterministic multiscale numerical approaches coupling 3D finite element Navier Stokes simulations to lumped parameter circulation models governed by ODEs. Development of next-generation stochastic multiscale models whose parameters can be learned from available clinical data under uncertainty constitutes a research challenge made more difficult by the high computational cost typically associated with the solution of these models. We present a methodology for constructing reduced representations that condense the behavior of 3D anatomical models using outlet pressure-flow polynomial surrogates, based on multiscale model solutions spanning several heart cycles. Relevance vector machine regression is compared with maximum likelihood estimation, showing that sparse pressure/flow rate approximations offer superior performance in producing working surrogate models to be included in lumped circulation networks. Sensitivities of outlets flow rates are also quantified through a Sobol’ decomposition of their total variance encoded in the orthogonal polynomial expansion. Finally, we show that augmented lumped parameter models including the proposed surrogates accurately reproduce the response of multiscale models they were derived from. In particular, results are presented for models of the coronary circulation with closed loop boundary conditions and the abdominal aorta with open loop boundary conditions. PMID:26671219

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Multi-scale streamflow variability responses to precipitation over the headwater catchments in southern China

NASA Astrophysics Data System (ADS)

Niu, Jun; Chen, Ji; Wang, Keyi; Sivakumar, Bellie

2017-08-01

This paper examines the multi-scale streamflow variability responses to precipitation over 16 headwater catchments in the Pearl River basin, South China. The long-term daily streamflow data (1952-2000), obtained using a macro-scale hydrological model, the Variable Infiltration Capacity (VIC) model, and a routing scheme, are studied. Temporal features of streamflow variability at 10 different timescales, ranging from 6 days to 8.4 years, are revealed with the Haar wavelet transform. The principal component analysis (PCA) is performed to categorize the headwater catchments with the coherent modes of multi-scale wavelet spectra. The results indicate that three distinct modes, with different variability distributions at small timescales and seasonal scales, can explain 95% of the streamflow variability. A large majority of the catchments (i.e. 12 out of 16) exhibit consistent mode feature on multi-scale variability throughout three sub-periods (1952-1968, 1969-1984, and 1985-2000). The multi-scale streamflow variability responses to precipitation are identified to be associated with the regional flood and drought tendency over the headwater catchments in southern China.

Multiscale Embedded Gene Co-expression Network Analysis

PubMed Central

Song, Won-Min; Zhang, Bin

2015-01-01

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. PMID:26618778

Multiscale Embedded Gene Co-expression Network Analysis.

PubMed

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.

Upscaling the Coupled Water and Heat Transport in the Shallow Subsurface

NASA Astrophysics Data System (ADS)

Sviercoski, R. F.; Efendiev, Y.; Mohanty, B. P.

2018-02-01

Predicting simultaneous movement of liquid water, water vapor, and heat in the shallow subsurface has many practical interests. The demand for multidimensional multiscale models for this region is important given: (a) the critical role that these processes play in the global water and energy balances, (b) that more data from air-borne and space-borne sensors are becoming available for parameterizations of modeling efforts. On the other hand, numerical models that consider spatial variations of the soil properties, termed here as multiscale, are prohibitively expensive. Thus, there is a need for upscaled models that take into consideration these features, and be computationally affordable. In this paper, a multidimensional multiscale model coupling the water flow and heat transfer and its respective upscaled version are proposed. The formulation is novel as it describes the multidimensional and multiscale tensorial versions of the hydraulic conductivity and the vapor diffusivity, taking into account the tortuosity and porosity properties of the medium. It also includes the coupling with the energy balance equation as a boundary describing atmospheric influences at the shallow subsurface. To demonstrate the accuracy of both models, comparisons were made between simulation and field experiments for soil moisture and temperature at 2, 7, and 12 cm deep, during 11 days. The root-mean-square errors showed that the upscaled version of the system captured the multiscale features with similar accuracy. Given the good matching between simulated and field data for near-surface soil temperature, the results suggest that it can be regarded as a 1-D variable.

Modeling and Simulations in Photoelectrochemical Water Oxidation: From Single Level to Multiscale Modeling.

PubMed

Zhang, Xueqing; Bieberle-Hütter, Anja

2016-06-08

This review summarizes recent developments, challenges, and strategies in the field of modeling and simulations of photoelectrochemical (PEC) water oxidation. We focus on water splitting by metal-oxide semiconductors and discuss topics such as theoretical calculations of light absorption, band gap/band edge, charge transport, and electrochemical reactions at the electrode-electrolyte interface. In particular, we review the mechanisms of the oxygen evolution reaction, strategies to lower overpotential, and computational methods applied to PEC systems with particular focus on multiscale modeling. The current challenges in modeling PEC interfaces and their processes are summarized. At the end, we propose a new multiscale modeling approach to simulate the PEC interface under conditions most similar to those of experiments. This approach will contribute to identifying the limitations at PEC interfaces. Its generic nature allows its application to a number of electrochemical systems. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multiscale Systems Analysis of Root Growth and Development: Modeling Beyond the Network and Cellular Scales

PubMed Central

Band, Leah R.; Fozard, John A.; Godin, Christophe; Jensen, Oliver E.; Pridmore, Tony; Bennett, Malcolm J.; King, John R.

2012-01-01

Over recent decades, we have gained detailed knowledge of many processes involved in root growth and development. However, with this knowledge come increasing complexity and an increasing need for mechanistic modeling to understand how those individual processes interact. One major challenge is in relating genotypes to phenotypes, requiring us to move beyond the network and cellular scales, to use multiscale modeling to predict emergent dynamics at the tissue and organ levels. In this review, we highlight recent developments in multiscale modeling, illustrating how these are generating new mechanistic insights into the regulation of root growth and development. We consider how these models are motivating new biological data analysis and explore directions for future research. This modeling progress will be crucial as we move from a qualitative to an increasingly quantitative understanding of root biology, generating predictive tools that accelerate the development of improved crop varieties. PMID:23110897

Multiscale Methods for Accurate, Efficient, and Scale-Aware Models of the Earth System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goldhaber, Steve; Holland, Marika

The major goal of this project was to contribute improvements to the infrastructure of an Earth System Model in order to support research in the Multiscale Methods for Accurate, Efficient, and Scale-Aware models of the Earth System project. In support of this, the NCAR team accomplished two main tasks: improving input/output performance of the model and improving atmospheric model simulation quality. Improvement of the performance and scalability of data input and diagnostic output within the model required a new infrastructure which can efficiently handle the unstructured grids common in multiscale simulations. This allows for a more computationally efficient model, enablingmore » more years of Earth System simulation. The quality of the model simulations was improved by reducing grid-point noise in the spectral element version of the Community Atmosphere Model (CAM-SE). This was achieved by running the physics of the model using grid-cell data on a finite-volume grid.« less

A new class of finite element variational multiscale turbulence models for incompressible magnetohydrodynamics

DOE PAGES

Sondak, D.; Shadid, J. N.; Oberai, A. A.; ...

2015-04-29

New large eddy simulation (LES) turbulence models for incompressible magnetohydrodynamics (MHD) derived from the variational multiscale (VMS) formulation for finite element simulations are introduced. The new models include the variational multiscale formulation, a residual-based eddy viscosity model, and a mixed model that combines both of these component models. Each model contains terms that are proportional to the residual of the incompressible MHD equations and is therefore numerically consistent. Moreover, each model is also dynamic, in that its effect vanishes when this residual is small. The new models are tested on the decaying MHD Taylor Green vortex at low and highmore » Reynolds numbers. The evaluation of the models is based on comparisons with available data from direct numerical simulations (DNS) of the time evolution of energies as well as energy spectra at various discrete times. Thus a numerical study, on a sequence of meshes, is presented that demonstrates that the large eddy simulation approaches the DNS solution for these quantities with spatial mesh refinement.« less

Multiscale model reduction for shale gas transport in poroelastic fractured media

NASA Astrophysics Data System (ADS)

Akkutlu, I. Yucel; Efendiev, Yalchin; Vasilyeva, Maria; Wang, Yuhe

2018-01-01

Inherently coupled flow and geomechanics processes in fractured shale media have implications for shale gas production. The system involves highly complex geo-textures comprised of a heterogeneous anisotropic fracture network spatially embedded in an ultra-tight matrix. In addition, nonlinearities due to viscous flow, diffusion, and desorption in the matrix and high velocity gas flow in the fractures complicates the transport. In this paper, we develop a multiscale model reduction approach to couple gas flow and geomechanics in fractured shale media. A Discrete Fracture Model (DFM) is used to treat the complex network of fractures on a fine grid. The coupled flow and geomechanics equations are solved using a fixed stress-splitting scheme by solving the pressure equation using a continuous Galerkin method and the displacement equation using an interior penalty discontinuous Galerkin method. We develop a coarse grid approximation and coupling using the Generalized Multiscale Finite Element Method (GMsFEM). GMsFEM constructs the multiscale basis functions in a systematic way to capture the fracture networks and their interactions with the shale matrix. Numerical results and an error analysis is provided showing that the proposed approach accurately captures the coupled process using a few multiscale basis functions, i.e. a small fraction of the degrees of freedom of the fine-scale problem.

The trend of the multi-scale temporal variability of precipitation in Colorado River Basin

NASA Astrophysics Data System (ADS)

Jiang, P.; Yu, Z.

2011-12-01

Hydrological problems like estimation of flood and drought frequencies under future climate change are not well addressed as a result of the disability of current climate models to provide reliable prediction (especially for precipitation) shorter than 1 month. In order to assess the possible impacts that multi-scale temporal distribution of precipitation may have on the hydrological processes in Colorado River Basin (CRB), a comparative analysis of multi-scale temporal variability of precipitation as well as the trend of extreme precipitation is conducted in four regions controlled by different climate systems. Multi-scale precipitation variability including within-storm patterns and intra-annual, inter-annual and decadal variabilities will be analyzed to explore the possible trends of storm durations, inter-storm periods, average storm precipitation intensities and extremes under both long-term natural climate variability and human-induced warming. Further more, we will examine the ability of current climate models to simulate the multi-scale temporal variability and extremes of precipitation. On the basis of these analyses, a statistical downscaling method will be developed to disaggregate the future precipitation scenarios which will provide a more reliable and finer temporal scale precipitation time series for hydrological modeling. Analysis results and downscaling results will be presented.

Multiscale Granger causality

NASA Astrophysics Data System (ADS)

Faes, Luca; Nollo, Giandomenico; Stramaglia, Sebastiano; Marinazzo, Daniele

2017-10-01

In the study of complex physical and biological systems represented by multivariate stochastic processes, an issue of great relevance is the description of the system dynamics spanning multiple temporal scales. While methods to assess the dynamic complexity of individual processes at different time scales are well established, multiscale analysis of directed interactions has never been formalized theoretically, and empirical evaluations are complicated by practical issues such as filtering and downsampling. Here we extend the very popular measure of Granger causality (GC), a prominent tool for assessing directed lagged interactions between joint processes, to quantify information transfer across multiple time scales. We show that the multiscale processing of a vector autoregressive (AR) process introduces a moving average (MA) component, and describe how to represent the resulting ARMA process using state space (SS) models and to combine the SS model parameters for computing exact GC values at arbitrarily large time scales. We exploit the theoretical formulation to identify peculiar features of multiscale GC in basic AR processes, and demonstrate with numerical simulations the much larger estimation accuracy of the SS approach compared to pure AR modeling of filtered and downsampled data. The improved computational reliability is exploited to disclose meaningful multiscale patterns of information transfer between global temperature and carbon dioxide concentration time series, both in paleoclimate and in recent years.

Multiscale information modelling for heart morphogenesis

NASA Astrophysics Data System (ADS)

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

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.

Deformation, crystal preferred orientations, and seismic anisotropy in the Earth's D″ layer

NASA Astrophysics Data System (ADS)

Tommasi, Andréa; Goryaeva, Alexandra; Carrez, Philippe; Cordier, Patrick; Mainprice, David

2018-06-01

We use a forward multiscale model that couples atomistic modeling of intracrystalline plasticity mechanisms (dislocation glide ± twinning) in MgSiO3 post-perovskite (PPv) and periclase (MgO) at lower mantle pressures and temperatures to polycrystal plasticity simulations to predict crystal preferred orientations (CPO) development and seismic anisotropy in D″. We model the CPO evolution in aggregates of 70% PPv and 30% MgO submitted to simple shear, axial shortening, and along corner-flow streamlines, which simulate changes in flow orientation similar to those expected at the transition between a downwelling and flow parallel to the core-mantle boundary (CMB) within D″ or between CMB-parallel flow and upwelling at the borders of the large low shear wave velocity provinces (LLSVP) in the lowermost mantle. Axial shortening results in alignment of PPv [010] axes with the shortening direction. Simple shear produces PPv CPO with a monoclinic symmetry that rapidly rotates towards parallelism between the dominant [100](010) slip system and the macroscopic shear. These predictions differ from MgSiO3 post-perovskite textures formed in diamond-anvil cell experiments, but agree with those obtained in simple shear and compression experiments using CaIrO3 post-perovskite. Development of CPO in PPv and MgO results in seismic anisotropy in D″. For shear parallel to the CMB, at low strain, the inclination of ScS, Sdiff, and SKKS fast polarizations and delay times vary depending on the propagation direction. At moderate and high shear strains, all S-waves are polarized nearly horizontally. Downwelling flow produces Sdiff, ScS, and SKKS fast polarization directions and birefringence that vary gradually as a function of the back-azimuth from nearly parallel to inclined by up to 70° to CMB and from null to ∼5%. Change in the flow to shear parallel to the CMB results in dispersion of the CPO, weakening of the anisotropy, and strong azimuthal variation of the S-wave splitting up to 250 km from the corner. Transition from horizontal shear to upwelling also produces weakening of the CPO and complex seismic anisotropy patterns, with dominantly inclined fast ScS and SKKS polarizations, over most of the upwelling path. Models that take into account twinning in PPv explain most observations of seismic anisotropy in D″, but heterogeneity of the flow at scales <1000 km is needed to comply with the seismological evidence for low apparent birefringence in D″.

Beyond 2D: Parallel Electric Fields and Dissipation in Guide Field Reconnectio

NASA Astrophysics Data System (ADS)

Wilder, F. D.; Ergun, R.; Ahmadi, N.; Goodrich, K.; Eriksson, S.; Shimoda, E.; Burch, J. L.; Phan, T.; Torbert, R. B.; Strangeway, R. J.; Giles, B. L.; Lindqvist, P. A.; Khotyaintsev, Y. V.

2017-12-01

In 2015, NASA launched the Magnetospheric Multiscale (MMS) mission to study phenomenon of magnetic reconnection down to the electron scale. Advantages of MMS include a 20s spin period and long axial booms, which together allow for measurement of 3-D electric fields with accuracy down to 1 mV/m. During the two dayside phases of the prime mission, MMS has observed multiple electron and ion diffusion region events at the Earth's subsolar and flank magnetopause, as well as in the magnetosheath, providing an option to study both symmetric and asymmetric reconnection at a variety of guide field strengths. We present a review of parallel electric fields observed by MMS during diffusion region events, and discuss their implications for simulations and laboratory observations of reconnection. We find that as the guide field increases, the dissipation in the diffusion region transitions from being due to currents and fields perpendicular to the background magnetic field, to being associated with parallel electric fields and currents. Additionally, the observed parallel electric fields are significantly larger than those predicted by simulations of reconnection under strong guide field conditions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Du, Qiang

The rational design of materials, the development of accurate and efficient material simulation algorithms, and the determination of the response of materials to environments and loads occurring in practice all require an understanding of mechanics at disparate spatial and temporal scales. The project addresses mathematical and numerical analyses for material problems for which relevant scales range from those usually treated by molecular dynamics all the way up to those most often treated by classical elasticity. The prevalent approach towards developing a multiscale material model couples two or more well known models, e.g., molecular dynamics and classical elasticity, each of whichmore » is useful at a different scale, creating a multiscale multi-model. However, the challenges behind such a coupling are formidable and largely arise because the atomistic and continuum models employ nonlocal and local models of force, respectively. The project focuses on a multiscale analysis of the peridynamics materials model. Peridynamics can be used as a transition between molecular dynamics and classical elasticity so that the difficulties encountered when directly coupling those two models are mitigated. In addition, in some situations, peridynamics can be used all by itself as a material model that accurately and efficiently captures the behavior of materials over a wide range of spatial and temporal scales. Peridynamics is well suited to these purposes because it employs a nonlocal model of force, analogous to that of molecular dynamics; furthermore, at sufficiently large length scales and assuming smooth deformation, peridynamics can be approximated by classical elasticity. The project will extend the emerging mathematical and numerical analysis of peridynamics. One goal is to develop a peridynamics-enabled multiscale multi-model that potentially provides a new and more extensive mathematical basis for coupling classical elasticity and molecular dynamics, thus enabling next generation atomistic-to-continuum multiscale simulations. In addition, a rigorous studyof nite element discretizations of peridynamics will be considered. Using the fact that peridynamics is spatially derivative free, we will also characterize the space of admissible peridynamic solutions and carry out systematic analyses of the models, in particular rigorously showing how peridynamics encompasses fracture and other failure phenomena. Additional aspects of the project include the mathematical and numerical analysis of peridynamics applied to stochastic peridynamics models. In summary, the project will make feasible mathematically consistent multiscale models for the analysis and design of advanced materials.« less

Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform.

PubMed

Marshall-Colon, Amy; Long, Stephen P; Allen, Douglas K; Allen, Gabrielle; Beard, Daniel A; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A J; Cox, Donna J; Hart, John C; Hirst, Peter M; Kannan, Kavya; Katz, Daniel S; Lynch, Jonathan P; Millar, Andrew J; Panneerselvam, Balaji; Price, Nathan D; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J; Voit, Eberhard O; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang

2017-01-01

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop.

Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform

PubMed Central

Marshall-Colon, Amy; Long, Stephen P.; Allen, Douglas K.; Allen, Gabrielle; Beard, Daniel A.; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A. J.; Cox, Donna J.; Hart, John C.; Hirst, Peter M.; Kannan, Kavya; Katz, Daniel S.; Lynch, Jonathan P.; Millar, Andrew J.; Panneerselvam, Balaji; Price, Nathan D.; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G.; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J.; Voit, Eberhard O.; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang

2017-01-01

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop. PMID:28555150

Magnetospheric Multiscale Mission Observations and Non-Force Free Modeling of a Flux Transfer Event Immersed in a Super-Alfvenic Flow

NASA Technical Reports Server (NTRS)

Farrugia, C. J.; Lavraud, B.; Torbert, R. B.; Argall, M.; Kacem, I.; Yu, W.; Alm, L.; Burch, J.; Russell, C. T.; Shuster, J.;

Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites

DTIC Science & Technology

2016-03-09

A - Approved for Public Release 13. SUPPLEMENTARY NOTES 14. ABSTRACT Incorporation of carbon nanotubes (CNTs) into epoxy-based composites for...materials with higher moduli and strength characteristics. 15. SUBJECT TERMS Molecular Dynamics, Carbon Nanotubes , Multi-scale Modeling, Micromechanics...Gregory M. Odegard Michigan Technological University Introduction This project was inspired from the AFOSR-sponsored workshop “ Nanotube

A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

EPA Science Inventory

This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM − KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosen...

Multiscale Modeling for Linking Growth, Microstructure, and Properties of Inorganic Microporous Films

NASA Technical Reports Server (NTRS)

Vlachos, Dion G.

2002-01-01

The focus of this presentation is on multiscale modeling in order to link processing, microstructure, and properties of materials. Overview of problems we study includes: Growth mechanisms in chemical and physical vapor epitaxy; thin films of zeolites for separation and sensing; thin Pd films for hydrogen separation and pattern formation by self-regulation routes.

Multiscale simulations of anisotropic particles combining molecular dynamics and Green's function reaction dynamics

NASA Astrophysics Data System (ADS)

Vijaykumar, Adithya; Ouldridge, Thomas E.; ten Wolde, Pieter Rein; Bolhuis, Peter G.

2017-03-01

The modeling of complex reaction-diffusion processes in, for instance, cellular biochemical networks or self-assembling soft matter can be tremendously sped up by employing a multiscale algorithm which combines the mesoscopic Green's Function Reaction Dynamics (GFRD) method with explicit stochastic Brownian, Langevin, or deterministic molecular dynamics to treat reactants at the microscopic scale [A. Vijaykumar, P. G. Bolhuis, and P. R. ten Wolde, J. Chem. Phys. 143, 214102 (2015)]. Here we extend this multiscale MD-GFRD approach to include the orientational dynamics that is crucial to describe the anisotropic interactions often prevalent in biomolecular systems. We present the novel algorithm focusing on Brownian dynamics only, although the methodology is generic. We illustrate the novel algorithm using a simple patchy particle model. After validation of the algorithm, we discuss its performance. The rotational Brownian dynamics MD-GFRD multiscale method will open up the possibility for large scale simulations of protein signalling networks.

Jet Fuel Exacerbated Noise-Induced Hearing Loss: Focus on Prediction of Central Auditory Processing Dysfunction

DTIC Science & Technology

2017-09-01

to develop a multi-scale model, together with relevant supporting experimental data, to describe jet fuel exacerbated noise induced hearing loss. In...scale model, together with relevant supporting experimental data, to describe jet fuel exacerbated noise-induced hearing loss. Such hearing loss...project was to develop a multi-scale model, together with relevant supporting experimental data, to describe jet fuel exacerbated NIHL. Herein we

A Hybrid Multiscale Framework for Subsurface Flow and Transport Simulations

DOE PAGES

Scheibe, Timothy D.; Yang, Xiaofan; Chen, Xingyuan; ...

2015-06-01

Extensive research efforts have been invested in reducing model errors to improve the predictive ability of biogeochemical earth and environmental system simulators, with applications ranging from contaminant transport and remediation to impacts of biogeochemical elemental cycling (e.g., carbon and nitrogen) on local ecosystems and regional to global climate. While the bulk of this research has focused on improving model parameterizations in the face of observational limitations, the more challenging type of model error/uncertainty to identify and quantify is model structural error which arises from incorrect mathematical representations of (or failure to consider) important physical, chemical, or biological processes, properties, ormore » system states in model formulations. While improved process understanding can be achieved through scientific study, such understanding is usually developed at small scales. Process-based numerical models are typically designed for a particular characteristic length and time scale. For application-relevant scales, it is generally necessary to introduce approximations and empirical parameterizations to describe complex systems or processes. This single-scale approach has been the best available to date because of limited understanding of process coupling combined with practical limitations on system characterization and computation. While computational power is increasing significantly and our understanding of biological and environmental processes at fundamental scales is accelerating, using this information to advance our knowledge of the larger system behavior requires the development of multiscale simulators. Accordingly there has been much recent interest in novel multiscale methods in which microscale and macroscale models are explicitly coupled in a single hybrid multiscale simulation. A limited number of hybrid multiscale simulations have been developed for biogeochemical earth systems, but they mostly utilize application-specific and sometimes ad-hoc approaches for model coupling. We are developing a generalized approach to hierarchical model coupling designed for high-performance computational systems, based on the Swift computing workflow framework. In this presentation we will describe the generalized approach and provide two use cases: 1) simulation of a mixing-controlled biogeochemical reaction coupling pore- and continuum-scale models, and 2) simulation of biogeochemical impacts of groundwater – river water interactions coupling fine- and coarse-grid model representations. This generalized framework can be customized for use with any pair of linked models (microscale and macroscale) with minimal intrusiveness to the at-scale simulators. It combines a set of python scripts with the Swift workflow environment to execute a complex multiscale simulation utilizing an approach similar to the well-known Heterogeneous Multiscale Method. User customization is facilitated through user-provided input and output file templates and processing function scripts, and execution within a high-performance computing environment is handled by Swift, such that minimal to no user modification of at-scale codes is required.« less

Multiscale Phenomena in the Solid-Liquid Transition State of a Granular Material: Analysis and Modelling of Dense Granular Materials

DTIC Science & Technology

2011-09-26

most challenging to characterize and model of the gamut of granular behaviour encountered in practice. In particular, it exhibits self-organized...is intrinsically multiscale and is arguably one of, if not, the most challenging to characterize and model of the gamut of granular behaviour...the most challenging to characterize and model of the gamut of granular behaviour encountered in practice. In particular, it exhibits self-organized

Towards Characterization, Modeling, and Uncertainty Quantification in Multi-scale Mechanics of Oragnic-rich Shales

NASA Astrophysics Data System (ADS)

Abedi, S.; Mashhadian, M.; Noshadravan, A.

2015-12-01

Increasing the efficiency and sustainability in operation of hydrocarbon recovery from organic-rich shales requires a fundamental understanding of chemomechanical properties of organic-rich shales. This understanding is manifested in form of physics-bases predictive models capable of capturing highly heterogeneous and multi-scale structure of organic-rich shale materials. In this work we present a framework of experimental characterization, micromechanical modeling, and uncertainty quantification that spans from nanoscale to macroscale. Application of experiments such as coupled grid nano-indentation and energy dispersive x-ray spectroscopy and micromechanical modeling attributing the role of organic maturity to the texture of the material, allow us to identify unique clay mechanical properties among different samples that are independent of maturity of shale formations and total organic content. The results can then be used to inform the physically-based multiscale model for organic rich shales consisting of three levels that spans from the scale of elementary building blocks (e.g. clay minerals in clay-dominated formations) of organic rich shales to the scale of the macroscopic inorganic/organic hard/soft inclusion composite. Although this approach is powerful in capturing the effective properties of organic-rich shale in an average sense, it does not account for the uncertainty in compositional and mechanical model parameters. Thus, we take this model one step forward by systematically incorporating the main sources of uncertainty in modeling multiscale behavior of organic-rich shales. In particular we account for the uncertainty in main model parameters at different scales such as porosity, elastic properties and mineralogy mass percent. To that end, we use Maximum Entropy Principle and random matrix theory to construct probabilistic descriptions of model inputs based on available information. The Monte Carlo simulation is then carried out to propagate the uncertainty and consequently construct probabilistic descriptions of properties at multiple length-scales. The combination of experimental characterization and stochastic multi-scale modeling presented in this work improves the robustness in the prediction of essential subsurface parameters in engineering scale.

Simulation of Left Atrial Function Using a Multi-Scale Model of the Cardiovascular System

PubMed Central

Pironet, Antoine; Dauby, Pierre C.; Paeme, Sabine; Kosta, Sarah; Chase, J. Geoffrey; Desaive, Thomas

2013-01-01

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. PMID:23755183

Multiscale modelling and nonlinear simulation of vascular tumour growth

PubMed Central

Macklin, Paul; Anderson, Alexander R. A.; Chaplain, Mark A. J.; Cristini, Vittorio

2011-01-01

In this article, we present a new multiscale mathematical model for solid tumour growth which couples an improved model of tumour invasion with a model of tumour-induced angiogenesis. We perform nonlinear simulations of the multi-scale model that demonstrate the importance of the coupling between the development and remodeling of the vascular network, the blood flow through the network and the tumour progression. Consistent with clinical observations, the hydrostatic stress generated by tumour cell proliferation shuts down large portions of the vascular network dramatically affecting the flow, the subsequent network remodeling, the delivery of nutrients to the tumour and the subsequent tumour progression. In addition, extracellular matrix degradation by tumour cells is seen to have a dramatic affect on both the development of the vascular network and the growth response of the tumour. In particular, the newly developing vessels tend to encapsulate, rather than penetrate, the tumour and are thus less effective in delivering nutrients. PMID:18781303

An optimized algorithm for multiscale wideband deconvolution of radio astronomical images

NASA Astrophysics Data System (ADS)

Offringa, A. R.; Smirnov, O.

2017-10-01

We describe a new multiscale deconvolution algorithm that can also be used in a multifrequency mode. The algorithm only affects the minor clean loop. In single-frequency mode, the minor loop of our improved multiscale algorithm is over an order of magnitude faster than the casa multiscale algorithm, and produces results of similar quality. For multifrequency deconvolution, a technique named joined-channel cleaning is used. In this mode, the minor loop of our algorithm is two to three orders of magnitude faster than casa msmfs. We extend the multiscale mode with automated scale-dependent masking, which allows structures to be cleaned below the noise. We describe a new scale-bias function for use in multiscale cleaning. We test a second deconvolution method that is a variant of the moresane deconvolution technique, and uses a convex optimization technique with isotropic undecimated wavelets as dictionary. On simple well-calibrated data, the convex optimization algorithm produces visually more representative models. On complex or imperfect data, the convex optimization algorithm has stability issues.

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

PubMed

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

2017-12-01

The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth.

Lamellar and fibre bundle mechanics of the annulus fibrosus in bovine intervertebral disc.

PubMed

Vergari, Claudio; Mansfield, Jessica; Meakin, Judith R; Winlove, Peter C

2016-06-01

The intervertebral disc is a multicomposite structure, with an outer fibrous ring, the annulus fibrosus, retaining a gel-like core, the nucleus pulposus. The disc presents complex mechanical behaviour, and it is of high importance for spine biomechanics. Advances in multiscale modelling and disc repair raised a need for new quantitative data on the finest details of annulus fibrosus mechanics. In this work we explored inter-lamella and inter-bundle behaviour of the outer annulus using micromechanical testing and second harmonic generation microscopy. Twenty-one intervertebral discs were dissected from cow tails; the nucleus and inner annulus were excised to leave a ring of outer annulus, which was tested in circumferential loading while imaging the tissue's collagen fibres network with sub-micron resolution. Custom software was developed to determine local tissue strains through image analysis. Inter-bundle linear and shear strains were 5.5 and 2.8 times higher than intra-bundle strains. Bundles tended to remain parallel while rotating under loading, with large slipping between them. Inter-lamella linear strain was almost 3 times the intra-lamella one, but no slipping was observed at the junction between lamellae. This study confirms that outer annulus straining is mainly due to bundles slipping and rotating. Further development of disc multiscale modelling and repair techniques should take into account this modular behaviour of the lamella, rather than considering it as a homogeneous fibre-reinforced matrix. The intervertebral disc is an organ tucked between each couple of vertebrae in the spine. It is composed by an outer fibrous layer retaining a gel-like core. This organ undergoes severe and repeated loading during everyday life activities, since it is the compliant component that gives the spine its flexibility. Its properties are affected by pathologies such as disc degeneration, a major cause of back pain. In this article we explored the micromechanical behaviour of the disc's outer layer using second harmonic generation, a technique which allowed us to visualize, with unprecedented detail, how bundles of collagen fibres slide relative to each other when loaded. Our results will help further the development of new multiscale numerical models and repairing techniques. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

A Multiscale Progressive Failure Modeling Methodology for Composites that Includes Fiber Strength Stochastics

NASA Technical Reports Server (NTRS)

Ricks, Trenton M.; Lacy, Thomas E., Jr.; Bednarcyk, Brett A.; Arnold, Steven M.; Hutchins, John W.

2014-01-01

A multiscale modeling methodology was developed for continuous fiber composites that incorporates a statistical distribution of fiber strengths into coupled multiscale micromechanics/finite element (FE) analyses. A modified two-parameter Weibull cumulative distribution function, which accounts for the effect of fiber length on the probability of failure, was used to characterize the statistical distribution of fiber strengths. A parametric study using the NASA Micromechanics Analysis Code with the Generalized Method of Cells (MAC/GMC) was performed to assess the effect of variable fiber strengths on local composite failure within a repeating unit cell (RUC) and subsequent global failure. The NASA code FEAMAC and the ABAQUS finite element solver were used to analyze the progressive failure of a unidirectional SCS-6/TIMETAL 21S metal matrix composite tensile dogbone specimen at 650 degC. Multiscale progressive failure analyses were performed to quantify the effect of spatially varying fiber strengths on the RUC-averaged and global stress-strain responses and failure. The ultimate composite strengths and distribution of failure locations (predominately within the gage section) reasonably matched the experimentally observed failure behavior. The predicted composite failure behavior suggests that use of macroscale models that exploit global geometric symmetries are inappropriate for cases where the actual distribution of local fiber strengths displays no such symmetries. This issue has not received much attention in the literature. Moreover, the model discretization at a specific length scale can have a profound effect on the computational costs associated with multiscale simulations.models that yield accurate yet tractable results.

Quantifying restoration effectiveness using multi-scale habitat models: Implications for sage-grouse in the Great Basin

Treesearch

Robert S. Arkle; David S. Pilliod; Steven E. Hanser; Matthew L. Brooks; Jeanne C. Chambers; James B. Grace; Kevin C. Knutson; David A. Pyke; Justin L. Welty; Troy A. Wirth

2014-01-01

A recurrent challenge in the conservation of wide-ranging, imperiled species is understanding which habitats to protect and whether we are capable of restoring degraded landscapes. For Greater Sage-grouse (Centrocercus urophasianus), a species of conservation concern in the western United States, we approached this problem by developing multi-scale empirical models of...

Capturing remote mixing due to internal tides using multi-scale modeling tool: SOMAR-LES

NASA Astrophysics Data System (ADS)

Santilli, Edward; Chalamalla, Vamsi; Scotti, Alberto; Sarkar, Sutanu

2016-11-01

Internal tides that are generated during the interaction of an oscillating barotropic tide with the bottom bathymetry dissipate only a fraction of their energy near the generation region. The rest is radiated away in the form of low- high-mode internal tides. These internal tides dissipate energy at remote locations when they interact with the upper ocean pycnocline, continental slope, and large scale eddies. Capturing the wide range of length and time scales involved during the life-cycle of internal tides is computationally very expensive. A recently developed multi-scale modeling tool called SOMAR-LES combines the adaptive grid refinement features of SOMAR with the turbulence modeling features of a Large Eddy Simulation (LES) to capture multi-scale processes at a reduced computational cost. Numerical simulations of internal tide generation at idealized bottom bathymetries are performed to demonstrate this multi-scale modeling technique. Although each of the remote mixing phenomena have been considered independently in previous studies, this work aims to capture remote mixing processes during the life cycle of an internal tide in more realistic settings, by allowing multi-level (coarse and fine) grids to co-exist and exchange information during the time stepping process.

A New Age-Structured Multiscale Model of the Hepatitis C Virus Life-Cycle During Infection and Therapy With Direct-Acting Antiviral Agents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quintela, Barbara de M.; Conway, Jessica M.; Hyman, James M.

Here, the dynamics of hepatitis C virus (HCV) RNA during translation and replication within infected cells were added to a previous age-structured multiscale mathematical model of HCV infection and treatment. The model allows the study of the dynamics of HCV RNA inside infected cells as well as the release of virus from infected cells and the dynamics of subsequent new cell infections. The model was used to fit in vitro data and estimate parameters characterizing HCV replication. This is the first model to our knowledge to consider both positive and negative strands of HCV RNA with an age-structured multiscale modelingmore » approach. Using this model we also studied the effects of direct-acting antiviral agents (DAAs) in blocking HCV RNA intracellular replication and the release of new virions and fit the model to in vivo data obtained from HCV-infected subjects under therapy.« less

A New Age-Structured Multiscale Model of the Hepatitis C Virus Life-Cycle During Infection and Therapy With Direct-Acting Antiviral Agents

DOE PAGES

Quintela, Barbara de M.; Conway, Jessica M.; Hyman, James M.; ...

2018-04-04

Here, the dynamics of hepatitis C virus (HCV) RNA during translation and replication within infected cells were added to a previous age-structured multiscale mathematical model of HCV infection and treatment. The model allows the study of the dynamics of HCV RNA inside infected cells as well as the release of virus from infected cells and the dynamics of subsequent new cell infections. The model was used to fit in vitro data and estimate parameters characterizing HCV replication. This is the first model to our knowledge to consider both positive and negative strands of HCV RNA with an age-structured multiscale modelingmore » approach. Using this model we also studied the effects of direct-acting antiviral agents (DAAs) in blocking HCV RNA intracellular replication and the release of new virions and fit the model to in vivo data obtained from HCV-infected subjects under therapy.« less

Electron Currents and Heating in the Ion Diffusion Region of Asymmetric Reconnection

NASA Technical Reports Server (NTRS)

Graham, D. B.; Khotyaintsev, Yu. V.; Norgren, C.; Vaivads, A.; Andre, M.; Lindqvist, P. A.; Marklund, G. T.; Ergun, R. E.; Paterson, W. R.; Gershman, D. J.;

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

PubMed

Hamdi, Mustapha

2009-12-02

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

Multiscale finite element modeling of sheet molding compound (SMC) composite structure based on stochastic mesostructure reconstruction

DOE PAGES

Chen, Zhangxing; Huang, Tianyu; Shao, Yimin; ...

2018-03-15

Predicting the mechanical behavior of the chopped carbon fiber Sheet Molding Compound (SMC) due to spatial variations in local material properties is critical for the structural performance analysis but is computationally challenging. Such spatial variations are induced by the material flow in the compression molding process. In this work, a new multiscale SMC modeling framework and the associated computational techniques are developed to provide accurate and efficient predictions of SMC mechanical performance. The proposed multiscale modeling framework contains three modules. First, a stochastic algorithm for 3D chip-packing reconstruction is developed to efficiently generate the SMC mesoscale Representative Volume Element (RVE)more » model for Finite Element Analysis (FEA). A new fiber orientation tensor recovery function is embedded in the reconstruction algorithm to match reconstructions with the target characteristics of fiber orientation distribution. Second, a metamodeling module is established to improve the computational efficiency by creating the surrogates of mesoscale analyses. Third, the macroscale behaviors are predicted by an efficient multiscale model, in which the spatially varying material properties are obtained based on the local fiber orientation tensors. Our approach is further validated through experiments at both meso- and macro-scales, such as tensile tests assisted by Digital Image Correlation (DIC) and mesostructure imaging.« less

Multiscale finite element modeling of sheet molding compound (SMC) composite structure based on stochastic mesostructure reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Zhangxing; Huang, Tianyu; Shao, Yimin

Predicting the mechanical behavior of the chopped carbon fiber Sheet Molding Compound (SMC) due to spatial variations in local material properties is critical for the structural performance analysis but is computationally challenging. Such spatial variations are induced by the material flow in the compression molding process. In this work, a new multiscale SMC modeling framework and the associated computational techniques are developed to provide accurate and efficient predictions of SMC mechanical performance. The proposed multiscale modeling framework contains three modules. First, a stochastic algorithm for 3D chip-packing reconstruction is developed to efficiently generate the SMC mesoscale Representative Volume Element (RVE)more » model for Finite Element Analysis (FEA). A new fiber orientation tensor recovery function is embedded in the reconstruction algorithm to match reconstructions with the target characteristics of fiber orientation distribution. Second, a metamodeling module is established to improve the computational efficiency by creating the surrogates of mesoscale analyses. Third, the macroscale behaviors are predicted by an efficient multiscale model, in which the spatially varying material properties are obtained based on the local fiber orientation tensors. Our approach is further validated through experiments at both meso- and macro-scales, such as tensile tests assisted by Digital Image Correlation (DIC) and mesostructure imaging.« less

Damage modeling of small-scale experiments on dental enamel with hierarchical microstructure.

PubMed

Scheider, I; Xiao, T; Yilmaz, E; Schneider, G A; Huber, N; Bargmann, S

2015-03-01

Dental enamel is a highly anisotropic and heterogeneous material, which exhibits an optimal reliability with respect to the various loads occurring over years. In this work, enamel's microstructure of parallel aligned rods of mineral fibers is modeled and mechanical properties are evaluated in terms of strength and toughness with the help of a multiscale modeling method. The established model is validated by comparing it with the stress-strain curves identified by microcantilever beam experiments extracted from these rods. Moreover, in order to gain further insight in the damage-tolerant behavior of enamel, the size of crystallites below which the structure becomes insensitive to flaws is studied by a microstructural finite element model. The assumption regarding the fiber strength is verified by a numerical study leading to accordance of fiber size and flaw tolerance size, and the debonding strength is estimated by optimizing the failure behavior of the microstructure on the hierarchical level above the individual fibers. Based on these well-grounded properties, the material behavior is predicted well by homogenization of a representative unit cell including damage, taking imperfections (like microcracks in the present case) into account. Copyright © 2014 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Simulating the heterogeneity in braided channel belt deposits: 1. A geometric-based methodology and code

NASA Astrophysics Data System (ADS)

Ramanathan, Ramya; Guin, Arijit; Ritzi, Robert W.; Dominic, David F.; Freedman, Vicky L.; Scheibe, Timothy D.; Lunt, Ian A.

2010-04-01

A geometric-based simulation methodology was developed and incorporated into a computer code to model the hierarchical stratal architecture, and the corresponding spatial distribution of permeability, in braided channel belt deposits. The code creates digital models of these deposits as a three-dimensional cubic lattice, which can be used directly in numerical aquifer or reservoir models for fluid flow. The digital models have stratal units defined from the kilometer scale to the centimeter scale. These synthetic deposits are intended to be used as high-resolution base cases in various areas of computational research on multiscale flow and transport processes, including the testing of upscaling theories. The input parameters are primarily univariate statistics. These include the mean and variance for characteristic lengths of sedimentary unit types at each hierarchical level, and the mean and variance of log-permeability for unit types defined at only the lowest level (smallest scale) of the hierarchy. The code has been written for both serial and parallel execution. The methodology is described in part 1 of this paper. In part 2 (Guin et al., 2010), models generated by the code are presented and evaluated.

Simulating the Heterogeneity in Braided Channel Belt Deposits: Part 1. A Geometric-Based Methodology and Code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramanathan, Ramya; Guin, Arijit; Ritzi, Robert W.

A geometric-based simulation methodology was developed and incorporated into a computer code to model the hierarchical stratal architecture, and the corresponding spatial distribution of permeability, in braided channel belt deposits. The code creates digital models of these deposits as a three-dimensional cubic lattice, which can be used directly in numerical aquifer or reservoir models for fluid flow. The digital models have stratal units defined from the km scale to the cm scale. These synthetic deposits are intended to be used as high-resolution base cases in various areas of computational research on multiscale flow and transport processes, including the testing ofmore » upscaling theories. The input parameters are primarily univariate statistics. These include the mean and variance for characteristic lengths of sedimentary unit types at each hierarchical level, and the mean and variance of log-permeability for unit types defined at only the lowest level (smallest scale) of the hierarchy. The code has been written for both serial and parallel execution. The methodology is described in Part 1 of this series. In Part 2, models generated by the code are presented and evaluated.« less

PDF-based heterogeneous multiscale filtration model.

PubMed

Gong, Jian; Rutland, Christopher J

2015-04-21

Motivated by modeling of gasoline particulate filters (GPFs), a probability density function (PDF) based heterogeneous multiscale filtration (HMF) model is developed to calculate filtration efficiency of clean particulate filters. A new methodology based on statistical theory and classic filtration theory is developed in the HMF model. Based on the analysis of experimental porosimetry data, a pore size probability density function is introduced to represent heterogeneity and multiscale characteristics of the porous wall. The filtration efficiency of a filter can be calculated as the sum of the contributions of individual collectors. The resulting HMF model overcomes the limitations of classic mean filtration models which rely on tuning of the mean collector size. Sensitivity analysis shows that the HMF model recovers the classical mean model when the pore size variance is very small. The HMF model is validated by fundamental filtration experimental data from different scales of filter samples. The model shows a good agreement with experimental data at various operating conditions. The effects of the microstructure of filters on filtration efficiency as well as the most penetrating particle size are correctly predicted by the model.

A Multiscale, Nonlinear, Modeling Framework Enabling the Design and Analysis of Composite Materials and Structures

NASA Technical Reports Server (NTRS)

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.

Multiscale modeling of a low magnetostrictive Fe-27wt%Co-0.5wt%Cr alloy

NASA Astrophysics Data System (ADS)

Savary, M.; Hubert, O.; Helbert, A. L.; Baudin, T.; Batonnet, R.; Waeckerlé, T.

2018-05-01

The present paper deals with the improvement of a multi-scale approach describing the magneto-mechanical coupling of Fe-27wt%Co-0.5wt%Cr alloy. The magnetostriction behavior is demonstrated as very different (low magnetostriction vs. high magnetostriction) when this material is submitted to two different final annealing conditions after cold rolling. The numerical data obtained from a multi-scale approach are in accordance with experimental data corresponding to the high magnetostriction level material. A bi-domain structure hypothesis is employed to explain the low magnetostriction behavior, in accordance with the effect of an applied tensile stress. A modification of the multiscale approach is proposed to match this result.

A Multiscale, Nonlinear, Modeling Framework Enabling the Design and Analysis of Composite Materials and Structures

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2011-01-01

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.

Processor farming in two-level analysis of historical bridge

NASA Astrophysics Data System (ADS)

Krejčí, T.; Kruis, J.; Koudelka, T.; Šejnoha, M.

2017-11-01

This contribution presents a processor farming method in connection with a multi-scale analysis. In this method, each macro-scopic integration point or each finite element is connected with a certain meso-scopic problem represented by an appropriate representative volume element (RVE). The solution of a meso-scale problem provides then effective parameters needed on the macro-scale. Such an analysis is suitable for parallel computing because the meso-scale problems can be distributed among many processors. The application of the processor farming method to a real world masonry structure is illustrated by an analysis of Charles bridge in Prague. The three-dimensional numerical model simulates the coupled heat and moisture transfer of one half of arch No. 3. and it is a part of a complex hygro-thermo-mechanical analysis which has been developed to determine the influence of climatic loading on the current state of the bridge.

Network neuroscience

PubMed Central

Bassett, Danielle S; Sporns, Olaf

2017-01-01

Despite substantial recent progress, our understanding of the principles and mechanisms underlying complex brain function and cognition remains incomplete. Network neuroscience proposes to tackle these enduring challenges. Approaching brain structure and function from an explicitly integrative perspective, network neuroscience pursues new ways to map, record, analyze and model the elements and interactions of neurobiological systems. Two parallel trends drive the approach: the availability of new empirical tools to create comprehensive maps and record dynamic patterns among molecules, neurons, brain areas and social systems; and the theoretical framework and computational tools of modern network science. The convergence of empirical and computational advances opens new frontiers of scientific inquiry, including network dynamics, manipulation and control of brain networks, and integration of network processes across spatiotemporal domains. We review emerging trends in network neuroscience and attempt to chart a path toward a better understanding of the brain as a multiscale networked system. PMID:28230844

Subcellular and supracellular mechanical stress prescribes cytoskeleton behavior in Arabidopsis cotyledon pavement cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sampathkumar, Arun; Krupinski, Pawel; Wightman, Raymond

Although it is a central question in biology, how cell shape controls intracellular dynamics largely remains an open question. Here, we show that the shape of Arabidopsis pavement cells creates a stress pattern that controls microtubule orientation, which then guides cell wall reinforcement. Live-imaging, combined with modeling of cell mechanics, shows that microtubules align along the maximal tensile stress direction within the cells, and atomic force microscopy demonstrates that this leads to reinforcement of the cell wall parallel to the microtubules. This feedback loop is regulated: cell-shape derived stresses could be overridden by imposed tissue level stresses, showing how competitionmore » between subcellular and supracellular cues control microtubule behavior. Furthermore, at the microtubule level, we identified an amplification mechanism in which mechanical stress promotes the microtubule response to stress by increasing severing activity. These multiscale feedbacks likely contribute to the robustness of microtubule behavior in plant epidermis.« less

Subcellular and supracellular mechanical stress prescribes cytoskeleton behavior in Arabidopsis cotyledon pavement cells

DOE PAGES

Sampathkumar, Arun; Krupinski, Pawel; Wightman, Raymond; ...

2014-04-16

Although it is a central question in biology, how cell shape controls intracellular dynamics largely remains an open question. Here, we show that the shape of Arabidopsis pavement cells creates a stress pattern that controls microtubule orientation, which then guides cell wall reinforcement. Live-imaging, combined with modeling of cell mechanics, shows that microtubules align along the maximal tensile stress direction within the cells, and atomic force microscopy demonstrates that this leads to reinforcement of the cell wall parallel to the microtubules. This feedback loop is regulated: cell-shape derived stresses could be overridden by imposed tissue level stresses, showing how competitionmore » between subcellular and supracellular cues control microtubule behavior. Furthermore, at the microtubule level, we identified an amplification mechanism in which mechanical stress promotes the microtubule response to stress by increasing severing activity. These multiscale feedbacks likely contribute to the robustness of microtubule behavior in plant epidermis.« less

Multiscale simulation of molecular processes in cellular environments.

PubMed

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).

A physics based multiscale modeling of cavitating flows.

PubMed

Ma, Jingsen; Hsiao, Chao-Tsung; Chahine, Georges L

2017-03-02

Numerical modeling of cavitating bubbly flows is challenging due to the wide range of characteristic lengths of the physics at play: from micrometers (e.g., bubble nuclei radius) to meters (e.g., propeller diameter or sheet cavity length). To address this, we present here a multiscale approach which integrates a Discrete Singularities Model (DSM) for dispersed microbubbles and a two-phase Navier Stokes solver for the bubbly medium, which includes a level set approach to describe large cavities or gaseous pockets. Inter-scale schemes are used to smoothly bridge the two transitioning subgrid DSM bubbles into larger discretized cavities. This approach is demonstrated on several problems including cavitation inception and vapor core formation in a vortex flow, sheet-to-cloud cavitation over a hydrofoil, cavitation behind a blunt body, and cavitation on a propeller. These examples highlight the capabilities of the developed multiscale model in simulating various form of cavitation.

A grain boundary damage model for delamination

NASA Astrophysics Data System (ADS)

Messner, M. C.; Beaudoin, A. J.; Dodds, R. H.

2015-07-01

Intergranular failure in metallic materials represents a multiscale damage mechanism: some feature of the material microstructure triggers the separation of grain boundaries on the microscale, but the intergranular fractures develop into long cracks on the macroscale. This work develops a multiscale model of grain boundary damage for modeling intergranular delamination—a failure of one particular family of grain boundaries sharing a common normal direction. The key feature of the model is a physically-consistent and mesh independent, multiscale scheme that homogenizes damage at many grain boundaries on the microscale into a single damage parameter on the macroscale to characterize material failure across a plane. The specific application of the damage framework developed here considers delamination failure in modern Al-Li alloys. However, the framework may be readily applied to other metals or composites and to other non-delamination interface geometries—for example, multiple populations of material interfaces with different geometric characteristics.

A physics based multiscale modeling of cavitating flows

PubMed Central

Ma, Jingsen; Hsiao, Chao-Tsung; Chahine, Georges L.

2018-01-01

Numerical modeling of cavitating bubbly flows is challenging due to the wide range of characteristic lengths of the physics at play: from micrometers (e.g., bubble nuclei radius) to meters (e.g., propeller diameter or sheet cavity length). To address this, we present here a multiscale approach which integrates a Discrete Singularities Model (DSM) for dispersed microbubbles and a two-phase Navier Stokes solver for the bubbly medium, which includes a level set approach to describe large cavities or gaseous pockets. Inter-scale schemes are used to smoothly bridge the two transitioning subgrid DSM bubbles into larger discretized cavities. This approach is demonstrated on several problems including cavitation inception and vapor core formation in a vortex flow, sheet-to-cloud cavitation over a hydrofoil, cavitation behind a blunt body, and cavitation on a propeller. These examples highlight the capabilities of the developed multiscale model in simulating various form of cavitation. PMID:29720773

Multi-scale Rule-of-Mixtures Model of Carbon Nanotube/Carbon Fiber/Epoxy Lamina

NASA Technical Reports Server (NTRS)

Frankland, Sarah-Jane V.; Roddick, Jaret C.; Gates, Thomas S.

2005-01-01

A unidirectional carbon fiber/epoxy lamina in which the carbon fibers are coated with single-walled carbon nanotubes is modeled with a multi-scale method, the atomistically informed rule-of-mixtures. This multi-scale model is designed to include the effect of the carbon nanotubes on the constitutive properties of the lamina. It included concepts from the molecular dynamics/equivalent continuum methods, micromechanics, and the strength of materials. Within the model both the nanotube volume fraction and nanotube distribution were varied. It was found that for a lamina with 60% carbon fiber volume fraction, the Young's modulus in the fiber direction varied with changes in the nanotube distribution, from 138.8 to 140 GPa with nanotube volume fractions ranging from 0.0001 to 0.0125. The presence of nanotube near the surface of the carbon fiber is therefore expected to have a small, but positive, effect on the constitutive properties of the lamina.

A Computational Framework for Efficient Low Temperature Plasma Simulations

NASA Astrophysics Data System (ADS)

Verma, Abhishek Kumar; Venkattraman, Ayyaswamy

2016-10-01

Over the past years, scientific computing has emerged as an essential tool for the investigation and prediction of low temperature plasmas (LTP) applications which includes electronics, nanomaterial synthesis, metamaterials etc. To further explore the LTP behavior with greater fidelity, we present a computational toolbox developed to perform LTP simulations. This framework will allow us to enhance our understanding of multiscale plasma phenomenon using high performance computing tools mainly based on OpenFOAM FVM distribution. Although aimed at microplasma simulations, the modular framework is able to perform multiscale, multiphysics simulations of physical systems comprises of LTP. Some salient introductory features are capability to perform parallel, 3D simulations of LTP applications on unstructured meshes. Performance of the solver is tested based on numerical results assessing accuracy and efficiency of benchmarks for problems in microdischarge devices. Numerical simulation of microplasma reactor at atmospheric pressure with hemispherical dielectric coated electrodes will be discussed and hence, provide an overview of applicability and future scope of this framework.

Multiscale measurements on temperature-dependent deformation of a textured magnesium alloy with synchrotron x-ray imaging and diffraction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, L.; Bie, B. X.; Li, Q. H.

2017-06-01

In situ synchrotron x-ray imaging and diffraction are used to investigate deformation of a rolled magnesium alloy under uniaxial compression at room and elevated temperatures along two different directions. The loading axis (LA) is either perpendicular or parallel to the normal direction, and these two cases are referred to as LA⊥ and LAk loading, respectively. Multiscale measurements including stressestrain curves (macroscale), strain fields (mesoscale), and diffraction patterns (microscale) are obtained simultaneously. Due to initial texture, f1012g extension twinning is predominant in the LA⊥ loading, while dislocation motion prevails in the LAk loading. With increasing temperature, fewer f1012g extension twins aremore » activated in the LA⊥ samples, giving rise to reduced strain homogenization, while pyramidal slip becomes readily activated, leading to more homogeneous deformation for the LAk loading. The difference in the strain hardening rates is attributed to that in strain field homogenization for these two loading directions« less

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

NASA Astrophysics Data System (ADS)

Bender, Jason D.

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

Three-Dimensional Visualization of Ozone Process Data.

DTIC Science & Technology

1997-06-18

Scattered Multivariate Data. IEEE Computer Graphics & Applications. 11 (May), 47-55. Odman, M.T. and Ingram, C.L. (1996) Multiscale Air Quality Simulation...the Multiscale Air Quality Simulation Platform (MAQSIP) modeling system. MAQSIP is a modular comprehensive air quality modeling system which MCNC...photolyzed back again to nitric oxide. Finally, oxides of 6 nitrogen are terminated through loss or combination into nitric acid, organic nitrates

Extreme-Scale Bayesian Inference for Uncertainty Quantification of Complex Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Biros, George

Uncertainty quantification (UQ)—that is, quantifying uncertainties in complex mathematical models and their large-scale computational implementations—is widely viewed as one of the outstanding challenges facing the field of CS&E over the coming decade. The EUREKA project set to address the most difficult class of UQ problems: those for which both the underlying PDE model as well as the uncertain parameters are of extreme scale. In the project we worked on these extreme-scale challenges in the following four areas: 1. Scalable parallel algorithms for sampling and characterizing the posterior distribution that exploit the structure of the underlying PDEs and parameter-to-observable map. Thesemore » include structure-exploiting versions of the randomized maximum likelihood method, which aims to overcome the intractability of employing conventional MCMC methods for solving extreme-scale Bayesian inversion problems by appealing to and adapting ideas from large-scale PDE-constrained optimization, which have been very successful at exploring high-dimensional spaces. 2. Scalable parallel algorithms for construction of prior and likelihood functions based on learning methods and non-parametric density estimation. Constructing problem-specific priors remains a critical challenge in Bayesian inference, and more so in high dimensions. Another challenge is construction of likelihood functions that capture unmodeled couplings between observations and parameters. We will create parallel algorithms for non-parametric density estimation using high dimensional N-body methods and combine them with supervised learning techniques for the construction of priors and likelihood functions. 3. Bayesian inadequacy models, which augment physics models with stochastic models that represent their imperfections. The success of the Bayesian inference framework depends on the ability to represent the uncertainty due to imperfections of the mathematical model of the phenomena of interest. This is a central challenge in UQ, especially for large-scale models. We propose to develop the mathematical tools to address these challenges in the context of extreme-scale problems. 4. Parallel scalable algorithms for Bayesian optimal experimental design (OED). Bayesian inversion yields quantified uncertainties in the model parameters, which can be propagated forward through the model to yield uncertainty in outputs of interest. This opens the way for designing new experiments to reduce the uncertainties in the model parameters and model predictions. Such experimental design problems have been intractable for large-scale problems using conventional methods; we will create OED algorithms that exploit the structure of the PDE model and the parameter-to-output map to overcome these challenges. Parallel algorithms for these four problems were created, analyzed, prototyped, implemented, tuned, and scaled up for leading-edge supercomputers, including UT-Austin’s own 10 petaflops Stampede system, ANL’s Mira system, and ORNL’s Titan system. While our focus is on fundamental mathematical/computational methods and algorithms, we will assess our methods on model problems derived from several DOE mission applications, including multiscale mechanics and ice sheet dynamics.« less

Multiscale Simulation of Blood Flow in Brain Arteries with an Aneurysm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leopold Grinberg; Vitali Morozov; Dmitry A. Fedosov

2013-04-24

Multi-scale modeling of arterial blood flow can shed light on the interaction between events happening at micro- and meso-scales (i.e., adhesion of red blood cells to the arterial wall, clot formation) and at macro-scales (i.e., change in flow patterns due to the clot). Coupled numerical simulations of such multi-scale flow require state-of-the-art computers and algorithms, along with techniques for multi-scale visualizations.This animation presents results of studies used in the development of a multi-scale visualization methodology. First we use streamlines to show the path the flow is taking as it moves through the system, including the aneurysm. Next we investigate themore » process of thrombus (blood clot) formation, which may be responsible for the rupture of aneurysms, by concentrating on the platelet blood cells, observing as they aggregate on the wall of the aneurysm.« less

Goal-oriented robot navigation learning using a multi-scale space representation.

PubMed

Llofriu, M; Tejera, G; Contreras, M; Pelc, T; Fellous, J M; Weitzenfeld, A

2015-12-01

There has been extensive research in recent years on the multi-scale nature of hippocampal place cells and entorhinal grid cells encoding which led to many speculations on their role in spatial cognition. In this paper we focus on the multi-scale nature of place cells and how they contribute to faster learning during goal-oriented navigation when compared to a spatial cognition system composed of single scale place cells. The task consists of a circular arena with a fixed goal location, in which a robot is trained to find the shortest path to the goal after a number of learning trials. Synaptic connections are modified using a reinforcement learning paradigm adapted to the place cells multi-scale architecture. The model is evaluated in both simulation and physical robots. We find that larger scale and combined multi-scale representations favor goal-oriented navigation task learning. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multiscale Modeling for the Analysis for Grain-Scale Fracture Within Aluminum Microstructures

NASA Technical Reports Server (NTRS)

Glaessgen, Edward H.; Phillips, Dawn R.; Yamakov, Vesselin; Saether, Erik

2005-01-01

Multiscale modeling methods for the analysis of metallic microstructures are discussed. Both molecular dynamics and the finite element method are used to analyze crack propagation and stress distribution in a nanoscale aluminum bicrystal model subjected to hydrostatic loading. Quantitative similarity is observed between the results from the two very different analysis methods. A bilinear traction-displacement relationship that may be embedded into cohesive zone finite elements is extracted from the nanoscale molecular dynamics results.

Evaluation of the Community Multiscale Air Quality (CMAQ) ...

EPA Pesticide Factsheets

This work evaluates particle size-composition distributions simulated by the Community Multiscale Air Quality (CMAQ) model using Micro-Orifice Uniform Deposit Impactor (MOUDI) measurements at 18 sites across North America. Size-resolved measurements of particulate SO4+, with the model ranging from an underestimation to overestimation of both the peak diameter and peak particle concentration across the sites. Computing PM2.5 from the modeled size distribution parameters rather than by summing the masses in the Aitken and a

Multiscale Analysis of Structurally-Graded Microstructures Using Molecular Dynamics, Discrete Dislocation Dynamics and Continuum Crystal Plasticity

NASA Technical Reports Server (NTRS)

Saether, Erik; Hochhalter, Jacob D.; Glaessgen, Edward H.; Mishin, Yuri

2014-01-01

A multiscale modeling methodology is developed for structurally-graded material microstructures. Molecular dynamic (MD) simulations are performed at the nanoscale to determine fundamental failure mechanisms and quantify material constitutive parameters. These parameters are used to calibrate material processes at the mesoscale using discrete dislocation dynamics (DD). Different grain boundary interactions with dislocations are analyzed using DD to predict grain-size dependent stress-strain behavior. These relationships are mapped into crystal plasticity (CP) parameters to develop a computationally efficient finite element-based DD/CP model for continuum-level simulations and complete the multiscale analysis by predicting the behavior of macroscopic physical specimens. The present analysis is focused on simulating the behavior of a graded microstructure in which grain sizes are on the order of nanometers in the exterior region and transition to larger, multi-micron size in the interior domain. This microstructural configuration has been shown to offer improved mechanical properties over homogeneous coarse-grained materials by increasing yield stress while maintaining ductility. Various mesoscopic polycrystal models of structurally-graded microstructures are generated, analyzed and used as a benchmark for comparison between multiscale DD/CP model and DD predictions. A final series of simulations utilize the DD/CP analysis method exclusively to study macroscopic models that cannot be analyzed by MD or DD methods alone due to the model size.

Efficient testing methodologies for microcameras in a gigapixel imaging system

NASA Astrophysics Data System (ADS)

Youn, Seo Ho; Marks, Daniel L.; McLaughlin, Paul O.; Brady, David J.; Kim, Jungsang

2013-04-01

Multiscale parallel imaging--based on a monocentric optical design--promises revolutionary advances in diverse imaging applications by enabling high resolution, real-time image capture over a wide field-of-view (FOV), including sport broadcast, wide-field microscopy, astronomy, and security surveillance. Recently demonstrated AWARE-2 is a gigapixel camera consisting of an objective lens and 98 microcameras spherically arranged to capture an image over FOV of 120° by 50°, using computational image processing to form a composite image of 0.96 gigapixels. Since microcameras are capable of individually adjusting exposure, gain, and focus, true parallel imaging is achieved with a high dynamic range. From the integration perspective, manufacturing and verifying consistent quality of microcameras is a key to successful realization of AWARE cameras. We have developed an efficient testing methodology that utilizes a precisely fabricated dot grid chart as a calibration target to extract critical optical properties such as optical distortion, veiling glare index, and modulation transfer function to validate imaging performance of microcameras. This approach utilizes an AWARE objective lens simulator which mimics the actual objective lens but operates with a short object distance, suitable for a laboratory environment. Here we describe the principles of the methodologies developed for AWARE microcameras and discuss the experimental results with our prototype microcameras. Reference Brady, D. J., Gehm, M. E., Stack, R. A., Marks, D. L., Kittle, D. S., Golish, D. R., Vera, E. M., and Feller, S. D., "Multiscale gigapixel photography," Nature 486, 386--389 (2012).

Magnetospheric Multiscale Observations of an Ion Diffusion Region With Large Guide Field at the Magnetopause: Current System, Electron Heating, and Plasma Waves

NASA Astrophysics Data System (ADS)

Zhou, M.; Berchem, J.; Walker, R. J.; El-Alaoui, M.; Goldstein, M. L.; Lapenta, G.; Deng, X.; Li, J.; Le Contel, O.; Graham, D. B.; Lavraud, B.; Paterson, W. R.; Giles, B. L.; Burch, J. L.; Torbert, R. B.; Russell, C. T.; Strangeway, R. J.; Zhao, C.; Ergun, R. E.; Lindqvist, P.-A.; Marklund, G.

2018-03-01

We report Magnetospheric Multiscale (MMS) observations of a reconnecting current sheet in the presence of a weak density asymmetry with large guide field at the dayside magnetopause. An ion diffusion region (IDR) was detected associated with this current sheet. Parallel current dominated over the perpendicular current in the IDR, as found in previous studies of component reconnection. Electrons were preferentially heated parallel to the magnetic field within the IDR. The heating was manifested as a flattop distribution below 400 eV. Two types of electromagnetic electron whistler waves were observed within the regions where electrons were heated. One type of whistler wave was associated with nonlinear structures in E|| with amplitudes up to 20 mV/m. The other type was not associated with any structures in E||. Poynting fluxes of these two types of whistler waves were directed away from the X-line. We suggest that the nonlinear evolution of the oblique whistler waves gave rise to the solitary structures in E||. There was a perpendicular super-Alfvénic outflow jet that was carried by magnetized electrons. Intense electrostatic lower hybrid drift waves were localized in the current sheet center and were probably driven by the super-Alfvénic electron jet, the velocity of which was approximately equal to the diamagnetic drift of demagnetized ions. Our observations suggest that the guide field significantly modified the structures (Hall electromagnetic fields and current system) and wave properties in the IDR.

Multiscale Modeling of Deformation Twinning Based on Field Theory of Multiscale Plasticity (FTMP)

DTIC Science & Technology

2013-09-01

of the deformation twinning: nucleation, growth (into, e.g., lenticular shapes), lattice rotation (satisfying the mirror symmetry), the attendant...Nucleation and subsequent growth into lenticular shapes is realistically captured. • Stress-strain responses accompanied by serration and overall softening

Multiscale synchrony behaviors of paired financial time series by 3D multi-continuum percolation

NASA Astrophysics Data System (ADS)

Wang, M.; Wang, J.; Wang, B. T.

2018-02-01

Multiscale synchrony behaviors and nonlinear dynamics of paired financial time series are investigated, in an attempt to study the cross correlation relationships between two stock markets. A random stock price model is developed by a new system called three-dimensional (3D) multi-continuum percolation system, which is utilized to imitate the formation mechanism of price dynamics and explain the nonlinear behaviors found in financial time series. We assume that the price fluctuations are caused by the spread of investment information. The cluster of 3D multi-continuum percolation represents the cluster of investors who share the same investment attitude. In this paper, we focus on the paired return series, the paired volatility series, and the paired intrinsic mode functions which are decomposed by empirical mode decomposition. A new cross recurrence quantification analysis is put forward, combining with multiscale cross-sample entropy, to investigate the multiscale synchrony of these paired series from the proposed model. The corresponding research is also carried out for two China stock markets as comparison.

Molecular systems biology of ErbB1 signaling: bridging the gap through multiscale modeling and high-performance computing.

PubMed

Shih, Andrew J; Purvis, Jeremy; Radhakrishnan, Ravi

2008-12-01

The complexity in intracellular signaling mechanisms relevant for the conquest of many diseases resides at different levels of organization with scales ranging from the subatomic realm relevant to catalytic functions of enzymes to the mesoscopic realm relevant to the cooperative association of molecular assemblies and membrane processes. Consequently, the challenge of representing and quantifying functional or dysfunctional modules within the networks remains due to the current limitations in our understanding of mesoscopic biology, i.e., how the components assemble into functional molecular ensembles. A multiscale approach is necessary to treat a hierarchy of interactions ranging from molecular (nm, ns) to signaling (microm, ms) length and time scales, which necessitates the development and application of specialized modeling tools. Complementary to multiscale experimentation (encompassing structural biology, mechanistic enzymology, cell biology, and single molecule studies) multiscale modeling offers a powerful and quantitative alternative for the study of functional intracellular signaling modules. Here, we describe the application of a multiscale approach to signaling mediated by the ErbB1 receptor which constitutes a network hub for the cell's proliferative, migratory, and survival programs. Through our multiscale model, we mechanistically describe how point-mutations in the ErbB1 receptor can profoundly alter signaling characteristics leading to the onset of oncogenic transformations. Specifically, we describe how the point mutations induce cascading fragility mechanisms at the molecular scale as well as at the scale of the signaling network to preferentially activate the survival factor Akt. We provide a quantitative explanation for how the hallmark of preferential Akt activation in cell-lines harboring the constitutively active mutant ErbB1 receptors causes these cell-lines to be addicted to ErbB1-mediated generation of survival signals. Consequently, inhibition of ErbB1 activity leads to a remarkable therapeutic response in the addicted cell lines.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

A predictive computational theory is shown for modeling complex, hierarchical materials ranging from metal alloys to polymer nanocomposites. The theory can capture complex mechanisms such as plasticity and failure that span across multiple length scales. This general multiscale material modeling theory relies on sound principles of mathematics and mechanics, and a cutting-edge reduced order modeling method named self-consistent clustering analysis (SCA) [Zeliang Liu, M.A. Bessa, Wing Kam Liu, “Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials,” Comput. Methods Appl. Mech. Engrg. 306 (2016) 319–341]. SCA reduces by several orders of magnitude the computational cost of micromechanical andmore » concurrent multiscale simulations, while retaining the microstructure information. This remarkable increase in efficiency is achieved with a data-driven clustering method. Computationally expensive operations are performed in the so-called offline stage, where degrees of freedom (DOFs) are agglomerated into clusters. The interaction tensor of these clusters is computed. In the online or predictive stage, the Lippmann-Schwinger integral equation is solved cluster-wise using a self-consistent scheme to ensure solution accuracy and avoid path dependence. To construct a concurrent multiscale model, this scheme is applied at each material point in a macroscale structure, replacing a conventional constitutive model with the average response computed from the microscale model using just the SCA online stage. A regularized damage theory is incorporated in the microscale that avoids the mesh and RVE size dependence that commonly plagues microscale damage calculations. The SCA method is illustrated with two cases: a carbon fiber reinforced polymer (CFRP) structure with the concurrent multiscale model and an application to fatigue prediction for additively manufactured metals. For the CFRP problem, a speed up estimated to be about 43,000 is achieved by using the SCA method, as opposed to FE2, enabling the solution of an otherwise computationally intractable problem. The second example uses a crystal plasticity constitutive law and computes the fatigue potency of extrinsic microscale features such as voids. This shows that local stress and strain are capture sufficiently well by SCA. This model has been incorporated in a process-structure-properties prediction framework for process design in additive manufacturing.« less

Toward GEOS-6, A Global Cloud System Resolving Atmospheric Model

NASA Technical Reports Server (NTRS)

Putman, William M.

2010-01-01

NASA is committed to observing and understanding the weather and climate of our home planet through the use of multi-scale modeling systems and space-based observations. Global climate models have evolved to take advantage of the influx of multi- and many-core computing technologies and the availability of large clusters of multi-core microprocessors. GEOS-6 is a next-generation cloud system resolving atmospheric model that will place NASA at the forefront of scientific exploration of our atmosphere and climate. Model simulations with GEOS-6 will produce a realistic representation of our atmosphere on the scale of typical satellite observations, bringing a visual comprehension of model results to a new level among the climate enthusiasts. In preparation for GEOS-6, the agency's flagship Earth System Modeling Framework [JDl] has been enhanced to support cutting-edge high-resolution global climate and weather simulations. Improvements include a cubed-sphere grid that exposes parallelism; a non-hydrostatic finite volume dynamical core, and algorithm designed for co-processor technologies, among others. GEOS-6 represents a fundamental advancement in the capability of global Earth system models. The ability to directly compare global simulations at the resolution of spaceborne satellite images will lead to algorithm improvements and better utilization of space-based observations within the GOES data assimilation system

Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2

EPA Pesticide Factsheets

The uploaded data consists of the BRACE Na aerosol observations paired with CMAQ model output, the updated model's parameterization of sea salt aerosol emission size distribution, and the model's parameterization of the sea salt emission factor as a function of sea surface temperature. This dataset is associated with the following publication:Gantt , B., J. Kelly , and J. Bash. Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2. Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau, GERMANY, 8: 3733-3746, (2015).

Multiscale Aspects of Modeling Gas-Phase Nanoparticle Synthesis

PubMed Central

Buesser, B.; Gröhn, A.J.

2013-01-01

Aerosol reactors are utilized to manufacture nanoparticles in industrially relevant quantities. The development, understanding and scale-up of aerosol reactors can be facilitated with models and computer simulations. This review aims to provide an overview of recent developments of models and simulations and discuss their interconnection in a multiscale approach. A short introduction of the various aerosol reactor types and gas-phase particle dynamics is presented as a background for the later discussion of the models and simulations. Models are presented with decreasing time and length scales in sections on continuum, mesoscale, molecular dynamics and quantum mechanics models. PMID:23729992

Crustal Seismic Vs and Vs anisotropy of Northeast Japan Revealed by Ambient Noise Tomography

NASA Astrophysics Data System (ADS)

Chen, K. X.; Gung, Y.; Kuo, B. Y.; Huang, T. Y.

2017-12-01

We present 3D crustal models of Vs and Vs azimuthal anisotropy of the Tohoku region, Japan. We employ the Welch's method to derive the empirical Green's functions (EGF) of Rayleigh waves from one year of continuous records of 123 short-period stations of the dense high-sensitivity seismograph network (Hi-net). We compute EGFs for about 4000 station pairs with interstation distance less than 300 km. For each qualified EGF, we measure the dispersion in the period range from 3 to 16 seconds. We then construct the models by using a wavelet-based multi-scale inversion technique. In the resulting models, characteristics of Vs variations and Vs azimuthal anisotropy are closely related to surface geology, Quaternary volcano activities, and plate motions. For the Vs variations in the shallow crust (< 12km), the prominent high velocity anomalies are observed in the eastern part of the volcano belt, and they can be attributed to the old (Palaeozoic to Mesozoic) sedimentary and plutonic rocks located in the northeastern and the southeastern Tohoku, respectively. In the middle crust, the distribution of the low velocity anomalies is well correlated to the volcano belt. For the Vs anisotropy, the strength and the patterns of fast polarization directions (FPD) are depth-dependent. In the shallow crust, the anisotropy is strong, and are dominated by the typical orogeny parallel anisotropy, with FPDs parallel to the main strikes of the mountain range. While in the lower crust, the FPDs are generally parallel to the absolute plate motion. Interestingly, the distribution of PFDs is rather chaotic and strength of anisotropy is weak in the middle crust ( 8 - 20 km). We propose that the weak and random anisotropy in this layer is likely related to the presence of magma reservoirs beneath the volcano belt, as the associated active volcanism may cause the destruction of the alignment of crustal fabrics Key words: Tohoku, ambient noise, seismic anisotropy, surface wave tomography, volcano activities

Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model

PubMed Central

Zhu, Qing; Zou, Yingchao; Lai, Kin Keung

2014-01-01

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations. PMID:25061614

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Day-ahead crude oil price forecasting using a novel morphological component analysis based model.

PubMed

Zhu, Qing; He, Kaijian; Zou, Yingchao; Lai, Kin Keung

2014-01-01

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations.

Multi-Scale Simulation of High Energy Density Ionic Liquids

DTIC Science & Technology

2007-06-19

and simulation of ionic liquids (ILs). A polarizable model was developed to simulate ILs more accurately at the atomistic level. A multiscale coarse...propellant, 1- hydroxyethyl-4-amino-1, 2, 4-triazolium nitrate (HEATN), were studied with the all-atom polarizable model. The mechanism suggested for HEATN...with this AFOSR-supported project, a polarizable forcefield for the ionic liquids such as 1-ethyl-3-methylimidazolium nitrate (EMIM*/NO3-) was

Multiscale agent-based cancer modeling.

PubMed

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.

On unified modeling, theory, and method for solving multi-scale global optimization problems

NASA Astrophysics Data System (ADS)

Gao, David Yang

2016-10-01

A unified model is proposed for general optimization problems in multi-scale complex systems. Based on this model and necessary assumptions in physics, the canonical duality theory is presented in a precise way to include traditional duality theories and popular methods as special applications. Two conjectures on NP-hardness are proposed, which should play important roles for correctly understanding and efficiently solving challenging real-world problems. Applications are illustrated for both nonconvex continuous optimization and mixed integer nonlinear programming.

Multiscale modeling of the human arterial tree on the TeraGrid.

NASA Astrophysics Data System (ADS)

Karniadakis, Gerorge

2009-03-01

A multiscale model of the human arterial tree will be presented consisting of the macrovascular network (MaN, arteries above 1-2 mm), the mesovascular network (MeN, arterioles above 10 micro-m) and the microvascular network (MiN, capillaries). Coupling conditions between the MaN-MeN-MiN will be discussed and three different methods in modeling each network will be presented. Specific examples will be shown for the intracranial arterial tree for healthy subjects but also for patients with hydrocephalus.

An Expanded Multi-scale Monte Carlo Simulation Method for Personalized Radiobiological Effect Estimation in Radiotherapy: a feasibility study

NASA Astrophysics Data System (ADS)

Zhang, Ying; Feng, Yuanming; Wang, Wei; Yang, Chengwen; Wang, Ping

2017-03-01

A novel and versatile “bottom-up” approach is developed to estimate the radiobiological effect of clinic radiotherapy. The model consists of multi-scale Monte Carlo simulations from organ to cell levels. At cellular level, accumulated damages are computed using a spectrum-based accumulation algorithm and predefined cellular damage database. The damage repair mechanism is modeled by an expanded reaction-rate two-lesion kinetic model, which were calibrated through replicating a radiobiological experiment. Multi-scale modeling is then performed on a lung cancer patient under conventional fractionated irradiation. The cell killing effects of two representative voxels (isocenter and peripheral voxel of the tumor) are computed and compared. At microscopic level, the nucleus dose and damage yields vary among all nucleuses within the voxels. Slightly larger percentage of cDSB yield is observed for the peripheral voxel (55.0%) compared to the isocenter one (52.5%). For isocenter voxel, survival fraction increase monotonically at reduced oxygen environment. Under an extreme anoxic condition (0.001%), survival fraction is calculated to be 80% and the hypoxia reduction factor reaches a maximum value of 2.24. In conclusion, with biological-related variations, the proposed multi-scale approach is more versatile than the existing approaches for evaluating personalized radiobiological effects in radiotherapy.

Resolving the Multi-scale Behavior of Geochemical Weathering in the Critical Zone Using High Resolution Hydro-geochemical Models

NASA Astrophysics Data System (ADS)

Pandey, S.; Rajaram, H.

2015-12-01

This work investigates hydrologic and geochemical interactions in the Critical Zone (CZ) using high-resolution reactive transport modeling. Reactive transport models can be used to predict the response of geochemical weathering and solute fluxes in the CZ to changes in a dynamic environment, such as those pertaining to human activities and climate change in recent years. The scales of hydrology and geochemistry in the CZ range from days to eons in time and centimeters to kilometers in space. Here, we present results of a multi-dimensional, multi-scale hydro-geochemical model to investigate the role of subsurface heterogeneity on the formation of mineral weathering fronts in the CZ, which requires consideration of many of these spatio-temporal scales. The model is implemented using the reactive transport code PFLOTRAN, an open source subsurface flow and reactive transport code that utilizes parallelization over multiple processing nodes and provides a strong framework for simulating weathering in the CZ. The model is set up to simulate weathering dynamics in the mountainous catchments representative of the Colorado Front Range. Model parameters were constrained based on hydrologic, geochemical, and geophysical observations from the Boulder Creek Critical Zone Observatory (BcCZO). Simulations were performed in fractured rock systems and compared with systems of heterogeneous and homogeneous permeability fields. Tracer simulations revealed that the mean residence time of solutes was drastically accelerated as fracture density increased. In simulations that include mineral reactions, distinct signatures of transport limitations on weathering arose when discrete flow paths were included. This transport limitation was related to both advective and diffusive processes in the highly heterogeneous systems (i.e. fractured media and correlated random permeability fields with σlnk > 3). The well-known time-dependence of mineral weathering rates was found to be the most pronounced in the fractured systems, with a departure from the maximum system-averaged dissolution rate occurring after ~100 kyr followed by a gradual decrease in the reaction rate with time that persists beyond 104 kyr.

Multiscale decoding for reliable brain-machine interface performance over time.

PubMed

Han-Lin Hsieh; Wong, Yan T; Pesaran, Bijan; Shanechi, Maryam M

2017-07-01

Recordings from invasive implants can degrade over time, resulting in a loss of spiking activity for some electrodes. For brain-machine interfaces (BMI), such a signal degradation lowers control performance. Achieving reliable performance over time is critical for BMI clinical viability. One approach to improve BMI longevity is to simultaneously use spikes and other recording modalities such as local field potentials (LFP), which are more robust to signal degradation over time. We have developed a multiscale decoder that can simultaneously model the different statistical profiles of multi-scale spike/LFP activity (discrete spikes vs. continuous LFP). This decoder can also run at multiple time-scales (millisecond for spikes vs. tens of milliseconds for LFP). Here, we validate the multiscale decoder for estimating the movement of 7 major upper-arm joint angles in a non-human primate (NHP) during a 3D reach-to-grasp task. The multiscale decoder uses motor cortical spike/LFP recordings as its input. We show that the multiscale decoder can improve decoding accuracy by adding information from LFP to spikes, while running at the fast millisecond time-scale of the spiking activity. Moreover, this improvement is achieved using relatively few LFP channels, demonstrating the robustness of the approach. These results suggest that using multiscale decoders has the potential to improve the reliability and longevity of BMIs.

Large-Scale Modeling of Epileptic Seizures: Scaling Properties of Two Parallel Neuronal Network Simulation Algorithms

DOE PAGES

Pesce, Lorenzo L.; Lee, Hyong C.; Hereld, Mark; ...

2013-01-01

Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determinedmore » the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons) and processor pool sizes (1 to 256 processors). Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.« less

Length scale effects and multiscale modeling of thermally induced phase transformation kinetics in NiTi SMA

NASA Astrophysics Data System (ADS)

Frantziskonis, George N.; Gur, Sourav

2017-06-01

Thermally induced phase transformation in NiTi shape memory alloys (SMAs) shows strong size and shape, collectively termed length scale effects, at the nano to micrometer scales, and that has important implications for the design and use of devices and structures at such scales. This paper, based on a recently developed multiscale model that utilizes molecular dynamics (MDs) simulations at small scales and MD-verified phase field (PhF) simulations at larger scales, reports results on specific length scale effects, i.e. length scale effects in martensite phase fraction (MPF) evolution, transformation temperatures (martensite and austenite start and finish) and in the thermally cyclic transformation between austenitic and martensitic phase. The multiscale study identifies saturation points for length scale effects and studies, for the first time, the length scale effect on the kinetics (i.e. developed internal strains) in the B19‧ phase during phase transformation. The major part of the work addresses small scale single crystals in specific orientations. However, the multiscale method is used in a unique and novel way to indirectly study length scale and grain size effects on evolution kinetics in polycrystalline NiTi, and to compare the simulation results to experiments. The interplay of the grain size and the length scale effect on the thermally induced MPF evolution is also shown in this present study. Finally, the multiscale coupling results are employed to improve phenomenological material models for NiTi SMA.

Bridging scales through multiscale modeling: a case study on protein kinase A.

PubMed

Boras, Britton W; Hirakis, Sophia P; Votapka, Lane W; Malmstrom, Robert D; Amaro, Rommie E; McCulloch, Andrew D

2015-01-01

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

Multi-Scale Human Respiratory System Simulations to Study Health Effects of Aging, Disease, and Inhaled Substances

NASA Astrophysics Data System (ADS)

Kunz, Robert; Haworth, Daniel; Dogan, Gulkiz; Kriete, Andres

2006-11-01

Three-dimensional, unsteady simulations of multiphase flow, gas exchange, and particle/aerosol deposition in the human lung are reported. Surface data for human tracheo-bronchial trees are derived from CT scans, and are used to generate three- dimensional CFD meshes for the first several generations of branching. One-dimensional meshes for the remaining generations down to the respiratory units are generated using branching algorithms based on those that have been proposed in the literature, and a zero-dimensional respiratory unit (pulmonary acinus) model is attached at the end of each terminal bronchiole. The process is automated to facilitate rapid model generation. The model is exercised through multiple breathing cycles to compute the spatial and temporal variations in flow, gas exchange, and particle/aerosol deposition. The depth of the 3D/1D transition (at branching generation n) is a key parameter, and can be varied. High-fidelity models (large n) are run on massively parallel distributed-memory clusters, and are used to generate physical insight and to calibrate/validate the 1D and 0D models. Suitably validated lower-order models (small n) can be run on single-processor PC’s with run times that allow model-based clinical intervention for individual patients.

Multi-Scale Computational Modeling of Two-Phased Metal Using GMC Method

NASA Technical Reports Server (NTRS)

Moghaddam, Masoud Ghorbani; Achuthan, A.; Bednacyk, B. A.; Arnold, S. M.; Pineda, E. J.

2014-01-01

A multi-scale computational model for determining plastic behavior in two-phased CMSX-4 Ni-based superalloys is developed on a finite element analysis (FEA) framework employing crystal plasticity constitutive model that can capture the microstructural scale stress field. The generalized method of cells (GMC) micromechanics model is used for homogenizing the local field quantities. At first, GMC as stand-alone is validated by analyzing a repeating unit cell (RUC) as a two-phased sample with 72.9% volume fraction of gamma'-precipitate in the gamma-matrix phase and comparing the results with those predicted by finite element analysis (FEA) models incorporating the same crystal plasticity constitutive model. The global stress-strain behavior and the local field quantity distributions predicted by GMC demonstrated good agreement with FEA. High computational saving, at the expense of some accuracy in the components of local tensor field quantities, was obtained with GMC. Finally, the capability of the developed multi-scale model linking FEA and GMC to solve real life sized structures is demonstrated by analyzing an engine disc component and determining the microstructural scale details of the field quantities.

Towards a new multiscale air quality transport model using the fully unstructured anisotropic adaptive mesh technology of Fluidity (version 4.1.9)

NASA Astrophysics Data System (ADS)

Zheng, J.; Zhu, J.; Wang, Z.; Fang, F.; Pain, C. C.; Xiang, J.

2015-10-01

An integrated method of advanced anisotropic hr-adaptive mesh and discretization numerical techniques has been, for first time, applied to modelling of multiscale advection-diffusion problems, which is based on a discontinuous Galerkin/control volume discretization on unstructured meshes. Over existing air quality models typically based on static-structured grids using a locally nesting technique, the advantage of the anisotropic hr-adaptive model has the ability to adapt the mesh according to the evolving pollutant distribution and flow features. That is, the mesh resolution can be adjusted dynamically to simulate the pollutant transport process accurately and effectively. To illustrate the capability of the anisotropic adaptive unstructured mesh model, three benchmark numerical experiments have been set up for two-dimensional (2-D) advection phenomena. Comparisons have been made between the results obtained using uniform resolution meshes and anisotropic adaptive resolution meshes. Performance achieved in 3-D simulation of power plant plumes indicates that this new adaptive multiscale model has the potential to provide accurate air quality modelling solutions effectively.

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

PubMed Central

2016-01-01

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

Multiscale modelling approaches for assessing cosmetic ingredients safety.

PubMed

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.

Blood Flow: Multi-scale Modeling and Visualization (July 2011)

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2011-01-01

Multi-scale modeling of arterial blood flow can shed light on the interaction between events happening at micro- and meso-scales (i.e., adhesion of red blood cells to the arterial wall, clot formation) and at macro-scales (i.e., change in flow patterns due to the clot). Coupled numerical simulations of such multi-scale flow require state-of-the-art computers and algorithms, along with techniques for multi-scale visualizations. This animation presents early results of two studies used in the development of a multi-scale visualization methodology. The fisrt illustrates a flow of healthy (red) and diseased (blue) blood cells with a Dissipative Particle Dynamics (DPD) method. Each bloodmore » cell is represented by a mesh, small spheres show a sub-set of particles representing the blood plasma, while instantaneous streamlines and slices represent the ensemble average velocity. In the second we investigate the process of thrombus (blood clot) formation, which may be responsible for the rupture of aneurysms, by concentrating on the platelet blood cells, observing as they aggregate on the wall of an aneruysm. Simulation was performed on Kraken at the National Institute for Computational Sciences. Visualization was produced using resources of the Argonne Leadership Computing Facility at Argonne National Laboratory.« less

A multiscale restriction-smoothed basis method for high contrast porous media represented on unstructured grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Møyner, Olav, E-mail: olav.moyner@sintef.no; Lie, Knut-Andreas, E-mail: knut-andreas.lie@sintef.no

2016-01-01

A wide variety of multiscale methods have been proposed in the literature to reduce runtime and provide better scaling for the solution of Poisson-type equations modeling flow in porous media. We present a new multiscale restricted-smoothed basis (MsRSB) method that is designed to be applicable to both rectilinear grids and unstructured grids. Like many other multiscale methods, MsRSB relies on a coarse partition of the underlying fine grid and a set of local prolongation operators (multiscale basis functions) that map unknowns associated with the fine grid cells to unknowns associated with blocks in the coarse partition. These mappings are constructedmore » by restricted smoothing: Starting from a constant, a localized iterative scheme is applied directly to the fine-scale discretization to compute prolongation operators that are consistent with the local properties of the differential operators. The resulting method has three main advantages: First of all, both the coarse and the fine grid can have general polyhedral geometry and unstructured topology. This means that partitions and good prolongation operators can easily be constructed for complex models involving high media contrasts and unstructured cell connections introduced by faults, pinch-outs, erosion, local grid refinement, etc. In particular, the coarse partition can be adapted to geological or flow-field properties represented on cells or faces to improve accuracy. Secondly, the method is accurate and robust when compared to existing multiscale methods and does not need expensive recomputation of local basis functions to account for transient behavior: Dynamic mobility changes are incorporated by continuing to iterate a few extra steps on existing basis functions. This way, the cost of updating the prolongation operators becomes proportional to the amount of change in fluid mobility and one reduces the need for expensive, tolerance-based updates. Finally, since the MsRSB method is formulated on top of a cell-centered, conservative, finite-volume method, it is applicable to any flow model in which one can isolate a pressure equation. Herein, we only discuss single and two-phase incompressible models. Compressible flow, e.g., as modeled by the black-oil equations, is discussed in a separate paper.« less

Efficient Integration of Coupled Electrical-Chemical Systems in Multiscale Neuronal Simulations

PubMed Central

Brocke, Ekaterina; Bhalla, Upinder S.; Djurfeldt, Mikael; Hellgren Kotaleski, Jeanette; Hanke, Michael

2016-01-01

Multiscale modeling and simulations in neuroscience is gaining scientific attention due to its growing importance and unexplored capabilities. For instance, it can help to acquire better understanding of biological phenomena that have important features at multiple scales of time and space. This includes synaptic plasticity, memory formation and modulation, homeostasis. There are several ways to organize multiscale simulations depending on the scientific problem and the system to be modeled. One of the possibilities is to simulate different components of a multiscale system simultaneously and exchange data when required. The latter may become a challenging task for several reasons. First, the components of a multiscale system usually span different spatial and temporal scales, such that rigorous analysis of possible coupling solutions is required. Then, the components can be defined by different mathematical formalisms. For certain classes of problems a number of coupling mechanisms have been proposed and successfully used. However, a strict mathematical theory is missing in many cases. Recent work in the field has not so far investigated artifacts that may arise during coupled integration of different approximation methods. Moreover, in neuroscience, the coupling of widely used numerical fixed step size solvers may lead to unexpected inefficiency. In this paper we address the question of possible numerical artifacts that can arise during the integration of a coupled system. We develop an efficient strategy to couple the components comprising a multiscale test problem in neuroscience. We introduce an efficient coupling method based on the second-order backward differentiation formula (BDF2) numerical approximation. The method uses an adaptive step size integration with an error estimation proposed by Skelboe (2000). The method shows a significant advantage over conventional fixed step size solvers used in neuroscience for similar problems. We explore different coupling strategies that define the organization of computations between system components. We study the importance of an appropriate approximation of exchanged variables during the simulation. The analysis shows a substantial impact of these aspects on the solution accuracy in the application to our multiscale neuroscientific test problem. We believe that the ideas presented in the paper may essentially contribute to the development of a robust and efficient framework for multiscale brain modeling and simulations in neuroscience. PMID:27672364

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

PubMed

Brocke, Ekaterina; Bhalla, Upinder S; Djurfeldt, Mikael; Hellgren Kotaleski, Jeanette; Hanke, Michael

2016-01-01

Multiscale modeling and simulations in neuroscience is gaining scientific attention due to its growing importance and unexplored capabilities. For instance, it can help to acquire better understanding of biological phenomena that have important features at multiple scales of time and space. This includes synaptic plasticity, memory formation and modulation, homeostasis. There are several ways to organize multiscale simulations depending on the scientific problem and the system to be modeled. One of the possibilities is to simulate different components of a multiscale system simultaneously and exchange data when required. The latter may become a challenging task for several reasons. First, the components of a multiscale system usually span different spatial and temporal scales, such that rigorous analysis of possible coupling solutions is required. Then, the components can be defined by different mathematical formalisms. For certain classes of problems a number of coupling mechanisms have been proposed and successfully used. However, a strict mathematical theory is missing in many cases. Recent work in the field has not so far investigated artifacts that may arise during coupled integration of different approximation methods. Moreover, in neuroscience, the coupling of widely used numerical fixed step size solvers may lead to unexpected inefficiency. In this paper we address the question of possible numerical artifacts that can arise during the integration of a coupled system. We develop an efficient strategy to couple the components comprising a multiscale test problem in neuroscience. We introduce an efficient coupling method based on the second-order backward differentiation formula (BDF2) numerical approximation. The method uses an adaptive step size integration with an error estimation proposed by Skelboe (2000). The method shows a significant advantage over conventional fixed step size solvers used in neuroscience for similar problems. We explore different coupling strategies that define the organization of computations between system components. We study the importance of an appropriate approximation of exchanged variables during the simulation. The analysis shows a substantial impact of these aspects on the solution accuracy in the application to our multiscale neuroscientific test problem. We believe that the ideas presented in the paper may essentially contribute to the development of a robust and efficient framework for multiscale brain modeling and simulations in neuroscience.

Design of a framework for modeling, integration and simulation of physiological models.

PubMed

Erson, E Zeynep; Cavuşoğlu, M Cenk

2012-09-01

Multiscale modeling and integration of physiological models carry challenges due to the complex nature of physiological processes. High coupling within and among scales present a significant challenge in constructing and integrating multiscale physiological models. In order to deal with such challenges in a systematic way, there is a significant need for an information technology framework together with related analytical and computational tools that will facilitate integration of models and simulations of complex biological systems. Physiological Model Simulation, Integration and Modeling Framework (Phy-SIM) is an information technology framework providing the tools to facilitate development, integration and simulation of integrated models of human physiology. Phy-SIM brings software level solutions to the challenges raised by the complex nature of physiological systems. The aim of Phy-SIM, and this paper is to lay some foundation with the new approaches such as information flow and modular representation of the physiological models. The ultimate goal is to enhance the development of both the models and the integration approaches of multiscale physiological processes and thus this paper focuses on the design approaches that would achieve such a goal. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Classification of JERS-1 Image Mosaic of Central Africa Using A Supervised Multiscale Classifier of Texture Features

NASA Technical Reports Server (NTRS)

Saatchi, Sassan; DeGrandi, Franco; Simard, Marc; Podest, Erika

1999-01-01

In this paper, a multiscale approach is introduced to classify the Japanese Research Satellite-1 (JERS-1) mosaic image over the Central African rainforest. A series of texture maps are generated from the 100 m mosaic image at various scales. Using a quadtree model and relating classes at each scale by a Markovian relationship, the multiscale images are classified from course to finer scale. The results are verified at various scales and the evolution of classification is monitored by calculating the error at each stage.

Multiscale characterization and mechanical modeling of an Al-Zn-Mg electron beam weld

NASA Astrophysics Data System (ADS)

Puydt, Quentin; Flouriot, Sylvain; Ringeval, Sylvain; Parry, Guillaume; De Geuser, Frédéric; Deschamps, Alexis

Welding of precipitation hardening alloys results in multi-scale microstructural heterogeneities, from the hardening nano-scale precipitates to the micron-scale solidification structures and to the component geometry. This heterogeneity results in a complex mechanical response, with gradients in strength, stress triaxiality and damage initiation sites.

A systematic multiscale modeling and experimental approach to protect grain boundaries in magnesium alloys from corrosion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Horstemeyer, Mark R.; Chaudhuri, Santanu

2015-09-30

A multiscale modeling Internal State Variable (ISV) constitutive model was developed that captures the fundamental structure-property relationships. The macroscale ISV model used lower length scale simulations (Butler-Volmer and Electronics Structures results) in order to inform the ISVs at the macroscale. The chemomechanical ISV model was calibrated and validated from experiments with magnesium (Mg) alloys that were investigated under corrosive environments coupled with experimental electrochemical studies. Because the ISV chemomechanical model is physically based, it can be used for other material systems to predict corrosion behavior. As such, others can use the chemomechanical model for analyzing corrosion effects on their designs.

Multi-Scale Modeling, Surrogate-Based Analysis, and Optimization of Lithium-Ion Batteries for Vehicle Applications

NASA Astrophysics Data System (ADS)

Du, Wenbo

A common attribute of electric-powered aerospace vehicles and systems such as unmanned aerial vehicles, hybrid- and fully-electric aircraft, and satellites is that their performance is usually limited by the energy density of their batteries. Although lithium-ion batteries offer distinct advantages such as high voltage and low weight over other battery technologies, they are a relatively new development, and thus significant gaps in the understanding of the physical phenomena that govern battery performance remain. As a result of this limited understanding, batteries must often undergo a cumbersome design process involving many manual iterations based on rules of thumb and ad-hoc design principles. A systematic study of the relationship between operational, geometric, morphological, and material-dependent properties and performance metrics such as energy and power density is non-trivial due to the multiphysics, multiphase, and multiscale nature of the battery system. To address these challenges, two numerical frameworks are established in this dissertation: a process for analyzing and optimizing several key design variables using surrogate modeling tools and gradient-based optimizers, and a multi-scale model that incorporates more detailed microstructural information into the computationally efficient but limited macro-homogeneous model. In the surrogate modeling process, multi-dimensional maps for the cell energy density with respect to design variables such as the particle size, ion diffusivity, and electron conductivity of the porous cathode material are created. A combined surrogate- and gradient-based approach is employed to identify optimal values for cathode thickness and porosity under various operating conditions, and quantify the uncertainty in the surrogate model. The performance of multiple cathode materials is also compared by defining dimensionless transport parameters. The multi-scale model makes use of detailed 3-D FEM simulations conducted at the particle-level. A monodisperse system of ellipsoidal particles is used to simulate the effective transport coefficients and interfacial reaction current density within the porous microstructure. Microscopic simulation results are shown to match well with experimental measurements, while differing significantly from homogenization approximations used in the macroscopic model. Global sensitivity analysis and surrogate modeling tools are applied to couple the two length scales and complete the multi-scale model.

Multiscale Architectures and Parallel Algorithms for Video Object Tracking

DTIC Science & Technology

2011-10-01

0 4 : if FIFO1 contains nDt frames then 5: Partition data into blocks. 6: Put SPE control block information...char buf 4 = FF; vec to r unsigned char buf 5 = FF; vec to r unsigned char buf 6 = FF; vec to r unsigned char buf 7 = FF; for ( j = 0 ; j < s i z e ; j...Public Release; Distribution Unlimited 8 7 u 6 ill :J (;) 5 E -;::; c 0 4 ~ u Q) X 3 Q) 8 7 6 u Q) Ul 5 :J (;) E :;::; 4 c 0

Analysis of Hepatitis C Virus Decline during Treatment with the Protease Inhibitor Danoprevir Using a Multiscale Model

DOE PAGES

Rong, Libin; Guedj, Jeremie; Dahari, Harel; ...

2013-03-14

The current paradigm for studying hepatitis C virus (HCV) dynamics in patients utilizes a standard viral dynamic model that keeps track of uninfected (target) cells, infected cells, and virus. The model does not account for the dynamics of intracellular viral replication, which is the major target of direct-acting antiviral agents (DAAs). In this paper, we describe and study a recently developed multiscale age-structured model that explicitly considers the potential effects of DAAs on intracellular viral RNA production, degradation, and secretion as virus into the circulation. We show that when therapy significantly blocks both intracellular viral RNA production and virus secretion,more » the serum viral load decline has three phases, with slopes reflecting the rate of serum viral clearance, the rate of loss of intracellular viral RNA, and the rate of loss of intracellular replication templates and infected cells, respectively. We also derive analytical approximations of the multiscale model and use one of them to analyze data from patients treated for 14 days with the HCV protease inhibitor danoprevir. Analysis suggests that danoprevir significantly blocks intracellular viral production (with mean effectiveness 99.2%), enhances intracellular viral RNA degradation about 5-fold, and moderately inhibits viral secretion (with mean effectiveness 56%). Finally, the multiscale model can be used to study viral dynamics in patients treated with other DAAs and explore their mechanisms of action in treatment of hepatitis C.« less

Prediction of water loss and viscoelastic deformation of apple tissue using a multiscale model.

PubMed

Aregawi, Wondwosen A; Abera, Metadel K; Fanta, Solomon W; Verboven, Pieter; Nicolai, Bart

2014-11-19

A two-dimensional multiscale water transport and mechanical model was developed to predict the water loss and deformation of apple tissue (Malus × domestica Borkh. cv. 'Jonagold') during dehydration. At the macroscopic level, a continuum approach was used to construct a coupled water transport and mechanical model. Water transport in the tissue was simulated using a phenomenological approach using Fick's second law of diffusion. Mechanical deformation due to shrinkage was based on a structural mechanics model consisting of two parts: Yeoh strain energy functions to account for non-linearity and Maxwell's rheological model of visco-elasticity. Apparent parameters of the macroscale model were computed from a microscale model. The latter accounted for water exchange between different microscopic structures of the tissue (intercellular space, the cell wall network and cytoplasm) using transport laws with the water potential as the driving force for water exchange between different compartments of tissue. The microscale deformation mechanics were computed using a model where the cells were represented as a closed thin walled structure. The predicted apparent water transport properties of apple cortex tissue from the microscale model showed good agreement with the experimentally measured values. Deviations between calculated and measured mechanical properties of apple tissue were observed at strains larger than 3%, and were attributed to differences in water transport behavior between the experimental compression tests and the simulated dehydration-deformation behavior. Tissue dehydration and deformation in the high relative humidity range ( > 97% RH) could, however, be accurately predicted by the multiscale model. The multiscale model helped to understand the dynamics of the dehydration process and the importance of the different microstructural compartments (intercellular space, cell wall, membrane and cytoplasm) for water transport and mechanical deformation.

Multiscale Space-Time Computational Methods for Fluid-Structure Interactions

DTIC Science & Technology

2015-09-13

prescribed fully or partially, is from an actual locust, extracted from high-speed, multi-camera video recordings of the locust in a wind tunnel . We use...With creative methods for coupling the fluid and structure, we can increase the scope and efficiency of the FSI modeling . Multiscale methods, which now...play an important role in computational mathematics, can also increase the accuracy and efficiency of the computer modeling techniques. The main

Augmenting Surgery via Multi-scale Modeling and Translational Systems Biology in the Era of Precision Medicine: A Multidisciplinary Perspective

PubMed Central

Kassab, Ghassan S.; An, Gary; Sander, Edward A.; Miga, Michael; Guccione, Julius M.; Ji, Songbai; Vodovotz, Yoram

2016-01-01

In this era of tremendous technological capabilities and increased focus on improving clinical outcomes, decreasing costs, and increasing precision, there is a need for a more quantitative approach to the field of surgery. Multiscale computational modeling has the potential to bridge the gap to the emerging paradigms of Precision Medicine and Translational Systems Biology, in which quantitative metrics and data guide patient care through improved stratification, diagnosis, and therapy. Achievements by multiple groups have demonstrated the potential for 1) multiscale computational modeling, at a biological level, of diseases treated with surgery and the surgical procedure process at the level of the individual and the population; along with 2) patient-specific, computationally-enabled surgical planning, delivery, and guidance and robotically-augmented manipulation. In this perspective article, we discuss these concepts, and cite emerging examples from the fields of trauma, wound healing, and cardiac surgery. PMID:27015816

Critical Issues on Materials for Gen-IV Reactors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caro, M; Marian, J; Martinez, E

2009-02-27

Within the LDRD on 'Critical Issues on Materials for Gen-IV Reactors' basic thermodynamics of the Fe-Cr alloy and accurate atomistic modeling were used to help develop the capability to predict hardening, swelling and embrittlement using the paradigm of Multiscale Materials Modeling. Approaches at atomistic and mesoscale levels were linked to build-up the first steps in an integrated modeling platform that seeks to relate in a near-term effort dislocation dynamics to polycrystal plasticity. The requirements originated in the reactor systems under consideration today for future sources of nuclear energy. These requirements are beyond the present day performance of nuclear materials andmore » calls for the development of new, high temperature, radiation resistant materials. Fe-Cr alloys with 9-12% Cr content are the base matrix of advanced ferritic/martensitic (FM) steels envisaged as fuel cladding and structural components of Gen-IV reactors. Predictive tools are needed to calculate structural and mechanical properties of these steels. This project represents a contribution in that direction. The synergy between the continuous progress of parallel computing and the spectacular advances in the theoretical framework that describes materials have lead to a significant advance in our comprehension of materials properties and their mechanical behavior. We took this progress to our advantage and within this LDRD were able to provide a detailed physical understanding of iron-chromium alloys microstructural behavior. By combining ab-initio simulations, many-body interatomic potential development, and mesoscale dislocation dynamics we were able to describe their microstructure evolution. For the first time in the case of Fe-Cr alloys, atomistic and mesoscale were merged and the first steps taken towards incorporating ordering and precipitation effects into dislocation dynamics (DD) simulations. Molecular dynamics (MD) studies of the transport of self-interstitial, vacancy and point defect clusters in concentrated Fe-Cr alloys were performed for future diffusion data calculations. A recently developed parallel MC code with displacement allowed us to predict the evolution of the defect microstructures, local chemistry changes, grain boundary segregation and precipitation resulting from radiation enhanced diffusion. We showed that grain boundaries, dislocations and free surfaces are not preferential for alpha-prime precipitation, and explained experimental observations of short-range order (SRO) in Fe-rich FeCr alloys. Our atomistic studies of dislocation hardening allowed us to obtain dislocation mobility functions for BCC pure iron and Fe-Cr and determine for FCC metals the dislocation interaction with precipitates with a description to be used in Dislocation Dynamic (DD) codes. A Synchronous parallel Kinetic Monte Carlo code was developed and tested which promises to expand the range of applicability of kMC simulations. This LDRD furthered the limits of the available science on the thermodynamic and mechanic behavior of metallic alloys and extended the application of physically-based multiscale materials modeling to cases of severe temperature and neutron fluence conditions in advanced future nuclear reactors. The report is organized as follows: after a brief introduction, we present the research activities, and results obtained. We give recommendations on future LLNL activities that may contribute to the progress in this area, together with examples of possible research lines to be supported.« less

Advancing predictive models for particulate formation in turbulent flames via massively parallel direct numerical simulations

PubMed Central

Bisetti, Fabrizio; Attili, Antonio; Pitsch, Heinz

2014-01-01

Combustion of fossil fuels is likely to continue for the near future due to the growing trends in energy consumption worldwide. The increase in efficiency and the reduction of pollutant emissions from combustion devices are pivotal to achieving meaningful levels of carbon abatement as part of the ongoing climate change efforts. Computational fluid dynamics featuring adequate combustion models will play an increasingly important role in the design of more efficient and cleaner industrial burners, internal combustion engines, and combustors for stationary power generation and aircraft propulsion. Today, turbulent combustion modelling is hindered severely by the lack of data that are accurate and sufficiently complete to assess and remedy model deficiencies effectively. In particular, the formation of pollutants is a complex, nonlinear and multi-scale process characterized by the interaction of molecular and turbulent mixing with a multitude of chemical reactions with disparate time scales. The use of direct numerical simulation (DNS) featuring a state of the art description of the underlying chemistry and physical processes has contributed greatly to combustion model development in recent years. In this paper, the analysis of the intricate evolution of soot formation in turbulent flames demonstrates how DNS databases are used to illuminate relevant physico-chemical mechanisms and to identify modelling needs. PMID:25024412

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ackerman, Thomas P.

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

Improvements in the Scalability of the NASA Goddard Multiscale Modeling Framework for Hurricane Climate Studies

NASA Technical Reports Server (NTRS)

Shen, Bo-Wen; Tao, Wei-Kuo; Chern, Jiun-Dar

2007-01-01

Improving our understanding of hurricane inter-annual variability and the impact of climate change (e.g., doubling CO2 and/or global warming) on hurricanes brings both scientific and computational challenges to researchers. As hurricane dynamics involves multiscale interactions among synoptic-scale flows, mesoscale vortices, and small-scale cloud motions, an ideal numerical model suitable for hurricane studies should demonstrate its capabilities in simulating these interactions. The newly-developed multiscale modeling framework (MMF, Tao et al., 2007) and the substantial computing power by the NASA Columbia supercomputer show promise in pursuing the related studies, as the MMF inherits the advantages of two NASA state-of-the-art modeling components: the GEOS4/fvGCM and 2D GCEs. This article focuses on the computational issues and proposes a revised methodology to improve the MMF's performance and scalability. It is shown that this prototype implementation enables 12-fold performance improvements with 364 CPUs, thereby making it more feasible to study hurricane climate.

A fast solver for the Helmholtz equation based on the generalized multiscale finite-element method

NASA Astrophysics Data System (ADS)

Fu, Shubin; Gao, Kai

2017-11-01

Conventional finite-element methods for solving the acoustic-wave Helmholtz equation in highly heterogeneous media usually require finely discretized mesh to represent the medium property variations with sufficient accuracy. Computational costs for solving the Helmholtz equation can therefore be considerably expensive for complicated and large geological models. Based on the generalized multiscale finite-element theory, we develop a novel continuous Galerkin method to solve the Helmholtz equation in acoustic media with spatially variable velocity and mass density. Instead of using conventional polynomial basis functions, we use multiscale basis functions to form the approximation space on the coarse mesh. The multiscale basis functions are obtained from multiplying the eigenfunctions of a carefully designed local spectral problem with an appropriate multiscale partition of unity. These multiscale basis functions can effectively incorporate the characteristics of heterogeneous media's fine-scale variations, thus enable us to obtain accurate solution to the Helmholtz equation without directly solving the large discrete system formed on the fine mesh. Numerical results show that our new solver can significantly reduce the dimension of the discrete Helmholtz equation system, and can also obviously reduce the computational time.

Center of Excellence for Geospatial Information Science research plan 2013-18

USGS Publications Warehouse

Usery, E. Lynn

2013-01-01

The U.S. Geological Survey Center of Excellence for Geospatial Information Science (CEGIS) was created in 2006 and since that time has provided research primarily in support of The National Map. The presentations and publications of the CEGIS researchers document the research accomplishments that include advances in electronic topographic map design, generalization, data integration, map projections, sea level rise modeling, geospatial semantics, ontology, user-centered design, volunteer geographic information, and parallel and grid computing for geospatial data from The National Map. A research plan spanning 2013–18 has been developed extending the accomplishments of the CEGIS researchers and documenting new research areas that are anticipated to support The National Map of the future. In addition to extending the 2006–12 research areas, the CEGIS research plan for 2013–18 includes new research areas in data models, geospatial semantics, high-performance computing, volunteered geographic information, crowdsourcing, social media, data integration, and multiscale representations to support the Three-Dimensional Elevation Program (3DEP) and The National Map of the future of the U.S. Geological Survey.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Collins, William D; Johansen, Hans; Evans, Katherine J

We present a survey of physical and computational techniques that have the potential to con- tribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enabling improved accuracy andmore » fidelity in simulation of dynamics and allow more complete representations of climate features at the global scale. At the same time, part- nerships with computer science teams have focused on taking advantage of evolving computer architectures, such as many-core processors and GPUs, so that these approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.« less

Multi-Scale Modeling of a Graphite-Epoxy-Nanotube System

NASA Technical Reports Server (NTRS)

Frankland, S. J. V.; Riddick, J. C.; Gates, T. S.

2005-01-01

A multi-scale method is utilized to determine some of the constitutive properties of a three component graphite-epoxy-nanotube system. This system is of interest because carbon nanotubes have been proposed as stiffening and toughening agents in the interlaminar regions of carbon fiber/epoxy laminates. The multi-scale method uses molecular dynamics simulation and equivalent-continuum modeling to compute three of the elastic constants of the graphite-epoxy-nanotube system: C11, C22, and C33. The 1-direction is along the nanotube axis, and the graphene sheets lie in the 1-2 plane. It was found that the C11 is only 4% larger than the C22. The nanotube therefore does have a small, but positive effect on the constitutive properties in the interlaminar region.

Intergranular Strain Evolution During Biaxial Loading: A Multiscale FE-FFT Approach

NASA Astrophysics Data System (ADS)

Upadhyay, M. V.; Capek, J.; Van Petegem, S.; Lebensohn, R. A.; Van Swygenhoven, H.

2017-05-01

Predicting the macroscopic and microscopic mechanical response of metals and alloys subjected to complex loading conditions necessarily requires a synergistic combination of multiscale material models and characterization techniques. This article focuses on the use of a multiscale approach to study the difference between intergranular lattice strain evolution for various grain families measured during in situ neutron diffraction on dog bone and cruciform 316L samples. At the macroscale, finite element simulations capture the complex coupling between applied forces and gauge stresses in cruciform geometries. The predicted gauge stresses are used as macroscopic boundary conditions to drive a mesoscale full-field elasto-viscoplastic fast Fourier transform crystal plasticity model. The results highlight the role of grain neighborhood on the intergranular strain evolution under uniaxial and equibiaxial loading.

A Computational Systems Biology Software Platform for Multiscale Modeling and Simulation: Integrating Whole-Body Physiology, Disease Biology, and Molecular Reaction Networks

PubMed Central

Eissing, Thomas; Kuepfer, Lars; Becker, Corina; Block, Michael; Coboeken, Katrin; Gaub, Thomas; Goerlitz, Linus; Jaeger, Juergen; Loosen, Roland; Ludewig, Bernd; Meyer, Michaela; Niederalt, Christoph; Sevestre, Michael; Siegmund, Hans-Ulrich; Solodenko, Juri; Thelen, Kirstin; Telle, Ulrich; Weiss, Wolfgang; Wendl, Thomas; Willmann, Stefan; Lippert, Joerg

2011-01-01

Today, in silico studies and trial simulations already complement experimental approaches in pharmaceutical R&D and have become indispensable tools for decision making and communication with regulatory agencies. While biology is multiscale by nature, project work, and software tools usually focus on isolated aspects of drug action, such as pharmacokinetics at the organism scale or pharmacodynamic interaction on the molecular level. We present a modeling and simulation software platform consisting of PK-Sim® and MoBi® capable of building and simulating models that integrate across biological scales. A prototypical multiscale model for the progression of a pancreatic tumor and its response to pharmacotherapy is constructed and virtual patients are treated with a prodrug activated by hepatic metabolization. Tumor growth is driven by signal transduction leading to cell cycle transition and proliferation. Free tumor concentrations of the active metabolite inhibit Raf kinase in the signaling cascade and thereby cell cycle progression. In a virtual clinical study, the individual therapeutic outcome of the chemotherapeutic intervention is simulated for a large population with heterogeneous genomic background. Thereby, the platform allows efficient model building and integration of biological knowledge and prior data from all biological scales. Experimental in vitro model systems can be linked with observations in animal experiments and clinical trials. The interplay between patients, diseases, and drugs and topics with high clinical relevance such as the role of pharmacogenomics, drug–drug, or drug–metabolite interactions can be addressed using this mechanistic, insight driven multiscale modeling approach. PMID:21483730

DOE Office of Scientific and Technical Information (OSTI.GOV)

Biyikli, Emre; To, Albert C., E-mail: albertto@pitt.edu

Atomistic/continuum coupling methods combine accurate atomistic methods and efficient continuum methods to simulate the behavior of highly ordered crystalline systems. Coupled methods utilize the advantages of both approaches to simulate systems at a lower computational cost, while retaining the accuracy associated with atomistic methods. Many concurrent atomistic/continuum coupling methods have been proposed in the past; however, their true computational efficiency has not been demonstrated. The present work presents an efficient implementation of a concurrent coupling method called the Multiresolution Molecular Mechanics (MMM) for serial, parallel, and adaptive analysis. First, we present the features of the software implemented along with themore » associated technologies. The scalability of the software implementation is demonstrated, and the competing effects of multiscale modeling and parallelization are discussed. Then, the algorithms contributing to the efficiency of the software are presented. These include algorithms for eliminating latent ghost atoms from calculations and measurement-based dynamic balancing of parallel workload. The efficiency improvements made by these algorithms are demonstrated by benchmark tests. The efficiency of the software is found to be on par with LAMMPS, a state-of-the-art Molecular Dynamics (MD) simulation code, when performing full atomistic simulations. Speed-up of the MMM method is shown to be directly proportional to the reduction of the number of the atoms visited in force computation. Finally, an adaptive MMM analysis on a nanoindentation problem, containing over a million atoms, is performed, yielding an improvement of 6.3–8.5 times in efficiency, over the full atomistic MD method. For the first time, the efficiency of a concurrent atomistic/continuum coupling method is comprehensively investigated and demonstrated.« less

Multiresolution molecular mechanics: Implementation and efficiency

NASA Astrophysics Data System (ADS)

Biyikli, Emre; To, Albert C.

2017-01-01

Atomistic/continuum coupling methods combine accurate atomistic methods and efficient continuum methods to simulate the behavior of highly ordered crystalline systems. Coupled methods utilize the advantages of both approaches to simulate systems at a lower computational cost, while retaining the accuracy associated with atomistic methods. Many concurrent atomistic/continuum coupling methods have been proposed in the past; however, their true computational efficiency has not been demonstrated. The present work presents an efficient implementation of a concurrent coupling method called the Multiresolution Molecular Mechanics (MMM) for serial, parallel, and adaptive analysis. First, we present the features of the software implemented along with the associated technologies. The scalability of the software implementation is demonstrated, and the competing effects of multiscale modeling and parallelization are discussed. Then, the algorithms contributing to the efficiency of the software are presented. These include algorithms for eliminating latent ghost atoms from calculations and measurement-based dynamic balancing of parallel workload. The efficiency improvements made by these algorithms are demonstrated by benchmark tests. The efficiency of the software is found to be on par with LAMMPS, a state-of-the-art Molecular Dynamics (MD) simulation code, when performing full atomistic simulations. Speed-up of the MMM method is shown to be directly proportional to the reduction of the number of the atoms visited in force computation. Finally, an adaptive MMM analysis on a nanoindentation problem, containing over a million atoms, is performed, yielding an improvement of 6.3-8.5 times in efficiency, over the full atomistic MD method. For the first time, the efficiency of a concurrent atomistic/continuum coupling method is comprehensively investigated and demonstrated.

Multi-Scale Modeling of an Integrated 3D Braided Composite with Applications to Helicopter Arm

NASA Astrophysics Data System (ADS)

Zhang, Diantang; Chen, Li; Sun, Ying; Zhang, Yifan; Qian, Kun

2017-10-01

A study is conducted with the aim of developing multi-scale analytical method for designing the composite helicopter arm with three-dimensional (3D) five-directional braided structure. Based on the analysis of 3D braided microstructure, the multi-scale finite element modeling is developed. Finite element analysis on the load capacity of 3D five-directional braided composites helicopter arm is carried out using the software ABAQUS/Standard. The influences of the braiding angle and loading condition on the stress and strain distribution of the helicopter arm are simulated. The results show that the proposed multi-scale method is capable of accurately predicting the mechanical properties of 3D braided composites, validated by the comparison the stress-strain curves of meso-scale RVCs. Furthermore, it is found that the braiding angle is an important factor affecting the mechanical properties of 3D five-directional braided composite helicopter arm. Based on the optimized structure parameters, the nearly net-shaped composite helicopter arm is fabricated using a novel resin transfer mould (RTM) process.

A FSI computational framework for vascular physiopathology: A novel flow-tissue multiscale strategy.

PubMed

Bianchi, Daniele; Monaldo, Elisabetta; Gizzi, Alessio; Marino, Michele; Filippi, Simonetta; Vairo, Giuseppe

2017-09-01

A novel fluid-structure computational framework for vascular applications is herein presented. It is developed by combining the double multi-scale nature of vascular physiopathology in terms of both tissue properties and blood flow. Addressing arterial tissues, they are modelled via a nonlinear multiscale constitutive rationale, based only on parameters having a clear histological and biochemical meaning. Moreover, blood flow is described by coupling a three-dimensional fluid domain (undergoing physiological inflow conditions) with a zero-dimensional model, which allows to reproduce the influence of the downstream vasculature, furnishing a realistic description of the outflow proximal pressure. The fluid-structure interaction is managed through an explicit time-marching approach, able to accurately describe tissue nonlinearities within each computational step for the fluid problem. A case study associated to a patient-specific aortic abdominal aneurysmatic geometry is numerically investigated, highlighting advantages gained from the proposed multiscale strategy, as well as showing soundness and effectiveness of the established framework for assessing useful clinical quantities and risk indexes. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Introduction and application of the multiscale coefficient of variation analysis.

PubMed

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.

Multiscale analysis of information dynamics for linear multivariate processes.

PubMed

Faes, Luca; Montalto, Alessandro; Stramaglia, Sebastiano; Nollo, Giandomenico; Marinazzo, Daniele

2016-08-01

In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving average (MA) component, we describe how to represent the resulting VARMA process using statespace (SS) models and how to exploit the SS model parameters to compute analytical measures of information storage and information transfer for the original and rescaled processes. The framework is then used to quantify multiscale information dynamics for simulated unidirectionally and bidirectionally coupled VAR processes, showing that rescaling may lead to insightful patterns of information storage and transfer but also to potentially misleading behaviors.

Modelling multiscale aspects of colorectal cancer

NASA Astrophysics Data System (ADS)

van Leeuwen, Ingeborg M. M.; Byrne, Helen M.; Johnston, Matthew D.; Edwards, Carina M.; Chapman, S. Jonathan; Bodmer, Walter F.; Maini, Philip K.

2008-01-01

Colorectal cancer (CRC) is responsible for nearly half a million deaths annually world-wide [11]. We present a series of mathematical models describing the dynamics of the intestinal epithelium and the kinetics of the molecular pathway most commonly mutated in CRC, the Wnt signalling network. We also discuss how we are coupling such models to build a multiscale model of normal and aberrant guts. This will enable us to combine disparate experimental and clinical data, to investigate interactions between phenomena taking place at different levels of organisation and, eventually, to test the efficacy of new drugs on the system as a whole.

A Novel Multiscale Physics Based Progressive Failure Methodology for Laminated Composite Structures

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Waas, Anthony M.; Bednarcyk, Brett A.; Collier, Craig S.; Yarrington, Phillip W.

2008-01-01

A variable fidelity, multiscale, physics based finite element procedure for predicting progressive damage and failure of laminated continuous fiber reinforced composites is introduced. At every integration point in a finite element model, progressive damage is accounted for at the lamina-level using thermodynamically based Schapery Theory. Separate failure criteria are applied at either the global-scale or the microscale in two different FEM models. A micromechanics model, the Generalized Method of Cells, is used to evaluate failure criteria at the micro-level. The stress-strain behavior and observed failure mechanisms are compared with experimental results for both models.

Multiscale Processes of Hurricane Sandy (2012) as Revealed by the CAMVis-MAP

NASA Astrophysics Data System (ADS)

Shen, B.; Li, J. F.; Cheung, S.

2013-12-01

In late October 2012, Storm Sandy made landfall near Brigantine, New Jersey, devastating surrounding areas and causing tremendous economic loss and hundreds of fatalities (Blake et al., 2013). An estimated damage of $50 billion made Sandy become the second costliest tropical cyclone (TC) in US history, surpassed only by Hurricane Katrina (2005). Central questions to be addressed include (1) to what extent the lead time of severe storm prediction such as Sandy can be extended (e.g., Emanuel 2012); and (2) whether and how advanced global model, supercomputing technology and numerical algorithm can help effectively illustrate the complicated physical processes that are associated with the evolution of the storms. In this study, the predictability of Sandy is addressed with a focus on short-term (or extended-range) genesis prediction as the first step toward the goal of understanding the relationship between extreme events, such as Sandy, and the current climate. The newly deployed Coupled Advanced global mesoscale Modeling (GMM) and concurrent Visualization (CAMVis) system is used for this study. We will show remarkable simulations of Hurricane Sandy with the GMM, including realistic 7-day track and intensity forecast and genesis predictions with a lead time of up to 6 days (e.g., Shen et al., 2013, GRL, submitted). We then discuss the enabling role of the high-resolution 4-D (time-X-Y-Z) visualizations in illustrating TC's transient dynamics and its interaction with tropical waves. In addition, we have finished the parallel implementation of the ensemble empirical mode decomposition (PEEMD, Cheung et al., 2013, AGU13, submitted) method that will be soon integrated into the multiscale analysis package (MAP) for the analysis of tropical weather systems such as TCs and tropical waves. While the original EEMD has previously shown superior performance in decomposition of nonlinear (local) and non-stationary data into different intrinsic modes which stay within the natural filter period windows, the PEEMD achieves a speedup of over 100 times as compared to the original EEMD. The advanced GMM, 4D visualizations and PEEMD method are being used to examine the multiscale processes of Sandy and its environmental flows that may contribute to the extended lead-time predictability of Hurricane Sandy. Figure 1: Evolution of Hurricane Sandy (2012) as revealed by the advanced visualization.

A Multi-scale Finite-frequency Approach to the Inversion of Reciprocal Travel Times for 3-D Velocity Structure beneath Taiwan

NASA Astrophysics Data System (ADS)

Chang, Y.; Hung, S.; Kuo, B.; Kuochen, H.

2012-12-01

Taiwan is one of the archetypical places for studying the active orogenic process in the world, where the Luzon arc has obliquely collided into the southwest China continental margin since 5 Ma ago. Because of the lack of convincing evidence for the structure in the lithospheric mantle and at even greater depths, several competing models have been proposed for the Taiwan mountain-building process. With the deployment of ocean-bottom seismometers (OBSs) on the seafloor around Taiwan from the TAIGER (TAiwan Integrated GEodynamic Research) and IES seismic experiments, the aperture of the seismic network is greatly extended to improve the depth resolution of tomographic imaging, which is critical to illuminate the nature of the arc-continent collision and accretion in Taiwan. In this study, we use relative travel-time residuals between a collection of teleseismic body wave arrivals to tomographically image the velocity structure beneath Taiwan. In addition to those from common distant earthquakes observed across an array of stations, we take advantage of dense seismicity in the vicinity of Taiwan and the source and receiver reciprocity to augment the data coverage from clustered earthquakes recorded by global stations. As waveforms are dependent of source mechanisms, we carry out the cluster analysis to group the phase arrivals with similar waveforms into clusters and simultaneously determine relative travel-time anomalies in the same cluster accurately by a cross correlation method. The combination of these two datasets would particularly enhance the resolvability of the tomographic models offshore of eastern Taiwan, where the two subduction systems of opposite polarity are taking place and have primarily shaped the present tectonic framework of Taiwan. On the other hand, our inversion adopts an innovation that invokes wavelet-based, multi-scale parameterization and finite-frequency theory. Not only does this approach make full use of frequency-dependent travel-time data providing different, but complementary sensitivity to velocity heterogeneity, but it also objectively addresses the intrinsically multi-scale characters of unevenly distributed data which yields the model with spatially-varying, data-adaptive resolution. Besides, we employ a parallelized singular value decomposition algorithm to directly solve for the resolution matrix and point spread functions (PSF). While the spatial distribution of a PSF is considered as the probability density function of multivariate normal distribution, we employ the principal component analysis (PCA) to estimate the lengths and directions of the principal axes of the PSF distribution, used for quantitative assessment of the resolvable scale-length and degree of smearing of the model and guidance to interpret the robust and trustworthy features in the resolved models.

Multiscale Cloud System Modeling

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Moncrieff, Mitchell W.

2009-01-01

The central theme of this paper is to describe how cloud system resolving models (CRMs) of grid spacing approximately 1 km have been applied to various important problems in atmospheric science across a wide range of spatial and temporal scales and how these applications relate to other modeling approaches. A long-standing problem concerns the representation of organized precipitating convective cloud systems in weather and climate models. Since CRMs resolve the mesoscale to large scales of motion (i.e., 10 km to global) they explicitly address the cloud system problem. By explicitly representing organized convection, CRMs bypass restrictive assumptions associated with convective parameterization such as the scale gap between cumulus and large-scale motion. Dynamical models provide insight into the physical mechanisms involved with scale interaction and convective organization. Multiscale CRMs simulate convective cloud systems in computational domains up to global and have been applied in place of contemporary convective parameterizations in global models. Multiscale CRMs pose a new challenge for model validation, which is met in an integrated approach involving CRMs, operational prediction systems, observational measurements, and dynamical models in a new international project: the Year of Tropical Convection, which has an emphasis on organized tropical convection and its global effects.

A Numerical Wind Tunnel Study of Viscous-Inviscid Interaction

DTIC Science & Technology

1992-01-01

partially successful. In Task 1 we devised surface boundary conditions for the multiscale model including effects of roughness and blowing. This work tied up ...directed at cleaning up some loose ends in de- veloping the Wilcox multiscale model (see Appendix R). The most significant issue was the development of...the following correlation between SR and k , will reproduce measured effects of sand-grain roughness for values of k up to about 400. ( k, ញ SiR (42

Multiscale Enaction Model (MEM): the case of complexity and “context-sensitivity” in vision

PubMed Central

Laurent, Éric

2014-01-01

I review the data on human visual perception that reveal the critical role played by non-visual contextual factors influencing visual activity. The global perspective that progressively emerges reveals that vision is sensitive to multiple couplings with other systems whose nature and levels of abstraction in science are highly variable. Contrary to some views where vision is immersed in modular hard-wired modules, rather independent from higher-level or other non-cognitive processes, converging data gathered in this article suggest that visual perception can be theorized in the larger context of biological, physical, and social systems with which it is coupled, and through which it is enacted. Therefore, any attempt to model complexity and multiscale couplings, or to develop a complex synthesis in the fields of mind, brain, and behavior, shall involve a systematic empirical study of both connectedness between systems or subsystems, and the embodied, multiscale and flexible teleology of subsystems. The conceptual model (Multiscale Enaction Model [MEM]) that is introduced in this paper finally relates empirical evidence gathered from psychology to biocomputational data concerning the human brain. Both psychological and biocomputational descriptions of MEM are proposed in order to help fill in the gap between scales of scientific analysis and to provide an account for both the autopoiesis-driven search for information, and emerging perception. PMID:25566115

Finite Dimensional Approximations for Continuum Multiscale Problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berlyand, Leonid

2017-01-24

The completed research project concerns the development of novel computational techniques for modeling nonlinear multiscale physical and biological phenomena. Specifically, it addresses the theoretical development and applications of the homogenization theory (coarse graining) approach to calculation of the effective properties of highly heterogenous biological and bio-inspired materials with many spatial scales and nonlinear behavior. This theory studies properties of strongly heterogeneous media in problems arising in materials science, geoscience, biology, etc. Modeling of such media raises fundamental mathematical questions, primarily in partial differential equations (PDEs) and calculus of variations, the subject of the PI’s research. The focus of completed researchmore » was on mathematical models of biological and bio-inspired materials with the common theme of multiscale analysis and coarse grain computational techniques. Biological and bio-inspired materials offer the unique ability to create environmentally clean functional materials used for energy conversion and storage. These materials are intrinsically complex, with hierarchical organization occurring on many nested length and time scales. The potential to rationally design and tailor the properties of these materials for broad energy applications has been hampered by the lack of computational techniques, which are able to bridge from the molecular to the macroscopic scale. The project addressed the challenge of computational treatments of such complex materials by the development of a synergistic approach that combines innovative multiscale modeling/analysis techniques with high performance computing.« less

Energy Dependence of Electron-Scale Currents and Dissipation During Magnetopause Reconnection

NASA Astrophysics Data System (ADS)

Shuster, J. R.; Gershman, D. J.; Giles, B. L.; Dorelli, J.; Avanov, L. A.; Chen, L. J.; Wang, S.; Bessho, N.; Torbert, R. B.; Farrugia, C. J.; Argall, M. R.; Strangeway, R. J.; Schwartz, S. J.

2017-12-01

We investigate the electron-scale physics of reconnecting current structures observed at the magnetopause during Phase 1B of the Magnetospheric Multiscale (MMS) mission when the spacecraft separation was less than 10 km. Using single-spacecraft measurements of the current density vector Jplasma = en(vi - ve) enabled by the accuracy of the Fast Plasma Investigation (FPI) electron moments as demonstrated by Phan et al. [2016], we consider perpendicular (J⊥1 and J⊥2) and parallel (J//) currents and their corresponding kinetic electron signatures. These currents can correspond to a variety of structures in the electron velocity distribution functions measured by FPI, including perpendicular and parallel crescents like those first reported by Burch et al. [2016], parallel electron beams, counter-streaming electron populations, or sometimes simply a bulk velocity shift. By integrating the distribution function over only its angular dimensions, we compute energy-dependent 'partial' moments and employ them to characterize the energy dependence of velocities, currents, and dissipation associated with magnetic reconnection diffusion regions caught by MMS. Our technique aids in visualizing and elucidating the plasma energization mechanisms that operate during collisionless reconnection.

Multiscale Modeling of Carbon Nanotube-Epoxy Nanocomposites

NASA Astrophysics Data System (ADS)

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; and the stiffness matrix was calculated. A rule of mixture approach was implemented in the ODF model to vary the SWNT volume fraction. Both the ODF and FE models are compared and contrasted. ODF analysis is significantly faster for nanocomposites and is a novel contribution in this thesis. Multiscale modeling allows for the effects of nanofillers in epoxy systems to be characterized without having to run costly experiments.

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study

PubMed Central

Vickers, T. Winston; Ernest, Holly B.; Boyce, Walter M.

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species. PMID:28609466

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study.

PubMed

Zeller, Katherine A; Vickers, T Winston; Ernest, Holly B; Boyce, Walter M

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species.

Differential Geometry Based Multiscale Models

PubMed Central

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 are coupled to generalized Navier–Stokes equations for fluid dynamics, Newton's equation for molecular dynamics, and potential and surface driving geometric flows for the micro-macro interface. For excessively large aqueous macromolecular complexes in chemistry and biology, we further develop differential geometry based multiscale fluid-electro-elastic models to replace the expensive molecular dynamics description with an alternative elasticity formulation. PMID:20169418

Modeling Materials: Design for Planetary Entry, Electric Aircraft, and Beyond

NASA Technical Reports Server (NTRS)

Thompson, Alexander; Lawson, John W.

2014-01-01

NASA missions push the limits of what is possible. The development of high-performance materials must keep pace with the agency's demanding, cutting-edge applications. Researchers at NASA's Ames Research Center are performing multiscale computational modeling to accelerate development times and further the design of next-generation aerospace materials. Multiscale modeling combines several computationally intensive techniques ranging from the atomic level to the macroscale, passing output from one level as input to the next level. These methods are applicable to a wide variety of materials systems. For example: (a) Ultra-high-temperature ceramics for hypersonic aircraft-we utilized the full range of multiscale modeling to characterize thermal protection materials for faster, safer air- and spacecraft, (b) Planetary entry heat shields for space vehicles-we computed thermal and mechanical properties of ablative composites by combining several methods, from atomistic simulations to macroscale computations, (c) Advanced batteries for electric aircraft-we performed large-scale molecular dynamics simulations of advanced electrolytes for ultra-high-energy capacity batteries to enable long-distance electric aircraft service; and (d) Shape-memory alloys for high-efficiency aircraft-we used high-fidelity electronic structure calculations to determine phase diagrams in shape-memory transformations. Advances in high-performance computing have been critical to the development of multiscale materials modeling. We used nearly one million processor hours on NASA's Pleiades supercomputer to characterize electrolytes with a fidelity that would be otherwise impossible. For this and other projects, Pleiades enables us to push the physics and accuracy of our calculations to new levels.

Integrative computational models of cardiac arrhythmias -- simulating the structurally realistic heart

PubMed Central

Trayanova, Natalia A; Tice, Brock M

2009-01-01

Simulation of cardiac electrical function, and specifically, simulation aimed at understanding the mechanisms of cardiac rhythm disorders, represents an example of a successful integrative multiscale modeling approach, uncovering emergent behavior at the successive scales in the hierarchy of structural complexity. The goal of this article is to present a review of the integrative multiscale models of realistic ventricular structure used in the quest to understand and treat ventricular arrhythmias. It concludes with the new advances in image-based modeling of the heart and the promise it holds for the development of individualized models of ventricular function in health and disease. PMID:20628585

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Multiscale Modeling of Grain-Boundary Fracture: Cohesive Zone Models Parameterized From Atomistic Simulations

NASA Technical Reports Server (NTRS)

Glaessgen, Edward H.; Saether, Erik; Phillips, Dawn R.; Yamakov, Vesselin

2006-01-01

A multiscale modeling strategy is developed to study grain boundary fracture in polycrystalline aluminum. Atomistic simulation is used to model fundamental nanoscale deformation and fracture mechanisms and to develop a constitutive relationship for separation along a grain boundary interface. The nanoscale constitutive relationship is then parameterized within a cohesive zone model to represent variations in grain boundary properties. These variations arise from the presence of vacancies, intersticies, and other defects in addition to deviations in grain boundary angle from the baseline configuration considered in the molecular dynamics simulation. The parameterized cohesive zone models are then used to model grain boundaries within finite element analyses of aluminum polycrystals.

A Multiscale Model for the Quasi-Static Thermo-Plastic Behavior of Highly Cross-Linked Glassy Polymers

DOE PAGES

Vu-Bac, N.; Bessa, M. A.; Rabczuk, Timon; ...

2015-09-10

In this paper, we present experimentally validated molecular dynamics predictions of the quasi- static yield and post-yield behavior for a highly cross-linked epoxy polymer under gen- eral stress states and for different temperatures. In addition, a hierarchical multiscale model is presented where the nano-scale simulations obtained from molecular dynamics were homogenized to a continuum thermoplastic constitutive model for the epoxy that can be used to describe the macroscopic behavior of the material. Three major conclusions were achieved: (1) the yield surfaces generated from the nano-scale model for different temperatures agree well with the paraboloid yield crite- rion, supporting previous macroscopicmore » experimental observations; (2) rescaling of the entire yield surfaces to the quasi-static case is possible by considering Argon’s theoretical predictions for pure compression of the polymer at absolute zero temperature; (3) nano- scale simulations can be used for an experimentally-free calibration of macroscopic con- tinuum models, opening new avenues for the design of materials and structures through multi-scale simulations that provide structure-property-performance relationships.« less

Complexity and multifractal behaviors of multiscale-continuum percolation financial system for Chinese stock markets

NASA Astrophysics Data System (ADS)

Zeng, Yayun; Wang, Jun; Xu, Kaixuan

2017-04-01

A new financial agent-based time series model is developed and investigated by multiscale-continuum percolation system, which can be viewed as an extended version of continuum percolation system. In this financial model, for different parameters of proportion and density, two Poisson point processes (where the radii of points represent the ability of receiving or transmitting information among investors) are applied to model a random stock price process, in an attempt to investigate the fluctuation dynamics of the financial market. To validate its effectiveness and rationality, we compare the statistical behaviors and the multifractal behaviors of the simulated data derived from the proposed model with those of the real stock markets. Further, the multiscale sample entropy analysis is employed to study the complexity of the returns, and the cross-sample entropy analysis is applied to measure the degree of asynchrony of return autocorrelation time series. The empirical results indicate that the proposed financial model can simulate and reproduce some significant characteristics of the real stock markets to a certain extent.

Acceleration for 2D time-domain elastic full waveform inversion using a single GPU card

NASA Astrophysics Data System (ADS)

Jiang, Jinpeng; Zhu, Peimin

2018-05-01

Full waveform inversion (FWI) is a challenging procedure due to the high computational cost related to the modeling, especially for the elastic case. The graphics processing unit (GPU) has become a popular device for the high-performance computing (HPC). To reduce the long computation time, we design and implement the GPU-based 2D elastic FWI (EFWI) in time domain using a single GPU card. We parallelize the forward modeling and gradient calculations using the CUDA programming language. To overcome the limitation of relatively small global memory on GPU, the boundary saving strategy is exploited to reconstruct the forward wavefield. Moreover, the L-BFGS optimization method used in the inversion increases the convergence of the misfit function. A multiscale inversion strategy is performed in the workflow to obtain the accurate inversion results. In our tests, the GPU-based implementations using a single GPU device achieve >15 times speedup in forward modeling, and about 12 times speedup in gradient calculation, compared with the eight-core CPU implementations optimized by OpenMP. The test results from the GPU implementations are verified to have enough accuracy by comparing the results obtained from the CPU implementations.

Biophysical Discovery through the Lens of a Computational Microscope

NASA Astrophysics Data System (ADS)

Amaro, Rommie

With exascale computing power on the horizon, improvements in the underlying algorithms and available structural experimental data are enabling new paradigms for chemical discovery. My work has provided key insights for the systematic incorporation of structural information resulting from state-of-the-art biophysical simulations into protocols for inhibitor and drug discovery. We have shown that many disease targets have druggable pockets that are otherwise ``hidden'' in high resolution x-ray structures, and that this is a common theme across a wide range of targets in different disease areas. We continue to push the limits of computational biophysical modeling by expanding the time and length scales accessible to molecular simulation. My sights are set on, ultimately, the development of detailed physical models of cells, as the fundamental unit of life, and two recent achievements highlight our efforts in this arena. First is the development of a molecular and Brownian dynamics multi-scale modeling framework, which allows us to investigate drug binding kinetics in addition to thermodynamics. In parallel, we have made significant progress developing new tools to extend molecular structure to cellular environments. Collectively, these achievements are enabling the investigation of the chemical and biophysical nature of cells at unprecedented scales.

The role of continuity in residual-based variational multiscale modeling of turbulence

NASA Astrophysics Data System (ADS)

Akkerman, I.; Bazilevs, Y.; Calo, V. M.; Hughes, T. J. R.; Hulshoff, S.

2008-02-01

This paper examines the role of continuity of the basis in the computation of turbulent flows. We compare standard finite elements and non-uniform rational B-splines (NURBS) discretizations that are employed in Isogeometric Analysis (Hughes et al. in Comput Methods Appl Mech Eng, 194:4135 4195, 2005). We make use of quadratic discretizations that are C 0-continuous across element boundaries in standard finite elements, and C 1-continuous in the case of NURBS. The variational multiscale residual-based method (Bazilevs in Isogeometric analysis of turbulence and fluid-structure interaction, PhD thesis, ICES, UT Austin, 2006; Bazilevs et al. in Comput Methods Appl Mech Eng, submitted, 2007; Calo in Residual-based multiscale turbulence modeling: finite volume simulation of bypass transition. PhD thesis, Department of Civil and Environmental Engineering, Stanford University, 2004; Hughes et al. in proceedings of the XXI international congress of theoretical and applied mechanics (IUTAM), Kluwer, 2004; Scovazzi in Multiscale methods in science and engineering, PhD thesis, Department of Mechanical Engineering, Stanford Universty, 2004) is employed as a turbulence modeling technique. We find that C 1-continuous discretizations outperform their C 0-continuous counterparts on a per-degree-of-freedom basis. We also find that the effect of continuity is greater for higher Reynolds number flows.

Contour Tracking in Echocardiographic Sequences via Sparse Representation and Dictionary Learning

PubMed Central

Huang, Xiaojie; Dione, Donald P.; Compas, Colin B.; Papademetris, Xenophon; Lin, Ben A.; Bregasi, Alda; Sinusas, Albert J.; Staib, Lawrence H.; Duncan, James S.

2013-01-01

This paper presents a dynamical appearance model based on sparse representation and dictionary learning for tracking both endocardial and epicardial contours of the left ventricle in echocardiographic sequences. Instead of learning offline spatiotemporal priors from databases, we exploit the inherent spatiotemporal coherence of individual data to constraint cardiac contour estimation. The contour tracker is initialized with a manual tracing of the first frame. It employs multiscale sparse representation of local image appearance and learns online multiscale appearance dictionaries in a boosting framework as the image sequence is segmented frame-by-frame sequentially. The weights of multiscale appearance dictionaries are optimized automatically. Our region-based level set segmentation integrates a spectrum of complementary multilevel information including intensity, multiscale local appearance, and dynamical shape prediction. The approach is validated on twenty-six 4D canine echocardiographic images acquired from both healthy and post-infarct canines. The segmentation results agree well with expert manual tracings. The ejection fraction estimates also show good agreement with manual results. Advantages of our approach are demonstrated by comparisons with a conventional pure intensity model, a registration-based contour tracker, and a state-of-the-art database-dependent offline dynamical shape model. We also demonstrate the feasibility of clinical application by applying the method to four 4D human data sets. PMID:24292554

Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata.

PubMed

Leempoel, Kevin; Parisod, Christian; Geiser, Céline; Joost, Stéphane

2018-02-01

Plant species are known to adapt locally to their environment, particularly in mountainous areas where conditions can vary drastically over short distances. The climate of such landscapes being largely influenced by topography, using fine-scale models to evaluate environmental heterogeneity may help detecting adaptation to micro-habitats. Here, we applied a multiscale landscape genomic approach to detect evidence of local adaptation in the alpine plant Biscutella laevigata . The two gene pools identified, experiencing limited gene flow along a 1-km ridge, were different in regard to several habitat features derived from a very high resolution (VHR) digital elevation model (DEM). A correlative approach detected signatures of selection along environmental gradients such as altitude, wind exposure, and solar radiation, indicating adaptive pressures likely driven by fine-scale topography. Using a large panel of DEM-derived variables as ecologically relevant proxies, our results highlighted the critical role of spatial resolution. These high-resolution multiscale variables indeed indicate that the robustness of associations between genetic loci and environmental features depends on spatial parameters that are poorly documented. We argue that the scale issue is critical in landscape genomics and that multiscale ecological variables are key to improve our understanding of local adaptation in highly heterogeneous landscapes.

Multiscale Analysis of Delamination of Carbon Fiber-Epoxy Laminates with Carbon Nanotubes

NASA Technical Reports Server (NTRS)

Riddick, Jaret C.; Frankland, SJV; Gates, TS

2006-01-01

A multi-scale analysis is presented to parametrically describe the Mode I delamination of a carbon fiber/epoxy laminate. In the midplane of the laminate, carbon nanotubes are included for the purposes of selectively enhancing the fracture toughness of the laminate. To analyze carbon fiber epoxy carbon nanotube laminate, the multi-scale methodology presented here links a series of parameterizations taken at various length scales ranging from the atomistic through the micromechanical to the structural level. At the atomistic scale molecular dynamics simulations are performed in conjunction with an equivalent continuum approach to develop constitutive properties for representative volume elements of the molecular structure of components of the laminate. The molecular-level constitutive results are then used in the Mori-Tanaka micromechanics to develop bulk properties for the epoxy-carbon nanotube matrix system. In order to demonstrate a possible application of this multi-scale methodology, a double cantilever beam specimen is modeled. An existing analysis is employed which uses discrete springs to model the fiber bridging affect during delamination propagation. In the absence of empirical data or a damage mechanics model describing the effect of CNTs on fracture toughness, several tractions laws are postulated, linking CNT volume fraction to fiber bridging in a DCB specimen. Results from this demonstration are presented in terms of DCB specimen load-displacement responses.

Multiscale Feature Analysis of Salivary Gland Branching Morphogenesis

PubMed Central

Baydil, Banu; Daley, William P.; Larsen, Melinda; Yener, Bülent

2012-01-01

Pattern formation in developing tissues involves dynamic spatio-temporal changes in cellular organization and subsequent evolution of functional adult structures. Branching morphogenesis is a developmental mechanism by which patterns are generated in many developing organs, which is controlled by underlying molecular pathways. Understanding the relationship between molecular signaling, cellular behavior and resulting morphological change requires quantification and categorization of the cellular behavior. In this study, tissue-level and cellular changes in developing salivary gland in response to disruption of ROCK-mediated signaling by are modeled by building cell-graphs to compute mathematical features capturing structural properties at multiple scales. These features were used to generate multiscale cell-graph signatures of untreated and ROCK signaling disrupted salivary gland organ explants. From confocal images of mouse submandibular salivary gland organ explants in which epithelial and mesenchymal nuclei were marked, a multiscale feature set capturing global structural properties, local structural properties, spectral, and morphological properties of the tissues was derived. Six feature selection algorithms and multiway modeling of the data was performed to identify distinct subsets of cell graph features that can uniquely classify and differentiate between different cell populations. Multiscale cell-graph analysis was most effective in classification of the tissue state. Cellular and tissue organization, as defined by a multiscale subset of cell-graph features, are both quantitatively distinct in epithelial and mesenchymal cell types both in the presence and absence of ROCK inhibitors. Whereas tensor analysis demonstrate that epithelial tissue was affected the most by inhibition of ROCK signaling, significant multiscale changes in mesenchymal tissue organization were identified with this analysis that were not identified in previous biological studies. We here show how to define and calculate a multiscale feature set as an effective computational approach to identify and quantify changes at multiple biological scales and to distinguish between different states in developing tissues. PMID:22403724

A novel method of multi-scale simulation of macro-scale deformation and microstructure evolution on metal forming

NASA Astrophysics Data System (ADS)

Huang, Shiquan; Yi, Youping; Li, Pengchuan

2011-05-01

In recent years, multi-scale simulation technique of metal forming is gaining significant attention for prediction of the whole deformation process and microstructure evolution of product. The advances of numerical simulation at macro-scale level on metal forming are remarkable and the commercial FEM software, such as Deform2D/3D, has found a wide application in the fields of metal forming. However, the simulation method of multi-scale has little application due to the non-linearity of microstructure evolution during forming and the difficulty of modeling at the micro-scale level. This work deals with the modeling of microstructure evolution and a new method of multi-scale simulation in forging process. The aviation material 7050 aluminum alloy has been used as example for modeling of microstructure evolution. The corresponding thermal simulated experiment has been performed on Gleeble 1500 machine. The tested specimens have been analyzed for modeling of dislocation density, nucleation and growth of recrystallization(DRX). The source program using cellular automaton (CA) method has been developed to simulate the grain nucleation and growth, in which the change of grain topology structure caused by the metal deformation was considered. The physical fields at macro-scale level such as temperature field, stress and strain fields, which can be obtained by commercial software Deform 3D, are coupled with the deformed storage energy at micro-scale level by dislocation model to realize the multi-scale simulation. This method was explained by forging process simulation of the aircraft wheel hub forging. Coupled the results of Deform 3D with CA results, the forging deformation progress and the microstructure evolution at any point of forging could be simulated. For verifying the efficiency of simulation, experiments of aircraft wheel hub forging have been done in the laboratory and the comparison of simulation and experiment result has been discussed in details.

Multi-scale Modeling of the Cardiovascular System: Disease Development, Progression, and Clinical Intervention.

PubMed

Zhang, Yanhang; Barocas, Victor H; Berceli, Scott A; Clancy, Colleen E; Eckmann, David M; Garbey, Marc; Kassab, Ghassan S; Lochner, Donna R; McCulloch, Andrew D; Tran-Son-Tay, Roger; Trayanova, Natalia A

2016-09-01

Cardiovascular diseases (CVDs) are the leading cause of death in the western world. With the current development of clinical diagnostics to more accurately measure the extent and specifics of CVDs, a laudable goal is a better understanding of the structure-function relation in the cardiovascular system. Much of this fundamental understanding comes from the development and study of models that integrate biology, medicine, imaging, and biomechanics. Information from these models provides guidance for developing diagnostics, and implementation of these diagnostics to the clinical setting, in turn, provides data for refining the models. In this review, we introduce multi-scale and multi-physical models for understanding disease development, progression, and designing clinical interventions. We begin with multi-scale models of cardiac electrophysiology and mechanics for diagnosis, clinical decision support, personalized and precision medicine in cardiology with examples in arrhythmia and heart failure. We then introduce computational models of vasculature mechanics and associated mechanical forces for understanding vascular disease progression, designing clinical interventions, and elucidating mechanisms that underlie diverse vascular conditions. We conclude with a discussion of barriers that must be overcome to provide enhanced insights, predictions, and decisions in pre-clinical and clinical applications.

Multi-scale Modeling of the Cardiovascular System: Disease Development, Progression, and Clinical Intervention

PubMed Central

Zhang, Yanhang; Barocas, Victor H.; Berceli, Scott A.; Clancy, Colleen E.; Eckmann, David M.; Garbey, Marc; Kassab, Ghassan S.; Lochner, Donna R.; McCulloch, Andrew D.; Tran-Son-Tay, Roger; Trayanova, Natalia A.

2016-01-01

Cardiovascular diseases (CVDs) are the leading cause of death in the western world. With the current development of clinical diagnostics to more accurately measure the extent and specifics of CVDs, a laudable goal is a better understanding of the structure-function relation in the cardiovascular system. Much of this fundamental understanding comes from the development and study of models that integrate biology, medicine, imaging, and biomechanics. Information from these models provides guidance for developing diagnostics, and implementation of these diagnostics to the clinical setting, in turn, provides data for refining the models. In this review, we introduce multi-scale and multi-physical models for understanding disease development, progression, and designing clinical interventions. We begin with multi-scale models of cardiac electrophysiology and mechanics for diagnosis, clinical decision support, personalized and precision medicine in cardiology with examples in arrhythmia and heart failure. We then introduce computational models of vasculature mechanics and associated mechanical forces for understanding vascular disease progression, designing clinical interventions, and elucidating mechanisms that underlie diverse vascular conditions. We conclude with a discussion of barriers that must be overcome to provide enhanced insights, predictions, and decisions in pre-clinical and clinical applications. PMID:27138523

Heat Source Characterization In A TREAT Fuel Particle Using Coupled Neutronics Binary Collision Monte-Carlo Calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schunert, Sebastian; Schwen, Daniel; Ghassemi, Pedram

This work presents a multi-physics, multi-scale approach to modeling the Transient Test Reactor (TREAT) currently prepared for restart at the Idaho National Laboratory. TREAT fuel is made up of microscopic fuel grains (r ˜ 20µm) dispersed in a graphite matrix. The novelty of this work is in coupling a binary collision Monte-Carlo (BCMC) model to the Finite Element based code Moose for solving a microsopic heat-conduction problem whose driving source is provided by the BCMC model tracking fission fragment energy deposition. This microscopic model is driven by a transient, engineering scale neutronics model coupled to an adiabatic heating model. Themore » macroscopic model provides local power densities and neutron energy spectra to the microscpic model. Currently, no feedback from the microscopic to the macroscopic model is considered. TREAT transient 15 is used to exemplify the capabilities of the multi-physics, multi-scale model, and it is found that the average fuel grain temperature differs from the average graphite temperature by 80 K despite the low-power transient. The large temperature difference has strong implications on the Doppler feedback a potential LEU TREAT core would see, and it underpins the need for multi-physics, multi-scale modeling of a TREAT LEU core.« less

Multi-scale simulations of space problems with iPIC3D

NASA Astrophysics Data System (ADS)

Lapenta, Giovanni; Bettarini, Lapo; Markidis, Stefano

The implicit Particle-in-Cell method for the computer simulation of space plasma, and its im-plementation in a three-dimensional parallel code, called iPIC3D, are presented. The implicit integration in time of the Vlasov-Maxwell system removes the numerical stability constraints and enables kinetic plasma simulations at magnetohydrodynamics scales. Simulations of mag-netic reconnection in plasma are presented to show the effectiveness of the algorithm. In particular we will show a number of simulations done for large scale 3D systems using the physical mass ratio for Hydrogen. Most notably one simulation treats kinetically a box of tens of Earth radii in each direction and was conducted using about 16000 processors of the Pleiades NASA computer. The work is conducted in collaboration with the MMS-IDS theory team from University of Colorado (M. Goldman, D. Newman and L. Andersson). Reference: Stefano Markidis, Giovanni Lapenta, Rizwan-uddin Multi-scale simulations of plasma with iPIC3D Mathematics and Computers in Simulation, Available online 17 October 2009, http://dx.doi.org/10.1016/j.matcom.2009.08.038

Physics-based multiscale coupling for full core nuclear reactor simulation

DOE PAGES

Gaston, Derek R.; Permann, Cody J.; Peterson, John W.; ...

2015-10-01

Numerical simulation of nuclear reactors is a key technology in the quest for improvements in efficiency, safety, and reliability of both existing and future reactor designs. Historically, simulation of an entire reactor was accomplished by linking together multiple existing codes that each simulated a subset of the relevant multiphysics phenomena. Recent advances in the MOOSE (Multiphysics Object Oriented Simulation Environment) framework have enabled a new approach: multiple domain-specific applications, all built on the same software framework, are efficiently linked to create a cohesive application. This is accomplished with a flexible coupling capability that allows for a variety of different datamore » exchanges to occur simultaneously on high performance parallel computational hardware. Examples based on the KAIST-3A benchmark core, as well as a simplified Westinghouse AP-1000 configuration, demonstrate the power of this new framework for tackling—in a coupled, multiscale manner—crucial reactor phenomena such as CRUD-induced power shift and fuel shuffle. 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-SA license« less

Structural setting and kinematics of Nubian fault system, SE Western Desert, Egypt: An example of multi-reactivated intraplate strike-slip faults

NASA Astrophysics Data System (ADS)

Sakran, Shawky; Said, Said Mohamed

2018-02-01

Detailed surface geological mapping and subsurface seismic interpretation have been integrated to unravel the structural style and kinematic history of the Nubian Fault System (NFS). The NFS consists of several E-W Principal Deformation Zones (PDZs) (e.g. Kalabsha fault). Each PDZ is defined by spectacular E-W, WNW and ENE dextral strike-slip faults, NNE sinistral strike-slip faults, NE to ENE folds, and NNW normal faults. Each fault zone has typical self-similar strike-slip architecture comprising multi-scale fault segments. Several multi-scale uplifts and basins were developed at the step-over zones between parallel strike-slip fault segments as a result of local extension or contraction. The NNE faults consist of right-stepping sinistral strike-slip fault segments (e.g. Sin El Kiddab fault). The NNE sinistral faults extend for long distances ranging from 30 to 100 kms and cut one or two E-W PDZs. Two nearly perpendicular strike-slip tectonic regimes are recognized in the NFS; an inactive E-W Late Cretaceous - Early Cenozoic dextral transpression and an active NNE sinistral shear.

Multi-scale modelling of elastic moduli of trabecular bone

PubMed Central

Hamed, Elham; Jasiuk, Iwona; Yoo, Andrew; Lee, YikHan; Liszka, Tadeusz

2012-01-01

We model trabecular bone as a nanocomposite material with hierarchical structure and predict its elastic properties at different structural scales. The analysis involves a bottom-up multi-scale approach, starting with nanoscale (mineralized collagen fibril) and moving up the scales to sub-microscale (single lamella), microscale (single trabecula) and mesoscale (trabecular bone) levels. Continuum micromechanics methods, composite materials laminate theory and finite-element methods are used in the analysis. Good agreement is found between theoretical and experimental results. PMID:22279160

Asymptotic-Preserving methods and multiscale models for plasma physics

NASA Astrophysics Data System (ADS)

Degond, Pierre; Deluzet, Fabrice

2017-05-01

The purpose of the present paper is to provide an overview of Asymptotic-Preserving methods for multiscale plasma simulations by addressing three singular perturbation problems. First, the quasi-neutral limit of fluid and kinetic models is investigated in the framework of non-magnetized as well as magnetized plasmas. Second, the drift limit for fluid descriptions of thermal plasmas under large magnetic fields is addressed. Finally efficient numerical resolutions of anisotropic elliptic or diffusion equations arising in magnetized plasma simulation are reviewed.

Relative entropy as a universal metric for multiscale errors

NASA Astrophysics Data System (ADS)

Chaimovich, Aviel; Shell, M. Scott

2010-06-01

We show that the relative entropy, Srel , suggests a fundamental indicator of the success of multiscale studies, in which coarse-grained (CG) models are linked to first-principles (FP) ones. We demonstrate that Srel inherently measures fluctuations in the differences between CG and FP potential energy landscapes, and develop a theory that tightly and generally links it to errors associated with coarse graining. We consider two simple case studies substantiating these results, and suggest that Srel has important ramifications for evaluating and designing coarse-grained models.

Relative entropy as a universal metric for multiscale errors.

PubMed

Chaimovich, Aviel; Shell, M Scott

2010-06-01

We show that the relative entropy, Srel, suggests a fundamental indicator of the success of multiscale studies, in which coarse-grained (CG) models are linked to first-principles (FP) ones. We demonstrate that Srel inherently measures fluctuations in the differences between CG and FP potential energy landscapes, and develop a theory that tightly and generally links it to errors associated with coarse graining. We consider two simple case studies substantiating these results, and suggest that Srel has important ramifications for evaluating and designing coarse-grained models.

The Discontinuous Galerkin Method for the Multiscale Modeling of Dynamics of Crystalline Solids

DTIC Science & Technology

2007-08-26

number. 1. REPORT DATE 26 AUG 2007 2 . REPORT TYPE 3. DATES COVERED 00-00-2007 to 00-00-2007 4. TITLE AND SUBTITLE The Discontinuous Galerkin...Dynamics method (MAAD) [ 2 ], the bridging scale method [47], the bridging domain methods [48], the heterogeneous multiscale method (HMM) [23, 36, 24], and...method consists of three components, 1. a macro solver for the continuum model, 2 . a micro solver to equilibrate the atomistic system locally to the appro

Composite annotations: requirements for mapping multiscale data and models to biomedical ontologies

PubMed Central

Cook, Daniel L.; Mejino, Jose L. V.; Neal, Maxwell L.; Gennari, John H.

2009-01-01

Current methods for annotating biomedical data resources rely on simple mappings between data elements and the contents of a variety of biomedical ontologies and controlled vocabularies. Here we point out that such simple mappings are inadequate for large-scale multiscale, multidomain integrative “virtual human” projects. For such integrative challenges, we describe a “composite annotation” schema that is simple yet sufficiently extensible for mapping the biomedical content of a variety of data sources and biosimulation models to available biomedical ontologies. PMID:19964601

Hybrid codes with finite electron mass

NASA Astrophysics Data System (ADS)

Lipatov, A. S.

This report is devoted to the current status of the hybrid multiscale simulation technique. The different aspects of modeling are discussed. In particular, we consider the different level for description of the plasma model, however, the main attention will be paid to conventional hybrid models. We discuss the main steps of time integration the Vlasov/Maxwell system of equations. The main attention will be paid to the models with finite electron mass. Such model may allow us to explore the plasma system with multiscale phenomena ranging from ion to electron scales. As an application of hybrid modeling technique we consider the simulation of the plasma processes at the collisionless shocks and very shortly ther magnetic field reconnection processes.

Multiscale Persistent Functions for Biomolecular Structure Characterization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xia, Kelin; Li, Zhiming; Mu, Lin

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 resolutionmore » 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 time, to describe the “regularity” of protein structures. Basically, a protein structure is deemed as regular if it has a consistent and orderly configuration. Our PSI model is tested on a database of 110 proteins; we find that structures with larger portions of loops and intrinsically disorder regions are always associated with larger PSI, meaning an irregular configuration, while proteins with larger portions of secondary structures, i.e., alpha-helix or beta-sheet, have smaller PSI. Essentially, PSI can be used to describe the “regularity” information in any systems.« less

Based on a multi-agent system for multi-scale simulation and application of household's LUCC: a case study for Mengcha village, Mizhi county, Shaanxi province.

PubMed

Chen, Hai; Liang, Xiaoying; Li, Rui

2013-01-01

Multi-Agent Systems (MAS) offer a conceptual approach to include multi-actor decision making into models of land use change. Through the simulation based on the MAS, this paper tries to show the application of MAS in the micro scale LUCC, and reveal the transformation mechanism of difference scale. This paper starts with a description of the context of MAS research. Then, it adopts the Nested Spatial Choice (NSC) method to construct the multi-scale LUCC decision-making model. And a case study for Mengcha village, Mizhi County, Shaanxi Province is reported. Finally, the potentials and drawbacks of the following approach is discussed and concluded. From our design and implementation of the MAS in multi-scale model, a number of observations and conclusions can be drawn on the implementation and future research directions. (1) The use of the LUCC decision-making and multi-scale transformation framework provides, according to us, a more realistic modeling of multi-scale decision making process. (2) By using continuous function, rather than discrete function, to construct the decision-making of the households is more realistic to reflect the effect. (3) In this paper, attempts have been made to give a quantitative analysis to research the household interaction. And it provides the premise and foundation for researching the communication and learning among the households. (4) The scale transformation architecture constructed in this paper helps to accumulate theory and experience for the interaction research between the micro land use decision-making and the macro land use landscape pattern. Our future research work will focus on: (1) how to rational use risk aversion principle, and put the rule on rotation between household parcels into model. (2) Exploring the methods aiming at researching the household decision-making over a long period, it allows us to find the bridge between the long-term LUCC data and the short-term household decision-making. (3) Researching the quantitative method and model, especially the scenario analysis model which may reflect the interaction among different household types.

An Unified Multiscale Framework for Planar, Surface, and Curve Skeletonization.

PubMed

Jalba, Andrei C; Sobiecki, Andre; Telea, Alexandru C

2016-01-01

Computing skeletons of 2D shapes, and medial surface and curve skeletons of 3D shapes, is a challenging task. In particular, there is no unified framework that detects all types of skeletons using a single model, and also produces a multiscale representation which allows to progressively simplify, or regularize, all skeleton types. In this paper, we present such a framework. We model skeleton detection and regularization by a conservative mass transport process from a shape's boundary to its surface skeleton, next to its curve skeleton, and finally to the shape center. The resulting density field can be thresholded to obtain a multiscale representation of progressively simplified surface, or curve, skeletons. We detail a numerical implementation of our framework which is demonstrably stable and has high computational efficiency. We demonstrate our framework on several complex 2D and 3D shapes.

Biological materials by design.

PubMed

Qin, Zhao; Dimas, Leon; Adler, David; Bratzel, Graham; Buehler, Markus J

2014-02-19

In this topical review we discuss recent advances in the use of physical insight into the way biological materials function, to design novel engineered materials 'from scratch', or from the level of fundamental building blocks upwards and by using computational multiscale methods that link chemistry to material function. We present studies that connect advances in multiscale hierarchical material structuring with material synthesis and testing, review case studies of wood and other biological materials, and illustrate how engineered fiber composites and bulk materials are designed, modeled, and then synthesized and tested experimentally. The integration of experiment and simulation in multiscale design opens new avenues to explore the physics of materials from a fundamental perspective, and using complementary strengths from models and empirical techniques. Recent developments in this field illustrate a new paradigm by which complex material functionality is achieved through hierarchical structuring in spite of simple material constituents.

Differential geometry based solvation model. III. Quantum formulation

PubMed Central

Chen, Zhan; Wei, Guo-Wei

2011-01-01

Solvation is of fundamental importance to biomolecular systems. Implicit solvent models, particularly those based on the Poisson-Boltzmann equation for electrostatic analysis, are established approaches for solvation analysis. However, ad hoc solvent-solute interfaces are commonly used in the implicit solvent theory. Recently, we have introduced differential geometry based solvation models which allow the solvent-solute interface to be determined by the variation of a total free energy functional. Atomic fixed partial charges (point charges) are used in our earlier models, which depends on existing molecular mechanical force field software packages for partial charge assignments. As most force field models are parameterized for a certain class of molecules or materials, the use of partial charges limits the accuracy and applicability of our earlier models. Moreover, fixed partial charges do not account for the charge rearrangement during the solvation process. The present work proposes a differential geometry based multiscale solvation model which makes use of the electron density computed directly from the quantum mechanical principle. To this end, we construct a new multiscale total energy functional which consists of not only polar and nonpolar solvation contributions, but also the electronic kinetic and potential energies. By using the Euler-Lagrange variation, we derive a system of three coupled governing equations, i.e., the generalized Poisson-Boltzmann equation for the electrostatic potential, the generalized Laplace-Beltrami equation for the solvent-solute boundary, and the Kohn-Sham equations for the electronic structure. We develop an iterative procedure to solve three coupled equations and to minimize the solvation free energy. The present multiscale model is numerically validated for its stability, consistency and accuracy, and is applied to a few sets of molecules, including a case which is difficult for existing solvation models. Comparison is made to many other classic and quantum models. By using experimental data, we show that the present quantum formulation of our differential geometry based multiscale solvation model improves the prediction of our earlier models, and outperforms some explicit solvation model. PMID:22112067

Multi-scale lung modeling.

PubMed

Tawhai, Merryn H; Bates, Jason H T

2011-05-01

Multi-scale modeling of biological systems has recently become fashionable due to the growing power of digital computers as well as to the growing realization that integrative systems behavior is as important to life as is the genome. While it is true that the behavior of a living organism must ultimately be traceable to all its components and their myriad interactions, attempting to codify this in its entirety in a model misses the insights gained from understanding how collections of system components at one level of scale conspire to produce qualitatively different behavior at higher levels. The essence of multi-scale modeling thus lies not in the inclusion of every conceivable biological detail, but rather in the judicious selection of emergent phenomena appropriate to the level of scale being modeled. These principles are exemplified in recent computational models of the lung. Airways responsiveness, for example, is an organ-level manifestation of events that begin at the molecular level within airway smooth muscle cells, yet it is not necessary to invoke all these molecular events to accurately describe the contraction dynamics of a cell, nor is it necessary to invoke all phenomena observable at the level of the cell to account for the changes in overall lung function that occur following methacholine challenge. Similarly, the regulation of pulmonary vascular tone has complex origins within the individual smooth muscle cells that line the blood vessels but, again, many of the fine details of cell behavior average out at the level of the organ to produce an effect on pulmonary vascular pressure that can be described in much simpler terms. The art of multi-scale lung modeling thus reduces not to being limitlessly inclusive, but rather to knowing what biological details to leave out.

Multiscale Particle-Based Modeling of Flowing Platelets in Blood Plasma Using Dissipative Particle Dynamics and Coarse Grained Molecular Dynamics

PubMed Central

Zhang, Peng; Gao, Chao; Zhang, Na; Slepian, Marvin J.; Deng, Yuefan; Bluestein, Danny

2014-01-01

We developed a multiscale particle-based model of platelets, to study the transport dynamics of shear stresses between the surrounding fluid and the platelet membrane. This model facilitates a more accurate prediction of the activation potential of platelets by viscous shear stresses - one of the major mechanisms leading to thrombus formation in cardiovascular diseases and in prosthetic cardiovascular devices. The interface of the model couples coarse-grained molecular dynamics (CGMD) with dissipative particle dynamics (DPD). The CGMD handles individual platelets while the DPD models the macroscopic transport of blood plasma in vessels. A hybrid force field is formulated for establishing a functional interface between the platelet membrane and the surrounding fluid, in which the microstructural changes of platelets may respond to the extracellular viscous shear stresses transferred to them. The interaction between the two systems preserves dynamic properties of the flowing platelets, such as the flipping motion. Using this multiscale particle-based approach, we have further studied the effects of the platelet elastic modulus by comparing the action of the flow-induced shear stresses on rigid and deformable platelet models. The results indicate that neglecting the platelet deformability may overestimate the stress on the platelet membrane, which in turn may lead to erroneous predictions of the platelet activation under viscous shear flow conditions. This particle-based fluid-structure interaction multiscale model offers for the first time a computationally feasible approach for simulating deformable platelets interacting with viscous blood flow, aimed at predicting flow induced platelet activation by using a highly resolved mapping of the stress distribution on the platelet membrane under dynamic flow conditions. PMID:25530818

Active learning of constitutive relation from mesoscopic dynamics for macroscopic modeling of non-Newtonian flows

NASA Astrophysics Data System (ADS)

Zhao, Lifei; Li, Zhen; Caswell, Bruce; Ouyang, Jie; Karniadakis, George Em

2018-06-01

We simulate complex fluids by means of an on-the-fly coupling of the bulk rheology to the underlying microstructure dynamics. In particular, a continuum model of polymeric fluids is constructed without a pre-specified constitutive relation, but instead it is actively learned from mesoscopic simulations where the dynamics of polymer chains is explicitly computed. To couple the bulk rheology of polymeric fluids and the microscale dynamics of polymer chains, the continuum approach (based on the finite volume method) provides the transient flow field as inputs for the (mesoscopic) dissipative particle dynamics (DPD), and in turn DPD returns an effective constitutive relation to close the continuum equations. In this multiscale modeling procedure, we employ an active learning strategy based on Gaussian process regression (GPR) to minimize the number of expensive DPD simulations, where adaptively selected DPD simulations are performed only as necessary. Numerical experiments are carried out for flow past a circular cylinder of a non-Newtonian fluid, modeled at the mesoscopic level by bead-spring chains. The results show that only five DPD simulations are required to achieve an effective closure of the continuum equations at Reynolds number Re = 10. Furthermore, when Re is increased to 100, only one additional DPD simulation is required for constructing an extended GPR-informed model closure. Compared to traditional message-passing multiscale approaches, applying an active learning scheme to multiscale modeling of non-Newtonian fluids can significantly increase the computational efficiency. Although the method demonstrated here obtains only a local viscosity from the polymer dynamics, it can be extended to other multiscale models of complex fluids whose macro-rheology is unknown.

American Society of Composites, 32nd Technical Conference

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aitharaju, Venkat; Wollschlager, Jeffrey; Plakomytis2, Dimitrios

This paper will present a general methodology by which weave draping manufacturing simulation results can be utilized to include the effects of weave draping and scissor angle in a structural multiscale simulation. While the methodology developed is general in nature, this paper will specifically demonstrate the methodology applied to a truncated pyramid, utilizing manufacturing simulation weave draping results from ESI PAM-FORM, and multiscale simulation using Altair Multiscale Designer (MDS) and OptiStruct. From a multiscale simulation perspective, the weave draping manufacturing simulation results will be used to develop a series of woven unit cells which cover the range of weave scissormore » angles existing within the part. For each unit cell, a multiscale material model will be developed, and applied to the corresponding spatial locations within the structural simulation mesh. In addition, the principal material orientation will be mapped from the wave draping manufacturing simulation mesh to the structural simulation mesh using Altair HyperMesh mapping technology. Results of the coupled simulation will be compared and verified against experimental data of the same available via General Motors (GM) Department of Energy (DOE) project.« less

Research Advances on Radiation Transfer Modeling and Inversion for Multi-Scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.

2011-09-01

At first, research advances on radiation transfer modeling on multi-scale remote sensing data are presented: after a general overview of remote sensing radiation transfer modeling, several recent research advances are presented, including leaf spectrum model (dPROS-PECT), vegetation canopy BRDF models, directional thermal infrared emission models(TRGM, SLEC), rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed. The land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation etc. are taken as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is designed and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China will be introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

Multiscale model within-host and between-host for viral infectious diseases.

PubMed

Almocera, Alexis Erich S; Nguyen, Van Kinh; Hernandez-Vargas, Esteban A

2018-05-08

Multiscale models possess the potential to uncover new insights into infectious diseases. Here, a rigorous stability analysis of a multiscale model within-host and between-host is presented. The within-host model describes viral replication and the respective immune response while disease transmission is represented by a susceptible-infected model. The bridging of scales from within- to between-host considered transmission as a function of the viral load. Consequently, stability and bifurcation analyses were developed coupling the two basic reproduction numbers [Formula: see text] and [Formula: see text] for the within- and the between-host subsystems, respectively. Local stability results for each subsystem, including a unique stable equilibrium point, recapitulate classical approaches to infection and epidemic control. Using a Lyapunov function, global stability of the between-host system was obtained. Our main result was the derivation of the [Formula: see text] as an increasing function of [Formula: see text]. Numerical analyses reveal that a Michaelis-Menten form based on the virus is more likely to recapitulate the behavior between the scales than a form directly proportional to the virus. Our work contributes basic understandings of the two models and casts light on the potential effects of the coupling function on linking the two scales.

GPU based framework for geospatial analyses

NASA Astrophysics Data System (ADS)

Cosmin Sandric, Ionut; Ionita, Cristian; Dardala, Marian; Furtuna, Titus

2017-04-01

Parallel processing on multiple CPU cores is already used at large scale in geocomputing, but parallel processing on graphics cards is just at the beginning. Being able to use an simple laptop with a dedicated graphics card for advanced and very fast geocomputation is an advantage that each scientist wants to have. The necessity to have high speed computation in geosciences has increased in the last 10 years, mostly due to the increase in the available datasets. These datasets are becoming more and more detailed and hence they require more space to store and more time to process. Distributed computation on multicore CPU's and GPU's plays an important role by processing one by one small parts from these big datasets. These way of computations allows to speed up the process, because instead of using just one process for each dataset, the user can use all the cores from a CPU or up to hundreds of cores from GPU The framework provide to the end user a standalone tools for morphometry analyses at multiscale level. An important part of the framework is dedicated to uncertainty propagation in geospatial analyses. The uncertainty may come from the data collection or may be induced by the model or may have an infinite sources. These uncertainties plays important roles when a spatial delineation of the phenomena is modelled. Uncertainty propagation is implemented inside the GPU framework using Monte Carlo simulations. The GPU framework with the standalone tools proved to be a reliable tool for modelling complex natural phenomena The framework is based on NVidia Cuda technology and is written in C++ programming language. The code source will be available on github at https://github.com/sandricionut/GeoRsGPU Acknowledgement: GPU framework for geospatial analysis, Young Researchers Grant (ICUB-University of Bucharest) 2016, director Ionut Sandric

Multiscale modelling of hydraulic conductivity in vuggy porous media

PubMed Central

Daly, K. R.; Roose, T.

2014-01-01

Flow in both saturated and non-saturated vuggy porous media, i.e. soil, is inherently multiscale. The complex microporous structure of the soil aggregates and the wider vugs provides a multitude of flow pathways and has received significant attention from the X-ray computed tomography (CT) community with a constant drive to image at higher resolution. Using multiscale homogenization, we derive averaged equations to study the effects of the microscale structure on the macroscopic flow. The averaged model captures the underlying geometry through a series of cell problems and is verified through direct comparison to numerical simulations of the full structure. These methods offer significant reductions in computation time and allow us to perform three-dimensional calculations with complex geometries on a desktop PC. The results show that the surface roughness of the aggregate has a significantly greater effect on the flow than the microstructure within the aggregate. Hence, this is the region in which the resolution of X-ray CT for image-based modelling has the greatest impact. PMID:24511248

Multiscale modeling for SiO2 atomic layer deposition for high-aspect-ratio hole patterns

NASA Astrophysics Data System (ADS)

Miyano, Yumiko; Narasaki, Ryota; Ichikawa, Takashi; Fukumoto, Atsushi; Aiso, Fumiki; Tamaoki, Naoki

2018-06-01

A multiscale simulation model is developed for optimizing the parameters of SiO2 plasma-enhanced atomic layer deposition of high-aspect-ratio hole patterns in three-dimensional (3D) stacked memory. This model takes into account the diffusion of a precursor in a reactor, that in holes, and the adsorption onto the wafer. It is found that the change in the aperture ratio of the holes on the wafer affects the concentration of the precursor near the top of the wafer surface, hence the deposition profile in the hole. The simulation results reproduced well the experimental results of the deposition thickness for the various hole aperture ratios. By this multiscale simulation, we can predict the deposition profile in a high-aspect-ratio hole pattern in 3D stacked memory. The atomic layer deposition parameters for conformal deposition such as precursor feeding time and partial pressure of precursor for wafers with various hole aperture ratios can be estimated.

Percolation properties of 3-D multiscale pore networks: how connectivity controls soil filtration processes

NASA Astrophysics Data System (ADS)

Perrier, E. M. A.; Bird, N. R. A.; Rieutord, T. B.

2010-04-01

Quantifying the connectivity of pore networks is a key issue not only for modelling fluid flow and solute transport in porous media but also for assessing the ability of soil ecosystems to filter bacteria, viruses and any type of living microorganisms as well inert particles which pose a contamination risk. Straining is the main mechanical component of filtration processes: it is due to size effects, when a given soil retains a conveyed entity larger than the pores through which it is attempting to pass. We postulate that the range of sizes of entities which can be trapped inside soils has to be associated with the large range of scales involved in natural soil structures and that information on the pore size distribution has to be complemented by information on a Critical Filtration Size (CFS) delimiting the transition between percolating and non percolating regimes in multiscale pore networks. We show that the mass fractal dimensions which are classically used in soil science to quantify scaling laws in observed pore size distributions can also be used to build 3-D multiscale models of pore networks exhibiting such a critical transition. We extend to the 3-D case a new theoretical approach recently developed to address the connectivity of 2-D fractal networks (Bird and Perrier, 2009). Theoretical arguments based on renormalisation functions provide insight into multi-scale connectivity and a first estimation of CFS. Numerical experiments on 3-D prefractal media confirm the qualitative theory. These results open the way towards a new methodology to estimate soil filtration efficiency from the construction of soil structural models to be calibrated on available multiscale data.

Percolation properties of 3-D multiscale pore networks: how connectivity controls soil filtration processes

NASA Astrophysics Data System (ADS)

Perrier, E. M. A.; Bird, N. R. A.; Rieutord, T. B.

2010-10-01

Quantifying the connectivity of pore networks is a key issue not only for modelling fluid flow and solute transport in porous media but also for assessing the ability of soil ecosystems to filter bacteria, viruses and any type of living microorganisms as well inert particles which pose a contamination risk. Straining is the main mechanical component of filtration processes: it is due to size effects, when a given soil retains a conveyed entity larger than the pores through which it is attempting to pass. We postulate that the range of sizes of entities which can be trapped inside soils has to be associated with the large range of scales involved in natural soil structures and that information on the pore size distribution has to be complemented by information on a critical filtration size (CFS) delimiting the transition between percolating and non percolating regimes in multiscale pore networks. We show that the mass fractal dimensions which are classically used in soil science to quantify scaling laws in observed pore size distributions can also be used to build 3-D multiscale models of pore networks exhibiting such a critical transition. We extend to the 3-D case a new theoretical approach recently developed to address the connectivity of 2-D fractal networks (Bird and Perrier, 2009). Theoretical arguments based on renormalisation functions provide insight into multi-scale connectivity and a first estimation of CFS. Numerical experiments on 3-D prefractal media confirm the qualitative theory. These results open the way towards a new methodology to estimate soil filtration efficiency from the construction of soil structural models to be calibrated on available multiscale data.

Multi-scale Modeling of the Impact Response of a Strain Rate Sensitive High-Manganese Austenitic Steel

NASA Astrophysics Data System (ADS)

Önal, Orkun; Ozmenci, Cemre; Canadinc, Demircan

2014-09-01

A multi-scale modeling approach was applied to predict the impact response of a strain rate sensitive high-manganese austenitic steel. The roles of texture, geometry and strain rate sensitivity were successfully taken into account all at once by coupling crystal plasticity and finite element (FE) analysis. Specifically, crystal plasticity was utilized to obtain the multi-axial flow rule at different strain rates based on the experimental deformation response under uniaxial tensile loading. The equivalent stress - equivalent strain response was then incorporated into the FE model for the sake of a more representative hardening rule under impact loading. The current results demonstrate that reliable predictions can be obtained by proper coupling of crystal plasticity and FE analysis even if the experimental flow rule of the material is acquired under uniaxial loading and at moderate strain rates that are significantly slower than those attained during impact loading. Furthermore, the current findings also demonstrate the need for an experiment-based multi-scale modeling approach for the sake of reliable predictions of the impact response.

Petascale computation of multi-physics seismic simulations

NASA Astrophysics Data System (ADS)

Gabriel, Alice-Agnes; Madden, Elizabeth H.; Ulrich, Thomas; Wollherr, Stephanie; Duru, Kenneth C.

2017-04-01

Capturing the observed complexity of earthquake sources in concurrence with seismic wave propagation simulations is an inherently multi-scale, multi-physics problem. In this presentation, we present simulations of earthquake scenarios resolving high-detail dynamic rupture evolution and high frequency ground motion. The simulations combine a multitude of representations of model complexity; such as non-linear fault friction, thermal and fluid effects, heterogeneous fault stress and fault strength initial conditions, fault curvature and roughness, on- and off-fault non-elastic failure to capture dynamic rupture behavior at the source; and seismic wave attenuation, 3D subsurface structure and bathymetry impacting seismic wave propagation. Performing such scenarios at the necessary spatio-temporal resolution requires highly optimized and massively parallel simulation tools which can efficiently exploit HPC facilities. Our up to multi-PetaFLOP simulations are performed with SeisSol (www.seissol.org), an open-source software package based on an ADER-Discontinuous Galerkin (DG) scheme solving the seismic wave equations in velocity-stress formulation in elastic, viscoelastic, and viscoplastic media with high-order accuracy in time and space. Our flux-based implementation of frictional failure remains free of spurious oscillations. Tetrahedral unstructured meshes allow for complicated model geometry. SeisSol has been optimized on all software levels, including: assembler-level DG kernels which obtain 50% peak performance on some of the largest supercomputers worldwide; an overlapping MPI-OpenMP parallelization shadowing the multiphysics computations; usage of local time stepping; parallel input and output schemes and direct interfaces to community standard data formats. All these factors enable aim to minimise the time-to-solution. The results presented highlight the fact that modern numerical methods and hardware-aware optimization for modern supercomputers are essential to further our understanding of earthquake source physics and complement both physic-based ground motion research and empirical approaches in seismic hazard analysis. Lastly, we will conclude with an outlook on future exascale ADER-DG solvers for seismological applications.

How does low-molecular-weight polystyrene dissolve: osmotic swelling vs. surface dissolution.

PubMed

Marcon, Valentina; van der Vegt, Nico F A

2014-12-07

By means of multiscale hierarchical modeling we study the real time evolution of low-molecular-weight polystyrene, below the glass transition temperature, in contact with its solvent, toluene. We observe two concurrent phenomena taking place: (1) the solvent diffuses into the polymer by a Case II mechanism, leading to osmotic driven swelling and progressive chain dilution (inside-out mechanism); (2) polymer chains are solvated, detach from the interface and move into the solvent before the film is completely swollen (outside-in mechanism). From our simulations we conclude that, below the entanglement length, a thin swollen layer, also observed in previous experiments, forms almost instantaneously, which allows for the outside-in mechanism to start a few tens of nanoseconds after the polymer-solvent initial contact. After this initial transient time the two mechanisms are concurrent. We furthermore observe that the presence of the solvent significantly enhances the mobility of the polymer chains of the surface layer, but only in the direction parallel to the interface.

Design of Nanomaterial Synthesis by Aerosol Processes

PubMed Central

Buesser, Beat; Pratsinis, Sotiris E.

2013-01-01

Aerosol synthesis of materials is a vibrant field of particle technology and chemical reaction engineering. Examples include the manufacture of carbon blacks, fumed SiO2, pigmentary TiO2, ZnO vulcanizing catalysts, filamentary Ni, and optical fibers, materials that impact transportation, construction, pharmaceuticals, energy, and communications. Parallel to this, development of novel, scalable aerosol processes has enabled synthesis of new functional nanomaterials (e.g., catalysts, biomaterials, electroceramics) and devices (e.g., gas sensors). This review provides an access point for engineers to the multiscale design of aerosol reactors for the synthesis of nanomaterials using continuum, mesoscale, molecular dynamics, and quantum mechanics models spanning 10 and 15 orders of magnitude in length and time, respectively. Key design features are the rapid chemistry; the high particle concentrations but low volume fractions; the attainment of a self-preserving particle size distribution by coagulation; the ratio of the characteristic times of coagulation and sintering, which controls the extent of particle aggregation; and the narrowing of the aggregate primary particle size distribution by sintering. PMID:22468598

Subcellular and supracellular mechanical stress prescribes cytoskeleton behavior in Arabidopsis cotyledon pavement cells

PubMed Central

Sampathkumar, Arun; Krupinski, Pawel; Wightman, Raymond; Milani, Pascale; Berquand, Alexandre; Boudaoud, Arezki; Hamant, Olivier; Jönsson, Henrik; Meyerowitz, Elliot M

2014-01-01

Although it is a central question in biology, how cell shape controls intracellular dynamics largely remains an open question. Here, we show that the shape of Arabidopsis pavement cells creates a stress pattern that controls microtubule orientation, which then guides cell wall reinforcement. Live-imaging, combined with modeling of cell mechanics, shows that microtubules align along the maximal tensile stress direction within the cells, and atomic force microscopy demonstrates that this leads to reinforcement of the cell wall parallel to the microtubules. This feedback loop is regulated: cell-shape derived stresses could be overridden by imposed tissue level stresses, showing how competition between subcellular and supracellular cues control microtubule behavior. Furthermore, at the microtubule level, we identified an amplification mechanism in which mechanical stress promotes the microtubule response to stress by increasing severing activity. These multiscale feedbacks likely contribute to the robustness of microtubule behavior in plant epidermis. DOI: http://dx.doi.org/10.7554/eLife.01967.001 PMID:24740969

A Comparison of Solver Performance for Complex Gastric Electrophysiology Models

PubMed Central

Sathar, Shameer; Cheng, Leo K.; Trew, Mark L.

2016-01-01

Computational techniques for solving systems of equations arising in gastric electrophysiology have not been studied for efficient solution process. We present a computationally challenging problem of simulating gastric electrophysiology in anatomically realistic stomach geometries with multiple intracellular and extracellular domains. The multiscale nature of the problem and mesh resolution required to capture geometric and functional features necessitates efficient solution methods if the problem is to be tractable. In this study, we investigated and compared several parallel preconditioners for the linear systems arising from tetrahedral discretisation of electrically isotropic and anisotropic problems, with and without stimuli. The results showed that the isotropic problem was computationally less challenging than the anisotropic problem and that the application of extracellular stimuli increased workload considerably. Preconditioning based on block Jacobi and algebraic multigrid solvers were found to have the best overall solution times and least iteration counts, respectively. The algebraic multigrid preconditioner would be expected to perform better on large problems. PMID:26736543

Design of nanomaterial synthesis by aerosol processes.

PubMed

Buesser, Beat; Pratsinis, Sotiris E

2012-01-01

Aerosol synthesis of materials is a vibrant field of particle technology and chemical reaction engineering. Examples include the manufacture of carbon blacks, fumed SiO(2), pigmentary TiO(2), ZnO vulcanizing catalysts, filamentary Ni, and optical fibers, materials that impact transportation, construction, pharmaceuticals, energy, and communications. Parallel to this, development of novel, scalable aerosol processes has enabled synthesis of new functional nanomaterials (e.g., catalysts, biomaterials, electroceramics) and devices (e.g., gas sensors). This review provides an access point for engineers to the multiscale design of aerosol reactors for the synthesis of nanomaterials using continuum, mesoscale, molecular dynamics, and quantum mechanics models spanning 10 and 15 orders of magnitude in length and time, respectively. Key design features are the rapid chemistry; the high particle concentrations but low volume fractions; the attainment of a self-preserving particle size distribution by coagulation; the ratio of the characteristic times of coagulation and sintering, which controls the extent of particle aggregation; and the narrowing of the aggregate primary particle size distribution by sintering.

Self-organization of muscle cell structure and function.

PubMed

Grosberg, Anna; Kuo, Po-Ling; Guo, Chin-Lin; Geisse, Nicholas A; Bray, Mark-Anthony; Adams, William J; Sheehy, Sean P; Parker, Kevin Kit

2011-02-01

The organization of muscle is the product of functional adaptation over several length scales spanning from the sarcomere to the muscle bundle. One possible strategy for solving this multiscale coupling problem is to physically constrain the muscle cells in microenvironments that potentiate the organization of their intracellular space. We hypothesized that boundary conditions in the extracellular space potentiate the organization of cytoskeletal scaffolds for directed sarcomeregenesis. We developed a quantitative model of how the cytoskeleton of neonatal rat ventricular myocytes organizes with respect to geometric cues in the extracellular matrix. Numerical results and in vitro assays to control myocyte shape indicated that distinct cytoskeletal architectures arise from two temporally-ordered, organizational processes: the interaction between actin fibers, premyofibrils and focal adhesions, as well as cooperative alignment and parallel bundling of nascent myofibrils. Our results suggest that a hierarchy of mechanisms regulate the self-organization of the contractile cytoskeleton and that a positive feedback loop is responsible for initiating the break in symmetry, potentiated by extracellular boundary conditions, is required to polarize the contractile cytoskeleton.

Top down and bottom up engineering of bone.

PubMed

Knothe Tate, Melissa L

2011-01-11

The goal of this retrospective article is to place the body of my lab's multiscale mechanobiology work in context of top-down and bottom-up engineering of bone. We have used biosystems engineering, computational modeling and novel experimental approaches to understand bone physiology, in health and disease, and across time (in utero, postnatal growth, maturity, aging and death, as well as evolution) and length scales (a single bone like a femur, m; a sample of bone tissue, mm-cm; a cell and its local environment, μm; down to the length scale of the cell's own skeleton, the cytoskeleton, nm). First we introduce the concept of flow in bone and the three calibers of porosity through which fluid flows. Then we describe, in the context of organ-tissue, tissue-cell and cell-molecule length scales, both multiscale computational models and experimental methods to predict flow in bone and to understand the flow of fluid as a means to deliver chemical and mechanical cues in bone. Addressing a number of studies in the context of multiple length and time scales, the importance of appropriate boundary conditions, site specific material parameters, permeability measures and even micro-nanoanatomically correct geometries are discussed in context of model predictions and their value for understanding multiscale mechanobiology of bone. Insights from these multiscale computational modeling and experimental methods are providing us with a means to predict, engineer and manufacture bone tissue in the laboratory and in the human body. Copyright © 2010 Elsevier Ltd. All rights reserved.

Virtual Patients and Sensitivity Analysis of the Guyton Model of Blood Pressure Regulation: Towards Individualized Models of Whole-Body Physiology

PubMed Central

Moss, Robert; Grosse, Thibault; Marchant, Ivanny; Lassau, Nathalie; Gueyffier, François; Thomas, S. Randall

2012-01-01

Mathematical models that integrate multi-scale physiological data can offer insight into physiological and pathophysiological function, and may eventually assist in individualized predictive medicine. We present a methodology for performing systematic analyses of multi-parameter interactions in such complex, multi-scale models. Human physiology models are often based on or inspired by Arthur Guyton's whole-body circulatory regulation model. Despite the significance of this model, it has not been the subject of a systematic and comprehensive sensitivity study. Therefore, we use this model as a case study for our methodology. Our analysis of the Guyton model reveals how the multitude of model parameters combine to affect the model dynamics, and how interesting combinations of parameters may be identified. It also includes a “virtual population” from which “virtual individuals” can be chosen, on the basis of exhibiting conditions similar to those of a real-world patient. This lays the groundwork for using the Guyton model for in silico exploration of pathophysiological states and treatment strategies. The results presented here illustrate several potential uses for the entire dataset of sensitivity results and the “virtual individuals” that we have generated, which are included in the supplementary material. More generally, the presented methodology is applicable to modern, more complex multi-scale physiological models. PMID:22761561

A Micromechanics-Based Method for Multiscale Fatigue Prediction

NASA Astrophysics Data System (ADS)

Moore, John Allan

An estimated 80% of all structural failures are due to mechanical fatigue, often resulting in catastrophic, dangerous and costly failure events. However, an accurate model to predict fatigue remains an elusive goal. One of the major challenges is that fatigue is intrinsically a multiscale process, which is dependent on a structure's geometric design as well as its material's microscale morphology. The following work begins with a microscale study of fatigue nucleation around non- metallic inclusions. Based on this analysis, a novel multiscale method for fatigue predictions is developed. This method simulates macroscale geometries explicitly while concurrently calculating the simplified response of microscale inclusions. Thus, providing adequate detail on multiple scales for accurate fatigue life predictions. The methods herein provide insight into the multiscale nature of fatigue, while also developing a tool to aid in geometric design and material optimization for fatigue critical devices such as biomedical stents and artificial heart valves.

Determining the multi-scale hedge ratios of stock index futures using the lower partial moments method

NASA Astrophysics Data System (ADS)

Dai, Jun; Zhou, Haigang; Zhao, Shaoquan

2017-01-01

This paper considers a multi-scale future hedge strategy that minimizes lower partial moments (LPM). To do this, wavelet analysis is adopted to decompose time series data into different components. Next, different parametric estimation methods with known distributions are applied to calculate the LPM of hedged portfolios, which is the key to determining multi-scale hedge ratios over different time scales. Then these parametric methods are compared with the prevailing nonparametric kernel metric method. Empirical results indicate that in the China Securities Index 300 (CSI 300) index futures and spot markets, hedge ratios and hedge efficiency estimated by the nonparametric kernel metric method are inferior to those estimated by parametric hedging model based on the features of sequence distributions. In addition, if minimum-LPM is selected as a hedge target, the hedging periods, degree of risk aversion, and target returns can affect the multi-scale hedge ratios and hedge efficiency, respectively.

A dynamic wall model for Large-Eddy simulations of wind turbine dedicated airfoils

NASA Astrophysics Data System (ADS)

J, Calafell; O, Lehmkuhl; A, Carmona; D, Pérez-Segarra C.; A, Oliva

2014-06-01

This work aims at modelling the flow behavior past a wind turbine dedicated airfoil at high Reynolds number and large angle of attack (AoA). The DU-93-W-210 airfoil has been selected. To do this, Large Eddy Simulations (LES) have been performed. Momentum equations have been solved with a parallel unstructured symmetry preserving formulation while the wall-adapting local-eddy viscosity model within a variational multi-scale framework (VMS- WALE) is used as the subgrid-scales model. Since LES calculations are still very expensive at high Reynolds Number, specially at the near-wall region, a dynamic wall model has been implemented in order to overcome this limitation. The model has been validated with a very unresolved Channel Flow case at Reτ = 2000. Afterwards, the model is also tested with the Ahmed Car case, that from the flow physics point of view is more similar to an stalled airfoil than the Channel Flow is, including flow features as boundary layer detachment and recirculations. This case has been selected because experimental results of mean velocity profiles are available. Finally, a flow around a DU-93-W-210 airfoil is computed at Re = 3 x 106 and with an AoA of 15°. Numerical results are presented in comparison with Direct Numerical Simulation (DNS) or experimental data for all cases.

Key Factors Influencing the Energy Absorption of Dual-Phase Steels: Multiscale Material Model Approach and Microstructural Optimization

NASA Astrophysics Data System (ADS)

Belgasam, Tarek M.; Zbib, Hussein M.

2018-06-01

The increase in use of dual-phase (DP) steel grades by vehicle manufacturers to enhance crash resistance and reduce body car weight requires the development of a clear understanding of the effect of various microstructural parameters on the energy absorption in these materials. Accordingly, DP steelmakers are interested in predicting the effect of various microscopic factors as well as optimizing microstructural properties for application in crash-relevant components of vehicle bodies. This study presents a microstructure-based approach using a multiscale material and structure model. In this approach, Digimat and LS-DYNA software were coupled and employed to provide a full micro-macro multiscale material model, which is then used to simulate tensile tests. Microstructures with varied ferrite grain sizes, martensite volume fractions, and carbon content in DP steels were studied. The impact of these microstructural features at different strain rates on energy absorption characteristics of DP steels is investigated numerically using an elasto-viscoplastic constitutive model. The model is implemented in a multiscale finite-element framework. A comprehensive statistical parametric study using response surface methodology is performed to determine the optimum microstructural features for a required tensile toughness at different strain rates. The simulation results are validated using experimental data found in the literature. The developed methodology proved to be effective for investigating the influence and interaction of key microscopic properties on the energy absorption characteristics of DP steels. Furthermore, it is shown that this method can be used to identify optimum microstructural conditions at different strain-rate conditions.

Key Factors Influencing the Energy Absorption of Dual-Phase Steels: Multiscale Material Model Approach and Microstructural Optimization

NASA Astrophysics Data System (ADS)

Belgasam, Tarek M.; Zbib, Hussein M.

2018-03-01

The increase in use of dual-phase (DP) steel grades by vehicle manufacturers to enhance crash resistance and reduce body car weight requires the development of a clear understanding of the effect of various microstructural parameters on the energy absorption in these materials. Accordingly, DP steelmakers are interested in predicting the effect of various microscopic factors as well as optimizing microstructural properties for application in crash-relevant components of vehicle bodies. This study presents a microstructure-based approach using a multiscale material and structure model. In this approach, Digimat and LS-DYNA software were coupled and employed to provide a full micro-macro multiscale material model, which is then used to simulate tensile tests. Microstructures with varied ferrite grain sizes, martensite volume fractions, and carbon content in DP steels were studied. The impact of these microstructural features at different strain rates on energy absorption characteristics of DP steels is investigated numerically using an elasto-viscoplastic constitutive model. The model is implemented in a multiscale finite-element framework. A comprehensive statistical parametric study using response surface methodology is performed to determine the optimum microstructural features for a required tensile toughness at different strain rates. The simulation results are validated using experimental data found in the literature. The developed methodology proved to be effective for investigating the influence and interaction of key microscopic properties on the energy absorption characteristics of DP steels. Furthermore, it is shown that this method can be used to identify optimum microstructural conditions at different strain-rate conditions.

Asymptotic Expansion Homogenization for Multiscale Nuclear Fuel Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hales, J. D.; Tonks, M. R.; Chockalingam, K.

2015-03-01

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.more » 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.« less

Automatic event detection in low SNR microseismic signals based on multi-scale permutation entropy and a support vector machine

NASA Astrophysics Data System (ADS)

Jia, Rui-Sheng; Sun, Hong-Mei; Peng, Yan-Jun; Liang, Yong-Quan; Lu, Xin-Ming

2017-07-01

Microseismic monitoring is an effective means for providing early warning of rock or coal dynamical disasters, and its first step is microseismic event detection, although low SNR microseismic signals often cannot effectively be detected by routine methods. To solve this problem, this paper presents permutation entropy and a support vector machine to detect low SNR microseismic events. First, an extraction method of signal features based on multi-scale permutation entropy is proposed by studying the influence of the scale factor on the signal permutation entropy. Second, the detection model of low SNR microseismic events based on the least squares support vector machine is built by performing a multi-scale permutation entropy calculation for the collected vibration signals, constructing a feature vector set of signals. Finally, a comparative analysis of the microseismic events and noise signals in the experiment proves that the different characteristics of the two can be fully expressed by using multi-scale permutation entropy. The detection model of microseismic events combined with the support vector machine, which has the features of high classification accuracy and fast real-time algorithms, can meet the requirements of online, real-time extractions of microseismic events.

Multiscale methods for gore curvature calculations from FSI modeling of spacecraft parachutes

NASA Astrophysics Data System (ADS)

Takizawa, Kenji; Tezduyar, Tayfun E.; Kolesar, Ryan; Boswell, Cody; Kanai, Taro; Montel, Kenneth

2014-12-01

There are now some sophisticated and powerful methods for computer modeling of parachutes. These methods are capable of addressing some of the most formidable computational challenges encountered in parachute modeling, including fluid-structure interaction (FSI) between the parachute and air flow, design complexities such as those seen in spacecraft parachutes, and operational complexities such as use in clusters and disreefing. One should be able to extract from a reliable full-scale parachute modeling any data or analysis needed. In some cases, however, the parachute engineers may want to perform quickly an extended or repetitive analysis with methods based on simplified models. Some of the data needed by a simplified model can very effectively be extracted from a full-scale computer modeling that serves as a pilot. A good example of such data is the circumferential curvature of a parachute gore, where a gore is the slice of the parachute canopy between two radial reinforcement cables running from the parachute vent to the skirt. We present the multiscale methods we devised for gore curvature calculation from FSI modeling of spacecraft parachutes. The methods include those based on the multiscale sequentially-coupled FSI technique and using NURBS meshes. We show how the methods work for the fully-open and two reefed stages of the Orion spacecraft main and drogue parachutes.

Adaptive Multiscale Modeling of Geochemical Impacts on Fracture Evolution

NASA Astrophysics Data System (ADS)

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 which not only enables mesh refinement, but also refinement of the model-pore scale or continuum Darcy scale-in a dynamic way such that the appropriate model is used only when and where it is needed. Explicit flux matching provides coupling betwen the scales.