A Multi-Scale Method for Dynamics Simulation in Continuum Solvent Models I: Finite-Difference Algorithm for Navier-Stokes Equation.

PubMed

Xiao, Li; Cai, Qin; Li, Zhilin; Zhao, Hongkai; Luo, Ray

2014-11-25

A multi-scale framework is proposed for more realistic molecular dynamics simulations in continuum solvent models by coupling a molecular mechanics treatment of solute with a fluid mechanics treatment of solvent. This article reports our initial efforts to formulate the physical concepts necessary for coupling the two mechanics and develop a 3D numerical algorithm to simulate the solvent fluid via the Navier-Stokes equation. The numerical algorithm was validated with multiple test cases. The validation shows that the algorithm is effective and stable, with observed accuracy consistent with our design.

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

Mathematical and Computational Aspects of Multiscale Materials Modeling, Mathematics-Numerical analysis, Section II.A.a.3.4, Conference and symposia organization II.A.2.a

DTIC Science & Technology

2015-02-04

dislocation dynamics models ( DDD ), continuum representations). Coupling of these models is difficult. Coupling of atomistics and DDD models has been...explored to some extent, but the coupling between DDD and continuum models of the evolution of large populations of dislocations is essentially unexplored

A Multi-Scale Method for Dynamics Simulation in Continuum Solvent Models I: Finite-Difference Algorithm for Navier-Stokes Equation

PubMed Central

Xiao, Li; Cai, Qin; Li, Zhilin; Zhao, Hongkai; Luo, Ray

2014-01-01

A multi-scale framework is proposed for more realistic molecular dynamics simulations in continuum solvent models by coupling a molecular mechanics treatment of solute with a fluid mechanics treatment of solvent. This article reports our initial efforts to formulate the physical concepts necessary for coupling the two mechanics and develop a 3D numerical algorithm to simulate the solvent fluid via the Navier-Stokes equation. The numerical algorithm was validated with multiple test cases. The validation shows that the algorithm is effective and stable, with observed accuracy consistent with our design. PMID:25404761

Isostaticity in Cosserat Continuum

DTIC Science & Technology

2012-01-01

Geotech . Eng. Div. 106(4), 419–433 (1980) 13. Walker, D.M., Tordesillas, A., Thornton, C., Behringer, R.P., Zhang, J., Peters, J.F.: Percolating contact...thermomicromechanical approach to multiscale continuum modeling of dense granular materials. Acta Geotech . 3, 225–240 (2008) 17. Oda, M., Takemura, T

Multiscale Modeling of Intergranular Fracture in Aluminum: Constitutive Relation For Interface Debonding

NASA Technical Reports Server (NTRS)

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

2008-01-01

Intergranular fracture is a dominant mode of failure in ultrafine grained materials. In the present study, the atomistic mechanisms of grain-boundary debonding during intergranular fracture in aluminum are modeled using a coupled molecular dynamics finite element simulation. Using a statistical mechanics approach, a cohesive-zone law in the form of a traction-displacement constitutive relationship, characterizing the load transfer across the plane of a growing edge crack, is extracted from atomistic simulations and then recast in a form suitable for inclusion within a continuum finite element model. The cohesive-zone law derived by the presented technique is free of finite size effects and is statistically representative for describing the interfacial debonding of a grain boundary (GB) interface examined at atomic length scales. By incorporating the cohesive-zone law in cohesive-zone finite elements, the debonding of a GB interface can be simulated in a coupled continuum-atomistic model, in which a crack starts in the continuum environment, smoothly penetrates the continuum-atomistic interface, and continues its propagation in the atomistic environment. This study is a step towards relating atomistically derived decohesion laws to macroscopic predictions of fracture and constructing multiscale models for nanocrystalline and ultrafine grained materials.

Multiscale Fiber Kinking: Computational Micromechanics and a Mesoscale Continuum Damage Mechanics Models

NASA Technical Reports Server (NTRS)

Herraez, Miguel; Bergan, Andrew C.; Gonzalez, Carlos; Lopes, Claudio S.

2017-01-01

In this work, the fiber kinking phenomenon, which is known as the failure mechanism that takes place when a fiber reinforced polymer is loaded under longitudinal compression, is studied. A computational micromechanics model is employed to interrogate the assumptions of a recently developed mesoscale continuum damage mechanics (CDM) model for fiber kinking based on the deformation gradient decomposition (DGD) and the LaRC04 failure criteria.

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.

Exploring a multi-scale method for molecular simulation in continuum solvent model: Explicit simulation of continuum solvent as an incompressible fluid.

PubMed

Xiao, Li; Luo, Ray

2017-12-07

We explored a multi-scale algorithm for the Poisson-Boltzmann continuum solvent model for more robust simulations of biomolecules. In this method, the continuum solvent/solute interface is explicitly simulated with a numerical fluid dynamics procedure, which is tightly coupled to the solute molecular dynamics simulation. There are multiple benefits to adopt such a strategy as presented below. At this stage of the development, only nonelectrostatic interactions, i.e., van der Waals and hydrophobic interactions, are included in the algorithm to assess the quality of the solvent-solute interface generated by the new method. Nevertheless, numerical challenges exist in accurately interpolating the highly nonlinear van der Waals term when solving the finite-difference fluid dynamics equations. We were able to bypass the challenge rigorously by merging the van der Waals potential and pressure together when solving the fluid dynamics equations and by considering its contribution in the free-boundary condition analytically. The multi-scale simulation method was first validated by reproducing the solute-solvent interface of a single atom with analytical solution. Next, we performed the relaxation simulation of a restrained symmetrical monomer and observed a symmetrical solvent interface at equilibrium with detailed surface features resembling those found on the solvent excluded surface. Four typical small molecular complexes were then tested, both volume and force balancing analyses showing that these simple complexes can reach equilibrium within the simulation time window. Finally, we studied the quality of the multi-scale solute-solvent interfaces for the four tested dimer complexes and found that they agree well with the boundaries as sampled in the explicit water simulations.

A concurrent multiscale micromorphic molecular dynamics

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

Li, Shaofan, E-mail: shaofan@berkeley.edu; Tong, Qi

2015-04-21

In this work, we have derived a multiscale micromorphic molecular dynamics (MMMD) from first principle to extend the (Andersen)-Parrinello-Rahman molecular dynamics to mesoscale and continuum scale. The multiscale micromorphic molecular dynamics is a con-current three-scale dynamics that couples a fine scale molecular dynamics, a mesoscale micromorphic dynamics, and a macroscale nonlocal particle dynamics together. By choosing proper statistical closure conditions, we have shown that the original Andersen-Parrinello-Rahman molecular dynamics is the homogeneous and equilibrium case of the proposed multiscale micromorphic molecular dynamics. In specific, we have shown that the Andersen-Parrinello-Rahman molecular dynamics can be rigorously formulated and justified from firstmore » principle, and its general inhomogeneous case, i.e., the three scale con-current multiscale micromorphic molecular dynamics can take into account of macroscale continuum mechanics boundary condition without the limitation of atomistic boundary condition or periodic boundary conditions. The discovered multiscale scale structure and the corresponding multiscale dynamics reveal a seamless transition from atomistic scale to continuum scale and the intrinsic coupling mechanism among them based on first principle formulation.« less

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.

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.

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.

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 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.

A multiscale MD-FE model of diffusion in composite media with internal surface interaction based on numerical homogenization procedure.

PubMed

Kojic, M; Milosevic, M; Kojic, N; Kim, K; Ferrari, M; Ziemys, A

2014-02-01

Mass transport by diffusion within composite materials may depend not only on internal microstructural geometry, but also on the chemical interactions between the transported substance and the material of the microstructure. Retrospectively, there is a gap in methods and theory to connect material microstructure properties with macroscale continuum diffusion characteristics. Here we present a new hierarchical multiscale model for diffusion within composite materials that couples material microstructural geometry and interactions between diffusing particles and the material matrix. This model, which bridges molecular dynamics (MD) and the finite element (FE) method, is employed to construct a continuum diffusion model based on a novel numerical homogenization procedure. The procedure is general and robust for evaluating constitutive material parameters of the continuum model. These parameters include the traditional bulk diffusion coefficients and, additionally, the distances from the solid surface accounting for surface interaction effects. We implemented our models to glucose diffusion through the following two geometrical/material configurations: tightly packed silica nanospheres, and a complex fibrous structure surrounding nanospheres. Then, rhodamine 6G diffusion analysis through an aga-rose gel network was performed, followed by a model validation using our experimental results. The microstructural model, numerical homogenization and continuum model offer a new platform for modeling and predicting mass diffusion through complex biological environment and within composite materials that are used in a wide range of applications, like drug delivery and nanoporous catalysts.

A multiscale MD–FE model of diffusion in composite media with internal surface interaction based on numerical homogenization procedure

PubMed Central

Kojic, M.; Milosevic, M.; Kojic, N.; Kim, K.; Ferrari, M.; Ziemys, A.

2014-01-01

Mass transport by diffusion within composite materials may depend not only on internal microstructural geometry, but also on the chemical interactions between the transported substance and the material of the microstructure. Retrospectively, there is a gap in methods and theory to connect material microstructure properties with macroscale continuum diffusion characteristics. Here we present a new hierarchical multiscale model for diffusion within composite materials that couples material microstructural geometry and interactions between diffusing particles and the material matrix. This model, which bridges molecular dynamics (MD) and the finite element (FE) method, is employed to construct a continuum diffusion model based on a novel numerical homogenization procedure. The procedure is general and robust for evaluating constitutive material parameters of the continuum model. These parameters include the traditional bulk diffusion coefficients and, additionally, the distances from the solid surface accounting for surface interaction effects. We implemented our models to glucose diffusion through the following two geometrical/material configurations: tightly packed silica nanospheres, and a complex fibrous structure surrounding nanospheres. Then, rhodamine 6G diffusion analysis through an aga-rose gel network was performed, followed by a model validation using our experimental results. The microstructural model, numerical homogenization and continuum model offer a new platform for modeling and predicting mass diffusion through complex biological environment and within composite materials that are used in a wide range of applications, like drug delivery and nanoporous catalysts. PMID:24578582

Parallel multiscale simulations of a brain aneurysm

PubMed Central

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

2012-01-01

Cardiovascular pathologies, such as a brain aneurysm, are affected by the global blood circulation as well as by the local microrheology. Hence, developing computational models for such cases requires the coupling of disparate spatial and temporal scales often governed by diverse mathematical descriptions, e.g., by partial differential equations (continuum) and ordinary differential equations for discrete particles (atomistic). However, interfacing atomistic-based with continuum-based domain discretizations is a challenging problem that requires both mathematical and computational advances. We present here a hybrid methodology that enabled us to perform the first multi-scale simulations of platelet depositions on the wall of a brain aneurysm. The large scale flow features in the intracranial network are accurately resolved by using the high-order spectral element Navier-Stokes solver εκ αr. The blood rheology inside the aneurysm is modeled using a coarse-grained stochastic molecular dynamics approach (the dissipative particle dynamics method) implemented in the parallel code LAMMPS. The continuum and atomistic domains overlap with interface conditions provided by effective forces computed adaptively to ensure continuity of states across the interface boundary. A two-way interaction is allowed with the time-evolving boundary of the (deposited) platelet clusters tracked by an immersed boundary method. The corresponding heterogeneous solvers ( εκ αr and LAMMPS) are linked together by a computational multilevel message passing interface that facilitates modularity and high parallel efficiency. Results of multiscale simulations of clot formation inside the aneurysm in a patient-specific arterial tree are presented. We also discuss the computational challenges involved and present scalability results of our coupled solver on up to 300K computer processors. Validation of such coupled atomistic-continuum models is a main open issue that has to be addressed in future work. PMID:23734066

Parallel multiscale simulations of a brain aneurysm.

PubMed

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

2013-07-01

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

Parallel multiscale simulations of a brain aneurysm

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

Grinberg, Leopold; Fedosov, Dmitry A.; Karniadakis, George Em, E-mail: george_karniadakis@brown.edu

2013-07-01

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

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

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

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

A Multiscale Model for Virus Capsid Dynamics

PubMed Central

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

2010-01-01

Viruses are infectious agents that can cause epidemics and pandemics. The understanding of virus formation, evolution, stability, and interaction with host cells is of great importance to the scientific community and public health. Typically, a virus complex in association with its aquatic environment poses a fabulous challenge to theoretical description and prediction. In this work, we propose a differential geometry-based multiscale paradigm to model complex biomolecule systems. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum domain of the fluid mechanical description of the aquatic environment from the microscopic discrete domain of the atomistic description of the biomolecule. A multiscale action functional is constructed as a unified framework to derive the governing equations for the dynamics of different scales. We show that the classical Navier-Stokes equation for the fluid dynamics and Newton's equation for the molecular dynamics can be derived from the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. PMID:20224756

Parallel algorithm for multiscale atomistic/continuum simulations using LAMMPS

NASA Astrophysics Data System (ADS)

Pavia, F.; Curtin, W. A.

2015-07-01

Deformation and fracture processes in engineering materials often require simultaneous descriptions over a range of length and time scales, with each scale using a different computational technique. Here we present a high-performance parallel 3D computing framework for executing large multiscale studies that couple an atomic domain, modeled using molecular dynamics and a continuum domain, modeled using explicit finite elements. We use the robust Coupled Atomistic/Discrete-Dislocation (CADD) displacement-coupling method, but without the transfer of dislocations between atoms and continuum. The main purpose of the work is to provide a multiscale implementation within an existing large-scale parallel molecular dynamics code (LAMMPS) that enables use of all the tools associated with this popular open-source code, while extending CADD-type coupling to 3D. Validation of the implementation includes the demonstration of (i) stability in finite-temperature dynamics using Langevin dynamics, (ii) elimination of wave reflections due to large dynamic events occurring in the MD region and (iii) the absence of spurious forces acting on dislocations due to the MD/FE coupling, for dislocations further than 10 Å from the coupling boundary. A first non-trivial example application of dislocation glide and bowing around obstacles is shown, for dislocation lengths of ∼50 nm using fewer than 1 000 000 atoms but reproducing results of extremely large atomistic simulations at much lower computational cost.

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.

Particle-Based Methods for Multiscale Modeling of Blood Flow in the Circulation and in Devices: Challenges and Future Directions

PubMed Central

Yamaguchi, Takami; Ishikawa, Takuji; Imai, Y.; Matsuki, N.; Xenos, Mikhail; Deng, Yuefan; Bluestein, Danny

2010-01-01

A major computational challenge for a multiscale modeling is the coupling of disparate length and timescales between molecular mechanics and macroscopic transport, spanning the spatial and temporal scales characterizing the complex processes taking place in flow-induced blood clotting. Flow and pressure effects on a cell-like platelet can be well represented by a continuum mechanics model down to the order of the micrometer level. However, the molecular effects of adhesion/aggregation bonds are on the order of nanometer. A successful multiscale model of platelet response to flow stresses in devices and the ensuing clotting responses should be able to characterize the clotting reactions and their interactions with the flow. This paper attempts to describe a few of the computational methods that were developed in recent years and became available to researchers in the field. They differ from traditional approaches that dominate the field by expanding on prevailing continuum-based approaches, or by completely departing from them, yielding an expanding toolkit that may facilitate further elucidation of the underlying mechanisms of blood flow and the cellular response to it. We offer a paradigm shift by adopting a multidisciplinary approach with fluid dynamics simulations coupled to biophysical and biochemical transport. PMID:20336827

Multiscale volatility duration characteristics on financial multi-continuum percolation dynamics

NASA Astrophysics Data System (ADS)

Wang, Min; Wang, Jun

A random stock price model based on the multi-continuum percolation system is developed to investigate the nonlinear dynamics of stock price volatility duration, in an attempt to explain various statistical facts found in financial data, and have a deeper understanding of mechanisms in the financial market. The continuum percolation system is usually referred to be a random coverage process or a Boolean model, it is a member of a class of statistical physics systems. In this paper, the multi-continuum percolation (with different values of radius) is employed to model and reproduce the dispersal of information among the investors. To testify the rationality of the proposed model, the nonlinear analyses of return volatility duration series are preformed by multifractal detrending moving average analysis and Zipf analysis. The comparison empirical results indicate the similar nonlinear behaviors for the proposed model and the actual Chinese stock market.

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

Multiscale Modeling of UHTC: Thermal Conductivity

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Components for Atomistic-to-Continuum Multiscale Modeling of Flow in Micro- and Nanofluidic Systems

DOE PAGES

Adalsteinsson, Helgi; Debusschere, Bert J.; Long, Kevin R.; ...

2008-01-01

Micro- and nanofluidics pose a series of significant challenges for science-based modeling. Key among those are the wide separation of length- and timescales between interface phenomena and bulk flow and the spatially heterogeneous solution properties near solid-liquid interfaces. It is not uncommon for characteristic scales in these systems to span nine orders of magnitude from the atomic motions in particle dynamics up to evolution of mass transport at the macroscale level, making explicit particle models intractable for all but the simplest systems. Recently, atomistic-to-continuum (A2C) multiscale simulations have gained a lot of interest as an approach to rigorously handle particle-levelmore » dynamics while also tracking evolution of large-scale macroscale behavior. While these methods are clearly not applicable to all classes of simulations, they are finding traction in systems in which tight-binding, and physically important, dynamics at system interfaces have complex effects on the slower-evolving large-scale evolution of the surrounding medium. These conditions allow decomposition of the simulation into discrete domains, either spatially or temporally. In this paper, we describe how features of domain decomposed simulation systems can be harnessed to yield flexible and efficient software for multiscale simulations of electric field-driven micro- and nanofluidics.« less

Using Multiscale Modeling to Study Coupled Flow, Transport, Reaction and Biofilm Growth Processes in Porous Media

NASA Astrophysics Data System (ADS)

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

2017-12-01

Perturbation of natural subsurface systems by fluid inputs may induce geochemical or microbiological reactions that change porosity and permeability, leading to complex coupled feedbacks between reaction and transport processes. Some examples are precipitation/dissolution processes associated with carbon capture and storage and biofilm growth associated with contaminant transport and remediation. We study biofilm growth due to mixing controlled reaction of multiple substrates. As biofilms grow, pore clogging occurs which alters pore-scale flow paths thus changing the mixing and reaction. These interactions are challenging to quantify using conventional continuum-scale porosity-permeability relations. Pore-scale models can accurately resolve coupled reaction, biofilm growth and transport processes, but modeling at this scale is not feasible for practical applications. There are two approaches to address this challenge. Results from pore-scale models in generic pore structures can be used to develop empirical relations between porosity and continuum-scale parameters, such as permeability and dispersion coefficients. The other approach is to develop a multiscale model of biofilm growth in which non-overlapping regions at pore and continuum spatial scales are coupled by a suitable method that ensures continuity of flux across the interface. Thus, regions of high reactivity where flow alteration occurs are resolved at the pore scale for accuracy while regions of low reactivity are resolved at the continuum scale for efficiency. This approach thus avoids the need for empirical upscaling relations in regions with strong feedbacks between reaction and porosity change. We explore and compare these approaches for several two-dimensional cases.

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

Multiscale Modeling of Mesoscale and Interfacial Phenomena

NASA Astrophysics Data System (ADS)

Petsev, Nikolai Dimitrov

With rapidly emerging technologies that feature interfaces modified at the nanoscale, traditional macroscopic models are pushed to their limits to explain phenomena where molecular processes can play a key role. Often, such problems appear to defy explanation when treated with coarse-grained continuum models alone, yet remain prohibitively expensive from a molecular simulation perspective. A prominent example is surface nanobubbles: nanoscopic gaseous domains typically found on hydrophobic surfaces that have puzzled researchers for over two decades due to their unusually long lifetimes. We show how an entirely macroscopic, non-equilibrium model explains many of their anomalous properties, including their stability and abnormally small gas-side contact angles. From this purely transport perspective, we investigate how factors such as temperature and saturation affect nanobubbles, providing numerous experimentally testable predictions. However, recent work also emphasizes the relevance of molecular-scale phenomena that cannot be described in terms of bulk phases or pristine interfaces. This is true for nanobubbles as well, whose nanoscale heights may require molecular detail to capture the relevant physics, in particular near the bubble three-phase contact line. Therefore, there is a clear need for general ways to link molecular granularity and behavior with large-scale continuum models in the treatment of many interfacial problems. In light of this, we have developed a general set of simulation strategies that couple mesoscale particle-based continuum models to molecular regions simulated through conventional molecular dynamics (MD). In addition, we derived a transport model for binary mixtures that opens the possibility for a wide range of applications in biological and drug delivery problems, and is readily reconciled with our hybrid MD-continuum techniques. Approaches that couple multiple length scales for fluid mixtures are largely absent in the literature, and we provide a novel and general framework for multiscale modeling of systems featuring one or more dissolved species. This makes it possible to retain molecular detail for parts of the problem that require it while using a simple, continuum description for parts where high detail is unnecessary, reducing the number of degrees of freedom (i.e. number of particles) dramatically. This opens the possibility for modeling ion transport in biological processes and biomolecule assembly in ionic solution, as well as electrokinetic phenomena at interfaces such as corrosion. The number of particles in the system is further reduced through an integrated boundary approach, which we apply to colloidal suspensions. In this thesis, we describe this general framework for multiscale modeling single- and multicomponent systems, provide several simple equilibrium and non-equilibrium case studies, and discuss future applications.

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

Multiscale Simulations of Reactive Transport

NASA Astrophysics Data System (ADS)

Tartakovsky, D. M.; Bakarji, J.

2014-12-01

Discrete, particle-based simulations offer distinct advantages when modeling solute transport and chemical reactions. For example, Brownian motion is often used to model diffusion in complex pore networks, and Gillespie-type algorithms allow one to handle multicomponent chemical reactions with uncertain reaction pathways. Yet such models can be computationally more intensive than their continuum-scale counterparts, e.g., advection-dispersion-reaction equations. Combining the discrete and continuum models has a potential to resolve the quantity of interest with a required degree of physicochemical granularity at acceptable computational cost. We present computational examples of such "hybrid models" and discuss the challenges associated with coupling these two levels of description.

Particle-based methods for multiscale modeling of blood flow in the circulation and in devices: challenges and future directions. Sixth International Bio-Fluid Mechanics Symposium and Workshop March 28-30, 2008 Pasadena, California.

PubMed

Yamaguchi, Takami; Ishikawa, Takuji; Imai, Y; Matsuki, N; Xenos, Mikhail; Deng, Yuefan; Bluestein, Danny

2010-03-01

A major computational challenge for a multiscale modeling is the coupling of disparate length and timescales between molecular mechanics and macroscopic transport, spanning the spatial and temporal scales characterizing the complex processes taking place in flow-induced blood clotting. Flow and pressure effects on a cell-like platelet can be well represented by a continuum mechanics model down to the order of the micrometer level. However, the molecular effects of adhesion/aggregation bonds are on the order of nanometer. A successful multiscale model of platelet response to flow stresses in devices and the ensuing clotting responses should be able to characterize the clotting reactions and their interactions with the flow. This paper attempts to describe a few of the computational methods that were developed in recent years and became available to researchers in the field. They differ from traditional approaches that dominate the field by expanding on prevailing continuum-based approaches, or by completely departing from them, yielding an expanding toolkit that may facilitate further elucidation of the underlying mechanisms of blood flow and the cellular response to it. We offer a paradigm shift by adopting a multidisciplinary approach with fluid dynamics simulations coupled to biophysical and biochemical transport.

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

PubMed Central

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

2016-01-01

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

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.

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.

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

Combining frozen-density embedding with the conductor-like screening model using Lagrangian techniques for response properties.

PubMed

Schieschke, Nils; Di Remigio, Roberto; Frediani, Luca; Heuser, Johannes; Höfener, Sebastian

2017-07-15

We present the explicit derivation of an approach to the multiscale description of molecules in complex environments that combines frozen-density embedding (FDE) with continuum solvation models, in particular the conductor-like screening model (COSMO). FDE provides an explicit atomistic description of molecule-environment interactions at reduced computational cost, while the outer continuum layer accounts for the effect of long-range isotropic electrostatic interactions. Our treatment is based on a variational Lagrangian framework, enabling rigorous derivations of ground- and excited-state response properties. As an example of the flexibility of the theoretical framework, we derive and discuss FDE + COSMO analytical molecular gradients for excited states within the Tamm-Dancoff approximation (TDA) and for ground states within second-order Møller-Plesset perturbation theory (MP2) and a second-order approximate coupled cluster with singles and doubles (CC2). It is shown how this method can be used to describe vertical electronic excitation (VEE) energies and Stokes shifts for uracil in water and carbostyril in dimethyl sulfoxide (DMSO), respectively. In addition, VEEs for some simplified protein models are computed, illustrating the performance of this method when applied to larger systems. The interaction terms between the FDE subsystem densities and the continuum can influence excitation energies up to 0.3 eV and, thus, cannot be neglected for general applications. We find that the net influence of the continuum in presence of the first FDE shell on the excitation energy amounts to about 0.05 eV for the cases investigated. The present work is an important step toward rigorously derived ab initio multilayer and multiscale modeling approaches. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Multiscale Molecular Dynamics Model for Heterogeneous Charged Systems

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Intercomparison of Multiscale Modeling Approaches in Simulating Subsurface Flow and Transport

NASA Astrophysics Data System (ADS)

Yang, X.; Mehmani, Y.; Barajas-Solano, D. A.; Song, H. S.; Balhoff, M.; Tartakovsky, A. M.; Scheibe, T. D.

2016-12-01

Hybrid multiscale simulations that couple models across scales are critical to advance predictions of the larger system behavior using understanding of fundamental processes. In the current study, three hybrid multiscale methods are intercompared: multiscale loose-coupling method, multiscale finite volume (MsFV) method and multiscale mortar method. The loose-coupling method enables a parallel workflow structure based on the Swift scripting environment that manages the complex process of executing coupled micro- and macro-scale models without being intrusive to the at-scale simulators. The MsFV method applies microscale and macroscale models over overlapping subdomains of the modeling domain and enforces continuity of concentration and transport fluxes between models via restriction and prolongation operators. The mortar method is a non-overlapping domain decomposition approach capable of coupling all permutations of pore- and continuum-scale models with each other. In doing so, Lagrange multipliers are used at interfaces shared between the subdomains so as to establish continuity of species/fluid mass flux. Subdomain computations can be performed either concurrently or non-concurrently depending on the algorithm used. All the above methods have been proven to be accurate and efficient in studying flow and transport in porous media. However, there has not been any field-scale applications and benchmarking among various hybrid multiscale approaches. To address this challenge, we apply all three hybrid multiscale methods to simulate water flow and transport in a conceptualized 2D modeling domain of the hyporheic zone, where strong interactions between groundwater and surface water exist across multiple scales. In all three multiscale methods, fine-scale simulations are applied to a thin layer of riverbed alluvial sediments while the macroscopic simulations are used for the larger subsurface aquifer domain. Different numerical coupling methods are then applied between scales and inter-compared. Comparisons are drawn in terms of velocity distributions, solute transport behavior, algorithm-induced numerical error and computing cost. The intercomparison work provides support for confidence in a variety of hybrid multiscale methods and motivates further development and applications.

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Atomistic to Continuum Multiscale and Multiphysics Simulation of NiTi Shape Memory Alloy

NASA Astrophysics Data System (ADS)

Gur, Sourav

Shape memory alloys (SMAs) are materials that show reversible, thermo-elastic, diffusionless, displacive (solid to solid) phase transformation, due to the application of temperature and/ or stress (/strain). Among different SMAs, NiTi is a popular one. NiTi shows reversible phase transformation, the shape memory effect (SME), where irreversible deformations are recovered upon heating, and superelasticity (SE), where large strains imposed at high enough temperatures are fully recovered. Phase transformation process in NiTi SMA is a very complex process that involves the competition between developed internal strain and phonon dispersion instability. In NiTi SMA, phase transformation occurs over a wide range of temperature and/ or stress (strain) which involves, evolution of different crystalline phases (cubic austenite i.e. B2, different monoclinic variant of martensite i.e. B19', and orthorhombic B19 or BCO structures). Further, it is observed from experimental and computational studies that the evolution kinetics and growth rate of different phases in NiTi SMA vary significantly over a wide spectrum of spatio-temporal scales, especially with length scales. At nano-meter length scale, phase transformation temperatures, critical transformation stress (or strain) and phase fraction evolution change significantly with sample or simulation cell size and grain size. Even, below a critical length scale, the phase transformation process stops. All these aspects make NiTi SMA very interesting to the science and engineering research community and in this context, the present focuses on the following aspects. At first this study address the stability, evolution and growth kinetics of different phases (B2 and variants of B19'), at different length scales, starting from the atomic level and ending at the continuum macroscopic level. The effects of simulation cell size, grain size, and presence of free surface and grain boundary on the phase transformation process (transformation temperature, phase fraction evolution kinetics due to temperature) are also demonstrated herein. Next, to couple and transfer the statistical information of length scale dependent phase transformation process, multiscale/ multiphysics methods are used. Here, the computational difficulty from the fact that the representative governing equations (i.e. different sub-methods such as molecular dynamics simulations, phase field simulations and continuum level constitutive/ material models) are only valid or can be implemented over a range of spatiotemporal scales. Therefore, in the present study, a wavelet based multiscale coupling method is used, where simulation results (phase fraction evolution kinetics) from different sub-methods are linked via concurrent multiscale coupling fashion. Finally, these multiscale/ multiphysics simulation results are used to develop/ modify the macro/ continuum scale thermo-mechanical constitutive relations for NiTi SMA. Finally, the improved material model is used to model new devices, such as thermal diodes and smart dampers.

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

PubMed Central

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

2012-01-01

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

Nonlinear modeling of crystal system transition of black phosphorus using continuum-DFT model.

PubMed

Setoodeh, A R; Farahmand, H

2018-01-24

In this paper, the nonlinear behavior of black phosphorus crystals is investigated in tandem with dispersion-corrected density functional theory (DFT-D) analysis under uniaxial loadings. From the identified anisotropic behavior of black phosphorus due to its morphological anisotropy, a hyperelastic anisotropic (HA) model named continuum-DFT is established to predict the nonlinear behavior of the material. In this respect, uniaxial Cauchy stresses are employed on both the DFT-D and HA models along the zig-zag and armchair directions. Simultaneously, the transition of the crystal system is recognized at about 4.5 GPa of the applied uniaxial tensile stress along the zig-zag direction on the DFT-D simulation in the nonlinear region. In order to develop the nonlinear continuum model, unknown constants are surveyed with the optimized least square technique. In this regard, the continuum model is obtained to reproduce the Cauchy stress-stretch and density of strain-stretch results of the DFT-D simulation. Consequently, the modified HA model is introduced to characterize the nonlinear behavior of black phosphorus along the zig-zag direction. More importantly, the specific transition of the crystal system is successfully predicted in the new modified continuum-DFT model. The results reveal that the multiscale continuum-DFT model is well defined to replicate the nonlinear behavior of black phosphorus along the zig-zag and armchair directions.

Multiscale study of metal nanoparticles

NASA Astrophysics Data System (ADS)

Lee, Byeongchan

Extremely small structures with reduced dimensionality have emerged as a scientific motif for their interesting properties. In particular, metal nanoparticles have been identified as a fundamental material in many catalytic activities; as a consequence, a better understanding of structure-function relationship of nanoparticles has become crucial. The functional analysis of nanoparticles, reactivity for example, requires an accurate method at the electronic structure level, whereas the structural analysis to find energetically stable local minima is beyond the scope of quantum mechanical methods as the computational cost becomes prohibitingly high. The challenge is that the inherent length scale and accuracy associated with any single method hardly covers the broad scale range spanned by both structural and functional analyses. In order to address this, and effectively explore the energetics and reactivity of metal nanoparticles, a hierarchical multiscale modeling is developed, where methodologies of different length scales, i.e. first principles density functional theory, atomistic calculations, and continuum modeling, are utilized in a sequential fashion. This work has focused on identifying the essential information that bridges two different methods so that a successive use of different methods is seamless. The bond characteristics of low coordination systems have been obtained with first principles calculations, and incorporated into the atomistic simulation. This also rectifies the deficiency of conventional interatomic potentials fitted to bulk properties, and improves the accuracy of atomistic calculations for nanoparticles. For the systematic shape selection of nanoparticles, we have improved the Wulff-type construction using a semi-continuum approach, in which atomistic surface energetics and crystallinity of materials are added on to the continuum framework. The developed multiscale modeling scheme is applied to the rational design of platinum nanoparticles in the range of 2.4 nm to 3.1 nm: energetically favorable structures have been determined in terms of semi-continuum binding energy, and the reactivity of the selected nanoparticle has been investigated based on local density of states from first principles calculations. The calculation suggests that the reactivity landscape of particles is more complex than the simple reactivity of clean surfaces, and the reactivity towards a particular reactant can be predicted for a given structure.

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.

Quantifying sampling noise and parametric uncertainty in atomistic-to-continuum simulations using surrogate models

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

Salloum, Maher N.; Sargsyan, Khachik; Jones, Reese E.

2015-08-11

We present a methodology to assess the predictive fidelity of multiscale simulations by incorporating uncertainty in the information exchanged between the components of an atomistic-to-continuum simulation. We account for both the uncertainty due to finite sampling in molecular dynamics (MD) simulations and the uncertainty in the physical parameters of the model. Using Bayesian inference, we represent the expensive atomistic component by a surrogate model that relates the long-term output of the atomistic simulation to its uncertain inputs. We then present algorithms to solve for the variables exchanged across the atomistic-continuum interface in terms of polynomial chaos expansions (PCEs). We alsomore » consider a simple Couette flow where velocities are exchanged between the atomistic and continuum components, while accounting for uncertainty in the atomistic model parameters and the continuum boundary conditions. Results show convergence of the coupling algorithm at a reasonable number of iterations. As a result, the uncertainty in the obtained variables significantly depends on the amount of data sampled from the MD simulations and on the width of the time averaging window used in the MD simulations.« less

Scalable free energy calculation of proteins via multiscale essential sampling

NASA Astrophysics Data System (ADS)

Moritsugu, Kei; Terada, Tohru; Kidera, Akinori

2010-12-01

A multiscale simulation method, "multiscale essential sampling (MSES)," is proposed for calculating free energy surface of proteins in a sizable dimensional space with good scalability. In MSES, the configurational sampling of a full-dimensional model is enhanced by coupling with the accelerated dynamics of the essential degrees of freedom. Applying the Hamiltonian exchange method to MSES can remove the biasing potential from the coupling term, deriving the free energy surface of the essential degrees of freedom. The form of the coupling term ensures good scalability in the Hamiltonian exchange. As a test application, the free energy surface of the folding process of a miniprotein, chignolin, was calculated in the continuum solvent model. Results agreed with the free energy surface derived from the multicanonical simulation. Significantly improved scalability with the MSES method was clearly shown in the free energy calculation of chignolin in explicit solvent, which was achieved without increasing the number of replicas in the Hamiltonian exchange.

Quantum Dynamics in Continuum for Proton Transport I: Basic Formulation.

PubMed

Chen, Duan; Wei, Guo-Wei

2013-01-01

Proton transport is one of the most important and interesting phenomena in living cells. The present work proposes a multiscale/multiphysics model for the understanding of the molecular mechanism of proton transport in transmembrane proteins. We describe proton dynamics quantum mechanically via a density functional approach while implicitly model other solvent ions as a dielectric continuum to reduce the number of degrees of freedom. The densities of all other ions in the solvent are assumed to obey the Boltzmann distribution. The impact of protein molecular structure and its charge polarization on the proton transport is considered explicitly at the atomic level. We formulate a total free energy functional to put proton kinetic and potential energies as well as electrostatic energy of all ions on an equal footing. The variational principle is employed to derive nonlinear governing equations for the proton transport system. Generalized Poisson-Boltzmann equation and Kohn-Sham equation are obtained from the variational framework. Theoretical formulations for the proton density and proton conductance are constructed based on fundamental principles. The molecular surface of the channel protein is utilized to split the discrete protein domain and the continuum solvent domain, and facilitate the multiscale discrete/continuum/quantum descriptions. A number of mathematical algorithms, including the Dirichlet to Neumann mapping, matched interface and boundary method, Gummel iteration, and Krylov space techniques are utilized to implement the proposed model in a computationally efficient manner. The Gramicidin A (GA) channel is used to demonstrate the performance of the proposed proton transport model and validate the efficiency of proposed mathematical algorithms. The electrostatic characteristics of the GA channel is analyzed with a wide range of model parameters. The proton conductances are studied over a number of applied voltages and reference concentrations. A comparison with experimental data verifies the present model predictions and validates the proposed model.

A Predictive Model for Chemically-Induced Fracture

NASA Astrophysics Data System (ADS)

Carter, Emily

2004-03-01

Mechanical properties of bulk solids are affected not only by macroscopic external loads, but also by chemical reactions, typically at surfaces and interfaces. For example, impurities in metals often coalesce at grain boundaries, leading to weakening of the sample under stress. Atmospheric corrosion is another example that, when combined with external loads, leads to stress-corrosion cracking. These are inherently multiscale phenomena, where the chemistry occurring at the atomic scale profoundly affects the mechanical properties at the micron to millimeter scale. Here we discuss a multiscale model of environmentally-assisted fracture. This involves coupling periodic density functional theory (DFT) at the atomic scale to a finite element continuum mechanics description of the coarser scale. A key component is the cohesive law, which we have shown takes on a universal form distinct from the generally used UBER model. Further, we propose a scheme to calculate physically realistic cohesive laws in the presence of mobile impurities. This cohesive law is then used to in a continuum model that couples stress-assisted diffusion with cohesive zone models of fracture to describe hydrogen embrittlement in metals. We show that this model, with a first principles-based cohesive law, provides insight into the observed intermittent cracking in steel, as well as good quantitative agreement with experiment.

Effect of initial strain and material nonlinearity on the nonlinear static and dynamic response of graphene sheets

NASA Astrophysics Data System (ADS)

Singh, Sandeep; Patel, B. P.

2018-06-01

Computationally efficient multiscale modelling based on Cauchy-Born rule in conjunction with finite element method is employed to study static and dynamic characteristics of graphene sheets, with/without considering initial strain, involving Green-Lagrange geometric and material nonlinearities. The strain energy density function at continuum level is established by coupling the deformation at continuum level to that at atomic level through Cauchy-Born rule. The atomic interactions between carbon atoms are modelled through Tersoff-Brenner potential. The governing equation of motion obtained using Hamilton's principle is solved through standard Newton-Raphson method for nonlinear static response and Newmark's time integration technique to obtain nonlinear transient response characteristics. Effect of initial strain on the linear free vibration frequencies, nonlinear static and dynamic response characteristics is investigated in detail. The present multiscale modelling based results are found to be in good agreement with those obtained through molecular mechanics simulation. Two different types of boundary constraints generally used in MM simulation are explored in detail and few interesting findings are brought out. The effect of initial strain is found to be greater in linear response when compared to that in nonlinear response.

Multiscale Simulation Platform Linking Lithium Ion Battery Electrode Fabrication Process with Performance at the Cell Level.

PubMed

Ngandjong, Alain C; Rucci, Alexis; Maiza, Mariem; Shukla, Garima; Vazquez-Arenas, Jorge; Franco, Alejandro A

2017-12-07

A novel multiscale modeling platform is proposed to demonstrate the importance of particle assembly during battery electrode fabrication by showing its effect on battery performance. For the first time, a discretized three-dimensional (3D) electrode resulting from the simulation of its fabrication has been incorporated within a 3D continuum performance model. The study used LiNi 0.5 Co 0.2 Mn 0.3 O 2 as active material, and the effect of changes of electrode formulation is explored for three cases, namely 85:15, 90:10, and 95:5 ratios between active material and carbon-binder domains. Coarse-grained molecular dynamics is used to simulate the electrode fabrication. The resulting electrode mesostructure is characterized in terms of active material surface coverage by the carbon-binder domains and porosity. The trends observed are nonintuitive, indicating a high degree of complexity of the system. These structures are subsequently implemented into a 3D continuum model which displays distinct discharge behaviors for the three cases. The study offers a method for developing a coherent theoretical understanding of electrode fabrication that can help optimize battery performance.

Mechanosensitive Channels: Insights from Continuum-Based Simulations

PubMed Central

Tang, Yuye; Yoo, Jejoong; Yethiraj, Arun; Cui, Qiang; Chen, Xi

2009-01-01

Mechanotransduction plays an important role in regulating cell functions and it is an active topic of research in biophysics. Despite recent advances in experimental and numerical techniques, the intrinsic multiscale nature imposes tremendous challenges for revealing the working mechanisms of mechanosensitive channels. Recently, a continuum-mechanics based hierarchical modeling and simulation framework has been established and applied to study the mechanical responses and gating behaviors of a prototypical mechanosensitive channel, the mechanosensitive channel of large conductance (MscL) in bacteria Escherichia coli (E. coli), from which several putative gating mechanisms have been tested and new insights deduced. This article reviews these latest findings using the continuum mechanics framework and suggests possible improvements for future simulation studies. This computationally efficient and versatile continuum-mechanics based protocol is poised to make contributions to the study of a variety of mechanobiology problems. PMID:18787764

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.

A general multiscale framework for the emergent effective elastodynamics of metamaterials

NASA Astrophysics Data System (ADS)

Sridhar, A.; Kouznetsova, V. G.; Geers, M. G. D.

2018-02-01

This paper presents a general multiscale framework towards the computation of the emergent effective elastodynamics of heterogeneous materials, to be applied for the analysis of acoustic metamaterials and phononic crystals. The generality of the framework is exemplified by two key characteristics. First, the underlying formalism relies on the Floquet-Bloch theorem to derive a robust definition of scales and scale separation. Second, unlike most homogenization approaches that rely on a classical volume average, a generalized homogenization operator is defined with respect to a family of particular projection functions. This yields a generalized macro-scale continuum, instead of the classical Cauchy continuum. This enables (in a micromorphic sense) to homogenize the rich dispersive behavior resulting from both Bragg scattering and local resonance. For an arbitrary unit cell, the homogenization projection functions are constructed using the Floquet-Bloch eigenvectors obtained in the desired frequency regime at select high symmetry points, which effectively resolves the emergent phenomena dominating that regime. Furthermore, a generalized Hill-Mandel condition is proposed that ensures power consistency between the homogenized and full-scale model. A high-order spatio-temporal gradient expansion is used to localize the multiscale problem leading to a series of recursive unit cell problems giving the appropriate micro-mechanical corrections. The developed multiscale method is validated against standard numerical Bloch analysis of the dispersion spectra of example unit cells encompassing multiple high-order branches generated by local resonance and/or Bragg scattering.

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

Computational Modeling of Multi-Scale Material Features in Cement Paste - An Overview

DTIC Science & Technology

2015-05-25

and concrete ; though commonly used are one of the most complex in terms of material morphology and structure than most materials, for example...across the multiple scales are required. In this paper, recent work from our research group on the nano to continuum level modeling of cementitious...of our research work consisting of, • Molecular Dynamics (MD) modeling for the nano scale features of the cementitious material chemistry. • Micro

Nonlinear Multiscale Modeling of 3D Woven Fiber Composites under Ballistic Loading

DTIC Science & Technology

2013-07-11

contact parameters on the underlying damage processes is being studied and worked on. We further develop a material model suitable particularly for...of Material and Process Engineering. 2011/05/23 00:00:00, . : , TOTAL: 1 (d) Manuscripts Number of Peer-Reviewed Conference Proceeding publications...continuum damage mechanics suitable for polymer materials. The effect of contact parameters on the underlying damage processes is being studied and

Multiscaling for systems with a broad continuum of characteristic lengths and times: Structural transitions in nanocomposites.

PubMed

Pankavich, S; Ortoleva, P

2010-06-01

The multiscale approach to N-body systems is generalized to address the broad continuum of long time and length scales associated with collective behaviors. A technique is developed based on the concept of an uncountable set of time variables and of order parameters (OPs) specifying major features of the system. We adopt this perspective as a natural extension of the commonly used discrete set of time scales and OPs which is practical when only a few, widely separated scales exist. The existence of a gap in the spectrum of time scales for such a system (under quasiequilibrium conditions) is used to introduce a continuous scaling and perform a multiscale analysis of the Liouville equation. A functional-differential Smoluchowski equation is derived for the stochastic dynamics of the continuum of Fourier component OPs. A continuum of spatially nonlocal Langevin equations for the OPs is also derived. The theory is demonstrated via the analysis of structural transitions in a composite material, as occurs for viral capsids and molecular circuits.

Mechanics of low-dimensional carbon nanostructures: Atomistic, continuum, and multi-scale approaches

NASA Astrophysics Data System (ADS)

Mahdavi, Arash

A new multiscale modeling technique called the Consistent Atomic-scale Finite Element (CAFE) method is introduced. Unlike traditional approaches for linking the atomic structure to its equivalent continuum, this method directly connects the atomic degrees of freedom to a reduced set of finite element degrees of freedom without passing through an intermediate homogenized continuum. As a result, there is no need to introduce stress and strain measures at the atomic level. The Tersoff-Brenner interatomic potential is used to calculate the consistent tangent stiffness matrix of the structure. In this finite element formulation, all local and non-local interactions between carbon atoms are taken into account using overlapping finite elements. In addition, a consistent hierarchical finite element modeling technique is developed for adaptively coarsening and refining the mesh over different parts of the model. This process is consistent with the underlying atomic structure and, by refining the mesh to the scale of atomic spacing, molecular dynamic results can be recovered. This method is valid across the scales and can be used to concurrently model atomistic and continuum phenomena so, in contrast with most other multi-scale methods, there is no need to introduce artificial boundaries for coupling atomistic and continuum regions. Effect of the length scale of the nanostructure is also included in the model by building the hierarchy of elements from bottom up using a finite size atom cluster as the building block. To be consistent with the bravais multi-lattice structure of sp2-bonded carbon, two independent displacement fields are used for reducing the order of the model. Sparse structure of the stiffness matrix of these nanostructures is exploited to reduce the memory requirement and to speed up the formation of the system matrices and solution of the equilibrium equations. Applicability of the method is shown with several examples of the nonlinear mechanics of carbon nanotubes and carbon nanocones subject to different loadings and boundary conditions. This finite element technique is also used to study the natural frequencies of low-dimensional carbon nanostructures and comparing the results with those of a homogenized isotropic continuum shell. Conclusion is that, replacing the atomic lattice with an isotropic continuum shell for a graphene sheet does not significantly affect the vibration frequencies while in the case of carbon nanotubes and carbon nanocones there is a significant difference between the natural frequencies of the atomistic model and its continuum counterpart. In the case of the carbon nanotube, continuum model successfully captures the beam bending vibration modes while overestimating frequencies of the modes in which the cross-section undergoes significant deformation. Furthermore, in the case of carbon nanotubes, the continuum shell exhibits a torsional mode which appears to be an artifact resulting from the small nominal thickness typically used in the continuum shell approximation of these nanostructures. Results of this study indicate that isotropic continuum shell models, while simple and useful in static analysis, cannot accurately predict the vibration frequencies of these nanostructures. We have studied the bistable nature of single-walled carbon nanotubes by investigating the change in the tube's energy as it is compressed between flat rigid indenters of various widths. Assuming the nanotube deformed uniformly along its length and modeling the cross-section as an inextensible, non-linear beam we found that tubes with a radius greater than 12 A are bistable and that tubes with a radius greater than 25 A have a lower energy in the collapsed state than in the inflated state. The difference in energy between the collapsed and inflated states decreases nearly linearly with increasing tube radius. While the inflated state remains stable for tubes of all diameters, the energy barrier keeping the tube from collapsing approaches zero as the tube radius increases. We also demonstrate why collapse with a wide indenter may be difficult to observe in narrow tubes. A reduced-order model is developed for the dynamics of the carbon nanotube atomic force microscope probes. Bending behavior of the nanotube probe is modeled using Euler's elastica. A nonlinear moment-curvature relationship is implemeneted to account for the ovalization of the cross section of the nanotube during bending. Van der Waal forces acting between tube and the substrate is integrated over the surface of the tube and used as distributed follower forces acting on the equivalent elastica. Approximating the behavior of the nanotube with an elastica proved to be a very effiecient technique for modeling these nanostructures.

Models of collective cell spreading with variable cell aspect ratio: a motivation for degenerate diffusion models.

PubMed

Simpson, Matthew J; Baker, Ruth E; McCue, Scott W

2011-02-01

Continuum diffusion models are often used to represent the collective motion of cell populations. Most previous studies have simply used linear diffusion to represent collective cell spreading, while others found that degenerate nonlinear diffusion provides a better match to experimental cell density profiles. In the cell modeling literature there is no guidance available with regard to which approach is more appropriate for representing the spreading of cell populations. Furthermore, there is no knowledge of particular experimental measurements that can be made to distinguish between situations where these two models are appropriate. Here we provide a link between individual-based and continuum models using a multiscale approach in which we analyze the collective motion of a population of interacting agents in a generalized lattice-based exclusion process. For round agents that occupy a single lattice site, we find that the relevant continuum description of the system is a linear diffusion equation, whereas for elongated rod-shaped agents that occupy L adjacent lattice sites we find that the relevant continuum description is connected to the porous media equation (PME). The exponent in the nonlinear diffusivity function is related to the aspect ratio of the agents. Our work provides a physical connection between modeling collective cell spreading and the use of either the linear diffusion equation or the PME to represent cell density profiles. Results suggest that when using continuum models to represent cell population spreading, we should take care to account for variations in the cell aspect ratio because different aspect ratios lead to different continuum models.

Multiscale modeling of fluid transport in tumors.

PubMed

Chapman, S Jonathan; Shipley, Rebecca J; Jawad, Rossa

2008-11-01

A model for fluid flow through the leaky neovasculature and porous interstitium of a solid tumor is developed. A network of isolated capillaries is analyzed in the limit of small capillary radius, and analytical expressions for the hydraulic conductivities and fractional leakage coefficients derived. This model is then homogenized to give a continuum description in terms of the vascular density. The resulting equations comprise a double porous medium with coupled Darcy flow through the interstitium and vasculature.

NUMERICAL SIMULATION OF NANOINDENTATION AND PATCH CLAMP EXPERIMENTS ON MECHANOSENSITIVE CHANNELS OF LARGE CONDUCTANCE IN ESCHERICHIA COLI

PubMed Central

Tang, Yuye; Chen, Xi; Yoo, Jejoong; Yethiraj, Arun; Cui, Qiang

2010-01-01

A hierarchical simulation framework that integrates information from all-atom simulations into a finite element model at the continuum level is established to study the mechanical response of a mechanosensitive channel of large conductance (MscL) in bacteria Escherichia Coli (E.coli) embedded in a vesicle formed by the dipalmitoylphosphatidycholine (DPPC) lipid bilayer. Sufficient structural details of the protein are built into the continuum model, with key parameters and material properties derived from molecular mechanics simulations. The multi-scale framework is used to analyze the gating of MscL when the lipid vesicle is subjective to nanoindentation and patch clamp experiments, and the detailed structural transitions of the protein are obtained explicitly as a function of external load; it is currently impossible to derive such information based solely on all-atom simulations. The gating pathways of E.coli-MscL qualitatively agree with results from previous patch clamp experiments. The gating mechanisms under complex indentation-induced deformation are also predicted. This versatile hierarchical multi-scale framework may be further extended to study the mechanical behaviors of cells and biomolecules, as well as to guide and stimulate biomechanics experiments. PMID:21874098

Computational modeling of brain tumors: discrete, continuum or hybrid?

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Deisboeck, Thomas S.

In spite of all efforts, patients diagnosed with highly malignant brain tumors (gliomas), continue to face a grim prognosis. Achieving significant therapeutic advances will also require a more detailed quantitative understanding of the dynamic interactions among tumor cells, and between these cells and their biological microenvironment. Data-driven computational brain tumor models have the potential to provide experimental tumor biologists with such quantitative and cost-efficient tools to generate and test hypotheses on tumor progression, and to infer fundamental operating principles governing bidirectional signal propagation in multicellular cancer systems. This review highlights the modeling objectives of and challenges with developing such in silico brain tumor models by outlining two distinct computational approaches: discrete and continuum, each with representative examples. Future directions of this integrative computational neuro-oncology field, such as hybrid multiscale multiresolution modeling are discussed.

Computational modeling of brain tumors: discrete, continuum or hybrid?

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Deisboeck, Thomas S.

2008-04-01

In spite of all efforts, patients diagnosed with highly malignant brain tumors (gliomas), continue to face a grim prognosis. Achieving significant therapeutic advances will also require a more detailed quantitative understanding of the dynamic interactions among tumor cells, and between these cells and their biological microenvironment. Data-driven computational brain tumor models have the potential to provide experimental tumor biologists with such quantitative and cost-efficient tools to generate and test hypotheses on tumor progression, and to infer fundamental operating principles governing bidirectional signal propagation in multicellular cancer systems. This review highlights the modeling objectives of and challenges with developing such in silicobrain tumor models by outlining two distinct computational approaches: discrete and continuum, each with representative examples. Future directions of this integrative computational neuro-oncology field, such as hybrid multiscale multiresolution modeling are discussed.

Prediction of Thermal Transport Properties of Materials with Microstructural Complexity

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

Chen, Youping

This project aims at overcoming the major obstacle standing in the way of progress in dynamic multiscale simulation, which is the lack of a concurrent atomistic-continuum method that allows phonons, heat and defects to pass through the atomistic-continuum interface. The research has led to the development of a concurrent atomistic-continuum (CAC) methodology for multiscale simulations of materials microstructural, mechanical and thermal transport behavior. Its efficacy has been tested and demonstrated through simulations of dislocation dynamics and phonon transport coupled with microstructural evolution in a variety of materials and through providing visual evidences of the nature of phonon transport, such asmore » showing the propagation of heat pulses in single and polycrystalline solids is partially ballistic and partially diffusive. In addition to providing understanding on phonon scattering with phase interface and with grain boundaries, the research has contributed a multiscale simulation tool for understanding of the behavior of complex materials and has demonstrated the capability of the tool in simulating the dynamic, in situ experimental studies of nonequilibrium transient transport processes in material samples that are at length scales typically inaccessible by atomistically resolved methods.« less

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.

Cross-Linked Nanotube Materials with Variable Stiffness Tethers

NASA Technical Reports Server (NTRS)

Frankland, Sarah-Jane V.; Odegard, Gregory M.; Herzog, Matthew N.; Gates, Thomas S.; Fay, Catherine C.

2004-01-01

The constitutive properties of a cross-linked single-walled carbon nanotube material are predicted with a multi-scale model. The material is modeled as a transversely isotropic solid using concepts from equivalent-continuum modeling. The elastic constants are determined using molecular dynamics simulation. Some parameters of the molecular force field are determined specifically for the cross-linker from ab initio calculations. A demonstration of how the cross-linked nanotubes may affect the properties of a nanotube/polyimide composite is included using a micromechanical analysis.

Multi-Scale Modeling of Liquid Phase Sintering Affected by Gravity: Preliminary Analysis

NASA Technical Reports Server (NTRS)

Olevsky, Eugene; German, Randall M.

2012-01-01

A multi-scale simulation concept taking into account impact of gravity on liquid phase sintering is described. The gravity influence can be included at both the micro- and macro-scales. At the micro-scale, the diffusion mass-transport is directionally modified in the framework of kinetic Monte-Carlo simulations to include the impact of gravity. The micro-scale simulations can provide the values of the constitutive parameters for macroscopic sintering simulations. At the macro-scale, we are attempting to embed a continuum model of sintering into a finite-element framework that includes the gravity forces and substrate friction. If successful, the finite elements analysis will enable predictions relevant to space-based processing, including size and shape and property predictions. Model experiments are underway to support the models via extraction of viscosity moduli versus composition, particle size, heating rate, temperature and time.

Modeling Progressive Damage Using Local Displacement Discontinuities Within the FEAMAC Multiscale Modeling Framework

NASA Technical Reports Server (NTRS)

Ranatunga, Vipul; Bednarcyk, Brett A.; Arnold, Steven M.

2010-01-01

A method for performing progressive damage modeling in composite materials and structures based on continuum level interfacial displacement discontinuities is presented. The proposed method enables the exponential evolution of the interfacial compliance, resulting in unloading of the tractions at the interface after delamination or failure occurs. In this paper, the proposed continuum displacement discontinuity model has been used to simulate failure within both isotropic and orthotropic materials efficiently and to explore the possibility of predicting the crack path, therein. Simulation results obtained from Mode-I and Mode-II fracture compare the proposed approach with the cohesive element approach and Virtual Crack Closure Techniques (VCCT) available within the ABAQUS (ABAQUS, Inc.) finite element software. Furthermore, an eccentrically loaded 3-point bend test has been simulated with the displacement discontinuity model, and the resulting crack path prediction has been compared with a prediction based on the extended finite element model (XFEM) approach.

Quantum dynamics in continuum for proton transport II: Variational solvent-solute interface.

PubMed

Chen, Duan; Chen, Zhan; Wei, Guo-Wei

2012-01-01

Proton transport plays an important role in biological energy transduction and sensory systems. Therefore, it has attracted much attention in biological science and biomedical engineering in the past few decades. The present work proposes a multiscale/multiphysics model for the understanding of the molecular mechanism of proton transport in transmembrane proteins involving continuum, atomic, and quantum descriptions, assisted with the evolution, formation, and visualization of membrane channel surfaces. We describe proton dynamics quantum mechanically via a new density functional theory based on the Boltzmann statistics, while implicitly model numerous solvent molecules as a dielectric continuum to reduce the number of degrees of freedom. The density of all other ions in the solvent is assumed to obey the Boltzmann distribution in a dynamic manner. The impact of protein molecular structure and its charge polarization on the proton transport is considered explicitly at the atomic scale. A variational solute-solvent interface is designed to separate the explicit molecule and implicit solvent regions. We formulate a total free-energy functional to put proton kinetic and potential energies, the free energy of all other ions, and the polar and nonpolar energies of the whole system on an equal footing. The variational principle is employed to derive coupled governing equations for the proton transport system. Generalized Laplace-Beltrami equation, generalized Poisson-Boltzmann equation, and generalized Kohn-Sham equation are obtained from the present variational framework. The variational solvent-solute interface is generated and visualized to facilitate the multiscale discrete/continuum/quantum descriptions. Theoretical formulations for the proton density and conductance are constructed based on fundamental laws of physics. A number of mathematical algorithms, including the Dirichlet-to-Neumann mapping, matched interface and boundary method, Gummel iteration, and Krylov space techniques are utilized to implement the proposed model in a computationally efficient manner. The gramicidin A channel is used to validate the performance of the proposed proton transport model and demonstrate the efficiency of the proposed mathematical algorithms. The proton channel conductances are studied over a number of applied voltages and reference concentrations. A comparison with experimental data verifies the present model predictions and confirms the proposed model. Copyright © 2011 John Wiley & Sons, Ltd.

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

A multiscale microstructural approach to ductile-phase toughened tungsten for plasma-facing materials

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

Nguyen, Ba Nghiep; Henager, Jr., Charles H.; Overman, Nicole R.

Increasing fracture toughness and modifying the ductile-brittle transition temperature of a tungsten-alloy relative to pure tungsten has been shown to be feasible by ductile-phase toughening (DPT) of tungsten for future plasma-facing materials for fusion energy. In DPT, a ductile phase is included in a brittle tungsten matrix to increase the overall work of fracture for the material. This research models the deformation behavior of DPT tungsten materials, such as tungsten-copper composites, using a multiscale modeling approach that involves a microstructural dual-phase (copper-tungsten) region of interest where the constituent phases are finely discretized and are described by a continuum damage mechanicsmore » model. Large deformation, damage, and fracture are allowed to occur and are modeled in a region that is connected to adjacent homogenized elastic regions to form a macroscopic structure, such as a test specimen. The present paper illustrates this multiscale modeling approach to analyze unnotched and single-edge notched (SENB) tungsten-copper composite specimens subjected to three-point bending. The predicted load-displacement responses and crack propagation patterns are compared to the corresponding experimental results to validate the model. Furthermore, such models may help design future DPT composite configurations for fusion materials, including volume fractions of ductile phase and microstructural optimization.« less

A multiscale microstructural approach to ductile-phase toughened tungsten for plasma-facing materials

DOE PAGES

Nguyen, Ba Nghiep; Henager, Jr., Charles H.; Overman, Nicole R.; ...

2018-05-23

Increasing fracture toughness and modifying the ductile-brittle transition temperature of a tungsten-alloy relative to pure tungsten has been shown to be feasible by ductile-phase toughening (DPT) of tungsten for future plasma-facing materials for fusion energy. In DPT, a ductile phase is included in a brittle tungsten matrix to increase the overall work of fracture for the material. This research models the deformation behavior of DPT tungsten materials, such as tungsten-copper composites, using a multiscale modeling approach that involves a microstructural dual-phase (copper-tungsten) region of interest where the constituent phases are finely discretized and are described by a continuum damage mechanicsmore » model. Large deformation, damage, and fracture are allowed to occur and are modeled in a region that is connected to adjacent homogenized elastic regions to form a macroscopic structure, such as a test specimen. The present paper illustrates this multiscale modeling approach to analyze unnotched and single-edge notched (SENB) tungsten-copper composite specimens subjected to three-point bending. The predicted load-displacement responses and crack propagation patterns are compared to the corresponding experimental results to validate the model. Furthermore, such models may help design future DPT composite configurations for fusion materials, including volume fractions of ductile phase and microstructural optimization.« less

New Developments in the Embedded Statistical Coupling Method: Atomistic/Continuum Crack Propagation

NASA Technical Reports Server (NTRS)

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

2008-01-01

A concurrent multiscale modeling methodology that embeds a molecular dynamics (MD) region within a finite element (FEM) domain has been enhanced. The concurrent MD-FEM coupling methodology uses statistical averaging of the deformation of the atomistic MD domain to provide interface displacement boundary conditions to the surrounding continuum FEM region, which, in turn, generates interface reaction forces that are applied as piecewise constant traction boundary conditions to the MD domain. The enhancement is based on the addition of molecular dynamics-based cohesive zone model (CZM) elements near the MD-FEM interface. The CZM elements are a continuum interpretation of the traction-displacement relationships taken from MD simulations using Cohesive Zone Volume Elements (CZVE). The addition of CZM elements to the concurrent MD-FEM analysis provides a consistent set of atomistically-based cohesive properties within the finite element region near the growing crack. Another set of CZVEs are then used to extract revised CZM relationships from the enhanced embedded statistical coupling method (ESCM) simulation of an edge crack under uniaxial loading.

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

Coarse-grained mechanics of viral shells

NASA Astrophysics Data System (ADS)

Klug, William S.; Gibbons, Melissa M.

2008-03-01

We present an approach for creating three-dimensional finite element models of viral capsids from atomic-level structural data (X-ray or cryo-EM). The models capture heterogeneous geometric features and are used in conjunction with three-dimensional nonlinear continuum elasticity to simulate nanoindentation experiments as performed using atomic force microscopy. The method is extremely flexible; able to capture varying levels of detail in the three-dimensional structure. Nanoindentation simulations are presented for several viruses: Hepatitis B, CCMV, HK97, and φ29. In addition to purely continuum elastic models a multiscale technique is developed that combines finite-element kinematics with MD energetics such that large-scale deformations are facilitated by a reduction in degrees of freedom. Simulations of these capsid deformation experiments provide a testing ground for the techniques, as well as insight into the strength-determining mechanisms of capsid deformation. These methods can be extended as a framework for modeling other proteins and macromolecular structures in cell biology.

Wavelet-based surrogate time series for multiscale simulation of heterogeneous catalysis

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

Savara, Aditya Ashi; Daw, C. Stuart; Xiong, Qingang

We propose a wavelet-based scheme that encodes the essential dynamics of discrete microscale surface reactions in a form that can be coupled with continuum macroscale flow simulations with high computational efficiency. This makes it possible to simulate the dynamic behavior of reactor-scale heterogeneous catalysis without requiring detailed concurrent simulations at both the surface and continuum scales using different models. Our scheme is based on the application of wavelet-based surrogate time series that encodes the essential temporal and/or spatial fine-scale dynamics at the catalyst surface. The encoded dynamics are then used to generate statistically equivalent, randomized surrogate time series, which canmore » be linked to the continuum scale simulation. As a result, we illustrate an application of this approach using two different kinetic Monte Carlo simulations with different characteristic behaviors typical for heterogeneous chemical reactions.« less

Wavelet-based surrogate time series for multiscale simulation of heterogeneous catalysis

DOE PAGES

Savara, Aditya Ashi; Daw, C. Stuart; Xiong, Qingang; ...

2016-01-28

We propose a wavelet-based scheme that encodes the essential dynamics of discrete microscale surface reactions in a form that can be coupled with continuum macroscale flow simulations with high computational efficiency. This makes it possible to simulate the dynamic behavior of reactor-scale heterogeneous catalysis without requiring detailed concurrent simulations at both the surface and continuum scales using different models. Our scheme is based on the application of wavelet-based surrogate time series that encodes the essential temporal and/or spatial fine-scale dynamics at the catalyst surface. The encoded dynamics are then used to generate statistically equivalent, randomized surrogate time series, which canmore » be linked to the continuum scale simulation. As a result, we illustrate an application of this approach using two different kinetic Monte Carlo simulations with different characteristic behaviors typical for heterogeneous chemical reactions.« less

Bottom-up modeling of damage in heterogeneous quasi-brittle solids

NASA Astrophysics Data System (ADS)

Rinaldi, Antonio

2013-03-01

The theoretical modeling of multisite cracking in quasi-brittle materials is a complex damage problem, hard to model with traditional methods of fracture mechanics due to its multiscale nature and to strain localization induced by microcracks interaction. Macroscale "effective" elastic models can be conveniently applied if a suitable Helmholtz free energy function is identified for a given material scenario. Del Piero and Truskinovsky (Continuum Mech Thermodyn 21:141-171, 2009), among other authors, investigated macroscale continuum solutions capable of matching—in a top-down view—the phenomenology of the damage process for quasi-brittle materials regardless of the microstructure. On the contrary, this paper features a physically based solution method that starts from the direct consideration of the microscale properties and, in a bottom-up view, recovers a continuum elastic description. This procedure is illustrated for a simple one-dimensional problem of this type, a bar modeled stretched by an axial displacement, where the bar is modeled as a 2D random lattice of decohesive spring elements of finite strength. The (microscale) data from simulations are used to identify the "exact" (macro-) damage parameter and to build up the (macro-) Helmholtz function for the equivalent elastic model, bridging the macroscale approach by Del Piero and Truskinovsky. The elastic approach, coupled with microstructural knowledge, becomes a more powerful tool to reproduce a broad class of macroscopic material responses by changing the convexity-concavity of the Helmholtz energy. The analysis points out that mean-field statistics are appropriate prior to damage localization but max-field statistics are better suited in the softening regime up to failure, where microstrain fluctuation needs to be incorporated in the continuum model. This observation is of consequence to revise mean-field damage models from literature and to calibrate Nth gradient continuum models.

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.

Continuum Multiscale Modeling of Finite Deformation Plasticity and Anisotropic Damage in Polycrystals

DTIC Science & Technology

2006-09-01

also been applied to describe degraded composite materials exhibiting a nominally elastic or viscoelastic response [7]. In brittle ceramics, scalar...assumptions regarding the composition of the material (e.g., crystal structure). 2.2. Stresses and balance relations Let s denote the local nominal...nickel (50 wt.%), iron (25 wt.%), and tungsten (25 wt.%). The composite microstructure nominally is comprised of 90% pure W and 10% matrix alloy, and

Virtual Design and Testing of Materials: A Multiscale Approach

DTIC Science & Technology

2006-06-30

Impurities in Aluminum and Their Effect on Mechanical Properties ", Phys. Rev. B 65, 064102 (2002). 21. G. Lu, V. Bulatov, and N. Kioussis, "Dislocation...materials: atomistic and continuum models with application to titanium - aluminides ", Phil. Mag. A 82, 2397-2417 (2002). 31. V.S. Deshpande, A. Needleman and...be used to test, and suggest design strategies for, new advanced structured materials. IS. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: Unclassified

Predicting the breakdown strength and lifetime of nanocomposites using a multi-scale modeling approach

NASA Astrophysics Data System (ADS)

Huang, Yanhui; Zhao, He; Wang, Yixing; Ratcliff, Tyree; Breneman, Curt; Brinson, L. Catherine; Chen, Wei; Schadler, Linda S.

2017-08-01

It has been found that doping dielectric polymers with a small amount of nanofiller or molecular additive can stabilize the material under a high field and lead to increased breakdown strength and lifetime. Choosing appropriate fillers is critical to optimizing the material performance, but current research largely relies on experimental trial and error. The employment of computer simulations for nanodielectric design is rarely reported. In this work, we propose a multi-scale modeling approach that employs ab initio, Monte Carlo, and continuum scales to predict the breakdown strength and lifetime of polymer nanocomposites based on the charge trapping effect of the nanofillers. The charge transfer, charge energy relaxation, and space charge effects are modeled in respective hierarchical scales by distinctive simulation techniques, and these models are connected together for high fidelity and robustness. The preliminary results show good agreement with the experimental data, suggesting its promise for use in the computer aided material design of high performance dielectrics.

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

NASA Astrophysics Data System (ADS)

Ray, Nadja; Rupp, Andreas; Prechtel, Alexander

2017-09-01

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

Differential porosimetry and permeametry for random porous media.

PubMed

Hilfer, R; Lemmer, A

2015-07-01

Accurate determination of geometrical and physical properties of natural porous materials is notoriously difficult. Continuum multiscale modeling has provided carefully calibrated realistic microstructure models of reservoir rocks with floating point accuracy. Previous measurements using synthetic microcomputed tomography (μ-CT) were based on extrapolation of resolution-dependent properties for discrete digitized approximations of the continuum microstructure. This paper reports continuum measurements of volume and specific surface with full floating point precision. It also corrects an incomplete description of rotations in earlier publications. More importantly, the methods of differential permeametry and differential porosimetry are introduced as precision tools. The continuum microstructure chosen to exemplify the methods is a homogeneous, carefully calibrated and characterized model for Fontainebleau sandstone. The sample has been publicly available since 2010 on the worldwide web as a benchmark for methodical studies of correlated random media. High-precision porosimetry gives the volume and internal surface area of the sample with floating point accuracy. Continuum results with floating point precision are compared to discrete approximations. Differential porosities and differential surface area densities allow geometrical fluctuations to be discriminated from discretization effects and numerical noise. Differential porosimetry and Fourier analysis reveal subtle periodic correlations. The findings uncover small oscillatory correlations with a period of roughly 850μm, thus implying that the sample is not strictly stationary. The correlations are attributed to the deposition algorithm that was used to ensure the grain overlap constraint. Differential permeabilities are introduced and studied. Differential porosities and permeabilities provide scale-dependent information on geometry fluctuations, thereby allowing quantitative error estimates.

Gating Mechanisms of Mechanosensitive Channels of Large Conductance, I: A Continuum Mechanics-Based Hierarchical Framework

PubMed Central

Chen, Xi; Cui, Qiang; Tang, Yuye; Yoo, Jejoong; Yethiraj, Arun

2008-01-01

A hierarchical simulation framework that integrates information from molecular dynamics (MD) simulations into a continuum model is established to study the mechanical response of mechanosensitive channel of large-conductance (MscL) using the finite element method (FEM). The proposed MD-decorated FEM (MDeFEM) approach is used to explore the detailed gating mechanisms of the MscL in Escherichia coli embedded in a palmitoyloleoylphosphatidylethanolamine lipid bilayer. In Part I of this study, the framework of MDeFEM is established. The transmembrane and cytoplasmic helices are taken to be elastic rods, the loops are modeled as springs, and the lipid bilayer is approximated by a three-layer sheet. The mechanical properties of the continuum components, as well as their interactions, are derived from molecular simulations based on atomic force fields. In addition, analytical closed-form continuum model and elastic network model are established to complement the MDeFEM approach and to capture the most essential features of gating. In Part II of this study, the detailed gating mechanisms of E. coli-MscL under various types of loading are presented and compared with experiments, structural model, and all-atom simulations, as well as the analytical models established in Part I. It is envisioned that such a hierarchical multiscale framework will find great value in the study of a variety of biological processes involving complex mechanical deformations such as muscle contraction and mechanotransduction. PMID:18390626

Multiscale Simulations of Dynamics of Ferroelectric Domains

NASA Astrophysics Data System (ADS)

Liu, Shi

Ferroelectrics with switchable polarization have many important technological applications, which heavily rely on the interactions between the polarization and external perturbations. Understanding the dynamical response of ferroelectric materials is crucial for the discovery and development of new design principles and engineering strategies for optimized and breakthrough applications of ferroelectrics. We developed a multiscale computational approach that combines methods at different length and time scales to elucidate the connection between local structures, domain dynamics, and macroscopic finite-temperature properties of ferroelectrics. We started from first-principles calculations of ferroelectrics to build a model interatomic potential, enabling large-scale molecular dynamics (MD) simulations. The atomistic insights of nucleation and growth at the domain wall obtained from MD were then incorporated into a continuum model within the framework of Landau-Ginzburg-Devonshire theory. This progressive theoretical framework allows for the first time an efficient and accurate estimation of macroscopic properties such as the coercive field for a broad range of ferroelectrics from first-principles. This multiscale approach has also been applied to explore the effect of dipolar defects on ferroelectric switching and to understand the origin of giant electro-strain coupling. ONR, NSF, Carnegie Institution for Science.

Coarse-Grained Models for Protein-Cell Membrane Interactions

PubMed Central

Bradley, Ryan; Radhakrishnan, Ravi

2015-01-01

The physiological properties of biological soft matter are the product of collective interactions, which span many time and length scales. Recent computational modeling efforts have helped illuminate experiments that characterize the ways in which proteins modulate membrane physics. Linking these models across time and length scales in a multiscale model explains how atomistic information propagates to larger scales. This paper reviews continuum modeling and coarse-grained molecular dynamics methods, which connect atomistic simulations and single-molecule experiments with the observed microscopic or mesoscale properties of soft-matter systems essential to our understanding of cells, particularly those involved in sculpting and remodeling cell membranes. PMID:26613047

Stress distribution retrieval in granular materials: A multi-scale model and digital image correlation measurements

NASA Astrophysics Data System (ADS)

Bruno, Luigi; Decuzzi, Paolo; Gentile, Francesco

2016-01-01

The promise of nanotechnology lies in the possibility of engineering matter on the nanoscale and creating technological interfaces that, because of their small scales, may directly interact with biological objects, creating new strategies for the treatment of pathologies that are otherwise beyond the reach of conventional medicine. Nanotechnology is inherently a multiscale, multiphenomena challenge. Fundamental understanding and highly accurate predictive methods are critical to successful manufacturing of nanostructured materials, bio/mechanical devices and systems. In biomedical engineering, and in the mechanical analysis of biological tissues, classical continuum approaches are routinely utilized, even if these disregard the discrete nature of tissues, that are an interpenetrating network of a matrix (the extra cellular matrix, ECM) and a generally large but finite number of cells with a size falling in the micrometer range. Here, we introduce a nano-mechanical theory that accounts for the-non continuum nature of bio systems and other discrete systems. This discrete field theory, doublet mechanics (DM), is a technique to model the mechanical behavior of materials over multiple scales, ranging from some millimeters down to few nanometers. In the paper, we use this theory to predict the response of a granular material to an external applied load. Such a representation is extremely attractive in modeling biological tissues which may be considered as a spatial set of a large number of particulate (cells) dispersed in an extracellular matrix. Possibly more important of this, using digital image correlation (DIC) optical methods, we provide an experimental verification of the model.

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

Zhang, Na; Zhang, Peng; Kang, Wei

Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters aremore » systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately.« less

Nonholonomic Hamiltonian Method for Meso-macroscale Simulations of Reacting Shocks

NASA Astrophysics Data System (ADS)

Fahrenthold, Eric; Lee, Sangyup

2015-06-01

The seamless integration of macroscale, mesoscale, and molecular scale models of reacting shock physics has been hindered by dramatic differences in the model formulation techniques normally used at different scales. In recent research the authors have developed the first unified discrete Hamiltonian approach to multiscale simulation of reacting shock physics. Unlike previous work, the formulation employs reacting themomechanical Hamiltonian formulations at all scales, including the continuum. Unlike previous work, the formulation employs a nonholonomic modeling approach to systematically couple the models developed at all scales. Example applications of the method show meso-macroscale shock to detonation simulations in nitromethane and RDX. Research supported by the Defense Threat Reduction Agency.

A mesoscopic bridging scale method for fluids and coupling dissipative particle dynamics with continuum finite element method

PubMed Central

Kojic, Milos; Filipovic, Nenad; Tsuda, Akira

2012-01-01

A multiscale procedure to couple a mesoscale discrete particle model and a macroscale continuum model of incompressible fluid flow is proposed in this study. We call this procedure the mesoscopic bridging scale (MBS) method since it is developed on the basis of the bridging scale method for coupling molecular dynamics and finite element models [G.J. Wagner, W.K. Liu, Coupling of atomistic and continuum simulations using a bridging scale decomposition, J. Comput. Phys. 190 (2003) 249–274]. We derive the governing equations of the MBS method and show that the differential equations of motion of the mesoscale discrete particle model and finite element (FE) model are only coupled through the force terms. Based on this coupling, we express the finite element equations which rely on the Navier–Stokes and continuity equations, in a way that the internal nodal FE forces are evaluated using viscous stresses from the mesoscale model. The dissipative particle dynamics (DPD) method for the discrete particle mesoscale model is employed. The entire fluid domain is divided into a local domain and a global domain. Fluid flow in the local domain is modeled with both DPD and FE method, while fluid flow in the global domain is modeled by the FE method only. The MBS method is suitable for modeling complex (colloidal) fluid flows, where continuum methods are sufficiently accurate only in the large fluid domain, while small, local regions of particular interest require detailed modeling by mesoscopic discrete particles. Solved examples – simple Poiseuille and driven cavity flows illustrate the applicability of the proposed MBS method. PMID:23814322

Multiscale framework for predicting the coupling between deformation and fluid diffusion in porous rocks

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

Andrade, José E; Rudnicki, John W

2012-12-14

In this project, a predictive multiscale framework will be developed to simulate the strong coupling between solid deformations and fluid diffusion in porous rocks. We intend to improve macroscale modeling by incorporating fundamental physical modeling at the microscale in a computationally efficient way. This is an essential step toward further developments in multiphysics modeling, linking hydraulic, thermal, chemical, and geomechanical processes. This research will focus on areas where severe deformations are observed, such as deformation bands, where classical phenomenology breaks down. Multiscale geometric complexities and key geomechanical and hydraulic attributes of deformation bands (e.g., grain sliding and crushing, and poremore » collapse, causing interstitial fluid expulsion under saturated conditions), can significantly affect the constitutive response of the skeleton and the intrinsic permeability. Discrete mechanics (DEM) and the lattice Boltzmann method (LBM) will be used to probe the microstructure---under the current state---to extract the evolution of macroscopic constitutive parameters and the permeability tensor. These evolving macroscopic constitutive parameters are then directly used in continuum scale predictions using the finite element method (FEM) accounting for the coupled solid deformation and fluid diffusion. A particularly valuable aspect of this research is the thorough quantitative verification and validation program at different scales. The multiscale homogenization framework will be validated using X-ray computed tomography and 3D digital image correlation in situ at the Advanced Photon Source in Argonne National Laboratories. Also, the hierarchical computations at the specimen level will be validated using the aforementioned techniques in samples of sandstone undergoing deformation bands.« less

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.

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

PubMed

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

2014-03-01

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

Free vibration analysis of single-walled boron nitride nanotubes based on a computational mechanics framework

NASA Astrophysics Data System (ADS)

Yan, J. W.; Tong, L. H.; Xiang, Ping

2017-12-01

Free vibration behaviors of single-walled boron nitride nanotubes are investigated using a computational mechanics approach. Tersoff-Brenner potential is used to reflect atomic interaction between boron and nitrogen atoms. The higher-order Cauchy-Born rule is employed to establish the constitutive relationship for single-walled boron nitride nanotubes on the basis of higher-order gradient continuum theory. It bridges the gaps between the nanoscale lattice structures with a continuum body. A mesh-free modeling framework is constructed, using the moving Kriging interpolation which automatically satisfies the higher-order continuity, to implement numerical simulation in order to match the higher-order constitutive model. In comparison with conventional atomistic simulation methods, the established atomistic-continuum multi-scale approach possesses advantages in tackling atomic structures with high-accuracy and high-efficiency. Free vibration characteristics of single-walled boron nitride nanotubes with different boundary conditions, tube chiralities, lengths and radii are examined in case studies. In this research, it is pointed out that a critical radius exists for the evaluation of fundamental vibration frequencies of boron nitride nanotubes; opposite trends can be observed prior to and beyond the critical radius. Simulation results are presented and discussed.

Experimental and Numerical Analysis of Hydroformed Tubular Materials for Superconducting Radio Frequency (SRF) Cavities

NASA Astrophysics Data System (ADS)

Kim, Hyun Sung

Superconducting radio frequency (SRF) cavities represent a well established technology benefiting from some 40 years of research and development. An increasing demand for electron and positron accelerators leads to a continuing interest in improved cavity performance and fabrication techniques. Therefore, several seamless cavity fabrication techniques have been proposed for eliminating the multitude of electron-beam welded seams that contribute to the introduction of performance-reducing defects. Among them, hydroforming using hydraulic pressure is a promising fabrication technique for producing the desired seamless cavities while at the same time reducing manufacturing cost. This study focused on experimental and numerical analysis of hydroformed niobium (Nb) tubes for the successful application of hydroforming technique to the seamless fabrication of multi-cell SRF cavities for particle acceleration. The heat treatment, tensile testing, and bulge testing of Cu and Nb tubes has been carried out to both provide starting data for models of hydroforming of Nb tube into seamless SRF cavities. Based on the results of these experiments, numerical analyses using finite element modeling were conducted for a bulge deformation of Cu and Nb. In the experimental part of the study samples removed from representative tubes were prepared for heat treatment, tensile testing, residual resistance ratio (RRR) measurement, and orientation imaging electron microscopy (OIM). After being optimally heat treated Cu and Nb tubes were subjected to hydraulic bulge testing and the results analyzed. For numerical analysis of hydroforming process, two different simulation approaches were used. The first model was the macro-scale continuum model using the constitutive equations (stress-strain relationship) as an input of the simulation. The constitutive equations were obtained from the experimental procedure including tensile and tube bulge tests in order to investigate the influence of loading condition on deformation behavior. The second model was a multi-scale model using both macroscopic continuum model and microscopic crystal plasticity (CP) model: First, the constitutive equation was obtained from the other microscopic simulation model (CP-FEM) using the microstructural information (i.e., orientation) of materials from the OIM and simple tensile test data. Continuum FE analysis based on the obtained constitutive equation using CP model were then fulfilled. Several conclusions can be drawn on the basis of the experimental and numerical analysis as follows: 1) The stress-strain relationship from the bulge test represents a more accurate description of the deformation behavior for a hydroforming than that from tensile tests made on segments cut from the tubular materials. 2) For anisotropic material, the incorporation of anisotropic effects using anisotropy coefficient from the tensile test led to even more accurate results. 3) A multi-scale simulation strategy using combination of continuum and CP models can give high quality predictions of the deformation under hydroforming of Cu and Nb tubes.

Parameterisation of multi-scale continuum perfusion models from discrete vascular networks.

PubMed

Hyde, Eoin R; Michler, Christian; Lee, Jack; Cookson, Andrew N; Chabiniok, Radek; Nordsletten, David A; Smith, Nicolas P

2013-05-01

Experimental data and advanced imaging techniques are increasingly enabling the extraction of detailed vascular anatomy from biological tissues. Incorporation of anatomical data within perfusion models is non-trivial, due to heterogeneous vessel density and disparate radii scales. Furthermore, previous idealised networks have assumed a spatially repeating motif or periodic canonical cell, thereby allowing for a flow solution via homogenisation. However, such periodicity is not observed throughout anatomical networks. In this study, we apply various spatial averaging methods to discrete vascular geometries in order to parameterise a continuum model of perfusion. Specifically, a multi-compartment Darcy model was used to provide vascular scale separation for the fluid flow. Permeability tensor fields were derived from both synthetic and anatomically realistic networks using (1) porosity-scaled isotropic, (2) Huyghe and Van Campen, and (3) projected-PCA methods. The Darcy pressure fields were compared via a root-mean-square error metric to an averaged Poiseuille pressure solution over the same domain. The method of Huyghe and Van Campen performed better than the other two methods in all simulations, even for relatively coarse networks. Furthermore, inter-compartment volumetric flux fields, determined using the spatially averaged discrete flux per unit pressure difference, were shown to be accurate across a range of pressure boundary conditions. This work justifies the application of continuum flow models to characterise perfusion resulting from flow in an underlying vascular network.

Parameterizing the Morse Potential for Coarse-Grained Modeling of Blood Plasma

PubMed Central

Zhang, Na; Zhang, Peng; Kang, Wei; Bluestein, Danny; Deng, Yuefan

2014-01-01

Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters are systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately. PMID:24910470

Bright breathers in nonlinear left-handed metamaterial lattices

NASA Astrophysics Data System (ADS)

Koukouloyannis, V.; Kevrekidis, P. G.; Veldes, G. P.; Frantzeskakis, D. J.; DiMarzio, D.; Lan, X.; Radisic, V.

2018-02-01

In the present work, we examine a prototypical model for the formation of bright breathers in nonlinear left-handed metamaterial lattices. Utilizing the paradigm of nonlinear transmission lines, we build a relevant lattice and develop a quasi-continuum multiscale approximation that enables us to appreciate both the underlying linear dispersion relation and the potential for bifurcation of nonlinear states. We focus here, more specifically, on bright discrete breathers which bifurcate from the lower edge of the linear dispersion relation at wavenumber k=π . Guided by the multiscale analysis, we calculate numerically both the stable inter-site centered and the unstable site-centered members of the relevant family. We quantify the associated stability via Floquet analysis and the Peierls-Nabarro barrier of the energy difference between these branches. Finally, we explore the dynamical implications of these findings towards the potential mobility or lack thereof (pinning) of such breather solutions.

On the Theory and Numerical Simulation of Cohesive Crack Propagation with Application to Fiber-Reinforced Composites

NASA Technical Reports Server (NTRS)

Rudraraju, Siva Shankar; Garikipati, Krishna; Waas, Anthony M.; Bednarcyk, Brett A.

2013-01-01

The phenomenon of crack propagation is among the predominant modes of failure in many natural and engineering structures, often leading to severe loss of structural integrity and catastrophic failure. Thus, the ability to understand and a priori simulate the evolution of this failure mode has been one of the cornerstones of applied mechanics and structural engineering and is broadly referred to as "fracture mechanics." The work reported herein focuses on extending this understanding, in the context of through-thickness crack propagation in cohesive materials, through the development of a continuum-level multiscale numerical framework, which represents cracks as displacement discontinuities across a surface of zero measure. This report presents the relevant theory, mathematical framework, numerical modeling, and experimental investigations of through-thickness crack propagation in fiber-reinforced composites using the Variational Multiscale Cohesive Method (VMCM) developed by the authors.

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

Microscopic and continuum descriptions of Janus motor fluid flow fields

PubMed Central

Reigh, Shang Yik; Schofield, Jeremy; Kapral, Raymond

2016-01-01

Active media, whose constituents are able to move autonomously, display novel features that differ from those of equilibrium systems. In addition to naturally occurring active systems such as populations of swimming bacteria, active systems of synthetic self-propelled nanomotors have been developed. These synthetic systems are interesting because of their potential applications in a variety of fields. Janus particles, synthetic motors of spherical geometry with one hemisphere that catalyses the conversion of fuel to product and one non-catalytic hemisphere, can propel themselves in solution by self-diffusiophoresis. In this mechanism, the concentration gradient generated by the asymmetric catalytic activity leads to a force on the motor that induces fluid flows in the surrounding medium. These fluid flows are studied in detail through microscopic simulations of Janus motor motion and continuum theory. It is shown that continuum theory is able to capture many, but not all, features of the dynamics of the Janus motor and the velocity fields of the fluid. This article is part of the themed issue ‘Multiscale modelling at the physics–chemistry–biology interface’. PMID:27698037

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

NASA Astrophysics Data System (ADS)

Xiao, Jie

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

Chondrocyte Deformations as a Function of Tibiofemoral Joint Loading Predicted by a Generalized High-Throughput Pipeline of Multi-Scale Simulations

PubMed Central

Sibole, Scott C.; Erdemir, Ahmet

2012-01-01

Cells of the musculoskeletal system are known to respond to mechanical loading and chondrocytes within the cartilage are not an exception. However, understanding how joint level loads relate to cell level deformations, e.g. in the cartilage, is not a straightforward task. In this study, a multi-scale analysis pipeline was implemented to post-process the results of a macro-scale finite element (FE) tibiofemoral joint model to provide joint mechanics based displacement boundary conditions to micro-scale cellular FE models of the cartilage, for the purpose of characterizing chondrocyte deformations in relation to tibiofemoral joint loading. It was possible to identify the load distribution within the knee among its tissue structures and ultimately within the cartilage among its extracellular matrix, pericellular environment and resident chondrocytes. Various cellular deformation metrics (aspect ratio change, volumetric strain, cellular effective strain and maximum shear strain) were calculated. To illustrate further utility of this multi-scale modeling pipeline, two micro-scale cartilage constructs were considered: an idealized single cell at the centroid of a 100×100×100 μm block commonly used in past research studies, and an anatomically based (11 cell model of the same volume) representation of the middle zone of tibiofemoral cartilage. In both cases, chondrocytes experienced amplified deformations compared to those at the macro-scale, predicted by simulating one body weight compressive loading on the tibiofemoral joint. In the 11 cell case, all cells experienced less deformation than the single cell case, and also exhibited a larger variance in deformation compared to other cells residing in the same block. The coupling method proved to be highly scalable due to micro-scale model independence that allowed for exploitation of distributed memory computing architecture. The method’s generalized nature also allows for substitution of any macro-scale and/or micro-scale model providing application for other multi-scale continuum mechanics problems. PMID:22649535

Multiscale modeling of lithium ion batteries: thermal aspects

PubMed Central

Zausch, Jochen

2015-01-01

Summary The thermal behavior of lithium ion batteries has a huge impact on their lifetime and the initiation of degradation processes. The development of hot spots or large local overpotentials leading, e.g., to lithium metal deposition depends on material properties as well as on the nano- und microstructure of the electrodes. In recent years a theoretical structure emerges, which opens the possibility to establish a systematic modeling strategy from atomistic to continuum scale to capture and couple the relevant phenomena on each scale. We outline the building blocks for such a systematic approach and discuss in detail a rigorous approach for the continuum scale based on rational thermodynamics and homogenization theories. Our focus is on the development of a systematic thermodynamically consistent theory for thermal phenomena in batteries at the microstructure scale and at the cell scale. We discuss the importance of carefully defining the continuum fields for being able to compare seemingly different phenomenological theories and for obtaining rules to determine unknown parameters of the theory by experiments or lower-scale theories. The resulting continuum models for the microscopic and the cell scale are numerically solved in full 3D resolution. The complex very localized distributions of heat sources in a microstructure of a battery and the problems of mapping these localized sources on an averaged porous electrode model are discussed by comparing the detailed 3D microstructure-resolved simulations of the heat distribution with the result of the upscaled porous electrode model. It is shown, that not all heat sources that exist on the microstructure scale are represented in the averaged theory due to subtle cancellation effects of interface and bulk heat sources. Nevertheless, we find that in special cases the averaged thermal behavior can be captured very well by porous electrode theory. PMID:25977870

Microscopic approach based on a multiscale algebraic version of the resonating group model for radiative capture reactions

NASA Astrophysics Data System (ADS)

Solovyev, Alexander S.; Igashov, Sergey Yu.

2017-12-01

A microscopic approach to description of radiative capture reactions based on a multiscale algebraic version of the resonating group model is developed. The main idea of the approach is to expand wave functions of discrete spectrum and continuum for a nuclear system over different bases of the algebraic version of the resonating group model. These bases differ from each other by values of oscillator radius playing a role of scale parameter. This allows us in a unified way to calculate total and partial cross sections (astrophysical S factors) as well as branching ratio for the radiative capture reaction, to describe phase shifts for the colliding nuclei in the initial channel of the reaction, and at the same time to reproduce breakup thresholds of the final nucleus. The approach is applied to the theoretical study of the mirror 3H(α ,γ )7Li and 3He(α ,γ )7Be reactions, which are of great interest to nuclear astrophysics. The calculated results are compared with existing experimental data and with our previous calculations in the framework of the single-scale algebraic version of the resonating group model.

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

A preliminary investigation of the growth of an aneurysm with a multiscale monolithic Fluid-Structure interaction solver

NASA Astrophysics Data System (ADS)

Cerroni, D.; Manservisi, S.; Pozzetti, G.

2015-11-01

In this work we investigate the potentialities of multi-scale engineering techniques to approach complex problems related to biomedical and biological fields. In particular we study the interaction between blood and blood vessel focusing on the presence of an aneurysm. The study of each component of the cardiovascular system is very difficult due to the fact that the movement of the fluid and solid is determined by the rest of system through dynamical boundary conditions. The use of multi-scale techniques allows us to investigate the effect of the whole loop on the aneurysm dynamic. A three-dimensional fluid-structure interaction model for the aneurysm is developed and coupled to a mono-dimensional one for the remaining part of the cardiovascular system, where a point zero-dimensional model for the heart is provided. In this manner it is possible to achieve rigorous and quantitative investigations of the cardiovascular disease without loosing the system dynamic. In order to study this biomedical problem we use a monolithic fluid-structure interaction (FSI) model where the fluid and solid equations are solved together. The use of a monolithic solver allows us to handle the convergence issues caused by large deformations. By using this monolithic approach different solid and fluid regions are treated as a single continuum and the interface conditions are automatically taken into account. In this way the iterative process characteristic of the commonly used segregated approach, it is not needed any more.

Simulating and mapping spatial complexity using multi-scale techniques

USGS Publications Warehouse

De Cola, L.

1994-01-01

A central problem in spatial analysis is the mapping of data for complex spatial fields using relatively simple data structures, such as those of a conventional GIS. This complexity can be measured using such indices as multi-scale variance, which reflects spatial autocorrelation, and multi-fractal dimension, which characterizes the values of fields. These indices are computed for three spatial processes: Gaussian noise, a simple mathematical function, and data for a random walk. Fractal analysis is then used to produce a vegetation map of the central region of California based on a satellite image. This analysis suggests that real world data lie on a continuum between the simple and the random, and that a major GIS challenge is the scientific representation and understanding of rapidly changing multi-scale fields. -Author

Hexagonal wavelet processing of digital mammography

NASA Astrophysics Data System (ADS)

Laine, Andrew F.; Schuler, Sergio; Huda, Walter; Honeyman-Buck, Janice C.; Steinbach, Barbara G.

1993-09-01

This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms and used to enhance features of importance to mammography within a continuum of scale-space. We present a method of contrast enhancement based on an overcomplete, non-separable multiscale representation: the hexagonal wavelet transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by local and global non-linear operators. Multiscale edges identified within distinct levels of transform space provide local support for enhancement. We demonstrate that features extracted from multiresolution representations can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification.

Multiscale modeling and simulation for nano/micro materials

NASA Astrophysics Data System (ADS)

Wang, Xianqiao

Continuum description and atomic description used to be two distinct methods in the community of modeling and simulations. Science and technology have become so advanced that our understanding of many physical phenomena involves the concepts of both. So our goal now is to build a bridge to make atoms and continua communicate with each other. Micromorphic theory (MMT) envisions a material body as a continuous collection of deformable particles; each possesses finite size and inner structure. It is considered as the most successful top-down formulation of a two-level continuum model to bridge the gap between the micro level and macro level. Therefore MMT can be expected to unveil many new classes of physical phenomena that fall beyond classical field theories. In this work, the constitutive equations for generalized Micromorphic thermoviscoelastic solid and generalized Micromorphic fluid have been formulated. To enlarge the domain of applicability of MMT, from nano, micro to macro, we take a bottom-up approach to re-derive the generalized atomistic field theory (AFT) comprehensively and completely and establish the relationship between AFT and MMT. Finite element (FE) method is then implemented to pursue the numerical solutions of the governing equations derived in AFT. When the finest mesh is used, i.e., the size of FE mesh is equal to the lattice constant of the material, the computational model becomes identical to molecular dynamics simulation. When a coarse mesh is used, the resulting model is a coarse-grained model, the majority of the degrees of freedom are eliminated and the computational cost is largely reduced. When the coarse mesh and finest mesh exist concurrently, i.e., the finest mesh is used in the critical regions and the coarser mesh is used in the far field, it leads naturally to a concurrent atomistic/continuum model. Atomic scale, coarse-grained scale and concurrent atomistic/continuum simulations have demonstrated the potential capability of AFT to simulate most grand challenging problems in nano/micro physics, and shown that AFT has the advantages of both atomic model and MMT. Therefore, AFT has accomplished the mission to bridge the gap between continuum mechanics and atomic physics.

Multi-scale kinetic description of granular clusters: invariance, balance, and temperature

NASA Astrophysics Data System (ADS)

Capriz, Gianfranco; Mariano, Paolo Maria

2017-12-01

We discuss a multi-scale continuum representation of bodies made of several mass particles flowing independently each other. From an invariance procedure and a nonstandard balance of inertial actions, we derive the balance equations introduced in earlier work directly in pointwise form, essentially on the basis of physical plausibility. In this way, we analyze their foundations. Then, we propose a Boltzmann-type equation for the distribution of kinetic energies within control volumes in space and indicate how such a distribution allows us to propose a definition of (granular) temperature along processes far from equilibrium.

Advances in modelling of biomimetic fluid flow at different scales

PubMed Central

2011-01-01

The biomimetic flow at different scales has been discussed at length. The need of looking into the biological surfaces and morphologies and both geometrical and physical similarities to imitate the technological products and processes has been emphasized. The complex fluid flow and heat transfer problems, the fluid-interface and the physics involved at multiscale and macro-, meso-, micro- and nano-scales have been discussed. The flow and heat transfer simulation is done by various CFD solvers including Navier-Stokes and energy equations, lattice Boltzmann method and molecular dynamics method. Combined continuum-molecular dynamics method is also reviewed. PMID:21711847

Multiscale modeling of a rectifying bipolar nanopore: Comparing Poisson-Nernst-Planck to Monte Carlo

NASA Astrophysics Data System (ADS)

Matejczyk, Bartłomiej; Valiskó, Mónika; Wolfram, Marie-Therese; Pietschmann, Jan-Frederik; Boda, Dezső

2017-03-01

In the framework of a multiscale modeling approach, we present a systematic study of a bipolar rectifying nanopore using a continuum and a particle simulation method. The common ground in the two methods is the application of the Nernst-Planck (NP) equation to compute ion transport in the framework of the implicit-water electrolyte model. The difference is that the Poisson-Boltzmann theory is used in the Poisson-Nernst-Planck (PNP) approach, while the Local Equilibrium Monte Carlo (LEMC) method is used in the particle simulation approach (NP+LEMC) to relate the concentration profile to the electrochemical potential profile. Since we consider a bipolar pore which is short and narrow, we perform simulations using two-dimensional PNP. In addition, results of a non-linear version of PNP that takes crowding of ions into account are shown. We observe that the mean field approximation applied in PNP is appropriate to reproduce the basic behavior of the bipolar nanopore (e.g., rectification) for varying parameters of the system (voltage, surface charge, electrolyte concentration, and pore radius). We present current data that characterize the nanopore's behavior as a device, as well as concentration, electrical potential, and electrochemical potential profiles.

Rapid freezing of water under dynamic compression

NASA Astrophysics Data System (ADS)

Myint, Philip C.; Belof, Jonathan L.

2018-06-01

Understanding the behavior of materials at extreme pressures is a central issue in fields like aerodynamics, astronomy, and geology, as well as for advancing technological grand challenges such as inertial confinement fusion. Dynamic compression experiments to probe high-pressure states often encounter rapid phase transitions that may cause the materials to behave in unexpected ways, and understanding the kinetics of these phase transitions remains an area of great interest. In this review, we examine experimental and theoretical/computational efforts to study the freezing kinetics of water to a high-pressure solid phase known as ice VII. We first present a detailed analysis of dynamic compression experiments in which water has been observed to freeze on sub-microsecond time scales to ice VII. This is followed by a discussion of the limitations of currently available molecular and continuum simulation methods in modeling these experiments. We then describe how our phase transition kinetics models, which are based on classical nucleation theory, provide a more physics-based framework that overcomes some of these limitations. Finally, we give suggestions on future experimental and modeling work on the liquid–ice VII transition, including an outline of the development of a predictive multiscale model in which molecular and continuum simulations are intimately coupled.

Rapid freezing of water under dynamic compression.

PubMed

Myint, Philip C; Belof, Jonathan L

2018-06-13

Understanding the behavior of materials at extreme pressures is a central issue in fields like aerodynamics, astronomy, and geology, as well as for advancing technological grand challenges such as inertial confinement fusion. Dynamic compression experiments to probe high-pressure states often encounter rapid phase transitions that may cause the materials to behave in unexpected ways, and understanding the kinetics of these phase transitions remains an area of great interest. In this review, we examine experimental and theoretical/computational efforts to study the freezing kinetics of water to a high-pressure solid phase known as ice VII. We first present a detailed analysis of dynamic compression experiments in which water has been observed to freeze on sub-microsecond time scales to ice VII. This is followed by a discussion of the limitations of currently available molecular and continuum simulation methods in modeling these experiments. We then describe how our phase transition kinetics models, which are based on classical nucleation theory, provide a more physics-based framework that overcomes some of these limitations. Finally, we give suggestions on future experimental and modeling work on the liquid-ice VII transition, including an outline of the development of a predictive multiscale model in which molecular and continuum simulations are intimately coupled.

Cohesive zone model for direct silicon wafer bonding

NASA Astrophysics Data System (ADS)

Kubair, D. V.; Spearing, S. M.

2007-05-01

Direct silicon wafer bonding and decohesion are simulated using a spectral scheme in conjunction with a rate-dependent cohesive model. The cohesive model is derived assuming the presence of a thin continuum liquid layer at the interface. Cohesive tractions due to the presence of a liquid meniscus always tend to reduce the separation distance between the wafers, thereby opposing debonding, while assisting the bonding process. In the absence of the rate-dependence effects the energy needed to bond a pair of wafers is equal to that needed to separate them. When rate-dependence is considered in the cohesive law, the experimentally observed asymmetry in the energetics can be explained. The derived cohesive model has the potential to form a bridge between experiments and a multiscale-modelling approach to understand the mechanics of wafer bonding.

Adaptive multiscale processing for contrast enhancement

NASA Astrophysics Data System (ADS)

Laine, Andrew F.; Song, Shuwu; Fan, Jian; Huda, Walter; Honeyman, Janice C.; Steinbach, Barbara G.

1993-07-01

This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms within a continuum of scale space and used to enhance features of importance to mammography. Choosing analyzing functions that are well localized in both space and frequency, results in a powerful methodology for image analysis. We describe methods of contrast enhancement based on two overcomplete (redundant) multiscale representations: (1) Dyadic wavelet transform (2) (phi) -transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by non-linear, logarithmic and constant scale-space weight functions. Multiscale edges identified within distinct levels of transform space provide a local support for enhancement throughout each decomposition. We demonstrate that features extracted from wavelet spaces can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification.

Multi-scale Multi-mechanism Toughening of Hydrogels

NASA Astrophysics Data System (ADS)

Zhao, Xuanhe

Hydrogels are widely used as scaffolds for tissue engineering, vehicles for drug delivery, actuators for optics and fluidics, and model extracellular matrices for biological studies. The scope of hydrogel applications, however, is often severely limited by their mechanical properties. Inspired by the mechanics and hierarchical structures of tough biological tissues, we propose that a general principle for the design of tough hydrogels is to implement two mechanisms for dissipating mechanical energy and maintaining high elasticity in hydrogels. A particularly promising strategy for the design is to integrate multiple pairs of mechanisms across multiple length scales into a hydrogel. We develop a multiscale theoretical framework to quantitatively guide the design of tough hydrogels. On the network level, we have developed micro-physical models to characterize the evolution of polymer networks under deformation. On the continuum level, we have implemented constitutive laws formulated from the network-level models into a coupled cohesive-zone and Mullins-effect model to quantitatively predict crack propagation and fracture toughness of hydrogels. Guided by the design principle and quantitative model, we will demonstrate a set of new hydrogels, based on diverse types of polymers, yet can achieve extremely high toughness superior to their natural counterparts such as cartilages. The work was supported by NSF(No. CMMI- 1253495) and ONR (No. N00014-14-1-0528).

Predicting electromyographic signals under realistic conditions using a multiscale chemo-electro-mechanical finite element model.

PubMed

Mordhorst, Mylena; Heidlauf, Thomas; Röhrle, Oliver

2015-04-06

This paper presents a novel multiscale finite element-based framework for modelling electromyographic (EMG) signals. The framework combines (i) a biophysical description of the excitation-contraction coupling at the half-sarcomere level, (ii) a model of the action potential (AP) propagation along muscle fibres, (iii) a continuum-mechanical formulation of force generation and deformation of the muscle, and (iv) a model for predicting the intramuscular and surface EMG. Owing to the biophysical description of the half-sarcomere, the model inherently accounts for physiological properties of skeletal muscle. To demonstrate this, the influence of membrane fatigue on the EMG signal during sustained contractions is investigated. During a stimulation period of 500 ms at 100 Hz, the predicted EMG amplitude decreases by 40% and the AP propagation velocity decreases by 15%. Further, the model can take into account contraction-induced deformations of the muscle. This is demonstrated by simulating fixed-length contractions of an idealized geometry and a model of the human tibialis anterior muscle (TA). The model of the TA furthermore demonstrates that the proposed finite element model is capable of simulating realistic geometries, complex fibre architectures, and can include different types of heterogeneities. In addition, the TA model accounts for a distributed innervation zone, different fibre types and appeals to motor unit discharge times that are based on a biophysical description of the α motor neurons.

Predicting electromyographic signals under realistic conditions using a multiscale chemo–electro–mechanical finite element model

PubMed Central

Mordhorst, Mylena; Heidlauf, Thomas; Röhrle, Oliver

2015-01-01

This paper presents a novel multiscale finite element-based framework for modelling electromyographic (EMG) signals. The framework combines (i) a biophysical description of the excitation–contraction coupling at the half-sarcomere level, (ii) a model of the action potential (AP) propagation along muscle fibres, (iii) a continuum-mechanical formulation of force generation and deformation of the muscle, and (iv) a model for predicting the intramuscular and surface EMG. Owing to the biophysical description of the half-sarcomere, the model inherently accounts for physiological properties of skeletal muscle. To demonstrate this, the influence of membrane fatigue on the EMG signal during sustained contractions is investigated. During a stimulation period of 500 ms at 100 Hz, the predicted EMG amplitude decreases by 40% and the AP propagation velocity decreases by 15%. Further, the model can take into account contraction-induced deformations of the muscle. This is demonstrated by simulating fixed-length contractions of an idealized geometry and a model of the human tibialis anterior muscle (TA). The model of the TA furthermore demonstrates that the proposed finite element model is capable of simulating realistic geometries, complex fibre architectures, and can include different types of heterogeneities. In addition, the TA model accounts for a distributed innervation zone, different fibre types and appeals to motor unit discharge times that are based on a biophysical description of the α motor neurons. PMID:25844148

Localized Scale Coupling and New Educational Paradigms in Multiscale Mathematics and Science

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

LEAL, L. GARY

2013-06-30

One of the most challenging multi-scale simulation problems in the area of multi-phase materials is to develop effective computational techniques for the prediction of coalescence and related phenomena involving rupture of a thin liquid film due to the onset of instability driven by van der Waals or other micro-scale attractive forces. Accurate modeling of this process is critical to prediction of the outcome of milling processes for immiscible polymer blends, one of the most important routes to new advanced polymeric materials. In typical situations, the blend evolves into an ?emulsion? of dispersed phase drops in a continuous matrix fluid. Coalescencemore » is then a critical factor in determining the size distribution of the dispersed phase, but is extremely difficult to predict from first principles. The thin film separating two drops may only achieve rupture at dimensions of approximately 10 nm while the drop sizes are 0(10 ?m). It is essential to achieve very accurate solutions for the flow and for the interface shape at both the macroscale of the full drops, and within the thin film (where the destabilizing disjoining pressure due to van der Waals forces is proportional approximately to the inverse third power of the local film thickness, h-3). Furthermore, the fluids of interest are polymeric (through Newtonian) and the classical continuum description begins to fail as the film thins ? requiring incorporation of molecular effects, such as a hybrid code that incorporates a version of coarse grain molecular dynamics within the thin film coupled with a classical continuum description elsewhere in the flow domain. Finally, the presence of surface active additions, either surfactants (in the form of di-block copolymers) or surface-functionalized micro- or nano-scale particles, adds an additional level of complexity, requiring development of a distinct numerical method to predict the nonuniform concentration gradients of these additives that are responsible for Marangoni stresses at the interface. Again, the physical dimensions of these additives may become comparable to the thin film dimensions, requiring an additional layer of multi-scale modeling.« less

Physically based multiscale-viscoplastic model for metals and steel alloys: Theory and computation

NASA Astrophysics Data System (ADS)

Abed, Farid H.

The main requirement of large deformation problems such as high-speed machining, impact, and various primarily metal forming, is to develop constitutive relations which are widely applicable and capable of accounting for complex paths of deformation. Achieving such desirable goals for material like metals and steel alloys involves a comprehensive study of their microstructures and experimental observations under different loading conditions. In general, metal structures display a strong rate- and temperature-dependence when deformed non-uniformly into the inelastic range. This effect has important implications for an increasing number of applications in structural and engineering mechanics. The mechanical behavior of these applications cannot be characterized by classical (rate-independent) continuum theories because they incorporate no 'material length scales'. It is therefore necessary to develop a rate-dependent (viscoplasticity) continuum theory bridging the gap between the classical continuum theories and the microstructure simulations. Physically based vicoplasticity models for different types of metals (body centered cubic, face centered cubic and hexagonal close-packed) and steel alloys are derived in this work for this purpose. We adopt a multi-scale, hierarchical thermodynamic consistent framework to construct the material constitutive relations for the rate-dependent behavior. The concept of thermal activation energy, dislocations interactions mechanisms and the role of dislocations dynamics in crystals are used in the derivation process taking into consideration the contribution of the plastic strain evolution of dislocation density to the flow stress of polycrystalline metals. Material length scales are implicitly introduced into the governing equations through material rate-dependency (viscosity). The proposed framework is implemented into the commercially well-known finite element software ABAQUS. The finite element simulations of material instability problems converge to meaningful results upon further refinement of the finite element mesh due to the successful incorporation of the material length scale in the model formulations. It is shown that the model predicted results compare very well with different experimental data over a wide range of temperatures (77K°-1000K°) and strain rates (10-3-10 4s-1). It is also concluded from this dissertation that the width of localization zone (shear band) exhibits tremendous changes with different initial temperatures (i.e., different initial viscosities and accordingly different length scales).

Multiscale Transient and Steady-State Study of the Influence of Microstructure Degradation and Chromium Oxide Poisoning on Solid Oxide Fuel Cell Cathode Performance

NASA Astrophysics Data System (ADS)

Li, Guanchen; von Spakovsky, Michael R.; Shen, Fengyu; Lu, Kathy

2018-01-01

Oxygen reduction in a solid oxide fuel cell cathode involves a nonequilibrium process of coupled mass and heat diffusion and electrochemical and chemical reactions. These phenomena occur at multiple temporal and spatial scales, making the modeling, especially in the transient regime, very difficult. Nonetheless, multiscale models are needed to improve the understanding of oxygen reduction and guide cathode design. Of particular importance for long-term operation are microstructure degradation and chromium oxide poisoning both of which degrade cathode performance. Existing methods are phenomenological or empirical in nature and their application limited to the continuum realm with quantum effects not captured. In contrast, steepest-entropy-ascent quantum thermodynamics can be used to model nonequilibrium processes (even those far-from equilibrium) at all scales. The nonequilibrium relaxation is characterized by entropy generation, which can unify coupled phenomena into one framework to model transient and steady behavior. The results reveal the effects on performance of the different timescales of the varied phenomena involved and their coupling. Results are included here for the effects of chromium oxide concentrations on cathode output as is a parametric study of the effects of interconnect-three-phase-boundary length, oxygen mean free path, and adsorption site effectiveness. A qualitative comparison with experimental results is made.

Combining cellular automata and Lattice Boltzmann method to model multiscale avascular tumor growth coupled with nutrient diffusion and immune competition.

PubMed

Alemani, Davide; Pappalardo, Francesco; Pennisi, Marzio; Motta, Santo; Brusic, Vladimir

2012-02-28

In the last decades the Lattice Boltzmann method (LB) has been successfully used to simulate a variety of processes. The LB model describes the microscopic processes occurring at the cellular level and the macroscopic processes occurring at the continuum level with a unique function, the probability distribution function. Recently, it has been tried to couple deterministic approaches with probabilistic cellular automata (probabilistic CA) methods with the aim to model temporal evolution of tumor growths and three dimensional spatial evolution, obtaining hybrid methodologies. Despite the good results attained by CA-PDE methods, there is one important issue which has not been completely solved: the intrinsic stochastic nature of the interactions at the interface between cellular (microscopic) and continuum (macroscopic) level. CA methods are able to cope with the stochastic phenomena because of their probabilistic nature, while PDE methods are fully deterministic. Even if the coupling is mathematically correct, there could be important statistical effects that could be missed by the PDE approach. For such a reason, to be able to develop and manage a model that takes into account all these three level of complexity (cellular, molecular and continuum), we believe that PDE should be replaced with a statistic and stochastic model based on the numerical discretization of the Boltzmann equation: The Lattice Boltzmann (LB) method. In this work we introduce a new hybrid method to simulate tumor growth and immune system, by applying Cellular Automata Lattice Boltzmann (CA-LB) approach. Copyright © 2011 Elsevier B.V. All rights reserved.

Anatomically realistic multiscale models of normal and abnormal gastrointestinal electrical activity

PubMed Central

Cheng, Leo K; Komuro, Rie; Austin, Travis M; Buist, Martin L; Pullan, Andrew J

2007-01-01

One of the major aims of the International Union of Physiological Sciences (IUPS) Physiome Project is to develop multiscale mathematical and computer models that can be used to help understand human health. We present here a small facet of this broad plan that applies to the gastrointestinal system. Specifically, we present an anatomically and physiologically based modelling framework that is capable of simulating normal and pathological electrical activity within the stomach and small intestine. The continuum models used within this framework have been created using anatomical information derived from common medical imaging modalities and data from the Visible Human Project. These models explicitly incorporate the various smooth muscle layers and networks of interstitial cells of Cajal (ICC) that are known to exist within the walls of the stomach and small bowel. Electrical activity within individual ICCs and smooth muscle cells is simulated using a previously published simplified representation of the cell level electrical activity. This simulated cell level activity is incorporated into a bidomain representation of the tissue, allowing electrical activity of the entire stomach or intestine to be simulated in the anatomically derived models. This electrical modelling framework successfully replicates many of the qualitative features of the slow wave activity within the stomach and intestine and has also been used to investigate activity associated with functional uncoupling of the stomach. PMID:17457969

Fluid-Driven Deformation of a Soft Granular Material

NASA Astrophysics Data System (ADS)

MacMinn, Christopher W.; Dufresne, Eric R.; Wettlaufer, John S.

2015-01-01

Compressing a porous, fluid-filled material drives the interstitial fluid out of the pore space, as when squeezing water out of a kitchen sponge. Inversely, injecting fluid into a porous material can deform the solid structure, as when fracturing a shale for natural gas recovery. These poromechanical interactions play an important role in geological and biological systems across a wide range of scales, from the propagation of magma through Earth's mantle to the transport of fluid through living cells and tissues. The theory of poroelasticity has been largely successful in modeling poromechanical behavior in relatively simple systems, but this continuum theory is fundamentally limited by our understanding of the pore-scale interactions between the fluid and the solid, and these problems are notoriously difficult to study in a laboratory setting. Here, we present a high-resolution measurement of injection-driven poromechanical deformation in a system with granular microsctructure: We inject fluid into a dense, confined monolayer of soft particles and use particle tracking to reveal the dynamics of the multiscale deformation field. We find that a continuum model based on poroelasticity theory captures certain macroscopic features of the deformation, but the particle-scale deformation field exhibits dramatic departures from smooth, continuum behavior. We observe particle-scale rearrangement and hysteresis, as well as petal-like mesoscale structures that are connected to material failure through spiral shear banding.

Molecular dynamics simulations in hybrid particle-continuum schemes: Pitfalls and caveats

NASA Astrophysics Data System (ADS)

Stalter, S.; Yelash, L.; Emamy, N.; Statt, A.; Hanke, M.; Lukáčová-Medvid'ová, M.; Virnau, P.

2018-03-01

Heterogeneous multiscale methods (HMM) combine molecular accuracy of particle-based simulations with the computational efficiency of continuum descriptions to model flow in soft matter liquids. In these schemes, molecular simulations typically pose a computational bottleneck, which we investigate in detail in this study. We find that it is preferable to simulate many small systems as opposed to a few large systems, and that a choice of a simple isokinetic thermostat is typically sufficient while thermostats such as Lowe-Andersen allow for simulations at elevated viscosity. We discuss suitable choices for time steps and finite-size effects which arise in the limit of very small simulation boxes. We also argue that if colloidal systems are considered as opposed to atomistic systems, the gap between microscopic and macroscopic simulations regarding time and length scales is significantly smaller. We propose a novel reduced-order technique for the coupling to the macroscopic solver, which allows us to approximate a non-linear stress-strain relation efficiently and thus further reduce computational effort of microscopic simulations.

Optical characterization of multi-scale morphologically complex heterogeneous media - Application to snow with soot impurities

NASA Astrophysics Data System (ADS)

Dai, Xiaoyu; Haussener, Sophia

2018-02-01

A multi-scale methodology for the radiative transfer analysis of heterogeneous media composed of morphologically-complex components on two distinct scales is presented. The methodology incorporates the exact morphology at the various scales and utilizes volume-averaging approaches with the corresponding effective properties to couple the scales. At the continuum level, the volume-averaged coupled radiative transfer equations are solved utilizing (i) effective radiative transport properties obtained by direct Monte Carlo simulations at the pore level, and (ii) averaged bulk material properties obtained at particle level by Lorenz-Mie theory or discrete dipole approximation calculations. This model is applied to a soot-contaminated snow layer, and is experimentally validated with reflectance measurements of such layers. A quantitative and decoupled understanding of the morphological effect on the radiative transport is achieved, and a significant influence of the dual-scale morphology on the macroscopic optical behavior is observed. Our results show that with a small amount of soot particles, of the order of 1ppb in volume fraction, the reduction in reflectance of a snow layer with large ice grains can reach up to 77% (at a wavelength of 0.3 μm). Soot impurities modeled as compact agglomerates yield 2-3% lower reduction of the reflectance in a thick show layer compared to snow with soot impurities modeled as chain-like agglomerates. Soot impurities modeled as equivalent spherical particles underestimate the reflectance reduction by 2-8%. This study implies that the morphology of the heterogeneities in a media significantly affects the macroscopic optical behavior and, specifically for the soot-contaminated snow, indicates the non-negligible role of soot on the absorption behavior of snow layers. It can be equally used in technical applications for the assessment and optimization of optical performance in multi-scale media.

Multiscale Static Analysis of Notched and Unnotched Laminates Using the Generalized Method of Cells

NASA Technical Reports Server (NTRS)

Naghipour Ghezeljeh, Paria; Arnold, Steven M.; Pineda, Evan J.; Stier, Bertram; Hansen, Lucas; Bednarcyk, Brett A.; Waas, Anthony M.

2016-01-01

The generalized method of cells (GMC) is demonstrated to be a viable micromechanics tool for predicting the deformation and failure response of laminated composites, with and without notches, subjected to tensile and compressive static loading. Given the axial [0], transverse [90], and shear [+45/-45] response of a carbon/epoxy (IM7/977-3) system, the unnotched and notched behavior of three multidirectional layups (Layup 1: [0,45,90,-45](sub 2S), Layup 2: [0,60,0](sub 3S), and Layup 3: [30,60,90,-30, -60](sub 2S)) are predicted under both tensile and compressive static loading. Matrix nonlinearity is modeled in two ways. The first assumes all nonlinearity is due to anisotropic progressive damage of the matrix only, which is modeled, using the multiaxial mixed-mode continuum damage model (MMCDM) within GMC. The second utilizes matrix plasticity coupled with brittle final failure based on the maximum principle strain criteria to account for matrix nonlinearity and failure within the Finite Element Analysis--Micromechanics Analysis Code (FEAMAC) software multiscale framework. Both MMCDM and plasticity models incorporate brittle strain- and stress-based failure criteria for the fiber. Upon satisfaction of these criteria, the fiber properties are immediately reduced to a nominal value. The constitutive response for each constituent (fiber and matrix) is characterized using a combination of vendor data and the axial, transverse, and shear responses of unnotched laminates. Then, the capability of the multiscale methodology is assessed by performing blind predictions of the mentioned notched and unnotched composite laminates response under tensile and compressive loading. Tabulated data along with the detailed results (i.e., stress-strain curves as well as damage evolution states at various ratios of strain to failure) for all laminates are presented.

Elastic Response and Failure Studies of Multi-Wall Carbon Nanotube Twisted Yarns

NASA Technical Reports Server (NTRS)

Gates, Thomas S.; Jefferson, Gail D.; Frankland, Sarah-Jane V.

2007-01-01

Experimental data on the stress-strain behavior of a polymer multiwall carbon nanotube (MWCNT) yarn composite are used to motivate an initial study in multi-scale modeling of strength and stiffness. Atomistic and continuum length scale modeling methods are outlined to illustrate the range of parameters required to accurately model behavior. The carbon nanotubes yarns are four-ply, twisted, and combined with an elastomer to form a single-layer, unidirectional composite. Due to this textile structure, the yarn is a complicated system of unique geometric relationships subjected to combined loads. Experimental data illustrate the local failure modes induced by static, tensile tests. Key structure-property relationships are highlighted at each length scale indicating opportunities for parametric studies to assist the selection of advantageous material development and manufacturing methods.

Numerical study of multiscale compaction-initiated detonation

NASA Astrophysics Data System (ADS)

Gambino, J. R.; Schwendeman, D. W.; Kapila, A. K.

2018-02-01

A multiscale model of heterogeneous condensed-phase explosives is examined computationally to determine the course of transient events following the application of a piston-driven stimulus. The model is a modified version of that introduced by Gonthier (Combust Sci Technol 175(9):1679-1709, 2003. https://doi.org/10.1080/00102200302373) in which the explosive is treated as a porous, compacting medium at the macro-scale and a collection of closely packed spherical grains capable of undergoing reaction and diffusive heat transfer at the meso-scale. A separate continuum description is ascribed to each scale, and the two scales are coupled together in an energetically consistent manner. Following piston-induced compaction, localized energy deposition at the sites of intergranular contact creates hot spots where reaction begins preferentially. Reaction progress at the macro-scale is determined by the spatial average of that at the grain scale. A parametric study shows that combustion at the macro-scale produces an unsteady detonation with a cyclical character, in which the lead shock loses strength and is overtaken by a stronger secondary shock generated in the partially reacted material behind it. The secondary shock in turn becomes the new lead shock and the process repeats itself.

Multiscale modeling of a rectifying bipolar nanopore: Comparing Poisson-Nernst-Planck to Monte Carlo.

PubMed

Matejczyk, Bartłomiej; Valiskó, Mónika; Wolfram, Marie-Therese; Pietschmann, Jan-Frederik; Boda, Dezső

2017-03-28

In the framework of a multiscale modeling approach, we present a systematic study of a bipolar rectifying nanopore using a continuum and a particle simulation method. The common ground in the two methods is the application of the Nernst-Planck (NP) equation to compute ion transport in the framework of the implicit-water electrolytemodel. The difference is that the Poisson-Boltzmann theory is used in the Poisson-Nernst-Planck (PNP) approach, while the Local Equilibrium Monte Carlo (LEMC) method is used in the particle simulation approach (NP+LEMC) to relate the concentration profile to the electrochemical potential profile. Since we consider a bipolar pore which is short and narrow, we perform simulations using two-dimensional PNP. In addition, results of a non-linear version of PNP that takes crowding of ions into account are shown. We observe that the mean field approximation applied in PNP is appropriate to reproduce the basic behavior of the bipolar nanopore (e.g., rectification) for varying parameters of the system (voltage, surface charge,electrolyte concentration, and pore radius). We present current data that characterize the nanopore's behavior as a device, as well as concentration, electrical potential, and electrochemical potential profiles.

A multiscale SPH particle model of the near-wall dynamics of leukocytes in flow.

PubMed

Gholami, Babak; Comerford, Andrew; Ellero, Marco

2014-01-01

A novel multiscale Lagrangian particle solver based on SPH is developed with the intended application of leukocyte transport in large arteries. In such arteries, the transport of leukocytes and red blood cells can be divided into two distinct regions: the bulk flow and the near-wall region. In the bulk flow, the transport can be modeled on a continuum basis as the transport of passive scalar concentrations. Whereas in the near-wall region, specific particle tracking of the leukocytes is required and lubrication forces need to be separately taken into account. Because of large separation of spatio-temporal scales involved in the problem, simulations of red blood cells and leukocytes are handled separately. In order to take the exchange of leukocytes between the bulk fluid and the near-wall region into account, solutions are communicated through coupling of conserved quantities at the interface between these regions. Because the particle tracking is limited to those leukocytes lying in the near-wall region only, our approach brings considerable speedup to the simulation of leukocyte circulation in a test geometry of a backward-facing step, which encompasses many flow features observed in vivo. Copyright © 2013 John Wiley & Sons, Ltd.

Multiscale modeling and simulation of microtubule-motor-protein assemblies

NASA Astrophysics Data System (ADS)

Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; Betterton, M. D.; Shelley, Michael J.

2015-12-01

Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate-consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation.

Multiscale modeling and simulation of microtubule-motor-protein assemblies.

PubMed

Gao, Tong; Blackwell, Robert; Glaser, Matthew A; Betterton, M D; Shelley, Michael J

2015-01-01

Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate-consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation.

Multiscale modeling and simulation of microtubule–motor-protein assemblies

PubMed Central

Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; Betterton, M. D.; Shelley, Michael J.

2016-01-01

Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate–consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation. PMID:26764729

Developing Higher-Order Materials Knowledge Systems

NASA Astrophysics Data System (ADS)

Fast, Anthony Nathan

2011-12-01

Advances in computational materials science and novel characterization techniques have allowed scientists to probe deeply into a diverse range of materials phenomena. These activities are producing enormous amounts of information regarding the roles of various hierarchical material features in the overall performance characteristics displayed by the material. Connecting the hierarchical information over disparate domains is at the crux of multiscale modeling. The inherent challenge of performing multiscale simulations is developing scale bridging relationships to couple material information between well separated length scales. Much progress has been made in the development of homogenization relationships which replace heterogeneous material features with effective homogenous descriptions. These relationships facilitate the flow of information from lower length scales to higher length scales. Meanwhile, most localization relationships that link the information from a from a higher length scale to a lower length scale are plagued by computationally intensive techniques which are not readily integrated into multiscale simulations. The challenge of executing fully coupled multiscale simulations is augmented by the need to incorporate the evolution of the material structure that may occur under conditions such as material processing. To address these challenges with multiscale simulation, a novel framework called the Materials Knowledge System (MKS) has been developed. This methodology efficiently extracts, stores, and recalls microstructure-property-processing localization relationships. This approach is built on the statistical continuum theories developed by Kroner that express the localization of the response field at the microscale using a series of highly complex convolution integrals, which have historically been evaluated analytically. The MKS approach dramatically improves the accuracy of these expressions by calibrating the convolution kernels in these expressions to results from previously validated physics-based models. These novel tools have been validated for the elastic strain localization in moderate contrast dual-phase composites by direct comparisons with predictions from finite element model. The versatility of the approach is further demonstrated by its successful application to capturing the structure evolution during spinodal decomposition of a binary alloy. Lastly, some key features in the future application of the MKS approach are developed using the Portevin-le Chaterlier effect. It has been shown with these case studies that the MKS approach is capable of accurately reproducing the results from physics based models with a drastic reduction in computational requirements.

On the use of reverse Brownian motion to accelerate hybrid simulations

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

Bakarji, Joseph; Tartakovsky, Daniel M., E-mail: tartakovsky@stanford.edu

Multiscale and multiphysics simulations are two rapidly developing fields of scientific computing. Efficient coupling of continuum (deterministic or stochastic) constitutive solvers with their discrete (stochastic, particle-based) counterparts is a common challenge in both kinds of simulations. We focus on interfacial, tightly coupled simulations of diffusion that combine continuum and particle-based solvers. The latter employs the reverse Brownian motion (rBm), a Monte Carlo approach that allows one to enforce inhomogeneous Dirichlet, Neumann, or Robin boundary conditions and is trivially parallelizable. We discuss numerical approaches for improving the accuracy of rBm in the presence of inhomogeneous Neumann boundary conditions and alternative strategiesmore » for coupling the rBm solver with its continuum counterpart. Numerical experiments are used to investigate the convergence, stability, and computational efficiency of the proposed hybrid algorithm.« less

Modeling Ductile-Phase Toughened Tungsten for Plasma-Facing Materials: Progress in Damage Finite Element Analysis of the Tungsten-Copper Bend Bar Tests

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

Nguyen, Ba Nghiep; Henager, Charles H.; Kurtz, Richard J.

The objective of this study is to investigate the deformation behavior of ductile phase toughened W-composites such as W-Cu and W-Ni-Fe by means of a multiscale finite element model that involves a microstructural dual-phase model where the constituent phases (i.e., W, Cu, Ni-Fe) are finely discretized and are described by a continuum damage model. Such a model is suitable for modeling deformation, cracking, and crack bridging for W-Cu, W-Ni-Fe, and other ductile phase toughened W-composites, or more generally, any multi-phase composite structure where two or more phases undergo cooperative deformation in a composite system. Our current work focuses on simulatingmore » the response and damage development of the W-Cu specimen subjected to three-point bending.« less

Elastic interaction of hydrogen atoms on graphene: A multiscale approach from first principles to continuum elasticity

NASA Astrophysics Data System (ADS)

Branicio, Paulo S.; Vastola, Guglielmo; Jhon, Mark H.; Sullivan, Michael B.; Shenoy, Vivek B.; Srolovitz, David J.

2016-10-01

The deformation of graphene due to the chemisorption of hydrogen atoms on its surface and the long-range elastic interaction between hydrogen atoms induced by these deformations are investigated using a multiscale approach based on first principles, empirical interactions, and continuum modeling. Focus is given to the intrinsic low-temperature structure and interactions. Therefore, all calculations are performed at T =0 , neglecting possible temperature or thermal fluctuation effects. Results from different methods agree well and consistently describe the local deformation of graphene on multiple length scales reaching 500 Å . The results indicate that the elastic interaction mediated by this deformation is significant and depends on the deformation of the graphene sheet both in and out of plane. Surprisingly, despite the isotropic elasticity of graphene, within the linear elastic regime, atoms elastically attract or repel each other depending on (i) the specific site they are chemisorbed; (ii) the relative position of the sites; (iii) and if they are on the same or on opposite surface sides. The interaction energy sign and power-law decay calculated from molecular statics agree well with theoretical predictions from linear elasticity theory, considering in-plane or out-of-plane deformations as a superposition or in a coupled nonlinear approach. Deviations on the exact power law between molecular statics and the linear elastic analysis are evidence of the importance of nonlinear effects on the elasticity of monolayer graphene. These results have implications for the understanding of the generation of clusters and regular formations of hydrogen and other chemisorbed atoms on graphene.

Microbiological-enhanced mixing across scales during in-situ bioreduction of metals and radionuclides at Department of Energy Sites

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

Valocchi, Albert; Werth, Charles; Liu, Wen-Tso

Bioreduction is being actively investigated as an effective strategy for subsurface remediation and long-term management of DOE sites contaminated by metals and radionuclides (i.e. U(VI)). These strategies require manipulation of the subsurface, usually through injection of chemicals (e.g., electron donor) which mix at varying scales with the contaminant to stimulate metal reducing bacteria. There is evidence from DOE field experiments suggesting that mixing limitations of substrates at all scales may affect biological growth and activity for U(VI) reduction. Although current conceptual models hold that biomass growth and reduction activity is limited by physical mixing processes, a growing body of literaturemore » suggests that reaction could be enhanced by cell-to-cell interaction occurring over length scales extending tens to thousands of microns. Our project investigated two potential mechanisms of enhanced electron transfer. The first is the formation of single- or multiple-species biofilms that transport electrons via direct electrical connection such as conductive pili (i.e. ‘nanowires’) through biofilms to where the electron acceptor is available. The second is through diffusion of electron carriers from syntrophic bacteria to dissimilatory metal reducing bacteria (DMRB). The specific objectives of this work are (i) to quantify the extent and rate that electrons are transported between microorganisms in physical mixing zones between an electron donor and electron acceptor (e.g. U(IV)), (ii) to quantify the extent that biomass growth and reaction are enhanced by interspecies electron transport, and (iii) to integrate mixing across scales (e.g., microscopic scale of electron transfer and macroscopic scale of diffusion) in an integrated numerical model to quantify these mechanisms on overall U(VI) reduction rates. We tested these hypotheses with five tasks that integrate microbiological experiments, unique micro-fluidics experiments, flow cell experiments, and multi-scale numerical models. Continuous fed-batch reactors were used to derive kinetic parameters for DMRB, and to develop an enrichment culture for elucidation of syntrophic relationships in a complex microbial community. Pore and continuum scale experiments using microfluidic and bench top flow cells were used to evaluate the impact of cell-to-cell and microbial interactions on reaction enhancement in mixing-limited bioactive zones, and the mechanisms of this interaction. Some of the microfluidic experiments were used to develop and test models that considers direct cell-to-cell interactions during metal reduction. Pore scale models were incorporated into a multi-scale hybrid modeling framework that combines pore scale modeling at the reaction interface with continuum scale modeling. New computational frameworks for combining continuum and pore-scale models were also developed« less

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.

Morphing Continuum Theory: A First Order Approximation to the Balance Laws

NASA Astrophysics Data System (ADS)

Wonnell, Louis; Cheikh, Mohamad Ibrahim; Chen, James

2017-11-01

Morphing Continuum Theory is constructed under the framework of Rational Continuum Mechanics (RCM) for fluid flows with inner structure. This multiscale theory has been successfully emplyed to model turbulent flows. The framework of RCM ensures the mathematical rigor of MCT, but contains new material constants related to the inner structure. The physical meanings of these material constants have yet to be determined. Here, a linear deviation from the zeroth-order Boltzmann-Curtiss distribution function is derived. When applied to the Boltzmann-Curtiss equation, a first-order approximation of the MCT governing equations is obtained. The integral equations are then related to the appropriate material constants found in the heat flux, Cauchy stress, and moment stress terms in the governing equations. These new material properties associated with the inner structure of the fluid are compared with the corresponding integrals, and a clearer physical interpretation of these coefficients emerges. The physical meanings of these material properties is determined by analyzing previous results obtained from numerical simulations of MCT for compressible and incompressible flows. The implications for the physics underlying the MCT governing equations will also be discussed. This material is based upon work supported by the Air Force Office of Scientific Research under Award Number FA9550-17-1-0154.

A multiscale model for charge inversion in electric double layers

NASA Astrophysics Data System (ADS)

Mashayak, S. Y.; Aluru, N. R.

2018-06-01

Charge inversion is a widely observed phenomenon. It is a result of the rich statistical mechanics of the molecular interactions between ions, solvent, and charged surfaces near electric double layers (EDLs). Electrostatic correlations between ions and hydration interactions between ions and water molecules play a dominant role in determining the distribution of ions in EDLs. Due to highly polar nature of water, near a surface, an inhomogeneous and anisotropic arrangement of water molecules gives rise to pronounced variations in the electrostatic and hydration energies of ions. Classical continuum theories fail to accurately describe electrostatic correlations and molecular effects of water in EDLs. In this work, we present an empirical potential based quasi-continuum theory (EQT) to accurately predict the molecular-level properties of aqueous electrolytes. In EQT, we employ rigorous statistical mechanics tools to incorporate interatomic interactions, long-range electrostatics, correlations, and orientation polarization effects at a continuum-level. Explicit consideration of atomic interactions of water molecules is both theoretically and numerically challenging. We develop a systematic coarse-graining approach to coarse-grain interactions of water molecules and electrolyte ions from a high-resolution atomistic scale to the continuum scale. To demonstrate the ability of EQT to incorporate the water orientation polarization, ion hydration, and electrostatic correlations effects, we simulate confined KCl aqueous electrolyte and show that EQT can accurately predict the distribution of ions in a thin EDL and also predict the complex phenomenon of charge inversion.

Variational multiscale models for charge transport.

PubMed

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

2012-01-01

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

Variational multiscale models for charge transport

PubMed Central

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

2012-01-01

This work presents a few variational multiscale models for charge transport in complex physical, chemical and biological systems and engineering devices, such as fuel cells, solar cells, battery cells, nanofluidics, transistors and ion channels. An essential ingredient of the present models, introduced in an earlier paper (Bulletin of Mathematical Biology, 72, 1562-1622, 2010), is the use of differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain from the microscopic domain, meanwhile, dynamically couple discrete and continuum descriptions. Our main strategy is to construct the total energy functional of a charge transport system to encompass the polar and nonpolar free energies of solvation, and chemical potential related energy. By using the Euler-Lagrange variation, coupled Laplace-Beltrami and Poisson-Nernst-Planck (LB-PNP) equations are derived. The solution of the LB-PNP equations leads to the minimization of the total free energy, and explicit profiles of electrostatic potential and densities of charge species. To further reduce the computational complexity, the Boltzmann distribution obtained from the Poisson-Boltzmann (PB) equation is utilized to represent the densities of certain charge species so as to avoid the computationally expensive solution of some Nernst-Planck (NP) equations. Consequently, the coupled Laplace-Beltrami and Poisson-Boltzmann-Nernst-Planck (LB-PBNP) equations are proposed for charge transport in heterogeneous systems. A major emphasis of the present formulation is the consistency between equilibrium LB-PB theory and non-equilibrium LB-PNP theory at equilibrium. Another major emphasis is the capability of the reduced LB-PBNP model to fully recover the prediction of the LB-PNP model at non-equilibrium settings. To account for the fluid impact on the charge transport, we derive coupled Laplace-Beltrami, Poisson-Nernst-Planck and Navier-Stokes equations from the variational principle for chemo-electro-fluid systems. A number of computational algorithms is developed to implement the proposed new variational multiscale models in an efficient manner. A set of ten protein molecules and a realistic ion channel, Gramicidin A, are employed to confirm the consistency and verify the capability. Extensive numerical experiment is designed to validate the proposed variational multiscale models. A good quantitative agreement between our model prediction and the experimental measurement of current-voltage curves is observed for the Gramicidin A channel transport. This paper also provides a brief review of the field. PMID:23172978

Validation of the Concurrent Atomistic-Continuum Method on Screw Dislocation/Stacking Fault Interactions

DOE PAGES

Xu, Shuozhi; Xiong, Liming; Chen, Youping; ...

2017-04-26

Dislocation/stacking fault interactions play an important role in the plastic deformation of metallic nanocrystals and polycrystals. These interactions have been explored in atomistic models, which are limited in scale length by high computational cost. In contrast, multiscale material modeling approaches have the potential to simulate the same systems at a fraction of the computational cost. In this paper, we validate the concurrent atomistic-continuum (CAC) method on the interactions between a lattice screw dislocation and a stacking fault (SF) in three face-centered cubic metallic materials—Ni, Al, and Ag. Two types of SFs are considered: intrinsic SF (ISF) and extrinsic SF (ESF).more » For the three materials at different strain levels, two screw dislocation/ISF interaction modes (annihilation of the ISF and transmission of the dislocation across the ISF) and three screw dislocation/ESF interaction modes (transformation of the ESF into a three-layer twin, transformation of the ESF into an ISF, and transmission of the dislocation across the ESF) are identified. Here, our results show that CAC is capable of accurately predicting the dislocation/SF interaction modes with greatly reduced DOFs compared to fully-resolved atomistic simulations.« less

Validation of the Concurrent Atomistic-Continuum Method on Screw Dislocation/Stacking Fault Interactions

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

Xu, Shuozhi; Xiong, Liming; Chen, Youping

Dislocation/stacking fault interactions play an important role in the plastic deformation of metallic nanocrystals and polycrystals. These interactions have been explored in atomistic models, which are limited in scale length by high computational cost. In contrast, multiscale material modeling approaches have the potential to simulate the same systems at a fraction of the computational cost. In this paper, we validate the concurrent atomistic-continuum (CAC) method on the interactions between a lattice screw dislocation and a stacking fault (SF) in three face-centered cubic metallic materials—Ni, Al, and Ag. Two types of SFs are considered: intrinsic SF (ISF) and extrinsic SF (ESF).more » For the three materials at different strain levels, two screw dislocation/ISF interaction modes (annihilation of the ISF and transmission of the dislocation across the ISF) and three screw dislocation/ESF interaction modes (transformation of the ESF into a three-layer twin, transformation of the ESF into an ISF, and transmission of the dislocation across the ESF) are identified. Here, our results show that CAC is capable of accurately predicting the dislocation/SF interaction modes with greatly reduced DOFs compared to fully-resolved atomistic simulations.« less

Hybrid molecular-continuum simulations using smoothed dissipative particle dynamics

PubMed Central

Petsev, Nikolai D.; Leal, L. Gary; Shell, M. Scott

2015-01-01

We present a new multiscale simulation methodology for coupling a region with atomistic detail simulated via molecular dynamics (MD) to a numerical solution of the fluctuating Navier-Stokes equations obtained from smoothed dissipative particle dynamics (SDPD). In this approach, chemical potential gradients emerge due to differences in resolution within the total system and are reduced by introducing a pairwise thermodynamic force inside the buffer region between the two domains where particles change from MD to SDPD types. When combined with a multi-resolution SDPD approach, such as the one proposed by Kulkarni et al. [J. Chem. Phys. 138, 234105 (2013)], this method makes it possible to systematically couple atomistic models to arbitrarily coarse continuum domains modeled as SDPD fluids with varying resolution. We test this technique by showing that it correctly reproduces thermodynamic properties across the entire simulation domain for a simple Lennard-Jones fluid. Furthermore, we demonstrate that this approach is also suitable for non-equilibrium problems by applying it to simulations of the start up of shear flow. The robustness of the method is illustrated with two different flow scenarios in which shear forces act in directions parallel and perpendicular to the interface separating the continuum and atomistic domains. In both cases, we obtain the correct transient velocity profile. We also perform a triple-scale shear flow simulation where we include two SDPD regions with different resolutions in addition to a MD domain, illustrating the feasibility of a three-scale coupling. PMID:25637963

Multi-Scale Observation of Time-Variable Interactions of a Stream and its Valley Bottom During a Storm Event

NASA Astrophysics Data System (ADS)

Hixson, J.; Ward, A. S.; Schmadel, N.

2015-12-01

The exchange of water and solutes across the stream-hyporheic-riparian-hillslope continuum is controlled by the interaction of dynamic hydrological processes with the underlying geological setting. Our current understanding of exchange processes is primarily based on field observations collected during baseflow conditions, with few studies considering time-variable stream-aquifer interactions during storm events. We completed ten sets of four in-stream tracer slug injections during and after a large storm event in a headwater catchment at the H.J. Andrews Experimental Forest, Oregon. The injections were performed in three adjacent 50-meter study reaches, enabling comparison of spatial heterogeneity in transport processes. Reach-scale data demonstrate apparent trends with discharge in both transient storage and long-term storage (commonly "channel water balance"). Comparison of flowpath-scale observations from a network of monitoring wells to reach-scale observations showed that the advective timescale changed with discharge making it difficult to infer process from simple, reach-scale tracer studies. Overall, our results highlight the opportunities and challenges for interpretation of multi-scale solute tracer data along the stream-hyporheic-riparian-hillslope continuum.

Coupling lattice Boltzmann and continuum equations for flow and reactive transport in porous media.

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

Coon, Ethan; Porter, Mark L.; Kang, Qinjun

2012-06-18

In spatially and temporally localized instances, capturing sub-reservoir scale information is necessary. Capturing sub-reservoir scale information everywhere is neither necessary, nor computationally possible. The lattice Boltzmann Method for solving pore-scale systems. At the pore-scale, LBM provides an extremely scalable, efficient way of solving Navier-Stokes equations on complex geometries. Coupling pore-scale and continuum scale systems via domain decomposition. By leveraging the interpolations implied by pore-scale and continuum scale discretizations, overlapping Schwartz domain decomposition is used to ensure continuity of pressure and flux. This approach is demonstrated on a fractured medium, in which Navier-Stokes equations are solved within the fracture while Darcy'smore » equation is solved away from the fracture Coupling reactive transport to pore-scale flow simulators allows hybrid approaches to be extended to solve multi-scale reactive transport.« less

Random blebbing motion: A simple model linking cell structural properties to migration characteristics.

PubMed

Woolley, Thomas E; Gaffney, Eamonn A; Goriely, Alain

2017-07-01

If the plasma membrane of a cell is able to delaminate locally from its actin cortex, a cellular bleb can be produced. Blebs are pressure-driven protrusions, which are noteworthy for their ability to produce cellular motion. Starting from a general continuum mechanics description, we restrict ourselves to considering cell and bleb shapes that maintain approximately spherical forms. From this assumption, we obtain a tractable algebraic system for bleb formation. By including cell-substrate adhesions, we can model blebbing cell motility. Further, by considering mechanically isolated blebbing events, which are randomly distributed over the cell, we can derive equations linking the macroscopic migration characteristics to the microscopic structural parameters of the cell. This multiscale modeling framework is then used to provide parameter estimates, which are in agreement with current experimental data. In summary, the construction of the mathematical model provides testable relationships between the bleb size and cell motility.

Multiscale Modeling of Angiogenesis and Predictive Capacity

NASA Astrophysics Data System (ADS)

Pillay, Samara; Byrne, Helen; Maini, Philip

Tumors induce the growth of new blood vessels from existing vasculature through angiogenesis. Using an agent-based approach, we model the behavior of individual endothelial cells during angiogenesis. We incorporate crowding effects through volume exclusion, motility of cells through biased random walks, and include birth and death-like processes. We use the transition probabilities associated with the discrete model and a discrete conservation equation for cell occupancy to determine collective cell behavior, in terms of partial differential equations (PDEs). We derive three PDE models incorporating single, multi-species and no volume exclusion. By fitting the parameters in our PDE models and other well-established continuum models to agent-based simulations during a specific time period, and then comparing the outputs from the PDE models and agent-based model at later times, we aim to determine how well the PDE models predict the future behavior of the agent-based model. We also determine whether predictions differ across PDE models and the significance of those differences. This may impact drug development strategies based on PDE models.

Multiscale multiphysics and multidomain models—Flexibility and rigidity

PubMed Central

Xia, Kelin; Opron, Kristopher; Wei, Guo-Wei

2013-01-01

The emerging complexity of large macromolecules has led to challenges in their full scale theoretical description and computer simulation. Multiscale multiphysics and multidomain models have been introduced to reduce the number of degrees of freedom while maintaining modeling accuracy and achieving computational efficiency. A total energy functional is constructed to put energies for polar and nonpolar solvation, chemical potential, fluid flow, molecular mechanics, and elastic dynamics on an equal footing. The variational principle is utilized to derive coupled governing equations for the above mentioned multiphysical descriptions. Among these governing equations is the Poisson-Boltzmann equation which describes continuum electrostatics with atomic charges. The present work introduces the theory of continuum elasticity with atomic rigidity (CEWAR). The essence of CEWAR is to formulate the shear modulus as a continuous function of atomic rigidity. As a result, the dynamics complexity of a macromolecular system is separated from its static complexity so that the more time-consuming dynamics is handled with continuum elasticity theory, while the less time-consuming static analysis is pursued with atomic approaches. We propose a simple method, flexibility-rigidity index (FRI), to analyze macromolecular flexibility and rigidity in atomic detail. The construction of FRI relies on the fundamental assumption that protein functions, such as flexibility, rigidity, and energy, are entirely determined by the structure of the protein and its environment, although the structure is in turn determined by all the interactions. As such, the FRI measures the topological connectivity of protein atoms or residues and characterizes the geometric compactness of the protein structure. As a consequence, the FRI does not resort to the interaction Hamiltonian and bypasses matrix diagonalization, which underpins most other flexibility analysis methods. FRI's computational complexity is of \\documentclass[12pt]{minimal}\\begin{document}${\\cal O}(N^2)$\\end{document}O(N2) at most, where N is the number of atoms or residues, in contrast to \\documentclass[12pt]{minimal}\\begin{document}${\\cal O}(N^3)$\\end{document}O(N3) for Hamiltonian based methods. We demonstrate that the proposed FRI gives rise to accurate prediction of protein B-Factor for a set of 263 proteins. We show that a parameter free FRI is able to achieve about 95% accuracy of the parameter optimized FRI. An interpolation algorithm is developed to construct continuous atomic flexibility functions for visualization and use with CEWAR. PMID:24320318

Multiscale multiphysics and multidomain models—Flexibility and rigidity

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

Xia, Kelin; Opron, Kristopher; Wei, Guo-Wei, E-mail: wei@math.msu.edu

The emerging complexity of large macromolecules has led to challenges in their full scale theoretical description and computer simulation. Multiscale multiphysics and multidomain models have been introduced to reduce the number of degrees of freedom while maintaining modeling accuracy and achieving computational efficiency. A total energy functional is constructed to put energies for polar and nonpolar solvation, chemical potential, fluid flow, molecular mechanics, and elastic dynamics on an equal footing. The variational principle is utilized to derive coupled governing equations for the above mentioned multiphysical descriptions. Among these governing equations is the Poisson-Boltzmann equation which describes continuum electrostatics with atomicmore » charges. The present work introduces the theory of continuum elasticity with atomic rigidity (CEWAR). The essence of CEWAR is to formulate the shear modulus as a continuous function of atomic rigidity. As a result, the dynamics complexity of a macromolecular system is separated from its static complexity so that the more time-consuming dynamics is handled with continuum elasticity theory, while the less time-consuming static analysis is pursued with atomic approaches. We propose a simple method, flexibility-rigidity index (FRI), to analyze macromolecular flexibility and rigidity in atomic detail. The construction of FRI relies on the fundamental assumption that protein functions, such as flexibility, rigidity, and energy, are entirely determined by the structure of the protein and its environment, although the structure is in turn determined by all the interactions. As such, the FRI measures the topological connectivity of protein atoms or residues and characterizes the geometric compactness of the protein structure. As a consequence, the FRI does not resort to the interaction Hamiltonian and bypasses matrix diagonalization, which underpins most other flexibility analysis methods. FRI's computational complexity is of O(N{sup 2}) at most, where N is the number of atoms or residues, in contrast to O(N{sup 3}) for Hamiltonian based methods. We demonstrate that the proposed FRI gives rise to accurate prediction of protein B-Factor for a set of 263 proteins. We show that a parameter free FRI is able to achieve about 95% accuracy of the parameter optimized FRI. An interpolation algorithm is developed to construct continuous atomic flexibility functions for visualization and use with CEWAR.« less

Ductile sliding between mineral crystals followed by rupture of collagen crosslinks: experimentally supported micromechanical explanation of bone strength.

PubMed

Fritsch, Andreas; Hellmich, Christian; Dormieux, Luc

2009-09-21

There is an ongoing discussion on how bone strength could be explained from its internal structure and composition. Reviewing recent experimental and molecular dynamics studies, we here propose a new vision on bone material failure: mutual ductile sliding of hydroxyapatite mineral crystals along layered water films is followed by rupture of collagen crosslinks. In order to cast this vision into a mathematical form, a multiscale continuum micromechanics theory for upscaling of elastoplastic properties is developed, based on the concept of concentration and influence tensors for eigenstressed microheterogeneous materials. The model reflects bone's hierarchical organization, in terms of representative volume elements for cortical bone, for extravascular and extracellular bone material, for mineralized fibrils and the extrafibrillar space, and for wet collagen. In order to get access to the stress states at the interfaces between crystals, the extrafibrillar mineral is resolved into an infinite amount of cylindrical material phases oriented in all directions in space. The multiscale micromechanics model is shown to be able to satisfactorily predict the strength characteristics of different bones from different species, on the basis of their mineral/collagen content, their intercrystalline, intermolecular, lacunar, and vascular porosities, and the elastic and strength properties of hydroxyapatite and (molecular) collagen.

First-principles simulations of doping-dependent mesoscale screening of adatoms in graphene

NASA Astrophysics Data System (ADS)

Mostofi, Arash; Corsetti, Fabiano; Wong, Dillon; Crommie, Michael; Lischner, Johannes

Adsorbed atoms and molecules play an important role in controlling and tuning the functional properties of 2D materials. Understanding and predicting this phenomenon from theory is challenging because of the need to capture both the local chemistry of the adsorbate-substrate interaction and its complex interplay with the long-range screening response of the substrate. To address this challenge, we have developed a first-principles multi-scale approach that combines linear-scaling density-functional theory, continuum screening theory and large-scale tight-binding simulations. Focussing on the case of a calcium adatom on graphene, we draw comparison between the effect of (i) non-linearity, (ii) intraband and interband transitions, and (iii) the exchange-correlation potential, thus providing insight into the relative importance of these different factors on the screening response. We also determine the charge transfer from the adatom to the graphene substrate (the key parameter used in continuum screening models), showing it to be significantly larger than previous estimates. AM and FC acknowledge support of the EPSRC under Grant EP/J015059/1, and JL under Grant EP/N005244/1.

Multiscale smeared finite element model for mass transport in biological tissue: From blood vessels to cells and cellular organelles.

PubMed

Kojic, M; Milosevic, M; Simic, V; Koay, E J; Kojic, N; Ziemys, A; Ferrari, M

2018-05-21

One of the basic and vital processes in living organisms is mass exchange, which occurs on several levels: it goes from blood vessels to cells and organelles within cells. On that path, molecules, as oxygen, metabolic products, drugs, etc. Traverse different macro and micro environments - blood, extracellular/intracellular space, and interior of organelles; and also biological barriers such as walls of blood vessels and membranes of cells and organelles. Many aspects of this mass transport remain unknown, particularly the biophysical mechanisms governing drug delivery. The main research approach relies on laboratory and clinical investigations. In parallel, considerable efforts have been directed to develop computational tools for additional insight into the intricate process of mass exchange and transport. Along these lines, we have recently formulated a composite smeared finite element (CSFE) which is composed of the smeared continuum pressure and concentration fields of the capillary and lymphatic system, and of these fields within tissue. The element offers an elegant and simple procedure which opens up new lines of inquiry and can be applied to large systems such as organs and tumors models. Here, we extend this concept to a multiscale scheme which concurrently couples domains that span from large blood vessels, capillaries and lymph, to cell cytosol and further to organelles of nanometer size. These spatial physical domains are coupled by the appropriate connectivity elements representing biological barriers. The composite finite element has "degrees of freedom" which include pressures and concentrations of all compartments of the vessels-tissue assemblage. The overall model uses the standard, measurable material properties of the continuum biological environments and biological barriers. It can be considered as a framework into which we can incorporate various additional effects (such as electrical or biochemical) for transport through membranes or within cells. This concept and the developed FE software within our package PAK offers a computational tool that can be applied to whole-organ systems, while also including specific domains such as tumors. The solved examples demonstrate the accuracy of this model and its applicability to large biological systems. Copyright © 2018. Published by Elsevier Ltd.

Multiscale modeling of interfacial flow in particle-solidification front dynamics

NASA Astrophysics Data System (ADS)

Garvin, Justin

2005-11-01

Particle-solidification front interactions are important in many applications, such as metal-matrix composite manufacture, frost heaving in soils and cryopreservation. The typical length scale of the particles and the solidification fronts are of the order of microns. However, the force of interaction between the particle and the front typically arises when the gap between them is of the order of tens of nanometers. Thus, a multiscale approach is necessary to analyze particle-front interactions. Solving the Navier-Stokes equations to simulate the dynamics by including the nano-scale gap between the particle and the front would be impossible. Therefore, the microscale dynamics is solved using a level-set based Eulerian technique, while an embedded model is developed for solution in the nano-scale (but continuum) gap region. The embedded model takes the form of a lubrication equation with disjoining pressure acting as a body force and is coupled to the outer solution. A particle is pushed by the front when the disjoining pressure is balanced by the viscous drag. The results obtained show that this balance can only occur when the thermal conductivity ratio of the particle to the melt is less than 1.0. The velocity of the front at which the particle pushing/engulfment transition occurs is predicted. In addition, this novel method allows for an in-depth analysis of the flow physics that cause particle pushing/engulfment.

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.

A multiscale model for reinforced concrete with macroscopic variation of reinforcement slip

NASA Astrophysics Data System (ADS)

Sciegaj, Adam; Larsson, Fredrik; Lundgren, Karin; Nilenius, Filip; Runesson, Kenneth

2018-06-01

A single-scale model for reinforced concrete, comprising the plain concrete continuum, reinforcement bars and the bond between them, is used as a basis for deriving a two-scale model. The large-scale problem, representing the "effective" reinforced concrete solid, is enriched by an effective reinforcement slip variable. The subscale problem on a Representative Volume Element (RVE) is defined by Dirichlet boundary conditions. The response of the RVEs of different sizes was investigated by means of pull-out tests. The resulting two-scale formulation was used in an FE^2 analysis of a deep beam. Load-deflection relations, crack widths, and strain fields were compared to those obtained from a single-scale analysis. Incorporating the independent macroscopic reinforcement slip variable resulted in a more pronounced localisation of the effective strain field. This produced a more accurate estimation of the crack widths than the two-scale formulation neglecting the effective reinforcement slip variable.

Multiscale Modeling: A Review

NASA Astrophysics Data System (ADS)

Horstemeyer, M. F.

This review of multiscale modeling covers a brief history of various multiscale methodologies related to solid materials and the associated experimental influences, the various influence of multiscale modeling on different disciplines, and some examples of multiscale modeling in the design of structural components. Although computational multiscale modeling methodologies have been developed in the late twentieth century, the fundamental notions of multiscale modeling have been around since da Vinci studied different sizes of ropes. The recent rapid growth in multiscale modeling is the result of the confluence of parallel computing power, experimental capabilities to characterize structure-property relations down to the atomic level, and theories that admit multiple length scales. The ubiquitous research that focus on multiscale modeling has broached different disciplines (solid mechanics, fluid mechanics, materials science, physics, mathematics, biological, and chemistry), different regions of the world (most continents), and different length scales (from atoms to autos).

Model Reduction in Biomechanics

NASA Astrophysics Data System (ADS)

Feng, Yan

The mechanical characteristic of the cell is primarily performed by the cytoskeleton. Microtubules, actin, and intermediate filaments are the three main cytoskeletal polymers. Of these, microtubules are the stiffest and have multiple functions within a cell that include: providing tracks for intracellular transport, transmitting the mechanical force necessary for cell division during mitosis, and providing sufficient stiffness for propulsion in flagella and cilia. Microtubule mechanics has been studied by a variety of methods: detailed molecular dynamics (MD), coarse-grained models, engineering type models, and elastic continuum models. In principle, atomistic MD simulations should be able to predict all desired mechanical properties of a single molecule, however, in practice the large computational resources are required to carry out a simulation of larger biomolecular system. Due to the limited accessibility using even the most ambitious all-atom models and the demand for the multiscale molecular modeling and simulation, the emergence of the reduced models is critically important to provide the capability for investigating the biomolecular dynamics that are critical to many biological processes. Then the coarse-grained models, such as elastic network models and anisotropic network models, have been shown to bequite accurate in predicting microtubule mechanical response, but still requires significant computational resources. On the other hand, the microtubule is treated as comprising materials with certain continuum material properties. Such continuum models, especially Euler-Bernoulli beam models, are often used to extract mechanical parameters from experimental results. The microtubule is treated as comprising materials with certain continuum material properties. Such continuum models, especially Euler-Bernoulli beam models in which the biomolecular system is assumed as homogeneous isotropic materials with solid cross-sections, are often used to extract mechanical parameters from experimental results. However, in real biological world, these homogeneous and isotropic assumptions are usually invalidate. Thus, instead of using hypothesized model, a specific continuum model at mesoscopic scale can be introduced based upon data reduction of the results from molecular simulations at atomistic level. Once a continuum model is established, it can provide details on the distribution of stresses and strains induced within the biomolecular system which is useful in determining the distribution and transmission of these forces to the cytoskeletal and sub-cellular components, and help us gain a better understanding in cell mechanics. A data-driven model reduction approach to the problem of microtubule mechanics as an application is present, a beam element is constructed for microtubules based upon data reduction of the results from molecular simulation of the carbon backbone chain of alphabeta-tubulin dimers. The data base of mechanical responses to various types of loads from molecular simulation is reduced to dominant modes. The dominant modes are subsequently used to construct the stiffness matrix of a beam element that captures the anisotropic behavior and deformation mode coupling that arises from a microtubule's spiral structure. In contrast to standard Euler-Bernoulli or Timoshenko beam elements, the link between forces and node displacements results not from hypothesized deformation behavior, but directly from the data obtained by molecular scale simulation. Differences between the resulting microtubule data-driven beam model (MTDDBM) and standard beam elements are presented, with a focus on coupling of bending, stretch, shear deformations. The MTDDBM is just as economical to use as a standard beam element, and allows accurate reconstruction of the mechanical behavior of structures within a cell as exemplified in a simple model of a component element of the mitotic spindle.

FY10 Report on Multi-scale Simulation of Solvent Extraction Processes: Molecular-scale and Continuum-scale Studies

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

Wardle, Kent E.; Frey, Kurt; Pereira, Candido

2014-02-02

This task is aimed at predictive modeling of solvent extraction processes in typical extraction equipment through multiple simulation methods at various scales of resolution. We have conducted detailed continuum fluid dynamics simulation on the process unit level as well as simulations of the molecular-level physical interactions which govern extraction chemistry. Through combination of information gained through simulations at each of these two tiers along with advanced techniques such as the Lattice Boltzmann Method (LBM) which can bridge these two scales, we can develop the tools to work towards predictive simulation for solvent extraction on the equipment scale (Figure 1). Themore » goal of such a tool-along with enabling optimized design and operation of extraction units-would be to allow prediction of stage extraction effrciency under specified conditions. Simulation efforts on each of the two scales will be described below. As the initial application of FELBM in the work performed during FYl0 has been on annular mixing it will be discussed in context of the continuum-scale. In the future, however, it is anticipated that the real value of FELBM will be in its use as a tool for sub-grid model development through highly refined DNS-like multiphase simulations facilitating exploration and development of droplet models including breakup and coalescence which will be needed for the large-scale simulations where droplet level physics cannot be resolved. In this area, it can have a significant advantage over traditional CFD methods as its high computational efficiency allows exploration of significantly greater physical detail especially as computational resources increase in the future.« less

Discontinuous Galerkin modeling of the Columbia River's coupled estuary-plume dynamics

NASA Astrophysics Data System (ADS)

Vallaeys, Valentin; Kärnä, Tuomas; Delandmeter, Philippe; Lambrechts, Jonathan; Baptista, António M.; Deleersnijder, Eric; Hanert, Emmanuel

2018-04-01

The Columbia River (CR) estuary is characterized by high river discharge and strong tides that generate high velocity flows and sharp density gradients. Its dynamics strongly affects the coastal ocean circulation. Tidal straining in turn modulates the stratification in the estuary. Simulating the hydrodynamics of the CR estuary and plume therefore requires a multi-scale model as both shelf and estuarine circulations are coupled. Such a model has to keep numerical dissipation as low as possible in order to correctly represent the plume propagation and the salinity intrusion in the estuary. Here, we show that the 3D baroclinic discontinuous Galerkin finite element model SLIM 3D is able to reproduce the main features of the CR estuary-to-ocean continuum. We introduce new vertical discretization and mode splitting that allow us to model a region characterized by complex bathymetry and sharp density and velocity gradients. Our model takes into account the major forcings, i.e. tides, surface wind stress and river discharge, on a single multi-scale grid. The simulation period covers the end of spring-early summer of 2006, a period of high river flow and strong changes in the wind regime. SLIM 3D is validated with in-situ data on the shelf and at multiple locations in the estuary and compared with an operational implementation of SELFE. The model skill in the estuary and on the shelf indicate that SLIM 3D is able to reproduce the key processes driving the river plume dynamics, such as the occurrence of bidirectional plumes or reversals of the inner shelf coastal currents.

Hybrid Multiscale Finite Volume Method for Advection-Diffusion Equations Subject to Heterogeneous Reactive Boundary Conditions

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

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

2016-10-13

We present a hybrid scheme for the coupling of macro and microscale continuum models for reactive contaminant transport in fractured and porous media. The transport model considered is the advection-dispersion equation, subject to linear heterogeneous reactive boundary conditions. The Multiscale Finite Volume method (MsFV) is employed to define an approximation to the microscale concentration field defined in terms of macroscopic or \\emph{global} degrees of freedom, together with local interpolator and corrector functions capturing microscopic spatial variability. The macroscopic mass balance relations for the MsFV global degrees of freedom are coupled with the macroscopic model, resulting in a global problem for the simultaneous time-stepping of all macroscopic degrees of freedom throughout the domain. In order to perform the hybrid coupling, the micro and macroscale models are applied over overlapping subdomains of the simulation domain, with the overlap denoted as the handshake subdomainmore » $$\\Omega^{hs}$$, over which continuity of concentration and transport fluxes between models is enforced. Continuity of concentration is enforced by posing a restriction relation between models over $$\\Omega^{hs}$$. Continuity of fluxes is enforced by prolongating the macroscopic model fluxes across the boundary of $$\\Omega^{hs}$$ to microscopic resolution. The microscopic interpolator and corrector functions are solutions to local microscopic advection-diffusion problems decoupled from the global degrees of freedom and from each other by virtue of the MsFV decoupling ansatz. The error introduced by the decoupling ansatz is reduced iteratively by the preconditioned GMRES algorithm, with the hybrid MsFV operator serving as the preconditioner.« less

Real-Time Description of the Electronic Dynamics for a Molecule Close to a Plasmonic Nanoparticle

PubMed Central

2016-01-01

The optical properties of molecules close to plasmonic nanostructures greatly differ from their isolated molecule counterparts. To theoretically investigate such systems from a quantum-chemistry perspective, one has to take into account that the plasmonic nanostructure (e.g., a metal nanoparticle–NP) is often too large to be treated atomistically. Therefore, a multiscale description, where the molecule is treated by an ab initio approach and the metal NP by a lower level description, is needed. Here we present an extension of one such multiscale model [Corni, S.; Tomasi, J. J. Chem. Phys.2001, 114, 3739], originally inspired by the polarizable continuum model, to a real-time description of the electronic dynamics of the molecule and of the NP. In particular, we adopt a time-dependent configuration interaction (TD CI) approach for the molecule, the metal NP is described as a continuous dielectric of complex shape characterized by a Drude–Lorentz dielectric function, and the molecule–NP electromagnetic coupling is treated by an equation-of-motion (EOM) extension of the quasi-static boundary element method (BEM). The model includes the effects of both the mutual molecule–NP time-dependent polarization and the modification of the probing electromagnetic field due to the plasmonic resonances of the NP. Finally, such an approach is applied to the investigation of the light absorption of a model chromophore, LiCN, in the presence of a metal–NP of complex shape. PMID:28035246

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.

Hybrid Particle-Continuum Numerical Methods for Aerospace Applications

DTIC Science & Technology

2011-01-01

may require kinetic analysis. Another possible option that will enable high-mass, Mars missions is supersonic retro -propulsion [17], where a jet is...exploration missions [15]. 2.3 Plumes Another class of multi-scale ows of interest is rocket exhaust plumes. Ecient and accurate predictions of...atmospheric exhaust plumes at high altitudes are necessary to ensure that the chemical rocket maintains eciency while also assuring that the vehicle heating

Lattice Boltzmann accelerated direct simulation Monte Carlo for dilute gas flow simulations.

PubMed

Di Staso, G; Clercx, H J H; Succi, S; Toschi, F

2016-11-13

Hybrid particle-continuum computational frameworks permit the simulation of gas flows by locally adjusting the resolution to the degree of non-equilibrium displayed by the flow in different regions of space and time. In this work, we present a new scheme that couples the direct simulation Monte Carlo (DSMC) with the lattice Boltzmann (LB) method in the limit of isothermal flows. The former handles strong non-equilibrium effects, as they typically occur in the vicinity of solid boundaries, whereas the latter is in charge of the bulk flow, where non-equilibrium can be dealt with perturbatively, i.e. according to Navier-Stokes hydrodynamics. The proposed concurrent multiscale method is applied to the dilute gas Couette flow, showing major computational gains when compared with the full DSMC scenarios. In addition, it is shown that the coupling with LB in the bulk flow can speed up the DSMC treatment of the Knudsen layer with respect to the full DSMC case. In other words, LB acts as a DSMC accelerator.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2016 The Author(s).

Consistent Temperature Coupling with Thermal Fluctuations of Smooth Particle Hydrodynamics and Molecular Dynamics

PubMed Central

Ganzenmüller, Georg C.; Hiermaier, Stefan; Steinhauser, Martin O.

2012-01-01

We propose a thermodynamically consistent and energy-conserving temperature coupling scheme between the atomistic and the continuum domain. The coupling scheme links the two domains using the DPDE (Dissipative Particle Dynamics at constant Energy) thermostat and is designed to handle strong temperature gradients across the atomistic/continuum domain interface. The fundamentally different definitions of temperature in the continuum and atomistic domain – internal energy and heat capacity versus particle velocity – are accounted for in a straightforward and conceptually intuitive way by the DPDE thermostat. We verify the here-proposed scheme using a fluid, which is simultaneously represented as a continuum using Smooth Particle Hydrodynamics, and as an atomistically resolved liquid using Molecular Dynamics. In the case of equilibrium contact between both domains, we show that the correct microscopic equilibrium properties of the atomistic fluid are obtained. As an example of a strong non-equilibrium situation, we consider the propagation of a steady shock-wave from the continuum domain into the atomistic domain, and show that the coupling scheme conserves both energy and shock-wave dynamics. To demonstrate the applicability of our scheme to real systems, we consider shock loading of a phospholipid bilayer immersed in water in a multi-scale simulation, an interesting topic of biological relevance. PMID:23300586

Quantum dynamics in continuum for proton transport—Generalized correlation

NASA Astrophysics Data System (ADS)

Chen, Duan; Wei, Guo-Wei

2012-04-01

As a key process of many biological reactions such as biological energy transduction or human sensory systems, proton transport has attracted much research attention in biological, biophysical, and mathematical fields. A quantum dynamics in continuum framework has been proposed to study proton permeation through membrane proteins in our earlier work and the present work focuses on the generalized correlation of protons with their environment. Being complementary to electrostatic potentials, generalized correlations consist of proton-proton, proton-ion, proton-protein, and proton-water interactions. In our approach, protons are treated as quantum particles while other components of generalized correlations are described classically and in different levels of approximations upon simulation feasibility and difficulty. Specifically, the membrane protein is modeled as a group of discrete atoms, while ion densities are approximated by Boltzmann distributions, and water molecules are represented as a dielectric continuum. These proton-environment interactions are formulated as convolutions between number densities of species and their corresponding interaction kernels, in which parameters are obtained from experimental data. In the present formulation, generalized correlations are important components in the total Hamiltonian of protons, and thus is seamlessly embedded in the multiscale/multiphysics total variational model of the system. It takes care of non-electrostatic interactions, including the finite size effect, the geometry confinement induced channel barriers, dehydration and hydrogen bond effects, etc. The variational principle or the Euler-Lagrange equation is utilized to minimize the total energy functional, which includes the total Hamiltonian of protons, and obtain a new version of generalized Laplace-Beltrami equation, generalized Poisson-Boltzmann equation and generalized Kohn-Sham equation. A set of numerical algorithms, such as the matched interface and boundary method, the Dirichlet to Neumann mapping, Gummel iteration, and Krylov space techniques, is employed to improve the accuracy, efficiency, and robustness of model simulations. Finally, comparisons between the present model predictions and experimental data of current-voltage curves, as well as current-concentration curves of the Gramicidin A channel, verify our new model.

Application of a Multiscale Model of Tantalum Deformation at Megabar Pressures

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

Cavallo, R M; Park, H; Barton, N R

A new multiscale simulation tool has been developed to model the strength of tantalum under high-pressure dynamic compression. This new model combines simulations at multiple length scales to explain macroscopic properties of materials. Previously known continuum models of material response under load have built upon a mixture of theoretical physics and experimental phenomenology. Experimental data, typically measured at static pressures, are used as a means of calibration to construct models that parameterize the material properties; e.g., yield stress, work hardening, strain-rate dependence, etc. The pressure dependence for most models enters through the shear modulus, which is used to scale themore » flow stress. When these models are applied to data taken far outside the calibrated regions of phase space (e.g., strain rate or pressure) they often diverge in their predicted behavior of material deformation. The new multiscale model, developed at Lawrence Livermore National Laboratory, starts with interatomic quantum mechanical potential and is based on the motion and multiplication of dislocations. The basis for the macroscale model is plastic deformation by phonon drag and thermally activated dislocation motion and strain hardening resulting from elastic interactions among dislocations. The dislocation density, {rho}, and dislocation velocity, {nu}, are connected to the plastic strain rate {var_epsilon}{sup p}, via Orowan's equation: {var_epsilon}{sup p} = {rho}b{nu}/M, where b is the Burger's vector, the shear magnitude associated with a dislocation, and M is the Taylor factor, which accounts for geometric effects in how slip systems accommodate the deformation. The evolution of the dislocation density and velocity is carried out in the continuum model by parameterized fits to smaller scale simulations, each informed by calculations on smaller length scales down to atomistic dimensions. We apply this new model for tantalum to two sets of experiments and compare the results with more traditional models. The experiments are based on the Barnes's technique in which a low density material loads against a metal surface containing a pre-imposed rippled pattern. The loaded sample is Rayleigh-Taylor unstable and the rippled amplitudes grow with time. The rate of growth differs depending on the material strength, with stronger materials growing less, even to the point of saturation. One set of experiments was conducted at the pRad facility at LANSCE at Los Alamos National Laboratory in 2007 using high-explosive (HE) driven tantalum samples. The other set of experiments was done at the Omega laser at the Laboratory for Laser Energetics at the University of Rochester, which used high-powered lasers to create plasmas to dynamically compress a rippled tantalum sample. The two techniques provide data at different pressures and strain rates: The HE technique drives the samples at around 2 x 10{sup 5} s{sup -1} strain rate and pressures near 500 kbar, while the laser technique hits strain rates around 2 x 10{sup 7} s{sup -1} and pressures close to 1.4 Mbar. The most recent laser experiments were conducted in February 2010 and they present a sample of the data in Figure 1, which shows a face-on radiograph at a time of 65 ns after the laser was turned on. From this radiograph, they measure the growth factor which is defined to be the change in amplitude of the ripples relative to their initial amplitude. Figure 2 shows the resulting growth factors along with various model fits. The error bars are typically 20-25%. Only the multiscale model predictions match the experimental measurements. The growth factors via the HE technique are determined from multiple side-on proton radiography images and thus provide a full growth curve per single experiment. A sample growth curve is shown in Figure 3, also with various model fits and error bars estimated at 25%. It should be noted that by 7.5 {micro}s the growth in this sample has exceeded the initial target thickness indicating that localizations not captured in the overall simulation have probably become dominant, i.e., the target is likely breaking up. Application of the multiscale dislocation dynamics model as implemented in the Ares hydrodynamics code shows excellent agreement with both the pRad and Omega data. They also compare the Steinberg-Lund (SL), Preston-Tonks-Wallace (PTW), and Stainberg-Guinan (SG) models with the data. The PTW and SG models provide good fits to the pRad data but over-predict the growth (underestimate the strength) on the laser platform. The SL model under-predicts the pRad data and over-predicts the Omega data. The excellent agreement of the multiscale model with the data over two orders of magnitude in strain rate and more than a factor of two in pressure lends credibility to the model. They continue to stress the model by conducting experiments at 5 Mbars and beyond at the National Ignition Facility at LLNL in the near future.« 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.

Nanoparticle interaction potentials constructed by multiscale computation

NASA Astrophysics Data System (ADS)

Lee, Cheng K.; Hua, Chi C.

2010-06-01

The van der Waals (vdW) potentials governing macroscopic objects have long been formulated in the context of classical theories, such as Hamaker's microscopic theory and Lifshitz's continuum theory. This work addresses the possibility of constructing the vdW interaction potentials of nanoparticle species using multiscale simulation schemes. Amorphous silica nanoparticles were considered as a benchmark example for which a series of (SiO2)n (n being an integer) has been systematically surveyed as the potential candidates of the packing units that reproduce known bulk material properties in atomistic molecular dynamics simulations. This strategy led to the identification of spherical Si6O12 molecules, later utilized as the elementary coarse-grained (CG) particles to compute the pair interaction potentials of silica nanoparticles ranging from 0.62 to 100 nm in diameter. The model nanoparticles so built may, in turn, serve as the children CG particles to construct nanoparticles assuming arbitrary sizes and shapes. Major observations are as follows. The pair interaction potentials for all the investigated spherical silica nanoparticles can be cast into a semiempirical, generalized Lennard-Jones 2α-α potential (α being a size-dependent, large integral number). In its reduced form, we discuss the implied universalities for the vdW potentials governing a certain range of amorphous nanoparticle species as well as how thermodynamic transferability can be fulfilled automatically. In view of future applications with colloidal suspensions, we briefly evaluated the vdW potential in the presence of a "screening" medium mimicking the effects of electrical double layers or grafting materials atop the nanoparticle core. The general observations shed new light on strategies to attain a microscopic control over interparticle attractions. In future perspectives, the proposed multiscale computation scheme shall help bridge the current gap between the modeling of polymer chains and macroscopic objects by introducing molecular models coarse-grained at a similar level so that the interactions between these two can be treated in a consistent and faithful way.

Micro- and nano-mechanics in China: A brief review of recent progress and perspectives

NASA Astrophysics Data System (ADS)

Xu, ZhiPing; Zheng, QuanShui

2018-07-01

The past three decades have witnessed the explosion of nanoscience and technology, where notable research efforts have been made in synthesizing nanomaterials and controlling nanostructures of bulk materials. The uncovered mechanical behaviors of structures and materials with reduced sizes and dimensions pose open questions to the community of mechanicians, which expand the framework of continuum mechanics by advancing the theory, as well as modeling and experimental tools. Researchers in China have been actively involved into this exciting area, making remarkable contributions to the understanding of nanoscale mechanical processes, the development of multi-scale, multi-field modeling and experimental techniques to resolve the processing-microstructures-properties relationship of materials, and the interdisciplinary studies that broaden the subjects of mechanics. This article reviews selected progress made by this community, with the aim to clarify the key concepts, methods and applications of micro- and nano-mechanics, and to outline the perspectives in this fast-evolving field.

3D braid scaffolds for regeneration of articular cartilage.

PubMed

Ahn, Hyunchul; Kim, Kyoung Ju; Park, Sook Young; Huh, Jeong Eun; Kim, Hyun Jeong; Yu, Woong-Ryeol

2014-06-01

Regenerating articular cartilage in vivo from cultured chondrocytes requires that the cells be cultured and implanted within a biocompatible, biodegradable scaffold. Such scaffolds must be mechanically stable; otherwise chondrocytes would not be supported and patients would experience severe pain. Here we report a new 3D braid scaffold that matches the anisotropic (gradient) mechanical properties of natural articular cartilage and is permissive to cell cultivation. To design an optimal structure, the scaffold unit cell was mathematically modeled and imported into finite element analysis. Based on this analysis, a 3D braid structure with gradient axial yarn distribution was designed and manufactured using a custom-built braiding machine. The mechanical properties of the 3D braid scaffold were evaluated and compared with simulated results, demonstrating that a multi-scale approach consisting of unit cell modeling and continuum analysis facilitates design of scaffolds that meet the requirements for mechanical compatibility with tissues. Copyright © 2014 Elsevier Ltd. All rights reserved.

Parallelization of fine-scale computation in Agile Multiscale Modelling Methodology

NASA Astrophysics Data System (ADS)

Macioł, Piotr; Michalik, Kazimierz

2016-10-01

Nowadays, multiscale modelling of material behavior is an extensively developed area. An important obstacle against its wide application is high computational demands. Among others, the parallelization of multiscale computations is a promising solution. Heterogeneous multiscale models are good candidates for parallelization, since communication between sub-models is limited. In this paper, the possibility of parallelization of multiscale models based on Agile Multiscale Methodology framework is discussed. A sequential, FEM based macroscopic model has been combined with concurrently computed fine-scale models, employing a MatCalc thermodynamic simulator. The main issues, being investigated in this work are: (i) the speed-up of multiscale models with special focus on fine-scale computations and (ii) on decreasing the quality of computations enforced by parallel execution. Speed-up has been evaluated on the basis of Amdahl's law equations. The problem of `delay error', rising from the parallel execution of fine scale sub-models, controlled by the sequential macroscopic sub-model is discussed. Some technical aspects of combining third-party commercial modelling software with an in-house multiscale framework and a MPI library are also discussed.

Scaling properties of multiscale equilibration

NASA Astrophysics Data System (ADS)

Detmold, W.; Endres, M. G.

2018-04-01

We investigate the lattice spacing dependence of the equilibration time for a recently proposed multiscale thermalization algorithm for Markov chain Monte Carlo simulations. The algorithm uses a renormalization-group matched coarse lattice action and prolongation operation to rapidly thermalize decorrelated initial configurations for evolution using a corresponding target lattice action defined at a finer scale. Focusing on nontopological long-distance observables in pure S U (3 ) gauge theory, we provide quantitative evidence that the slow modes of the Markov process, which provide the dominant contribution to the rethermalization time, have a suppressed contribution toward the continuum limit, despite their associated timescales increasing. Based on these numerical investigations, we conjecture that the prolongation operation used herein will produce ensembles that are indistinguishable from the target fine-action distribution for a sufficiently fine coupling at a given level of statistical precision, thereby eliminating the cost of rethermalization.

Nonlinear modelling of cancer: bridging the gap between cells and tumours

PubMed Central

Lowengrub, J S; Frieboes, H B; Jin, F; Chuang, Y-L; Li, X; Macklin, P; Wise, S M; Cristini, V

2010-01-01

Despite major scientific, medical and technological advances over the last few decades, a cure for cancer remains elusive. The disease initiation is complex, and including initiation and avascular growth, onset of hypoxia and acidosis due to accumulation of cells beyond normal physiological conditions, inducement of angiogenesis from the surrounding vasculature, tumour vascularization and further growth, and invasion of surrounding tissue and metastasis. Although the focus historically has been to study these events through experimental and clinical observations, mathematical modelling and simulation that enable analysis at multiple time and spatial scales have also complemented these efforts. Here, we provide an overview of this multiscale modelling focusing on the growth phase of tumours and bypassing the initial stage of tumourigenesis. While we briefly review discrete modelling, our focus is on the continuum approach. We limit the scope further by considering models of tumour progression that do not distinguish tumour cells by their age. We also do not consider immune system interactions nor do we describe models of therapy. We do discuss hybrid-modelling frameworks, where the tumour tissue is modelled using both discrete (cell-scale) and continuum (tumour-scale) elements, thus connecting the micrometre to the centimetre tumour scale. We review recent examples that incorporate experimental data into model parameters. We show that recent mathematical modelling predicts that transport limitations of cell nutrients, oxygen and growth factors may result in cell death that leads to morphological instability, providing a mechanism for invasion via tumour fingering and fragmentation. These conditions induce selection pressure for cell survivability, and may lead to additional genetic mutations. Mathematical modelling further shows that parameters that control the tumour mass shape also control its ability to invade. Thus, tumour morphology may serve as a predictor of invasiveness and treatment prognosis. PMID:20808719

Nonlinear modelling of cancer: bridging the gap between cells and tumours

NASA Astrophysics Data System (ADS)

Lowengrub, J. S.; Frieboes, H. B.; Jin, F.; Chuang, Y.-L.; Li, X.; Macklin, P.; Wise, S. M.; Cristini, V.

2010-01-01

Despite major scientific, medical and technological advances over the last few decades, a cure for cancer remains elusive. The disease initiation is complex, and including initiation and avascular growth, onset of hypoxia and acidosis due to accumulation of cells beyond normal physiological conditions, inducement of angiogenesis from the surrounding vasculature, tumour vascularization and further growth, and invasion of surrounding tissue and metastasis. Although the focus historically has been to study these events through experimental and clinical observations, mathematical modelling and simulation that enable analysis at multiple time and spatial scales have also complemented these efforts. Here, we provide an overview of this multiscale modelling focusing on the growth phase of tumours and bypassing the initial stage of tumourigenesis. While we briefly review discrete modelling, our focus is on the continuum approach. We limit the scope further by considering models of tumour progression that do not distinguish tumour cells by their age. We also do not consider immune system interactions nor do we describe models of therapy. We do discuss hybrid-modelling frameworks, where the tumour tissue is modelled using both discrete (cell-scale) and continuum (tumour-scale) elements, thus connecting the micrometre to the centimetre tumour scale. We review recent examples that incorporate experimental data into model parameters. We show that recent mathematical modelling predicts that transport limitations of cell nutrients, oxygen and growth factors may result in cell death that leads to morphological instability, providing a mechanism for invasion via tumour fingering and fragmentation. These conditions induce selection pressure for cell survivability, and may lead to additional genetic mutations. Mathematical modelling further shows that parameters that control the tumour mass shape also control its ability to invade. Thus, tumour morphology may serve as a predictor of invasiveness and treatment prognosis.

Understanding Greenland ice sheet hydrology using an integrated multi-scale approach

NASA Astrophysics Data System (ADS)

Rennermalm, A. K.; Moustafa, S. E.; Mioduszewski, J.; Chu, V. W.; Forster, R. R.; Hagedorn, B.; Harper, J. T.; Mote, T. L.; Robinson, D. A.; Shuman, C. A.; Smith, L. C.; Tedesco, M.

2013-03-01

Improved understanding of Greenland ice sheet hydrology is critically important for assessing its impact on current and future ice sheet dynamics and global sea level rise. This has motivated the collection and integration of in situ observations, model development, and remote sensing efforts to quantify meltwater production, as well as its phase changes, transport, and export. Particularly urgent is a better understanding of albedo feedbacks leading to enhanced surface melt, potential positive feedbacks between ice sheet hydrology and dynamics, and meltwater retention in firn. These processes are not isolated, but must be understood as part of a continuum of processes within an integrated system. This letter describes a systems approach to the study of Greenland ice sheet hydrology, emphasizing component interconnections and feedbacks, and highlighting research and observational needs.

Computational optogenetics: A novel continuum framework for the photoelectrochemistry of living systems

NASA Astrophysics Data System (ADS)

Wong, Jonathan; Abilez, Oscar J.; Kuhl, Ellen

2012-06-01

Electrical stimulation is currently the gold standard treatment for heart rhythm disorders. However, electrical pacing is associated with technical limitations and unavoidable potential complications. Recent developments now enable the stimulation of mammalian cells with light using a novel technology known as optogenetics. The optical stimulation of genetically engineered cells has significantly changed our understanding of electrically excitable tissues, paving the way towards controlling heart rhythm disorders by means of photostimulation. Controlling these disorders, in turn, restores coordinated force generation to avoid sudden cardiac death. Here, we report a novel continuum framework for the photoelectrochemistry of living systems that allows us to decipher the mechanisms by which this technology regulates the electrical and mechanical function of the heart. Using a modular multiscale approach, we introduce a non-selective cation channel, channelrhodopsin-2, into a conventional cardiac muscle cell model via an additional photocurrent governed by a light-sensitive gating variable. Upon optical stimulation, this channel opens and allows sodium ions to enter the cell, inducing electrical activation. In side-by-side comparisons with conventional heart muscle cells, we show that photostimulation directly increases the sodium concentration, which indirectly decreases the potassium concentration in the cell, while all other characteristics of the cell remain virtually unchanged. We integrate our model cells into a continuum model for excitable tissue using a nonlinear parabolic second-order partial differential equation, which we discretize in time using finite differences and in space using finite elements. To illustrate the potential of this computational model, we virtually inject our photosensitive cells into different locations of a human heart, and explore its activation sequences upon photostimulation. Our computational optogenetics tool box allows us to virtually probe landscapes of process parameters, and to identify optimal photostimulation sequences with the goal to pace human hearts with light and, ultimately, to restore mechanical function.

Computational Optogenetics: A Novel Continuum Framework for the Photoelectrochemistry of Living Systems.

PubMed

Wong, Jonathan; Abilez, Oscar J; Kuhl, Ellen

2012-06-01

Electrical stimulation is currently the gold standard treatment for heart rhythm disorders. However, electrical pacing is associated with technical limitations and unavoidable potential complications. Recent developments now enable the stimulation of mammalian cells with light using a novel technology known as optogenetics. The optical stimulation of genetically engineered cells has significantly changed our understanding of electrically excitable tissues, paving the way towards controlling heart rhythm disorders by means of photostimulation. Controlling these disorders, in turn, restores coordinated force generation to avoid sudden cardiac death. Here, we report a novel continuum framework for the photoelectrochemistry of living systems that allows us to decipher the mechanisms by which this technology regulates the electrical and mechanical function of the heart. Using a modular multiscale approach, we introduce a non-selective cation channel, channelrhodopsin-2, into a conventional cardiac muscle cell model via an additional photocurrent governed by a light-sensitive gating variable. Upon optical stimulation, this channel opens and allows sodium ions to enter the cell, inducing electrical activation. In side-by-side comparisons with conventional heart muscle cells, we show that photostimulation directly increases the sodium concentration, which indirectly decreases the potassium concentration in the cell, while all other characteristics of the cell remain virtually unchanged. We integrate our model cells into a continuum model for excitable tissue using a nonlinear parabolic second order partial differential equation, which we discretize in time using finite differences and in space using finite elements. To illustrate the potential of this computational model, we virtually inject our photosensitive cells into different locations of a human heart, and explore its activation sequences upon photostimulation. Our computational optogenetics tool box allows us to virtually probe landscapes of process parameters, and to identify optimal photostimulation sequences with the goal to pace human hearts with light and, ultimately, to restore mechanical function.

Multiscale modeling of particle in suspension with smoothed dissipative particle dynamics

NASA Astrophysics Data System (ADS)

Bian, Xin; Litvinov, Sergey; Qian, Rui; Ellero, Marco; Adams, Nikolaus A.

2012-01-01

We apply smoothed dissipative particle dynamics (SDPD) [Español and Revenga, Phys. Rev. E 67, 026705 (2003)] to model solid particles in suspension. SDPD is a thermodynamically consistent version of smoothed particle hydrodynamics (SPH) and can be interpreted as a multiscale particle framework linking the macroscopic SPH to the mesoscopic dissipative particle dynamics (DPD) method. Rigid structures of arbitrary shape embedded in the fluid are modeled by frozen particles on which artificial velocities are assigned in order to satisfy exactly the no-slip boundary condition on the solid-liquid interface. The dynamics of the rigid structures is decoupled from the solvent by solving extra equations for the rigid body translational/angular velocities derived from the total drag/torque exerted by the surrounding liquid. The correct scaling of the SDPD thermal fluctuations with the fluid-particle size allows us to describe the behavior of the particle suspension on spatial scales ranging continuously from the diffusion-dominated regime typical of sub-micron-sized objects towards the non-Brownian regime characterizing macro-continuum flow conditions. Extensive tests of the method are performed for the case of two/three dimensional bulk particle-system both in Brownian/ non-Brownian environment showing numerical convergence and excellent agreement with analytical theories. Finally, to illustrate the ability of the model to couple with external boundary geometries, the effect of confinement on the diffusional properties of a single sphere within a micro-channel is considered, and the dependence of the diffusion coefficient on the wall-separation distance is evaluated and compared with available analytical results.

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.

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.

Mesoscopic Modeling of Blood Clotting: Coagulation Cascade and Platelets Adhesion

NASA Astrophysics Data System (ADS)

Yazdani, Alireza; Li, Zhen; Karniadakis, George

2015-11-01

The process of clot formation and growth at a site on a blood vessel wall involve a number of multi-scale simultaneous processes including: multiple chemical reactions in the coagulation cascade, species transport and flow. To model these processes we have incorporated advection-diffusion-reaction (ADR) of multiple species into an extended version of Dissipative Particle Dynamics (DPD) method which is considered as a coarse-grained Molecular Dynamics method. At the continuum level this is equivalent to the Navier-Stokes equation plus one advection-diffusion equation for each specie. The chemistry of clot formation is now understood to be determined by mechanisms involving reactions among many species in dilute solution, where reaction rate constants and species diffusion coefficients in plasma are known. The role of blood particulates, i.e. red cells and platelets, in the clotting process is studied by including them separately and together in the simulations. An agonist-induced platelet activation mechanism is presented, while platelets adhesive dynamics based on a stochastic bond formation/dissociation process is included in the model.

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.

Modeling of Ti-W Solidification Microstructures Under Additive Manufacturing Conditions

NASA Astrophysics Data System (ADS)

Rolchigo, Matthew R.; Mendoza, Michael Y.; Samimi, Peyman; Brice, David A.; Martin, Brian; Collins, Peter C.; LeSar, Richard

2017-07-01

Additive manufacturing (AM) processes have many benefits for the fabrication of alloy parts, including the potential for greater microstructural control and targeted properties than traditional metallurgy processes. To accelerate utilization of this process to produce such parts, an effective computational modeling approach to identify the relationships between material and process parameters, microstructure, and part properties is essential. Development of such a model requires accounting for the many factors in play during this process, including laser absorption, material addition and melting, fluid flow, various modes of heat transport, and solidification. In this paper, we start with a more modest goal, to create a multiscale model for a specific AM process, Laser Engineered Net Shaping (LENS™), which couples a continuum-level description of a simplified beam melting problem (coupling heat absorption, heat transport, and fluid flow) with a Lattice Boltzmann-cellular automata (LB-CA) microscale model of combined fluid flow, solute transport, and solidification. We apply this model to a binary Ti-5.5 wt pct W alloy and compare calculated quantities, such as dendrite arm spacing, with experimental results reported in a companion paper.

Multiscale Modeling of Cell Interaction in Angiogenesis: From the Micro- to Macro-scale

NASA Astrophysics Data System (ADS)

Pillay, Samara; Maini, Philip; Byrne, Helen

Solid tumors require a supply of nutrients to grow in size. To this end, tumors induce the growth of new blood vessels from existing vasculature through the process of angiogenesis. In this work, we use a discrete agent-based approach to model the behavior of individual endothelial cells during angiogenesis. We incorporate crowding effects through volume exclusion, motility of cells through biased random walks, and include birth and death processes. We use the transition probabilities associated with the discrete models to determine collective cell behavior, in terms of partial differential equations, using a Markov chain and master equation framework. We find that the cell-level dynamics gives rise to a migrating cell front in the form of a traveling wave on the macro-scale. The behavior of this front depends on the cell interactions that are included and the extent to which volume exclusion is taken into account in the discrete micro-scale model. We also find that well-established continuum models of angiogenesis cannot distinguish between certain types of cell behavior on the micro-scale. This may impact drug development strategies based on these models.

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.

Physical controls and predictability of stream hyporheic flow evaluated with a multiscale model

USGS Publications Warehouse

Stonedahl, Susa H.; Harvey, Judson W.; Detty, Joel; Aubeneau, Antoine; Packman, Aaron I.

2012-01-01

Improved predictions of hyporheic exchange based on easily measured physical variables are needed to improve assessment of solute transport and reaction processes in watersheds. Here we compare physically based model predictions for an Indiana stream with stream tracer results interpreted using the Transient Storage Model (TSM). We parameterized the physically based, Multiscale Model (MSM) of stream-groundwater interactions with measured stream planform and discharge, stream velocity, streambed hydraulic conductivity and porosity, and topography of the streambed at distinct spatial scales (i.e., ripple, bar, and reach scales). We predicted hyporheic exchange fluxes and hyporheic residence times using the MSM. A Continuous Time Random Walk (CTRW) model was used to convert the MSM output into predictions of in stream solute transport, which we compared with field observations and TSM parameters obtained by fitting solute transport data. MSM simulations indicated that surface-subsurface exchange through smaller topographic features such as ripples was much faster than exchange through larger topographic features such as bars. However, hyporheic exchange varies nonlinearly with groundwater discharge owing to interactions between flows induced at different topographic scales. MSM simulations showed that groundwater discharge significantly decreased both the volume of water entering the subsurface and the time it spent in the subsurface. The MSM also characterized longer timescales of exchange than were observed by the tracer-injection approach. The tracer data, and corresponding TSM fits, were limited by tracer measurement sensitivity and uncertainty in estimates of background tracer concentrations. Our results indicate that rates and patterns of hyporheic exchange are strongly influenced by a continuum of surface-subsurface hydrologic interactions over a wide range of spatial and temporal scales rather than discrete processes.

Multiscale polar theory of microtubule and motor-protein assemblies

DOE PAGES

Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; ...

2015-01-27

Microtubules and motor proteins are building blocks of self-organized subcellular biological structures such as the mitotic spindle and the centrosomal microtubule array. These same ingredients can form new “bioactive” liquid-crystalline fluids that are intrinsically out of equilibrium and which display complex flows and defect dynamics. It is not yet well understood how microscopic activity, which involves polarity-dependent interactions between motor proteins and microtubules, yields such larger-scale dynamical structures. In our multiscale theory, Brownian dynamics simulations of polar microtubule ensembles driven by cross-linking motors allow us to study microscopic organization and stresses. Polarity sorting and cross-link relaxation emerge as two polar-specificmore » sources of active destabilizing stress. On larger length scales, our continuum Doi-Onsager theory captures the hydrodynamic flows generated by polarity-dependent active stresses. Finally, the results connect local polar structure to flow structures and defect dynamics.« less

All-Particle Multiscale Computation of Hypersonic Rarefied Flow

NASA Astrophysics Data System (ADS)

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

2011-05-01

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

Solid-Liquid Interface Thermal Resistance Affects the Evaporation Rate of Droplets from a Surface: A Study of Perfluorohexane on Chromium Using Molecular Dynamics and Continuum Theory.

PubMed

Han, Haoxue; Schlawitschek, Christiane; Katyal, Naman; Stephan, Peter; Gambaryan-Roisman, Tatiana; Leroy, Frédéric; Müller-Plathe, Florian

2017-05-30

We study the role of solid-liquid interface thermal resistance (Kapitza resistance) on the evaporation rate of droplets on a heated surface by using a multiscale combination of molecular dynamics (MD) simulations and analytical continuum theory. We parametrize the nonbonded interaction potential between perfluorohexane (C 6 F 14 ) and a face-centered-cubic solid surface to reproduce the experimental wetting behavior of C 6 F 14 on black chromium through the solid-liquid work of adhesion (quantity directly related to the wetting angle). The thermal conductances between C 6 F 14 and (100) and (111) solid substrates are evaluated by a nonequilibrium molecular dynamics approach for a liquid pressure lower than 2 MPa. Finally, we examine the influence of the Kapitza resistance on evaporation of droplets in the vicinity of a three-phase contact line with continuum theory, where the thermal resistance of liquid layer is comparable with the Kapitza resistance. We determine the thermodynamic conditions under which the Kapitza resistance plays an important role in correctly predicting the evaporation heat flux.

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.

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...

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.

Multiscale Mechano-Biological Finite Element Modelling of Oncoplastic Breast Surgery—Numerical Study towards Surgical Planning and Cosmetic Outcome Prediction

PubMed Central

Eiben, Bjoern; Hipwell, John H.; Williams, Norman R.; Keshtgar, Mo; Hawkes, David J.

2016-01-01

Surgical treatment for early-stage breast carcinoma primarily necessitates breast conserving therapy (BCT), where the tumour is removed while preserving the breast shape. To date, there have been very few attempts to develop accurate and efficient computational tools that could be used in the clinical environment for pre-operative planning and oncoplastic breast surgery assessment. Moreover, from the breast cancer research perspective, there has been very little effort to model complex mechano-biological processes involved in wound healing. We address this by providing an integrated numerical framework that can simulate the therapeutic effects of BCT over the extended period of treatment and recovery. A validated, three-dimensional, multiscale finite element procedure that simulates breast tissue deformations and physiological wound healing is presented. In the proposed methodology, a partitioned, continuum-based mathematical model for tissue recovery and angiogenesis, and breast tissue deformation is considered. The effectiveness and accuracy of the proposed numerical scheme is illustrated through patient-specific representative examples. Wound repair and contraction numerical analyses of real MRI-derived breast geometries are investigated, and the final predictions of the breast shape are validated against post-operative follow-up optical surface scans from four patients. Mean (standard deviation) breast surface distance errors in millimetres of 3.1 (±3.1), 3.2 (±2.4), 2.8 (±2.7) and 4.1 (±3.3) were obtained, demonstrating the ability of the surgical simulation tool to predict, pre-operatively, the outcome of BCT to clinically useful accuracy. PMID:27466815

Mechanistic insights into electrochemical reduction of CO2 over Ag using density functional theory and transport models

PubMed Central

Goodpaster, Jason D.; Weber, Adam Z.

2017-01-01

Electrochemical reduction of CO2 using renewable sources of electrical energy holds promise for converting CO2 to fuels and chemicals. Since this process is complex and involves a large number of species and physical phenomena, a comprehensive understanding of the factors controlling product distribution is required. While the most plausible reaction pathway is usually identified from quantum-chemical calculation of the lowest free-energy pathway, this approach can be misleading when coverages of adsorbed species determined for alternative mechanism differ significantly, since elementary reaction rates depend on the product of the rate coefficient and the coverage of species involved in the reaction. Moreover, cathode polarization can influence the kinetics of CO2 reduction. Here, we present a multiscale framework for ab initio simulation of the electrochemical reduction of CO2 over an Ag(110) surface. A continuum model for species transport is combined with a microkinetic model for the cathode reaction dynamics. Free energies of activation for all elementary reactions are determined from density functional theory calculations. Using this approach, three alternative mechanisms for CO2 reduction were examined. The rate-limiting step in each mechanism is **COOH formation at higher negative potentials. However, only via the multiscale simulation was it possible to identify the mechanism that leads to a dependence of the rate of CO formation on the partial pressure of CO2 that is consistent with experiments. Simulations based on this mechanism also describe the dependence of the H2 and CO current densities on cathode voltage that are in strikingly good agreement with experimental observation. PMID:28973926

Multi-scale continuum modeling of biological processes: from molecular electro-diffusion to sub-cellular signaling transduction

NASA Astrophysics Data System (ADS)

Cheng, Y.; Kekenes-Huskey, P.; Hake, J. E.; Holst, M. J.; McCammon, J. A.; Michailova, A. P.

2012-01-01

This paper presents a brief review of multi-scale modeling at the molecular to cellular scale, with new results for heart muscle cells. A finite element-based simulation package (SMOL) was used to investigate the signaling transduction at molecular and sub-cellular scales (http://mccammon.ucsd.edu/smol/, http://FETK.org) by numerical solution of the time-dependent Smoluchowski equations and a reaction-diffusion system. At the molecular scale, SMOL has yielded experimentally validated estimates of the diffusion-limited association rates for the binding of acetylcholine to mouse acetylcholinesterase using crystallographic structural data. The predicted rate constants exhibit increasingly delayed steady-state times, with increasing ionic strength, and demonstrate the role of an enzyme's electrostatic potential in influencing ligand binding. At the sub-cellular scale, an extension of SMOL solves a nonlinear, reaction-diffusion system describing Ca2+ ligand buffering and diffusion in experimentally derived rodent ventricular myocyte geometries. Results reveal the important role of mobile and stationary Ca2+ buffers, including Ca2+ indicator dye. We found that alterations in Ca2+-binding and dissociation rates of troponin C (TnC) and total TnC concentration modulate sub-cellular Ca2+ signals. The model predicts that reduced off-rate in the whole troponin complex (TnC, TnI, TnT) versus reconstructed thin filaments (Tn, Tm, actin) alters cytosolic Ca2+ dynamics under control conditions or in disease-linked TnC mutations. The ultimate goal of these studies is to develop scalable methods and theories for the integration of molecular-scale information into simulations of cellular-scale systems.

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

Predicting the Influence of Nano-Scale Material Structure on the In-Plane Buckling of Orthotropic Plates

NASA Technical Reports Server (NTRS)

Gates, Thomas S.; Odegard, Gregory M.; Nemeth, Michael P.; Frankland, Sarah-Jane V.

2004-01-01

A multi-scale analysis of the structural stability of a carbon nanotube-polymer composite material is developed. The influence of intrinsic molecular structure, such as nanotube length, volume fraction, orientation and chemical functionalization, is investigated by assessing the relative change in critical, in-plane buckling loads. The analysis method relies on elastic properties predicted using the hierarchical, constitutive equations developed from the equivalent-continuum modeling technique applied to the buckling analysis of an orthotropic plate. The results indicate that for the specific composite materials considered in this study, a composite with randomly orientated carbon nanotubes consistently provides the highest values of critical buckling load and that for low volume fraction composites, the non-functionalized nanotube material provides an increase in critical buckling stability with respect to the functionalized system.

Linking the Grain Scale to Experimental Measurements and Other Scales

NASA Astrophysics Data System (ADS)

Vogler, Tracy

2017-06-01

A number of physical processes occur at the scale of grains that can have a profound influence on the behavior of materials under shock loading. Examples include inelastic deformation, pore collapse, fracture, friction, and internal wave reflections. In some cases such as the initiation of energetics and brittle fracture, these processes can have first order effects on the behavior of materials: the emergent behavior from the grain scale is the dominant one. In other cases, many aspects of the bulk behavior can be described by a continuum description, but some details of the behavior are missed by continuum descriptions. The multi-scale model paradigm envisions flow of information from smaller scales (atomic, dislocation, etc.) to the grain or mesoscale and the up to the continuum scale. A significant challenge in this approach is the need to validate each step. For the grain scale, diagnosing behavior is challenging because of the small spatial and temporal scales involved. Spatially resolved diagnostics have begun to shed light on these processes, and, more recently, advanced light sources have started to be used to probe behavior at the grain scale. In this talk, I will discuss some interesting phenomena that occur at the grain scale in shock loading, experimental approaches to probe the grain scale, and efforts to link the grain scale to smaller and larger scales. Sandia National Laboratories is a multi-mission laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE.

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

Predicting dynamics and rheology of blood flow: A comparative study of multiscale and low-dimensional models of red blood cells

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

Pan, Wenxiao; Fedosov, Dmitry A.; Caswell, Bruce

In this work we compare the predictive capability of two mathematical models for red blood cells (RBCs) focusing on blood flow in capillaries and arterioles. Both RBC models as well as their corresponding blood flows are based on the dissipative particle dynamics (DPD) method, a coarse-grained molecular dynamics approach. The first model employs a multiscale description of the RBC (MS-RBC), with its membrane represented by hundreds or even thousands of DPD-particles connected by springs into a triangular network in combination with out-of-plane elastic bending resistance. Extra dissipation within the network accounts for membrane viscosity, while the characteristic biconcave RBC shapemore » is achieved by imposition of constraints for constant membrane area and constant cell volume. The second model is based on a low-dimensional description (LD-RBC) constructed as a closed torus-like ring of only 10 large DPD colloidal particles. They are connected into a ring by worm-like chain (WLC) springs combined with bending resistance. The LD-RBC model can be fitted to represent the entire range of nonlinear elastic deformations as measured by optical-tweezers for healthy and for infected RBCs in malaria. MS-RBCs suspensions model the dynamics and rheology of blood flow accurately for any size vessel but this approach is computationally expensive above 100 microns. Surprisingly, the much more economical suspensions of LD-RBCs also capture the blood flow dynamics and rheology accurately except for vessels with sizes comparable to RBC diameter. In particular, the LD-RBC suspensions are shown to properly capture the experimental data for the apparent viscosity of blood and its cell-free layer (CFL) in tube flow. Taken together, these findings suggest a hierarchical approach in modeling blood flow in the arterial tree, whereby the MS-RBC model should be employed for capillaries and arterioles below 100 microns, the LD-RBC model for arterioles, and the continuum description for arteries.« less

A Mass Diffusion Model for Dry Snow Utilizing a Fabric Tensor to Characterize Anisotropy

NASA Astrophysics Data System (ADS)

Shertzer, Richard H.; Adams, Edward E.

2018-03-01

A homogenization algorithm for randomly distributed microstructures is applied to develop a mass diffusion model for dry snow. Homogenization is a multiscale approach linking constituent behavior at the microscopic level—among ice and air—to the macroscopic material—snow. Principles of continuum mechanics at the microscopic scale describe water vapor diffusion across an ice grain's surface to the air-filled pore space. Volume averaging and a localization assumption scale up and down, respectively, between microscopic and macroscopic scales. The model yields a mass diffusivity expression at the macroscopic scale that is, in general, a second-order tensor parameterized by both bulk and microstructural variables. The model predicts a mass diffusivity of water vapor through snow that is less than that through air. Mass diffusivity is expected to decrease linearly with ice volume fraction. Potential anisotropy in snow's mass diffusivity is captured due to the tensor representation. The tensor is built from directional data assigned to specific, idealized microstructural features. Such anisotropy has been observed in the field and laboratories in snow morphologies of interest such as weak layers of depth hoar and near-surface facets.

Predicting the continuum between corridors and barriers to animal movements using Step Selection Functions and Randomized Shortest Paths.

PubMed

Panzacchi, Manuela; Van Moorter, Bram; Strand, Olav; Saerens, Marco; Kivimäki, Ilkka; St Clair, Colleen C; Herfindal, Ivar; Boitani, Luigi

2016-01-01

The loss, fragmentation and degradation of habitat everywhere on Earth prompts increasing attention to identifying landscape features that support animal movement (corridors) or impedes it (barriers). Most algorithms used to predict corridors assume that animals move through preferred habitat either optimally (e.g. least cost path) or as random walkers (e.g. current models), but neither extreme is realistic. We propose that corridors and barriers are two sides of the same coin and that animals experience landscapes as spatiotemporally dynamic corridor-barrier continua connecting (separating) functional areas where individuals fulfil specific ecological processes. Based on this conceptual framework, we propose a novel methodological approach that uses high-resolution individual-based movement data to predict corridor-barrier continua with increased realism. Our approach consists of two innovations. First, we use step selection functions (SSF) to predict friction maps quantifying corridor-barrier continua for tactical steps between consecutive locations. Secondly, we introduce to movement ecology the randomized shortest path algorithm (RSP) which operates on friction maps to predict the corridor-barrier continuum for strategic movements between functional areas. By modulating the parameter Ѳ, which controls the trade-off between exploration and optimal exploitation of the environment, RSP bridges the gap between algorithms assuming optimal movements (when Ѳ approaches infinity, RSP is equivalent to LCP) or random walk (when Ѳ → 0, RSP → current models). Using this approach, we identify migration corridors for GPS-monitored wild reindeer (Rangifer t. tarandus) in Norway. We demonstrate that reindeer movement is best predicted by an intermediate value of Ѳ, indicative of a movement trade-off between optimization and exploration. Model calibration allows identification of a corridor-barrier continuum that closely fits empirical data and demonstrates that RSP outperforms models that assume either optimality or random walk. The proposed approach models the multiscale cognitive maps by which animals likely navigate real landscapes and generalizes the most common algorithms for identifying corridors. Because suboptimal, but non-random, movement strategies are likely widespread, our approach has the potential to predict more realistic corridor-barrier continua for a wide range of species. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

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

Multi-scale Modeling of Plasticity in Tantalum.

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

Lim, Hojun; Battaile, Corbett Chandler.; Carroll, Jay

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

JDFTx: Software for joint density-functional theory

DOE PAGES

Sundararaman, Ravishankar; Letchworth-Weaver, Kendra; Schwarz, Kathleen A.; ...

2017-11-14

Density-functional theory (DFT) has revolutionized computational prediction of atomic-scale properties from first principles in physics, chemistry and materials science. Continuing development of new methods is necessary for accurate predictions of new classes of materials and properties, and for connecting to nano- and mesoscale properties using coarse-grained theories. JDFTx is a fully-featured open-source electronic DFT software designed specifically to facilitate rapid development of new theories, models and algorithms. Using an algebraic formulation as an abstraction layer, compact C++11 code automatically performs well on diverse hardware including GPUs (Graphics Processing Units). This code hosts the development of joint density-functional theory (JDFT) thatmore » combines electronic DFT with classical DFT and continuum models of liquids for first-principles calculations of solvated and electrochemical systems. In addition, the modular nature of the code makes it easy to extend and interface with, facilitating the development of multi-scale toolkits that connect to ab initio calculations, e.g. photo-excited carrier dynamics combining electron and phonon calculations with electromagnetic simulations.« less

JDFTx: Software for joint density-functional theory

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

Sundararaman, Ravishankar; Letchworth-Weaver, Kendra; Schwarz, Kathleen A.

Density-functional theory (DFT) has revolutionized computational prediction of atomic-scale properties from first principles in physics, chemistry and materials science. Continuing development of new methods is necessary for accurate predictions of new classes of materials and properties, and for connecting to nano- and mesoscale properties using coarse-grained theories. JDFTx is a fully-featured open-source electronic DFT software designed specifically to facilitate rapid development of new theories, models and algorithms. Using an algebraic formulation as an abstraction layer, compact C++11 code automatically performs well on diverse hardware including GPUs (Graphics Processing Units). This code hosts the development of joint density-functional theory (JDFT) thatmore » combines electronic DFT with classical DFT and continuum models of liquids for first-principles calculations of solvated and electrochemical systems. In addition, the modular nature of the code makes it easy to extend and interface with, facilitating the development of multi-scale toolkits that connect to ab initio calculations, e.g. photo-excited carrier dynamics combining electron and phonon calculations with electromagnetic simulations.« less

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.

Multiscale Multiphysics and Multidomain Models I: Basic Theory

PubMed Central

Wei, Guo-Wei

2013-01-01

This work extends our earlier two-domain formulation of a differential geometry based multiscale paradigm into a multidomain theory, which endows us the ability to simultaneously accommodate multiphysical descriptions of aqueous chemical, physical and biological systems, such as fuel cells, solar cells, nanofluidics, ion channels, viruses, RNA polymerases, molecular motors and large macromolecular complexes. The essential idea is to make use of the differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain of solvent from the microscopic domain of solute, and dynamically couple continuum and discrete descriptions. Our main strategy is to construct energy functionals to put on an equal footing of multiphysics, including polar (i.e., electrostatic) solvation, nonpolar solvation, chemical potential, quantum mechanics, fluid mechanics, molecular mechanics, coarse grained dynamics and elastic dynamics. The variational principle is applied to the energy functionals to derive desirable governing equations, such as multidomain Laplace-Beltrami (LB) equations for macromolecular morphologies, multidomain Poisson-Boltzmann (PB) equation or Poisson equation for electrostatic potential, generalized Nernst-Planck (NP) equations for the dynamics of charged solvent species, generalized Navier-Stokes (NS) equation for fluid dynamics, generalized Newton's equations for molecular dynamics (MD) or coarse-grained dynamics and equation of motion for elastic dynamics. Unlike the classical PB equation, our PB equation is an integral-differential equation due to solvent-solute interactions. To illustrate the proposed formalism, we have explicitly constructed three models, a multidomain solvation model, a multidomain charge transport model and a multidomain chemo-electro-fluid-MD-elastic model. Each solute domain is equipped with distinct surface tension, pressure, dielectric function, and charge density distribution. In addition to long-range Coulombic interactions, various non-electrostatic solvent-solute interactions are considered in the present modeling. We demonstrate the consistency between the non-equilibrium charge transport model and the equilibrium solvation model by showing the systematical reduction of the former to the latter at equilibrium. This paper also offers a brief review of the field. PMID:25382892

Multiscale Multiphysics and Multidomain Models I: Basic Theory.

PubMed

Wei, Guo-Wei

2013-12-01

This work extends our earlier two-domain formulation of a differential geometry based multiscale paradigm into a multidomain theory, which endows us the ability to simultaneously accommodate multiphysical descriptions of aqueous chemical, physical and biological systems, such as fuel cells, solar cells, nanofluidics, ion channels, viruses, RNA polymerases, molecular motors and large macromolecular complexes. The essential idea is to make use of the differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain of solvent from the microscopic domain of solute, and dynamically couple continuum and discrete descriptions. Our main strategy is to construct energy functionals to put on an equal footing of multiphysics, including polar (i.e., electrostatic) solvation, nonpolar solvation, chemical potential, quantum mechanics, fluid mechanics, molecular mechanics, coarse grained dynamics and elastic dynamics. The variational principle is applied to the energy functionals to derive desirable governing equations, such as multidomain Laplace-Beltrami (LB) equations for macromolecular morphologies, multidomain Poisson-Boltzmann (PB) equation or Poisson equation for electrostatic potential, generalized Nernst-Planck (NP) equations for the dynamics of charged solvent species, generalized Navier-Stokes (NS) equation for fluid dynamics, generalized Newton's equations for molecular dynamics (MD) or coarse-grained dynamics and equation of motion for elastic dynamics. Unlike the classical PB equation, our PB equation is an integral-differential equation due to solvent-solute interactions. To illustrate the proposed formalism, we have explicitly constructed three models, a multidomain solvation model, a multidomain charge transport model and a multidomain chemo-electro-fluid-MD-elastic model. Each solute domain is equipped with distinct surface tension, pressure, dielectric function, and charge density distribution. In addition to long-range Coulombic interactions, various non-electrostatic solvent-solute interactions are considered in the present modeling. We demonstrate the consistency between the non-equilibrium charge transport model and the equilibrium solvation model by showing the systematical reduction of the former to the latter at equilibrium. This paper also offers a brief review of the field.

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.

Enabling Microscopic Simulators to Perform System Level Tasks: A System-Identification Based, Closure-on-Demand Toolkit for Multiscale Simulation Stability/Bifurcation Analysis, Optimization and Control

DTIC Science & Technology

2006-10-01

The objective was to construct a bridge between existing and future microscopic simulation codes ( kMC , MD, MC, BD, LB etc.) and traditional, continuum...kinetic Monte Carlo, kMC , equilibrium MC, Lattice-Boltzmann, LB, Brownian Dynamics, BD, or general agent-based, AB) simulators. It also, fortuitously...cond-mat/0310460 at arXiv.org. 27. Coarse Projective kMC Integration: Forward/Reverse Initial and Boundary Value Problems", R. Rico-Martinez, C. W

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.

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.

Solute effect on basal and prismatic slip systems of Mg.

PubMed

Moitra, Amitava; Kim, Seong-Gon; Horstemeyer, M F

2014-11-05

In an effort to design novel magnesium (Mg) alloys with high ductility, we present a first principles data based on the Density Functional Theory (DFT). The DFT was employed to calculate the generalized stacking fault energy curves, which can be used in the generalized Peierls-Nabarro (PN) model to study the energetics of basal slip and prismatic slip in Mg with and without solutes to calculate continuum scale dislocation core widths, stacking fault widths and Peierls stresses. The generalized stacking fault energy curves for pure Mg agreed well with other DFT calculations. Solute effects on these curves were calculated for nine alloying elements, namely Al, Ca, Ce, Gd, Li, Si, Sn, Zn and Zr, which allowed the strength and ductility to be qualitatively estimated based on the basal dislocation properties. Based on our multiscale methodology, a suggestion has been made to improve Mg formability.

A multiscale quasi-continuum theory to determine thermodynamic properties of fluid mixtures in nanochannels

NASA Astrophysics Data System (ADS)

Motevaselian, Mohammad Hossein; Mashayak, Sikandar Y.; Aluru, Narayana R.

2015-11-01

We present an empirical potential-based quasi-continuum theory (EQT) that seamlessly integrates the interatomic potentials into a continuum framework such as the Nernst-Planck equation. EQT is a simple and fast approach, which provides accurate predictions of potential of mean force (PMF) and density distribution of confined fluids at multiple length-scales, ranging from few Angstroms to macro meters. The EQT potentials can be used to construct the excess free energy functional in the classical density functional theory (cDFT). The combination of EQT and cDFT (EQT-cDFT), allows one to predict the thermodynamic properties of confined fluids. Recently, the EQT-cDFT framework was developed for single component LJ fluids confined in slit-like graphene channels. In this work, we extend the framework to confined LJ fluid mixtures and demonstrate it by simulating a mixture of methane and hydrogen molecules inside slit-like graphene channels. We show that the EQT-cDFT predictions for the structure of the confined fluid mixture compare well with the MD simulations. In addition, our results show that graphene nanochannels exhibit a selective adsorption of methane over hydrogen.

A multi-scale Lattice Boltzmann model for simulating solute transport in 3D X-ray micro-tomography images of aggregated porous materials

NASA Astrophysics Data System (ADS)

Zhang, Xiaoxian; Crawford, John W.; Flavel, Richard J.; Young, Iain M.

2016-10-01

The Lattice Boltzmann (LB) model and X-ray computed tomography (CT) have been increasingly used in combination over the past decade to simulate water flow and chemical transport at pore scale in porous materials. Because of its limitation in resolution and the hierarchical structure of most natural soils, the X-ray CT tomography can only identify pores that are greater than its resolution and treats other pores as solid. As a result, the so-called solid phase in X-ray images may in reality be a grey phase, containing substantial connected pores capable of conducing fluids and solute. Although modified LB models have been developed to simulate fluid flow in such media, models for solute transport are relatively limited. In this paper, we propose a LB model for simulating solute transport in binary soil images containing permeable solid phase. The model is based on the single-relaxation time approach and uses a modified partial bounce-back method to describe the resistance caused by the permeable solid phase to chemical transport. We derive the relationship between the diffusion coefficient and the parameter introduced in the partial bounce-back method, and test the model against analytical solution for movement of a pulse of tracer. We also validate it against classical finite volume method for solute diffusion in a simple 2D image, and then apply the model to a soil image acquired using X-ray tomography at resolution of 30 μm in attempts to analyse how the ability of the solid phase to diffuse solute at micron-scale affects the behaviour of the solute at macro-scale after a volumetric average. Based on the simulated results, we discuss briefly the danger in interpreting experimental results using the continuum model without fully understanding the pore-scale processes, as well as the potential of using pore-scale modelling and tomography to help improve the continuum models.

A Multiscale Virtual Fabrication and Lattice Modeling Approach for the Fatigue Performance Prediction of Asphalt Concrete

NASA Astrophysics Data System (ADS)

Dehghan Banadaki, Arash

Predicting the ultimate performance of asphalt concrete under realistic loading conditions is the main key to developing better-performing materials, designing long-lasting pavements, and performing reliable lifecycle analysis for pavements. The fatigue performance of asphalt concrete depends on the mechanical properties of the constituent materials, namely asphalt binder and aggregate. This dependent link between performance and mechanical properties is extremely complex, and experimental techniques often are used to try to characterize the performance of hot mix asphalt. However, given the seemingly uncountable number of mixture designs and loading conditions, it is simply not economical to try to understand and characterize the material behavior solely by experimentation. It is well known that analytical and computational modeling methods can be combined with experimental techniques to reduce the costs associated with understanding and characterizing the mechanical behavior of the constituent materials. This study aims to develop a multiscale micromechanical lattice-based model to predict cracking in asphalt concrete using component material properties. The proposed algorithm, while capturing different phenomena for different scales, also minimizes the need for laboratory experiments. The developed methodology builds on a previously developed lattice model and the viscoelastic continuum damage model to link the component material properties to the mixture fatigue performance. The resulting lattice model is applied to predict the dynamic modulus mastercurves for different scales. A framework for capturing the so-called structuralization effects is introduced that significantly improves the accuracy of the modulus prediction. Furthermore, air voids are added to the model to help capture this important micromechanical feature that affects the fatigue performance of asphalt concrete as well as the modulus value. The effects of rate dependency are captured by implementing the viscoelastic fracture criterion. In the end, an efficient cyclic loading framework is developed to evaluate the damage accumulation in the material that is caused by long-sustained cyclic loads.

Sequential slip transfer of mixed-character dislocations across Σ3 coherent twin boundary in FCC metals: a concurrent atomistic-continuum study

DOE PAGES

Xu, Shuozhi; Xiong, Liming; Chen, Youping; ...

2016-01-29

Sequential slip transfer across grain boundaries (GB) has an important role in size-dependent propagation of plastic deformation in polycrystalline metals. For example, the Hall–Petch effect, which states that a smaller average grain size results in a higher yield stress, can be rationalised in terms of dislocation pile-ups against GBs. In spite of extensive studies in modelling individual phases and grains using atomistic simulations, well-accepted criteria of slip transfer across GBs are still lacking, as well as models of predicting irreversible GB structure evolution. Slip transfer is inherently multiscale since both the atomic structure of the boundary and the long-range fieldsmore » of the dislocation pile-up come into play. In this work, concurrent atomistic-continuum simulations are performed to study sequential slip transfer of a series of curved dislocations from a given pile-up on Σ3 coherent twin boundary (CTB) in Cu and Al, with dominant leading screw character at the site of interaction. A Frank-Read source is employed to nucleate dislocations continuously. It is found that subject to a shear stress of 1.2 GPa, screw dislocations transfer into the twinned grain in Cu, but glide on the twin boundary plane in Al. Moreover, four dislocation/CTB interaction modes are identified in Al, which are affected by (1) applied shear stress, (2) dislocation line length, and (3) dislocation line curvature. Our results elucidate the discrepancies between atomistic simulations and experimental observations of dislocation-GB reactions and highlight the importance of directly modeling sequential dislocation slip transfer reactions using fully 3D models.« less

Sequential slip transfer of mixed-character dislocations across Σ3 coherent twin boundary in FCC metals: a concurrent atomistic-continuum study

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

Xu, Shuozhi; Xiong, Liming; Chen, Youping

Sequential slip transfer across grain boundaries (GB) has an important role in size-dependent propagation of plastic deformation in polycrystalline metals. For example, the Hall–Petch effect, which states that a smaller average grain size results in a higher yield stress, can be rationalised in terms of dislocation pile-ups against GBs. In spite of extensive studies in modelling individual phases and grains using atomistic simulations, well-accepted criteria of slip transfer across GBs are still lacking, as well as models of predicting irreversible GB structure evolution. Slip transfer is inherently multiscale since both the atomic structure of the boundary and the long-range fieldsmore » of the dislocation pile-up come into play. In this work, concurrent atomistic-continuum simulations are performed to study sequential slip transfer of a series of curved dislocations from a given pile-up on Σ3 coherent twin boundary (CTB) in Cu and Al, with dominant leading screw character at the site of interaction. A Frank-Read source is employed to nucleate dislocations continuously. It is found that subject to a shear stress of 1.2 GPa, screw dislocations transfer into the twinned grain in Cu, but glide on the twin boundary plane in Al. Moreover, four dislocation/CTB interaction modes are identified in Al, which are affected by (1) applied shear stress, (2) dislocation line length, and (3) dislocation line curvature. Our results elucidate the discrepancies between atomistic simulations and experimental observations of dislocation-GB reactions and highlight the importance of directly modeling sequential dislocation slip transfer reactions using fully 3D models.« less

Cells competition in tumor growth poroelasticity

NASA Astrophysics Data System (ADS)

Fraldi, Massimiliano; Carotenuto, Angelo R.

2018-03-01

Growth of biological tissues has been recently treated within the framework of Continuum Mechanics, by adopting heterogeneous poroelastic models where the interaction between soft matrix and interstitial fluid flow is coupled with inelastic effects ad hoc introduced to simulate the macroscopic volumetric growth determined by cells division, cells growth and extracellular matrix changes occurring at the micro-scale level. These continuum models seem to overcome some limitations intrinsically associated to other alternative approaches based on mass balances in multiphase systems, because the crucial role played by residual stresses accompanying growth and nutrients walkway is preserved. Nevertheless, when these strategies are applied to analyze solid tumors, mass growth is usually assigned in a prescribed form that essentially copies the in vitro measured intrinsic growth rates of the cell species. As a consequence, some important cell-cell dynamics governing mass evolution and invasion rates of cancer cells, as well as their coupling with feedback mechanisms associated to in situ stresses, are inevitably lost and thus the spatial distribution and the evolution with time of the growth inside the tumor -which would be results rather than inputs- are forced to enter in the model simply as data. In order to solve this paradox, it is here proposed an enhanced multi-scale poroelastic model undergoing large deformations and embodying inelastic growth, where the net growth terms directly result from the "interspecific" predator-prey (Volterra/Lotka-like) competition occurring at the micro-scale level between healthy and abnormal cell species. In this way, a system of fully-coupled non-linear PDEs is derived to describe how the fight among cell species to grab the available common resources, stress field, pressure gradients, interstitial fluid flows driving nutrients and inhomogeneous growth all simultaneously interact to decide the tumor fate.

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...

Mechanistic insights into electrochemical reduction of CO 2 over Ag using density functional theory and transport models

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

Singh, Meenesh R.; Goodpaster, Jason D.; Weber, Adam Z.

Electrochemical reduction of CO 2 using renewable sources of electrical energy holds promise for converting CO 2 to fuels and chemicals. Since this process is complex and involves a large number of species and physical phenomena, a comprehensive understanding of the factors controlling product distribution is required. While the most plausible reaction pathway is usually identified from quantum-chemical calculation of the lowest free-energy pathway, this approach can be misleading when coverages of adsorbed species determined for alternative mechanism differ significantly, since elementary reaction rates depend on the product of the rate coefficient and the coverage of species involved in themore » reaction. Moreover, cathode polarization can influence the kinetics of CO 2 reduction. Here in this work, we present a multiscale framework for ab initio simulation of the electrochemical reduction of CO 2 over an Ag(110) surface. A continuum model for species transport is combined with a microkinetic model for the cathode reaction dynamics. Free energies of activation for all elementary reactions are determined from density functional theory calculations. Using this approach, three alternative mechanisms for CO 2 reduction were examined. The rate-limiting step in each mechanism is **COOH formation at higher negative potentials. However, only via the multiscale simulation was it possible to identify the mechanism that leads to a dependence of the rate of CO formation on the partial pressure of CO 2 that is consistent with experiments. Additionally, simulations based on this mechanism also describe the dependence of the H 2 and CO current densities on cathode voltage that are in strikingly good agreement with experimental observation.« less

Multiscale modeling of the dynamics of multicellular systems

NASA Astrophysics Data System (ADS)

Kosztin, Ioan

2011-03-01

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

Mechanistic insights into electrochemical reduction of CO 2 over Ag using density functional theory and transport models

DOE PAGES

Singh, Meenesh R.; Goodpaster, Jason D.; Weber, Adam Z.; ...

2017-10-02

Electrochemical reduction of CO 2 using renewable sources of electrical energy holds promise for converting CO 2 to fuels and chemicals. Since this process is complex and involves a large number of species and physical phenomena, a comprehensive understanding of the factors controlling product distribution is required. While the most plausible reaction pathway is usually identified from quantum-chemical calculation of the lowest free-energy pathway, this approach can be misleading when coverages of adsorbed species determined for alternative mechanism differ significantly, since elementary reaction rates depend on the product of the rate coefficient and the coverage of species involved in themore » reaction. Moreover, cathode polarization can influence the kinetics of CO 2 reduction. Here in this work, we present a multiscale framework for ab initio simulation of the electrochemical reduction of CO 2 over an Ag(110) surface. A continuum model for species transport is combined with a microkinetic model for the cathode reaction dynamics. Free energies of activation for all elementary reactions are determined from density functional theory calculations. Using this approach, three alternative mechanisms for CO 2 reduction were examined. The rate-limiting step in each mechanism is **COOH formation at higher negative potentials. However, only via the multiscale simulation was it possible to identify the mechanism that leads to a dependence of the rate of CO formation on the partial pressure of CO 2 that is consistent with experiments. Additionally, simulations based on this mechanism also describe the dependence of the H 2 and CO current densities on cathode voltage that are in strikingly good agreement with experimental observation.« less

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 wavelet representations for mammographic feature analysis

NASA Astrophysics Data System (ADS)

Laine, Andrew F.; Song, Shuwu

1992-12-01

This paper introduces a novel approach for accomplishing mammographic feature analysis through multiresolution representations. We show that efficient (nonredundant) representations may be identified from digital mammography and used to enhance specific mammographic features within a continuum of scale space. The multiresolution decomposition of wavelet transforms provides a natural hierarchy in which to embed an interactive paradigm for accomplishing scale space feature analysis. Choosing wavelets (or analyzing functions) that are simultaneously localized in both space and frequency, results in a powerful methodology for image analysis. Multiresolution and orientation selectivity, known biological mechanisms in primate vision, are ingrained in wavelet representations and inspire the techniques presented in this paper. Our approach includes local analysis of complete multiscale representations. Mammograms are reconstructed from wavelet coefficients, enhanced by linear, exponential and constant weight functions localized in scale space. By improving the visualization of breast pathology we can improve the changes of early detection of breast cancers (improve quality) while requiring less time to evaluate mammograms for most patients (lower costs).

Multiscale 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.

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.

Predictive oncology: multidisciplinary, multi-scale in-silico modeling linking phenotype, morphology and growth

PubMed Central

Sanga, Sandeep; Frieboes, Hermann B.; Zheng, Xiaoming; Gatenby, Robert; Bearer, Elaine L.; Cristini, Vittorio

2007-01-01

Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically review advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we propose and discuss a multi-scale, i.e., from the molecular to the gross tumor scale, mathematical and computational “first-principle” approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We demonstrate that this methodology, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as phenotype-diagnostic tool and thus to predict collective and individual tumor cell invasion of surrounding host. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior. PMID:17629503

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

Use of the Fracture Continuum Model for Numerical Modeling of Flow and Transport of Deep Geologic Disposal of Nuclear Waste in Crystalline Rock

NASA Astrophysics Data System (ADS)

Hadgu, T.; Kalinina, E.; Klise, K. A.; Wang, Y.

2015-12-01

Numerical modeling of disposal of nuclear waste in a deep geologic repository in fractured crystalline rock requires robust characterization of fractures. Various methods for fracture representation in granitic rocks exist. In this study we used the fracture continuum model (FCM) to characterize fractured rock for use in the simulation of flow and transport in the far field of a generic nuclear waste repository located at 500 m depth. The FCM approach is a stochastic method that maps the permeability of discrete fractures onto a regular grid. The method generates permeability fields using field observations of fracture sets. The original method described in McKenna and Reeves (2005) was designed for vertical fractures. The method has since then been extended to incorporate fully three-dimensional representations of anisotropic permeability, multiple independent fracture sets, and arbitrary fracture dips and orientations, and spatial correlation (Kalinina et al. 20012, 2014). For this study the numerical code PFLOTRAN (Lichtner et al., 2015) has been used to model flow and transport. PFLOTRAN solves a system of generally nonlinear partial differential equations describing multiphase, 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). Benchmark tests were conducted to simulate flow and transport in a specified model domain. Distributions of fracture parameters were used to generate a selected number of realizations. For each realization, the FCM method was used to generate a permeability field of the fractured rock. The PFLOTRAN code was then used to simulate flow and transport in the domain. Simulation results and analysis are presented. The results indicate that the FCM approach is a viable method to model fractured crystalline rocks. The FCM is a computationally efficient way to generate realistic representation of complex fracture systems. This approach is of interest for nuclear waste disposal models applied over large domains.

Dynamic Behavior of Sand: Annual Report FY 11

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

Antoun, T; Herbold, E; Johnson, S

2012-03-15

Currently, design of earth-penetrating munitions relies heavily on empirical relationships to estimate behavior, making it difficult to design novel munitions or address novel target situations without expensive and time-consuming full-scale testing with relevant system and target characteristics. Enhancing design through numerical studies and modeling could help reduce the extent and duration of full-scale testing if the models have enough fidelity to capture all of the relevant parameters. This can be separated into three distinct problems: that of the penetrator structural and component response, that of the target response, and that of the coupling between the two. This project focuses onmore » enhancing understanding of the target response, specifically granular geomaterials, where the temporal and spatial multi-scale nature of the material controls its response. As part of the overarching goal of developing computational capabilities to predict the performance of conventional earth-penetrating weapons, this project focuses specifically on developing new models and numerical capabilities for modeling sand response in ALE3D. There is general recognition that granular materials behave in a manner that defies conventional continuum approaches which rely on response locality and which degrade in the presence of strong response nonlinearities, localization, and phase gradients. There are many numerical tools available to address parts of the problem. However, to enhance modeling capability, this project is pursuing a bottom-up approach of building constitutive models from higher fidelity, smaller spatial scale simulations (rather than from macro-scale observations of physical behavior as is traditionally employed) that are being augmented to address the unique challenges of mesoscale modeling of dynamically loaded granular materials. Through understanding response and sensitivity at the grain-scale, it is expected that better reduced order representations of response can be formulated at the continuum scale as illustrated in Figure 1 and Figure 2. The final result of this project is to implement such reduced order models in the ALE3D material library for general use.« less

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.

In silico biology of bone modelling and remodelling: adaptation.

PubMed

Gerhard, Friederike A; Webster, Duncan J; van Lenthe, G Harry; Müller, Ralph

2009-05-28

Modelling and remodelling are the processes by which bone adapts its shape and internal structure to external influences. However, the cellular mechanisms triggering osteoclastic resorption and osteoblastic formation are still unknown. In order to investigate current biological theories, in silico models can be applied. In the past, most of these models were based on the continuum assumption, but some questions related to bone adaptation can be addressed better by models incorporating the trabecular microstructure. In this paper, existing simulation models are reviewed and one of the microstructural models is extended to test the hypothesis that bone adaptation can be simulated without particular knowledge of the local strain distribution in the bone. Validation using an experimental murine loading model showed that this is possible. Furthermore, the experimental model revealed that bone formation cannot be attributed only to an increase in trabecular thickness but also to structural reorganization including the growth of new trabeculae. How these new trabeculae arise is still an unresolved issue and might be better addressed by incorporating other levels of hierarchy, especially the cellular level. The cellular level sheds light on the activity and interplay between the different cell types, leading to the effective change in the whole bone. For this reason, hierarchical multi-scale simulations might help in the future to better understand the biomathematical laws behind bone adaptation.

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.

Multiscale computational modeling of a radiantly driven solar thermal collector

NASA Astrophysics Data System (ADS)

Ponnuru, Koushik

The objectives of the master's thesis are to present, discuss and apply sequential multiscale modeling that combines analytical, numerical (finite element-based) and computational fluid dynamic (CFD) analysis to assist in the development of a radiantly driven macroscale solar thermal collector for energy harvesting. The solar thermal collector is a novel green energy system that converts solar energy to heat and utilizes dry air as a working heat transfer fluid (HTF). This energy system has important advantages over competitive technologies: it is self-contained (no energy sources are needed), there are no moving parts, no oil or supplementary fluids are needed and it is environmentally friendly since it is powered by solar radiation. This work focuses on the development of multi-physics and multiscale models for predicting the performance of the solar thermal collector. Model construction and validation is organized around three distinct and complementary levels. The first level involves an analytical analysis of the thermal transpiration phenomenon and models for predicting the associated mass flow pumping that occurs in an aerogel membrane in the presence of a large thermal gradient. Within the aerogel, a combination of convection, conduction and radiation occurs simultaneously in a domain where the pore size is comparable to the mean free path of the gas molecules. CFD modeling of thermal transpiration is not possible because all the available commercial CFD codes solve the Navier Stokes equations only for continuum flow, which is based on the assumption that the net molecular mass diffusion is zero. However, thermal transpiration occurs in a flow regime where a non-zero net molecular mass diffusion exists. Thus these effects are modeled by using Sharipov's [2] analytical expression for gas flow characterized by high Knudsen number. The second level uses a detailed CFD model solving Navier Stokes equations for momentum, heat and mass transfer in the various components of the device. We have used state-of-the-art computational fluid dynamics (CFD) software, Flow3D (www.flow3d.com) to model the effects of multiple coupled physical processes including buoyancy driven flow from local temperature differences within the plenums, fluid-solid momentum and heat transfer, and coupled radiation exchange between the aerogel, top glazing and environment. In addition, the CFD models include both convection and radiation exchange between the top glazing and the environment. Transient and steady-state thermal models have been constructed using COMSOL Multiphysics. The third level consists of a lumped-element system model, which enables rapid parametric analysis and helps to develop an understanding of the system behavior; the mathematical models developed and multiple CFD simulations studies focus on simultaneous solution of heat, momentum, mass and gas volume fraction balances and succeed in accurate state variable distributions confirmed by experimental measurements.

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

A Finite Element Framework for Studying the Mechanical Response of Macromolecules: Application to the Gating of the Mechanosensitive Channel MscL

PubMed Central

Tang, Yuye; Cao, Guoxin; Chen, Xi; Yoo, Jejoong; Yethiraj, Arun; Cui, Qiang

2006-01-01

The gating pathways of mechanosensitive channels of large conductance (MscL) in two bacteria (Mycobacterium tuberculosis and Escherichia coli) are studied using the finite element method. The phenomenological model treats transmembrane helices as elastic rods and the lipid membrane as an elastic sheet of finite thickness; the model is inspired by the crystal structure of MscL. The interactions between various continuum components are derived from molecular-mechanics energy calculations using the CHARMM all-atom force field. Both bacterial MscLs open fully upon in-plane tension in the membrane and the variation of pore diameter with membrane tension is found to be essentially linear. The estimated gating tension is close to the experimental value. The structural variations along the gating pathway are consistent with previous analyses based on structural models with experimental constraints and biased atomistic molecular-dynamics simulations. Upon membrane bending, neither MscL opens substantially, although there is notable and nonmonotonic variation in the pore radius. This emphasizes that the gating behavior of MscL depends critically on the form of the mechanical perturbation and reinforces the idea that the crucial gating parameter is lateral tension in the membrane rather than the curvature of the membrane. Compared to popular all-atom-based techniques such as targeted or steered molecular-dynamics simulations, the finite element method-based continuum-mechanics framework offers a unique alternative to bridge detailed intermolecular interactions and biological processes occurring at large spatial scales and long timescales. It is envisioned that such a hierarchical multiscale framework will find great value in the study of a variety of biological processes involving complex mechanical deformations such as muscle contraction and mechanotransduction. PMID:16731564

A New Concurrent Multiscale Methodology for Coupling Molecular Dynamics and Finite Element Analyses

NASA Technical Reports Server (NTRS)

Yamakov, Vesselin; Saether, Erik; Glaessgen, Edward H/.

2008-01-01

The coupling of molecular dynamics (MD) simulations with finite element methods (FEM) yields computationally efficient models that link fundamental material processes at the atomistic level with continuum field responses at higher length scales. The theoretical challenge involves developing a seamless connection along an interface between two inherently different simulation frameworks. Various specialized methods have been developed to solve particular classes of problems. Many of these methods link the kinematics of individual MD atoms with FEM nodes at their common interface, necessarily requiring that the finite element mesh be refined to atomic resolution. Some of these coupling approaches also require simulations to be carried out at 0 K and restrict modeling to two-dimensional material domains due to difficulties in simulating full three-dimensional material processes. In the present work, a new approach to MD-FEM coupling is developed based on a restatement of the standard boundary value problem used to define a coupled domain. The method replaces a direct linkage of individual MD atoms and finite element (FE) nodes with a statistical averaging of atomistic displacements in local atomic volumes associated with each FE node in an interface region. The FEM and MD computational systems are effectively independent and communicate only through an iterative update of their boundary conditions. With the use of statistical averages of the atomistic quantities to couple the two computational schemes, the developed approach is referred to as an embedded statistical coupling method (ESCM). ESCM provides an enhanced coupling methodology that is inherently applicable to three-dimensional domains, avoids discretization of the continuum model to atomic scale resolution, and permits finite temperature states to be applied.

Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen

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

Plechac, Petr; Vlachos, Dionisios; Katsoulakis, Markos

2013-09-05

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

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

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.

Mathematical modeling of postmenopausal osteoporosis and its treatment by the anti-catabolic drug denosumab

PubMed Central

Scheiner, S; Pivonka, P; Smith, D W; Dunstan, C R; Hellmich, C

2014-01-01

Denosumab, a fully human monoclonal antibody, has been approved for the treatment of postmenopausal osteoporosis. The therapeutic effect of denosumab rests on its ability to inhibit osteoclast differentiation. Here, we present a computational approach on the basis of coupling a pharmacokinetics model of denosumab with a pharmacodynamics model for quantifying the effect of denosumab on bone remodeling. The pharmacodynamics model comprises an integrated systems biology-continuum micromechanics approach, including a bone cell population model, considering the governing biochemical factors of bone remodeling (including the action of denosumab), and a multiscale micromechanics-based bone mechanics model, for implementing the mechanobiology of bone remodeling in our model. Numerical studies of postmenopausal osteoporosis show that denosumab suppresses osteoclast differentiation, thus strongly curtailing bone resorption. Simulation results also suggest that denosumab may trigger a short-term bone volume gain, which is, however, followed by constant or decreasing bone volume. This evolution is accompanied by a dramatic decrease of the bone turnover rate by more than one order of magnitude. The latter proposes dominant occurrence of secondary mineralization (which is not anymore impeded through cellular activity), leading to higher mineral concentration per bone volume. This explains the overall higher bone mineral density observed in denosumab-related clinical studies. Copyright © 2013 John Wiley & Sons, Ltd. PMID:24039120

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

Nonlinear photomechanics of nematic networks: upscaling microscopic behaviour to macroscopic deformation

NASA Astrophysics Data System (ADS)

Chung, Hayoung; Choi, Joonmyung; Yun, Jung-Hoon; Cho, Maenghyo

2016-02-01

A liquid crystal network whose chromophores are functionalized by photochromic dye exhibits light-induced mechanical behaviour. As a result, the micro-scaled thermotropic traits of the network and the macroscopic phase behaviour are both influenced as light alternates the shape of the dyes. In this paper, we present an analysis of this photomechanical behaviour based on the proposed multiscale framework, which incorporates the molecular details of microstate evolution into a continuum-based understanding. The effects of trans-to-cis photoisomerization driven by actinic light irradiation are first examined using molecular dynamics simulations, and are compared against the predictions of the classical dilution model; this reveals certain characteristics of mesogenic interaction upon isomerization, followed by changes in the polymeric structure. We then upscale the thermotropic phase-related information with the aid of a nonlinear finite element analysis; macroscopic deflection with respect to the wide ranges of temperature and actinic light intensity are thereby examined, which reveals that the classical model underestimates the true deformation. This work therefore provides measures for analysing photomechanics in general by bridging the gap between the micro- and macro-scales.

A Continuum-Atomistic Analysis of Transgranular Crack Propagation in Aluminum

NASA Technical Reports Server (NTRS)

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

2009-01-01

A concurrent multiscale modeling methodology that embeds a molecular dynamics (MD) region within a finite element (FEM) domain is used to study plastic processes at a crack tip in a single crystal of aluminum. The case of mode I loading is studied. A transition from deformation twinning to full dislocation emission from the crack tip is found when the crack plane is rotated around the [111] crystallographic axis. When the crack plane normal coincides with the [112] twinning direction, the crack propagates through a twinning mechanism. When the crack plane normal coincides with the [011] slip direction, the crack propagates through the emission of full dislocations. In intermediate orientations, a transition from full dislocation emission to twinning is found to occur with an increase in the stress intensity at the crack tip. This finding confirms the suggestion that the very high strain rates, inherently present in MD simulations, which produce higher stress intensities at the crack tip, over-predict the tendency for deformation twinning compared to experiments. The present study, therefore, aims to develop a more realistic and accurate predictive modeling of fracture processes.

From the Nano- to the Macroscale - Bridging Scales for the Moving Contact Line Problem

NASA Astrophysics Data System (ADS)

Nold, Andreas; Sibley, David; Goddard, Benjamin; Kalliadasis, Serafim; Complex Multiscale Systems Team

2016-11-01

The moving contact line problem remains an unsolved fundamental problem in fluid mechanics. At the heart of the problem is its multiscale nature: a nanoscale region close to the solid boundary where the continuum hypothesis breaks down, must be resolved before effective macroscale parameters such as contact line friction and slip can be obtained. To capture nanoscale properties very close to the contact line and to establish a link to the macroscale behaviour, we employ classical density-functional theory (DFT), in combination with extended Navier-Stokes-like equations. Using simple models for viscosity and slip at the wall, we compare our computations with the Molecular Kinetic Theory, by extracting the contact line friction, depending on the imposed temperature of the fluid. A key fluid property captured by DFT is the fluid layering at the wall-fluid interface, which has a large effect on the shearing properties of a fluid. To capture this crucial property, we propose an anisotropic model for the viscosity, which also allows us to scrutinize the effect of fluid layering on contact line friction.

Multiscale modeling and computation of nano-electronic transistors and transmembrane proton channels

NASA Astrophysics Data System (ADS)

Chen, Duan

The miniaturization of nano-scale electronic transistors, such as metal oxide semiconductor field effect transistors (MOSFETs), has given rise to a pressing demand in the new theoretical understanding and practical tactic for dealing with quantum mechanical effects in integrated circuits. In biology, proton dynamics and transport across membrane proteins are of paramount importance to the normal function of living cells. Similar physical characteristics are behind the two subjects, and model simulations share common mathematical interests/challenges. In this thesis work, multiscale and multiphysical models are proposed to study the mechanisms of nanotransistors and proton transport in transmembrane at the atomic level. For nano-electronic transistors, we introduce a unified two-scale energy functional to describe the electrons and the continuum electrostatic potential. This framework enables us to put microscopic and macroscopic descriptions on an equal footing at nano-scale. Additionally, this model includes layered structures and random doping effect of nano-transistors. For transmembrane proton channels, we describe proton dynamics quantum mechanically via a density functional approach while implicitly treat numerous solvent molecules as a dielectric continuum. The densities of all other ions in the solvent are assumed to obey the Boltzmann distribution. The impact of protein molecular structure and its charge polarization on the proton transport is considered in atomic details. We formulate a total free energy functional to include kinetic and potential energies of protons, as well as electrostatic energy of all other ions on an equal footing. For both nano-transistors and proton channels systems, the variational principle is employed to derive nonlinear governing equations. The Poisson-Kohn-Sham equations are derived for nano-transistors while the generalized Poisson-Boltzmann equation and Kohn-Sham equation are obtained for proton channels. Related numerical challenges in simulations are addressed: the matched interface and boundary (MIB) method, the Dirichlet-to-Neumann mapping (DNM) technique, and the Krylov subspace and preconditioner theory are introduced to improve the computational efficiency of the Poisson-type equation. The quantum transport theory is employed to solve the Kohn-Sham equation. The Gummel iteration and relaxation technique are utilized for overall self-consistent iterations. Finally, applications are considered and model validations are verified by realistic nano-transistors and transmembrane proteins. Two distinct device configurations, a double-gate MOSFET and a four-gate MOSFET, are considered in our threedimensional numerical simulations. For these devices, the current uctuation and voltage threshold lowering effect induced by discrete dopants are explored. For proton transport, a realistic channel protein, the Gramicidin A (GA) is used to demonstrate the performance of the proposed proton channel model and validate the efficiency of the proposed mathematical algorithms. The electrostatic characteristics of the GA channel is analyzed with a wide range of model parameters. Proton channel conductances are studied over a number of applied voltages and reference concentrations. Comparisons with experimental data are utilized to verify our model predictions.

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.

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

Development of an Image-based Multi-Scale Finite Element Approach to Predict Fatigue Damage in Asphalt Mixtures

NASA Astrophysics Data System (ADS)

Arshadi, Amir

Image-based simulation of complex materials is a very important tool for understanding their mechanical behavior and an effective tool for successful design of composite materials. In this thesis an image-based multi-scale finite element approach is developed to predict the mechanical properties of asphalt mixtures. In this approach the "up-scaling" and homogenization of each scale to the next is critically designed to improve accuracy. In addition to this multi-scale efficiency, this study introduces an approach for consideration of particle contacts at each of the scales in which mineral particles exist. One of the most important pavement distresses which seriously affects the pavement performance is fatigue cracking. As this cracking generally takes place in the binder phase of the asphalt mixture, the binder fatigue behavior is assumed to be one of the main factors influencing the overall pavement fatigue performance. It is also known that aggregate gradation, mixture volumetric properties, and filler type and concentration can affect damage initiation and progression in the asphalt mixtures. This study was conducted to develop a tool to characterize the damage properties of the asphalt mixtures at all scales. In the present study the Viscoelastic continuum damage model is implemented into the well-known finite element software ABAQUS via the user material subroutine (UMAT) in order to simulate the state of damage in the binder phase under the repeated uniaxial sinusoidal loading. The inputs are based on the experimentally derived measurements for the binder properties. For the scales of mastic and mortar, the artificially 2-Dimensional images of mastic and mortar scales were generated and used to characterize the properties of those scales. Finally, the 2D scanned images of asphalt mixtures are used to study the asphalt mixture fatigue behavior under loading. In order to validate the proposed model, the experimental test results and the simulation results were compared. Indirect tensile fatigue tests were conducted on asphalt mixture samples. A comparison between experimental results and the results from simulation shows that the model developed in this study is capable of predicting the effect of asphalt binder properties and aggregate micro-structure on mechanical behavior of asphalt concrete under loading.

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.

A multiscale computational approach to dissect early events in the Erb family receptor mediated activation, differential signaling, and relevance to oncogenic transformations.

PubMed

Liu, Yingting; Purvis, Jeremy; Shih, Andrew; Weinstein, Joshua; Agrawal, Neeraj; Radhakrishnan, Ravi

2007-06-01

We describe a hierarchical multiscale computational approach based on molecular dynamics simulations, free energy-based molecular docking simulations, deterministic network-based kinetic modeling, and hybrid discrete/continuum stochastic dynamics protocols to study the dimer-mediated receptor activation characteristics of the Erb family receptors, specifically the epidermal growth factor receptor (EGFR). Through these modeling approaches, we are able to extend the prior modeling of EGF-mediated signal transduction by considering specific EGFR tyrosine kinase (EGFRTK) docking interactions mediated by differential binding and phosphorylation of different C-terminal peptide tyrosines on the RTK tail. By modeling signal flows through branching pathways of the EGFRTK resolved on a molecular basis, we are able to transcribe the effects of molecular alterations in the receptor (e.g., mutant forms of the receptor) to differing kinetic behavior and downstream signaling response. Our molecular dynamics simulations show that the drug sensitizing mutation (L834R) of EGFR stabilizes the active conformation to make the system constitutively active. Docking simulations show preferential characteristics (for wildtype vs. mutant receptors) in inhibitor binding as well as preferential enhancement of phosphorylation of particular substrate tyrosines over others. We find that in comparison to the wildtype system, the L834R mutant RTK preferentially binds the inhibitor erlotinib, as well as preferentially phosphorylates the substrate tyrosine Y1068 but not Y1173. We predict that these molecular level changes result in preferential activation of the Akt signaling pathway in comparison to the Erk signaling pathway for cells with normal EGFR expression. For cells with EGFR over expression, the mutant over activates both Erk and Akt pathways, in comparison to wildtype. These results are consistent with qualitative experimental measurements reported in the literature. We discuss these consequences in light of how the network topology and signaling characteristics of altered (mutant) cell lines are shaped differently in relationship to native cell lines.

Dissolution of covalent adaptable network polymers in organic solvent

NASA Astrophysics Data System (ADS)

Yu, Kai; Yang, Hua; Dao, Binh H.; Shi, Qian; Yakacki, Christopher M.

2017-12-01

It was recently reported that thermosetting polymers can be fully dissolved in a proper organic solvent utilizing a bond-exchange reaction (BER), where small molecules diffuse into the polymer, break the long polymer chains into short segments, and eventually dissolve the network when sufficient solvent is provided. The solvent-assisted dissolution approach was applied to fully recycle thermosets and their fiber composites. This paper presents the first multi-scale modeling framework to predict the dissolution kinetics and mechanics of thermosets in organic solvent. The model connects the micro-scale network dynamics with macro-scale material properties: in the micro-scale, a model is developed based on the kinetics of BERs to describe the cleavage rate of polymer chains and evolution of chain segment length during the dissolution. The micro-scale model is then fed into a continuum-level model with considerations of the transportation of solvent molecules and chain segments in the system. The model shows good prediction on conversion rate of functional groups, degradation of network mechanical properties, and dissolution rate of thermosets during the dissolution. It identifies the underlying kinetic factors governing the dissolution process, and reveals the influence of different material and processing variables on the dissolution process, such as time, temperature, catalyst concentration, and chain length between cross-links.

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.

Towards a physics-based multiscale modelling of the electro-mechanical coupling in electro-active polymers.

PubMed

Cohen, Noy; Menzel, Andreas; deBotton, Gal

2016-02-01

Owing to the increasing number of industrial applications of electro-active polymers (EAPs), there is a growing need for electromechanical models which accurately capture their behaviour. To this end, we compare the predicted behaviour of EAPs undergoing homogeneous deformations according to three electromechanical models. The first model is a phenomenological continuum-based model composed of the mechanical Gent model and a linear relationship between the electric field and the polarization. The electrical and the mechanical responses according to the second model are based on the physical structure of the polymer chain network. The third model incorporates a neo-Hookean mechanical response and a physically motivated microstructurally based long-chains model for the electrical behaviour. In the microstructural-motivated models, the integration from the microscopic to the macroscopic levels is accomplished by the micro-sphere technique. Four types of homogeneous boundary conditions are considered and the behaviours determined according to the three models are compared. For the microstructurally motivated models, these analyses are performed and compared with the widely used phenomenological model for the first time. Some of the aspects revealed in this investigation, such as the dependence of the intensity of the polarization field on the deformation, highlight the need for an in-depth investigation of the relationships between the structure and the behaviours of the EAPs at the microscopic level and their overall macroscopic response.

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.

Numerical Simulation of Transitional, Hypersonic Flows using a Hybrid Particle-Continuum Method

NASA Astrophysics Data System (ADS)

Verhoff, Ashley Marie

Analysis of hypersonic flows requires consideration of multiscale phenomena due to the range of flight regimes encountered, from rarefied conditions in the upper atmosphere to fully continuum flow at low altitudes. At transitional Knudsen numbers there are likely to be localized regions of strong thermodynamic nonequilibrium effects that invalidate the continuum assumptions of the Navier-Stokes equations. Accurate simulation of these regions, which include shock waves, boundary and shear layers, and low-density wakes, requires a kinetic theory-based approach where no prior assumptions are made regarding the molecular distribution function. Because of the nature of these types of flows, there is much to be gained in terms of both numerical efficiency and physical accuracy by developing hybrid particle-continuum simulation approaches. The focus of the present research effort is the continued development of the Modular Particle-Continuum (MPC) method, where the Navier-Stokes equations are solved numerically using computational fluid dynamics (CFD) techniques in regions of the flow field where continuum assumptions are valid, and the direct simulation Monte Carlo (DSMC) method is used where strong thermodynamic nonequilibrium effects are present. Numerical solutions of transitional, hypersonic flows are thus obtained with increased physical accuracy relative to CFD alone, and improved numerical efficiency is achieved in comparison to DSMC alone because this more computationally expensive method is restricted to those regions of the flow field where it is necessary to maintain physical accuracy. In this dissertation, a comprehensive assessment of the physical accuracy of the MPC method is performed, leading to the implementation of a non-vacuum supersonic outflow boundary condition in particle domains, and more consistent initialization of DSMC simulator particles along hybrid interfaces. The relative errors between MPC and full DSMC results are greatly reduced as a direct result of these improvements. Next, a new parameter for detecting rotational nonequilibrium effects is proposed and shown to offer advantages over other continuum breakdown parameters, achieving further accuracy gains. Lastly, the capabilities of the MPC method are extended to accommodate multiple chemical species in rotational nonequilibrium, each of which is allowed to equilibrate independently, enabling application of the MPC method to more realistic atmospheric flows.

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.

Modelling Stream-Fish Functional Traits in Reference Conditions: Regional and Local Environmental Correlates

PubMed Central

Oliveira, João M.; Segurado, Pedro; Santos, José M.; Teixeira, Amílcar; Ferreira, Maria T.; Cortes, Rui V.

2012-01-01

Identifying the environmental gradients that control the functional structure of biological assemblages in reference conditions is fundamental to help river management and predict the consequences of anthropogenic stressors. Fish metrics (density of ecological guilds, and species richness) from 117 least disturbed stream reaches in several western Iberia river basins were modelled with generalized linear models in order to investigate the importance of regional- and local-scale abiotic gradients to variation in functional structure of fish assemblages. Functional patterns were primarily associated with regional features, such as catchment elevation and slope, rainfall, and drainage area. Spatial variations of fish guilds were thus associated with broad geographic gradients, showing (1) pronounced latitudinal patterns, affected mainly by climatic factors and topography, or (2) at the basin level, strong upstream-downstream patterns related to stream position in the longitudinal gradient. Maximum native species richness was observed in midsize streams in accordance with the river continuum concept. The findings of our study emphasized the need to use a multi-scale approach in order to fully assess the factors that govern the functional organization of biotic assemblages in ‘natural’ streams, as well as to improve biomonitoring and restoration of fluvial ecosystems. PMID:23029242

Long-wave model for strongly anisotropic growth of a crystal step.

PubMed

Khenner, Mikhail

2013-08-01

A continuum model for the dynamics of a single step with the strongly anisotropic line energy is formulated and analyzed. The step grows by attachment of adatoms from the lower terrace, onto which atoms adsorb from a vapor phase or from a molecular beam, and the desorption is nonnegligible (the "one-sided" model). Via a multiscale expansion, we derived a long-wave, strongly nonlinear, and strongly anisotropic evolution PDE for the step profile. Written in terms of the step slope, the PDE can be represented in a form similar to a convective Cahn-Hilliard equation. We performed the linear stability analysis and computed the nonlinear dynamics. Linear stability depends on whether the stiffness is minimum or maximum in the direction of the step growth. It also depends nontrivially on the combination of the anisotropy strength parameter and the atomic flux from the terrace to the step. Computations show formation and coarsening of a hill-and-valley structure superimposed onto a long-wavelength profile, which independently coarsens. Coarsening laws for the hill-and-valley structure are computed for two principal orientations of a maximum step stiffness, the increasing anisotropy strength, and the varying atomic flux.

Persistent Homology fingerprinting of microstructural controls on larger-scale fluid flow in porous media

NASA Astrophysics Data System (ADS)

Moon, C.; Mitchell, S. A.; Callor, N.; Dewers, T. A.; Heath, J. E.; Yoon, H.; Conner, G. R.

2017-12-01

Traditional subsurface continuum multiphysics models include useful yet limiting geometrical assumptions: penny- or disc-shaped cracks, spherical or elliptical pores, bundles of capillary tubes, cubic law fracture permeability, etc. Each physics (flow, transport, mechanics) uses constitutive models with an increasing number of fit parameters that pertain to the microporous structure of the rock, but bear no inter-physics relationships or self-consistency. Recent advances in digital rock physics and pore-scale modeling link complex physics to detailed pore-level geometries, but measures for upscaling are somewhat unsatisfactory and come at a high computational cost. Continuum mechanics rely on a separation between small scale pore fluctuations and larger scale heterogeneity (and perhaps anisotropy), but this can break down (particularly for shales). Algebraic topology offers powerful mathematical tools for describing a local-to-global structure of shapes. Persistent homology, in particular, analyzes the dynamics of topological features and summarizes into numeric values. It offers a roadmap to both "fingerprint" topologies of pore structure and multiscale connectedness as well as links pore structure to physical behavior, thus potentially providing a means to relate the dependence of constitutive behaviors of pore structures in a self-consistent way. We present a persistence homology (PH) analysis framework of 3D image sets including a focused ion beam-scanning electron microscopy data set of the Selma Chalk. We extract structural characteristics of sampling volumes via persistence homology and fit a statistical model using the summarized values to estimate porosity, permeability, and connectivity—Lattice Boltzmann methods for single phase flow modeling are used to obtain the relationships. These PH methods allow for prediction of geophysical properties based on the geometry and connectivity in a computationally efficient way. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

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

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

WAKES: Wavelet Adaptive Kinetic Evolution Solvers

NASA Astrophysics Data System (ADS)

Mardirian, Marine; Afeyan, Bedros; Larson, David

2016-10-01

We are developing a general capability to adaptively solve phase space evolution equations mixing particle and continuum techniques in an adaptive manner. The multi-scale approach is achieved using wavelet decompositions which allow phase space density estimation to occur with scale dependent increased accuracy and variable time stepping. Possible improvements on the SFK method of Larson are discussed, including the use of multiresolution analysis based Richardson-Lucy Iteration, adaptive step size control in explicit vs implicit approaches. Examples will be shown with KEEN waves and KEEPN (Kinetic Electrostatic Electron Positron Nonlinear) waves, which are the pair plasma generalization of the former, and have a much richer span of dynamical behavior. WAKES techniques are well suited for the study of driven and released nonlinear, non-stationary, self-organized structures in phase space which have no fluid, limit nor a linear limit, and yet remain undamped and coherent well past the drive period. The work reported here is based on the Vlasov-Poisson model of plasma dynamics. Work supported by a Grant from the AFOSR.

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

Electrochemical Transport Phenomena in Hybrid Pseudocapacitors under Galvanostatic Cycling

DOE PAGES

d'Entremont, Anna L.; Girard, Henri -Louis; Wang, Hainan; ...

2015-11-18

Here, this study aims to provide insights into the electrochemical transport and interfacial phenomena in hybrid pseudocapacitors under galvanostatic cycling. Pseudocapacitors are promising electrical energy storage devices for applications requiring large power density. They also involve complex, coupled, and multiscale physical phenomena that are difficult to probe experimentally. The present study performed detailed numerical simulations for a hybrid pseudocapacitor with planar electrodes and binary, asymmetric electrolyte under various cycling conditions, based on a first-principles continuum model accounting simultaneously for charge storage by electric double layer (EDL) formation and by faradaic reactions with intercalation. Two asymptotic regimes were identified corresponding tomore » (i) dominant faradaic charge storage at low current and low frequency or (ii) dominant EDL charge storage at high current and high frequency. Analytical expressions for the intercalated ion concentration and surface overpotential were derived for both asymptotic regimes. Features of typical experimentally measured cell potential were physically interpreted. These insights could guide the optimization of hybrid pseudocapacitors.« less

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.

The pseudo-compartment method for coupling partial differential equation and compartment-based models of diffusion.

PubMed

Yates, Christian A; Flegg, Mark B

2015-05-06

Spatial reaction-diffusion models have been employed to describe many emergent phenomena in biological systems. The modelling technique most commonly adopted in the literature implements systems of partial differential equations (PDEs), which assumes there are sufficient densities of particles that a continuum approximation is valid. However, owing to recent advances in computational power, the simulation and therefore postulation, of computationally intensive individual-based models has become a popular way to investigate the effects of noise in reaction-diffusion systems in which regions of low copy numbers exist. The specific stochastic models with which we shall be concerned in this manuscript are referred to as 'compartment-based' or 'on-lattice'. These models are characterized by a discretization of the computational domain into a grid/lattice of 'compartments'. Within each compartment, particles are assumed to be well mixed and are permitted to react with other particles within their compartment or to transfer between neighbouring compartments. Stochastic models provide accuracy, but at the cost of significant computational resources. For models that have regions of both low and high concentrations, it is often desirable, for reasons of efficiency, to employ coupled multi-scale modelling paradigms. In this work, we develop two hybrid algorithms in which a PDE in one region of the domain is coupled to a compartment-based model in the other. Rather than attempting to balance average fluxes, our algorithms answer a more fundamental question: 'how are individual particles transported between the vastly different model descriptions?' First, we present an algorithm derived by carefully redefining the continuous PDE concentration as a probability distribution. While this first algorithm shows very strong convergence to analytical solutions of test problems, it can be cumbersome to simulate. Our second algorithm is a simplified and more efficient implementation of the first, it is derived in the continuum limit over the PDE region alone. We test our hybrid methods for functionality and accuracy in a variety of different scenarios by comparing the averaged simulations with analytical solutions of PDEs for mean concentrations. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

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.

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.

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...

Continuum modeling of large lattice structures: Status and projections

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.; Mikulas, Martin M., Jr.

1988-01-01

The status and some recent developments of continuum modeling for large repetitive lattice structures are summarized. Discussion focuses on a number of aspects including definition of an effective substitute continuum; characterization of the continuum model; and the different approaches for generating the properties of the continuum, namely, the constitutive matrix, the matrix of mass densities, and the matrix of thermal coefficients. Also, a simple approach is presented for generating the continuum properties. The approach can be used to generate analytic and/or numerical values of the continuum properties.

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.

Application of ERT, Saline Tracer and Numerical Studies to Delineate Preferential Paths in Fractured Granites.

PubMed

Sreeparvathy, Vijay; Kambhammettu, B V N P; Peddinti, Srinivasa Rao; Sarada, P S L

2018-03-22

Accurate quantification of in situ heterogeneity and flow processes through fractured geologic media remains elusive for hydrogeologists due to the complexity in fracture characterization and its multiscale behavior. In this research, we demonstrated the efficacy of tracer-electrical resistivity tomography (ERT) experiments combined with numerical simulations to characterize heterogeneity and delineate preferential flow paths in a fractured granite aquifer. A series of natural gradient saline tracer experiments were conducted from a depth window of 18 to 22 m in an injection well (IW) located inside the Indian Institute of Technology Hyderabad campus. Tracer migration was monitored in a time-lapse mode using two cross-sectional surface ERT profiles placed in the direction of flow gradient. ERT data quality was improved by considering stacking, reciprocal measurements, resolution indicators, and geophysical logs. Dynamic changes in subsurface electrical properties inferred via resistivity anomalies were used to highlight preferential flow paths of the study area. Temporal changes in electrical resistivity and tracer concentration were monitored along the vertical in an observation well located at 48 m to the east of the IW. ERT-derived tracer breakthrough curves were in agreement with geochemical sample measurements. Fracture geometry and hydraulic properties derived from ERT and pumping tests were further used to evaluate two mathematical conceptualizations that are relevant to fractured aquifers. Results of numerical analysis conclude that dual continuum model that combines matrix and fracture systems through a flow exchange term has outperformed equivalent continuum model in reproducing tracer concentrations at the monitoring wells (evident by a decrease in RMSE from 199 to 65 mg/L). A sensitivity analysis on model simulations conclude that spatial variability in hydraulic conductivity, local-scale dispersion, and flow exchange at fracture-matrix interface have a profound effect on model simulations. © 2018, National Ground Water Association.

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.

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...

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.

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 ...

Continuum Fatigue Damage Modeling for Use in Life Extending Control

NASA Technical Reports Server (NTRS)

Lorenzo, Carl F.

1994-01-01

This paper develops a simplified continuum (continuous wrp to time, stress, etc.) fatigue damage model for use in Life Extending Controls (LEC) studies. The work is based on zero mean stress local strain cyclic damage modeling. New nonlinear explicit equation forms of cyclic damage in terms of stress amplitude are derived to facilitate the continuum modeling. Stress based continuum models are derived. Extension to plastic strain-strain rate models are also presented. Application of these models to LEC applications is considered. Progress toward a nonzero mean stress based continuum model is presented. Also, new nonlinear explicit equation forms in terms of stress amplitude are also derived for this case.

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…

A review on nanomechanical resonators and their applications in sensors and molecular transportation

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

Arash, Behrouz; Rabczuk, Timon, E-mail: timon.rabczuk@uni-weimar.de; Jiang, Jin-Wu

2015-06-15

Nanotechnology has opened a new area in science and engineering, leading to the development of novel nano-electromechanical systems such as nanoresonators with ultra-high resonant frequencies. The ultra-high-frequency resonators facilitate wide-ranging applications such as ultra-high sensitive sensing, molecular transportation, molecular separation, high-frequency signal processing, and biological imaging. This paper reviews recent studies on dynamic characteristics of nanoresonators. A variety of theoretical approaches, i.e., continuum modeling, molecular simulations, and multiscale methods, in modeling of nanoresonators are reviewed. The potential application of nanoresonators in design of sensor devices and molecular transportation systems is introduced. The essence of nanoresonator sensors for detection of atomsmore » and molecules with vibration and wave propagation analyses is outlined. The sensitivity of the resonator sensors and their feasibility in detecting different atoms and molecules are particularly discussed. Furthermore, the applicability of molecular transportation using the propagation of mechanical waves in nanoresonators is presented. An extended application of the transportation methods for building nanofiltering systems with ultra-high selectivity is surveyed. The article aims to provide an up-to-date review on the mechanical properties and applications of nanoresonators, and inspire additional potential of the resonators.« less

Multiscale computational models in physical systems biology of intracellular trafficking.

PubMed

Tourdot, Richard W; Bradley, Ryan P; Ramakrishnan, Natesan; Radhakrishnan, Ravi

2014-10-01

In intracellular trafficking, a definitive understanding of the interplay between protein binding and membrane morphology remains incomplete. The authors describe a computational approach by integrating coarse-grained molecular dynamics (CGMD) simulations with continuum Monte Carlo (CM) simulations of the membrane to study protein-membrane interactions and the ensuing membrane curvature. They relate the curvature field strength discerned from the molecular level to its effect at the cellular length-scale. They perform thermodynamic integration on the CM model to describe the free energy landscape of vesiculation in clathrin-mediated endocytosis. The method presented here delineates membrane morphologies and maps out the free energy changes associated with membrane remodeling due to varying coat sizes, coat curvature strengths, membrane bending rigidities, and tensions; furthermore several constraints on mechanisms underlying clathrin-mediated endocytosis have also been identified, Their CGMD simulations have revealed the importance of PIP2 for stable binding of proteins essential for curvature induction in the bilayer and have provided a molecular basis for the positive curvature induction by the epsin N-terminal homology (EIMTH) domain. Calculation of the free energy landscape for vesicle budding has identified the critical size and curvature strength of a clathrin coat required for nucleation and stabilisation of a mature vesicle.

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...

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...

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

Hybrid particle-continuum simulations coupling Brownian dynamics and local dynamic density functional theory.

PubMed

Qi, Shuanhu; Schmid, Friederike

2017-11-08

We present a multiscale hybrid particle-field scheme for the simulation of relaxation and diffusion behavior of soft condensed matter systems. It combines particle-based Brownian dynamics and field-based local dynamics in an adaptive sense such that particles can switch their level of resolution on the fly. The switching of resolution is controlled by a tuning function which can be chosen at will according to the geometry of the system. As an application, the hybrid scheme is used to study the kinetics of interfacial broadening of a polymer blend, and is validated by comparing the results to the predictions from pure Brownian dynamics and pure local dynamics calculations.

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

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.

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 unified gas-kinetic scheme for continuum and rarefied flows IV: Full Boltzmann and model equations

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

Liu, Chang, E-mail: cliuaa@ust.hk; Xu, Kun, E-mail: makxu@ust.hk; Sun, Quanhua, E-mail: qsun@imech.ac.cn

Fluid dynamic equations are valid in their respective modeling scales, such as the particle mean free path scale of the Boltzmann equation and the hydrodynamic scale of the Navier–Stokes (NS) equations. With a variation of the modeling scales, theoretically there should have a continuous spectrum of fluid dynamic equations. Even though the Boltzmann equation is claimed to be valid in all scales, many Boltzmann solvers, including direct simulation Monte Carlo method, require the cell resolution to the order of particle mean free path scale. Therefore, they are still single scale methods. In order to study multiscale flow evolution efficiently, themore » dynamics in the computational fluid has to be changed with the scales. A direct modeling of flow physics with a changeable scale may become an appropriate approach. The unified gas-kinetic scheme (UGKS) is a direct modeling method in the mesh size scale, and its underlying flow physics depends on the resolution of the cell size relative to the particle mean free path. The cell size of UGKS is not limited by the particle mean free path. With the variation of the ratio between the numerical cell size and local particle mean free path, the UGKS recovers the flow dynamics from the particle transport and collision in the kinetic scale to the wave propagation in the hydrodynamic scale. The previous UGKS is mostly constructed from the evolution solution of kinetic model equations. Even though the UGKS is very accurate and effective in the low transition and continuum flow regimes with the time step being much larger than the particle mean free time, it still has space to develop more accurate flow solver in the region, where the time step is comparable with the local particle mean free time. In such a scale, there is dynamic difference from the full Boltzmann collision term and the model equations. This work is about the further development of the UGKS with the implementation of the full Boltzmann collision term in the region where it is needed. The central ingredient of the UGKS is the coupled treatment of particle transport and collision in the flux evaluation across a cell interface, where a continuous flow dynamics from kinetic to hydrodynamic scales is modeled. The newly developed UGKS has the asymptotic preserving (AP) property of recovering the NS solutions in the continuum flow regime, and the full Boltzmann solution in the rarefied regime. In the mostly unexplored transition regime, the UGKS itself provides a valuable tool for the non-equilibrium flow study. The mathematical properties of the scheme, such as stability, accuracy, and the asymptotic preserving, will be analyzed in this paper as well.« less

A Numerical Multiscale Framework for Modeling Patient-Specific Coronary Artery Bypass Surgeries

NASA Astrophysics Data System (ADS)

Ramachandra, Abhay B.; Kahn, Andrew; Marsden, Alison

2014-11-01

Coronary artery bypass graft (CABG) surgery is performed to revascularize diseased coronary arteries, using arterial, venous or synthetic grafts. Vein grafts, used in more than 70% of procedures, have failure rates as high as 50% in less than 10 years. Hemodynamics is known to play a key role in the mechano-biological response of vein grafts, but current non-invasive imaging techniques cannot fully characterize the hemodynamic and biomechanical environment. We numerically compute hemodynamics and wall mechanics in patient-specific 3D CABG geometries using stabilized finite element methods. The 3D patient-specific domain is coupled to a 0D lumped parameter circulatory model and parameters are tuned to match patient-specific blood pressures, stroke volumes, heart rates and heuristic flow-split values. We quantify differences in hemodynamics between arterial and venous grafts and discuss possible correlations to graft failure. Extension to a deformable wall approximation will also be discussed. The quantification of wall mechanics and hemodynamics is a necessary step towards coupling continuum models in solid and fluid mechanics with the cellular and sub-cellular responses of grafts, which in turn, should lead to a more accurate prediction of the long term outcome of CABG surgeries, including predictions of growth and remodeling.

Simulating Fragmentation and Fluid-Induced Fracture in Disordered Media Using Random Finite-Element Meshes

DOE PAGES

Bishop, Joseph E.; Martinez, Mario J.; Newell, Pania

2016-11-08

Fracture and fragmentation are extremely nonlinear multiscale processes in which microscale damage mechanisms emerge at the macroscale as new fracture surfaces. Numerous numerical methods have been developed for simulating fracture initiation, propagation, and coalescence. In this paper, we present a computational approach for modeling pervasive fracture in quasi-brittle materials based on random close-packed Voronoi tessellations. Each Voronoi cell is formulated as a polyhedral finite element containing an arbitrary number of vertices and faces. Fracture surfaces are allowed to nucleate only at the intercell faces. Cohesive softening tractions are applied to new fracture surfaces in order to model the energy dissipatedmore » during fracture growth. The randomly seeded Voronoi cells provide a regularized discrete random network for representing fracture surfaces. The potential crack paths within the random network are viewed as instances of realizable crack paths within the continuum material. Mesh convergence of fracture simulations is viewed in a weak, or distributional, sense. The explicit facet representation of fractures within this approach is advantageous for modeling contact on new fracture surfaces and fluid flow within the evolving fracture network. Finally, applications of interest include fracture and fragmentation in quasi-brittle materials and geomechanical applications such as hydraulic fracturing, engineered geothermal systems, compressed-air energy storage, and carbon sequestration.« less

Simulating Fragmentation and Fluid-Induced Fracture in Disordered Media Using Random Finite-Element Meshes

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

Bishop, Joseph E.; Martinez, Mario J.; Newell, Pania

Fracture and fragmentation are extremely nonlinear multiscale processes in which microscale damage mechanisms emerge at the macroscale as new fracture surfaces. Numerous numerical methods have been developed for simulating fracture initiation, propagation, and coalescence. In this paper, we present a computational approach for modeling pervasive fracture in quasi-brittle materials based on random close-packed Voronoi tessellations. Each Voronoi cell is formulated as a polyhedral finite element containing an arbitrary number of vertices and faces. Fracture surfaces are allowed to nucleate only at the intercell faces. Cohesive softening tractions are applied to new fracture surfaces in order to model the energy dissipatedmore » during fracture growth. The randomly seeded Voronoi cells provide a regularized discrete random network for representing fracture surfaces. The potential crack paths within the random network are viewed as instances of realizable crack paths within the continuum material. Mesh convergence of fracture simulations is viewed in a weak, or distributional, sense. The explicit facet representation of fractures within this approach is advantageous for modeling contact on new fracture surfaces and fluid flow within the evolving fracture network. Finally, applications of interest include fracture and fragmentation in quasi-brittle materials and geomechanical applications such as hydraulic fracturing, engineered geothermal systems, compressed-air energy storage, and carbon sequestration.« less

Multiscale asymmetric orthogonal wavelet kernel for linear programming support vector learning and nonlinear dynamic systems identification.

PubMed

Lu, Zhao; Sun, Jing; Butts, Kenneth

2014-05-01

Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.

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.

Hybrid Markov-mass action law model for cell activation by rare binding events: Application to calcium induced vesicular release at neuronal synapses.

PubMed

Guerrier, Claire; Holcman, David

2016-10-18

Binding of molecules, ions or proteins to small target sites is a generic step of cell activation. This process relies on rare stochastic events where a particle located in a large bulk has to find small and often hidden targets. We present here a hybrid discrete-continuum model that takes into account a stochastic regime governed by rare events and a continuous regime in the bulk. The rare discrete binding events are modeled by a Markov chain for the encounter of small targets by few Brownian particles, for which the arrival time is Poissonian. The large ensemble of particles is described by mass action laws. We use this novel model to predict the time distribution of vesicular release at neuronal synapses. Vesicular release is triggered by the binding of few calcium ions that can originate either from the synaptic bulk or from the entry through calcium channels. We report here that the distribution of release time is bimodal although it is triggered by a single fast action potential. While the first peak follows a stimulation, the second corresponds to the random arrival over much longer time of ions located in the synaptic terminal to small binding vesicular targets. To conclude, the present multiscale stochastic modeling approach allows studying cellular events based on integrating discrete molecular events over several time scales.

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

Equivalent-Continuum Modeling With Application to Carbon Nanotubes

NASA Technical Reports Server (NTRS)

Odegard, Gregory M.; Gates, Thomas S.; Nicholson, Lee M.; Wise, Kristopher E.

2002-01-01

A method has been proposed for developing structure-property relationships of nano-structured materials. This method serves as a link between computational chemistry and solid mechanics by substituting discrete molecular structures with equivalent-continuum models. It has been shown that this substitution may be accomplished by equating the vibrational potential energy of a nano-structured material with the strain energy of representative truss and continuum models. As important examples with direct application to the development and characterization of single-walled carbon nanotubes and the design of nanotube-based devices, the modeling technique has been applied to determine the effective-continuum geometry and bending rigidity of a graphene sheet. A representative volume element of the chemical structure of graphene has been substituted with equivalent-truss and equivalent continuum models. As a result, an effective thickness of the continuum model has been determined. This effective thickness has been shown to be significantly larger than the interatomic spacing of graphite. The effective thickness has been shown to be significantly larger than the inter-planar spacing of graphite. The effective bending rigidity of the equivalent-continuum model of a graphene sheet was determined by equating the vibrational potential energy of the molecular model of a graphene sheet subjected to cylindrical bending with the strain energy of an equivalent continuum plate subjected to cylindrical bending.

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

Multiscale pore structure and constitutive models of fine-grained rocks

NASA Astrophysics Data System (ADS)

Heath, J. E.; Dewers, T. A.; Shields, E. A.; Yoon, H.; Milliken, K. L.

2017-12-01

A foundational concept of continuum poromechanics is the representative elementary volume or REV: an amount of material large enough that pore- or grain-scale fluctuations in relevant properties are dissipated to a definable mean, but smaller than length scales of heterogeneity. We determine 2D-equivalent representative elementary areas (REAs) of pore areal fraction of three major types of mudrocks by applying multi-beam scanning electron microscopy (mSEM) to obtain terapixel image mosaics. Image analysis obtains pore areal fraction and pore size and shape as a function of progressively larger measurement areas. Using backscattering imaging and mSEM data, pores are identified by the components within which they occur, such as in organics or the clastic matrix. We correlate pore areal fraction with nano-indentation, micropillar compression, and axysimmetic testing at multiple length scales on a terrigenous-argillaceous mudrock sample. The combined data set is used to: investigate representative elementary volumes (and areas for the 2D images); determine if scale separation occurs; and determine if transport and mechanical properties at a given length scale can be statistically defined. Clear scale separation occurs between REAs and observable heterogeneity in two of the samples. A highly-laminated sample exhibits fine-scale heterogeneity and an overlapping in scales, in which case typical continuum assumptions on statistical variability may break down. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Reproducing the nonlinear dynamic behavior of a structured beam with a generalized continuum model

NASA Astrophysics Data System (ADS)

Vila, J.; Fernández-Sáez, J.; Zaera, R.

2018-04-01

In this paper we study the coupled axial-transverse nonlinear vibrations of a kind of one dimensional structured solids by application of the so called Inertia Gradient Nonlinear continuum model. To show the accuracy of this axiomatic model, previously proposed by the authors, its predictions are compared with numeric results from a previously defined finite discrete chain of lumped masses and springs, for several number of particles. A continualization of the discrete model equations based on Taylor series allowed us to set equivalent values of the mechanical properties in both discrete and axiomatic continuum models. Contrary to the classical continuum model, the inertia gradient nonlinear continuum model used herein is able to capture scale effects, which arise for modes in which the wavelength is comparable to the characteristic distance of the structured solid. The main conclusion of the work is that the proposed generalized continuum model captures the scale effects in both linear and nonlinear regimes, reproducing the behavior of the 1D nonlinear discrete model adequately.

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

How does a three-dimensional continuum muscle model affect the kinematics and muscle strains of a finite element neck model compared to a discrete muscle model in rear-end, frontal, and lateral impacts.

PubMed

Hedenstierna, Sofia; Halldin, Peter

2008-04-15

A finite element (FE) model of the human neck with incorporated continuum or discrete muscles was used to simulate experimental impacts in rear, frontal, and lateral directions. The aim of this study was to determine how a continuum muscle model influences the impact behavior of a FE human neck model compared with a discrete muscle model. Most FE neck models used for impact analysis today include a spring element musculature and are limited to discrete geometries and nodal output results. A solid-element muscle model was thought to improve the behavior of the model by adding properties such as tissue inertia and compressive stiffness and by improving the geometry. It would also predict the strain distribution within the continuum elements. A passive continuum muscle model with nonlinear viscoelastic materials was incorporated into the KTH neck model together with active spring muscles and used in impact simulations. The resulting head and vertebral kinematics was compared with the results from a discrete muscle model as well as volunteer corridors. The muscle strain prediction was compared between the 2 muscle models. The head and vertebral kinematics were within the volunteer corridors for both models when activated. The continuum model behaved more stiffly than the discrete model and needed less active force to fit the experimental results. The largest difference was seen in the rear impact. The strain predicted by the continuum model was lower than for the discrete model. The continuum muscle model stiffened the response of the KTH neck model compared with a discrete model, and the strain prediction in the muscles was improved.

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...

Evaluation of Advanced Reactive Surface Area Estimates for Improved Prediction of Mineral Reaction Rates in Porous Media

NASA Astrophysics Data System (ADS)

Beckingham, L. E.; Mitnick, E. H.; Zhang, S.; Voltolini, M.; Yang, L.; Steefel, C. I.; Swift, A.; Cole, D. R.; Sheets, J.; Kneafsey, T. J.; Landrot, G.; Anovitz, L. M.; Mito, S.; Xue, Z.; Ajo Franklin, J. B.; DePaolo, D.

2015-12-01

CO2 sequestration in deep sedimentary formations is a promising means of reducing atmospheric CO2 emissions but the rate and extent of mineral trapping remains difficult to predict. Reactive transport models provide predictions of mineral trapping based on laboratory mineral reaction rates, which have been shown to have large discrepancies with field rates. This, in part, may be due to poor quantification of mineral reactive surface area in natural porous media. Common estimates of mineral reactive surface area are ad hoc and typically based on grain size, adjusted several orders of magnitude to account for surface roughness and reactivity. This results in orders of magnitude discrepancies in estimated surface areas that directly translate into orders of magnitude discrepancies in model predictions. Additionally, natural systems can be highly heterogeneous and contain abundant nano- and micro-porosity, which can limit connected porosity and access to mineral surfaces. In this study, mineral-specific accessible surface areas are computed for a sample from the reservoir formation at the Nagaoka pilot CO2 injection site (Japan). Accessible mineral surface areas are determined from a multi-scale image analysis including X-ray microCT, SEM QEMSCAN, XRD, SANS, and SEM-FIB. Powder and flow-through column laboratory experiments are performed and the evolution of solutes in the aqueous phase is tracked. Continuum-scale reactive transport models are used to evaluate the impact of reactive surface area on predictions of experimental reaction rates. Evaluated reactive surface areas include geometric and specific surface areas (eg. BET) in addition to their reactive-site weighted counterparts. The most accurate predictions of observed powder mineral dissolution rates were obtained through use of grain-size specific surface areas computed from a BET-based correlation. Effectively, this surface area reflects the grain-fluid contact area, or accessible surface area, in the powder dissolution experiment. In the model of the flow-through column experiment, the accessible mineral surface area, computed from the multi-scale image analysis, is evaluated in addition to the traditional surface area estimates.

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.

Atomistic potentials based energy flux integral criterion for dynamic adiabatic shear banding

NASA Astrophysics Data System (ADS)

Xu, Yun; Chen, Jun

2015-02-01

The energy flux integral criterion based on atomistic potentials within the framework of hyperelasticity-plasticity is proposed for dynamic adiabatic shear banding (ASB). System Helmholtz energy decomposition reveals that the dynamic influence on the integral path dependence is originated from the volumetric strain energy and partial deviatoric strain energy, and the plastic influence only from the rest part of deviatoric strain energy. The concept of critical shear banding energy is suggested for describing the initiation of ASB, which consists of the dynamic recrystallization (DRX) threshold energy and the thermal softening energy. The criterion directly relates energy flux to the basic physical processes that induce shear instability such as dislocation nucleations and multiplications, without introducing ad-hoc parameters in empirical constitutive models. It reduces to the classical path independent J-integral for quasi-static loading and elastic solids. The atomistic-to-continuum multiscale coupling method is used to simulate the initiation of ASB. Atomic configurations indicate that DRX induced microstructural softening may be essential to the dynamic shear localization and hence the initiation of ASB.

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.

Multiscale Simulation and Modeling of Multilayer Heteroepitactic Growth of C60 on Pentacene.

PubMed

Acevedo, Yaset M; Cantrell, Rebecca A; Berard, Philip G; Koch, Donald L; Clancy, Paulette

2016-03-29

We apply multiscale methods to describe the strained growth of multiple layers of C60 on a thin film of pentacene. We study this growth in the presence of a monolayer pentacene step to compare our simulations to recent experimental studies by Breuer and Witte of submonolayer growth in the presence of monolayer steps. The molecular-level details of this organic semiconductor interface have ramifications on the macroscale structural and electronic behavior of this system and allow us to describe several unexplained experimental observations for this system. The growth of a C60 thin film on a pentacene surface is complicated by the differing crystal habits of the two component species, leading to heteroepitactical growth. In order to probe this growth, we use three computational methods that offer different approaches to coarse-graining the system and differing degrees of computational efficiency. We present a new, efficient reaction-diffusion continuum model for 2D systems whose results compare well with mesoscale kinetic Monte Carlo (KMC) results for submonolayer growth. KMC extends our ability to simulate multiple layers but requires a library of predefined rates for event transitions. Coarse-grained molecular dynamics (CGMD) circumvents KMC's need for predefined lattices, allowing defects and grain boundaries to provide a more realistic thin film morphology. For multilayer growth, in this particularly suitable candidate for coarse-graining, CGMD is a preferable approach to KMC. Combining the results from these three methods, we show that the lattice strain induced by heteroepitactical growth promotes 3D growth and the creation of defects in the first monolayer. The CGMD results are consistent with experimental results on the same system by Conrad et al. and by Breuer and Witte in which C60 aggregates change from a 2D structure at low temperature to 3D clusters along the pentacene step edges at higher temperatures.

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 (...

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

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.

Equivalent-Continuum Modeling of Nano-Structured Materials

NASA Technical Reports Server (NTRS)

Odegard, Gregory M.; Gates, Thomas S.; Nicholson, Lee M.; Wise, Kristopher E.

2001-01-01

A method has been developed for modeling structure-property relationships of nano-structured materials. This method serves as a link between computational chemistry and solid mechanics by substituting discrete molecular structures with an equivalent-continuum model. It has been shown that this substitution may be accomplished by equating the vibrational potential energy of a nano-structured material with the strain energy of representative truss and continuum models. As an important example with direct application to the development and characterization of single-walled carbon nanotubes, the model has been applied to determine the effective continuum geometry of a graphene sheet. A representative volume element of the equivalent-continuum model has been developed with an effective thickness. This effective thickness has been shown to be similar to, but slightly smaller than, the interatomic spacing of graphite.

Prediction of Size Effects in Notched Laminates Using Continuum Damage Mechanics

NASA Technical Reports Server (NTRS)

Camanho, D. P.; Maimi, P.; Davila, C. G.

2007-01-01

This paper examines the use of a continuum damage model to predict strength and size effects in notched carbon-epoxy laminates. The effects of size and the development of a fracture process zone before final failure are identified in an experimental program. The continuum damage model is described and the resulting predictions of size effects are compared with alternative approaches: the point stress and the inherent flaw models, the Linear-Elastic Fracture Mechanics approach, and the strength of materials approach. The results indicate that the continuum damage model is the most accurate technique to predict size effects in composites. Furthermore, the continuum damage model does not require any calibration and it is applicable to general geometries and boundary conditions.

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 (...

Effects of continuum breakdown on hypersonic aerothermodynamics for reacting flow

NASA Astrophysics Data System (ADS)

Holman, Timothy D.; Boyd, Iain D.

2011-02-01

This study investigates the effects of continuum breakdown on the surface aerothermodynamic properties (pressure, stress, and heat transfer rate) of a sphere in a Mach 25 flow of reacting air in regimes varying from continuum to a rarefied gas. Results are generated using both continuum [computational fluid dynamics (CFD)] and particle [direct simulation Monte Carlo (DSMC)] approaches. The DSMC method utilizes a chemistry model that calculates the backward rates from an equilibrium constant. A preferential dissociation model is modified in the CFD method to better compare with the vibrationally favored dissociation model that is utilized in the DSMC method. Tests of these models are performed to confirm their validity and to compare the chemistry models in both numerical methods. This study examines the effect of reacting air flow on continuum breakdown and the surface properties of the sphere. As the global Knudsen number increases, the amount of continuum breakdown in the flow and on the surface increases. This increase in continuum breakdown significantly affects the surface properties, causing an increase in the differences between CFD and DSMC. Explanations are provided for the trends observed.

Revisiting the continuum model of tendon pathology: what is its merit in clinical practice and research?

PubMed Central

Cook, J L; Rio, E; Purdam, C R; Docking, S I

2016-01-01

The pathogenesis of tendinopathy and the primary biological change in the tendon that precipitates pathology have generated several pathoaetiological models in the literature. The continuum model of tendon pathology, proposed in 2009, synthesised clinical and laboratory-based research to guide treatment choices for the clinical presentations of tendinopathy. While the continuum has been cited extensively in the literature, its clinical utility has yet to be fully elucidated. The continuum model proposed a model for staging tendinopathy based on the changes and distribution of disorganisation within the tendon. However, classifying tendinopathy based on structure in what is primarily a pain condition has been challenged. The interplay between structure, pain and function is not yet fully understood, which has partly contributed to the complex clinical picture of tendinopathy. Here we revisit and assess the merit of the continuum model in the context of new evidence. We (1) summarise new evidence in tendinopathy research in the context of the continuum, (2) discuss tendon pain and the relevance of a model based on structure and (3) describe relevant clinical elements (pain, function and structure) to begin to build a better understanding of the condition. Our goal is that the continuum model may help guide targeted treatments and improved patient outcomes. PMID:27127294

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

Modelling the development of defects during composite reinforcements and prepreg forming

PubMed Central

Hamila, N.; Madeo, A.

2016-01-01

Defects in composite materials are created during manufacture to a large extent. To avoid them as much as possible, it is important that process simulations model the onset and the development of these defects. It is then possible to determine the manufacturing conditions that lead to the absence or to the controlled presence of such defects. Three types of defects that may appear during textile composite reinforcement or prepreg forming are analysed and modelled in this paper. Wrinkling is one of the most common flaws that occur during textile composite reinforcement forming processes. The influence of the different rigidities of the textile reinforcement is studied. The concept of ‘locking angle’ is questioned. A second type of unusual behaviour of fibrous composite reinforcements that can be seen as a flaw during their forming process is the onset of peculiar ‘transition zones’ that are directly related to the bending stiffness of the fibres. The ‘transition zones’ are due to the bending stiffness of fibres. The standard continuum mechanics of Cauchy is not sufficient to model these defects. A second gradient approach is presented that allows one to account for such unusual behaviours and to master their onset and development during forming process simulations. Finally, the large slippages that may occur during a preform forming are discussed and simulated with meso finite-element models used for macroscopic forming. This article is part of the themed issue ‘Multiscale modelling of the structural integrity of composite materials’. PMID:27242300

Modelling the development of defects during composite reinforcements and prepreg forming.

PubMed

Boisse, P; Hamila, N; Madeo, A

2016-07-13

Defects in composite materials are created during manufacture to a large extent. To avoid them as much as possible, it is important that process simulations model the onset and the development of these defects. It is then possible to determine the manufacturing conditions that lead to the absence or to the controlled presence of such defects. Three types of defects that may appear during textile composite reinforcement or prepreg forming are analysed and modelled in this paper. Wrinkling is one of the most common flaws that occur during textile composite reinforcement forming processes. The influence of the different rigidities of the textile reinforcement is studied. The concept of 'locking angle' is questioned. A second type of unusual behaviour of fibrous composite reinforcements that can be seen as a flaw during their forming process is the onset of peculiar 'transition zones' that are directly related to the bending stiffness of the fibres. The 'transition zones' are due to the bending stiffness of fibres. The standard continuum mechanics of Cauchy is not sufficient to model these defects. A second gradient approach is presented that allows one to account for such unusual behaviours and to master their onset and development during forming process simulations. Finally, the large slippages that may occur during a preform forming are discussed and simulated with meso finite-element models used for macroscopic forming. This article is part of the themed issue 'Multiscale modelling of the structural integrity of composite materials'. © 2016 The Author(s).

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.

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.

A Nonlocal Peridynamic Plasticity Model for the Dynamic Flow and Fracture of Concrete.

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

Vogler, Tracy; Lammi, Christopher James

A nonlocal, ordinary peridynamic constitutive model is formulated to numerically simulate the pressure-dependent flow and fracture of heterogeneous, quasi-brittle ma- terials, such as concrete. Classical mechanics and traditional computational modeling methods do not accurately model the distributed fracture observed within this family of materials. The peridynamic horizon, or range of influence, provides a characteristic length to the continuum and limits localization of fracture. Scaling laws are derived to relate the parameters of peridynamic constitutive model to the parameters of the classical Drucker-Prager plasticity model. Thermodynamic analysis of associated and non-associated plastic flow is performed. An implicit integration algorithm is formu-more » lated to calculate the accumulated plastic bond extension and force state. The gov- erning equations are linearized and the simulation of the quasi-static compression of a cylinder is compared to the classical theory. A dissipation-based peridynamic bond failure criteria is implemented to model fracture and the splitting of a concrete cylinder is numerically simulated. Finally, calculation of the impact and spallation of a con- crete structure is performed to assess the suitability of the material and failure models for simulating concrete during dynamic loadings. The peridynamic model is found to accurately simulate the inelastic deformation and fracture behavior of concrete during compression, splitting, and dynamically induced spall. The work expands the types of materials that can be modeled using peridynamics. A multi-scale methodology for simulating concrete to be used in conjunction with the plasticity model is presented. The work was funded by LDRD 158806.« less

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.

NASA Workshop on Distributed Parameter Modeling and Control of Flexible Aerospace Systems

NASA Technical Reports Server (NTRS)

Marks, Virginia B. (Compiler); Keckler, Claude R. (Compiler)

1994-01-01

Although significant advances have been made in modeling and controlling flexible systems, there remains a need for improvements in model accuracy and in control performance. The finite element models of flexible systems are unduly complex and are almost intractable to optimum parameter estimation for refinement using experimental data. Distributed parameter or continuum modeling offers some advantages and some challenges in both modeling and control. Continuum models often result in a significantly reduced number of model parameters, thereby enabling optimum parameter estimation. The dynamic equations of motion of continuum models provide the advantage of allowing the embedding of the control system dynamics, thus forming a complete set of system dynamics. There is also increased insight provided by the continuum model approach.

Multi-Scale Effects in the Strength of Ceramics

PubMed Central

Cook, Robert F.

2016-01-01

Multiple length-scale effects are demonstrated in indentation-strength measurements of a range of ceramic materials under inert and reactive conditions. Meso-scale effects associated with flaw disruption by lateral cracking at large indentation loads are shown to increase strengths above the ideal indentation response. Micro-scale effects associated with toughening by microstructural restraints at small indentation loads are shown to decrease strengths below the ideal response. A combined meso-micro-scale analysis is developed that describes ceramic inert strength behaviors over the complete indentation flaw size range. Nano-scale effects associated with chemical equilibria and crack velocity thresholds are shown to lead to invariant minimum strengths at slow applied stressing rates under reactive conditions. A combined meso-micro-nano-scale analysis is developed that describes the full range of reactive and inert strength behaviors as a function of indentation load and applied stressing rate. Applications of the multi-scale analysis are demonstrated for materials design, materials selection, toughness determination, crack velocity determination, bond-rupture parameter determination, and prediction of reactive strengths. The measurements and analysis provide strong support for the existence of sharp crack tips in ceramics such that the nano-scale mechanisms of discrete bond rupture are separate from the larger scale crack driving force mechanics characterized by continuum-based stress-intensity factors. PMID:27563150

Theory of nonlinear, distortive phenomena in solids: Martensitic, crack, and multiscale structures-phenomenology and physics. Progress summary, 1991--1994

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

Sethna, J.P.; Krumhansl, J.A.

1994-08-01

We have identified tweed precursors to martensitic phase transformations as a spin glass phase due to composition variations, and used simulations and exact replica theory predictions to predict diffraction peaks and model phase diagrams, and provide real space data for comparison to transmission electron micrograph images. We have used symmetry principles to derive the crack growth laws for mixed-mode brittle fracture, explaining the results for two-dimensional fracture and deriving the growth laws in three dimensions. We have used recent advances in dynamical critical phenomena to study hysteresis in disordered systems, explaining the return-point-memory effect, predicting distributions for Barkhausen noise, andmore » elucidating the transition from athermal to burst behavior in martensites. From a nonlinear lattice-dynamical model of a first-order transition using simulations, finite-size scaling, and transfer matrix methods, it is shown that heterophase transformation precursors cannot occur in a pure homogeneous system, thus emphasizing the role of disorder in real materials. Full integration of nonlinear Landau-Ginzburg continuum theory with experimental neutron-scattering data and first-principles calculations has been carried out to compute semi-quantitative values of the energy and thickness of twin boundaries in InTl and FePd martensites.« less

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

The significance of turbulent flow representation in single-continuum models

USGS Publications Warehouse

Reimann, T.; Rehrl, C.; Shoemaker, W.B.; Geyer, T.; Birk, S.

2011-01-01

Karst aquifers exhibit highly conductive features caused from rock dissolution processes. Flow within these structures can become turbulent and therefore can be expressed by nonlinear gradient functions. One way to account for these effects is by coupling a continuum model with a conduit network. Alternatively, turbulent flow can be considered by adapting the hydraulic conductivity within the continuum model. Consequently, the significance of turbulent flow on the dynamic behavior of karst springs is investigated by an enhanced single-continuum model that results in conduit-type flow in continuum cells (CTFC). The single-continuum approach CTFC represents laminar and turbulent flow as well as more complex hybrid models that require additional programming and numerical efforts. A parameter study is conducted to investigate the effects of turbulent flow on the response of karst springs to recharge events using the new CTFC approach, existing hybrid models, and MODFLOW-2005. Results reflect the importance of representing (1) turbulent flow in karst conduits and (2) the exchange between conduits and continuum cells. More specifically, laminar models overestimate maximum spring discharge and underestimate hydraulic gradients within the conduit. It follows that aquifer properties inferred from spring hydrographs are potentially impaired by ignoring flow effects due to turbulence. The exchange factor used for hybrid models is necessary to account for the scale dependency between hydraulic properties of the matrix continuum and conduits. This functionality, which is not included in CTFC, can be mimicked by appropriate use of the Horizontal Flow Barrier package for MODFLOW. Copyright 2011 by the American Geophysical Union.

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 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.

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.

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.

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

Microscale Modeling of Porous Thermal Protection System Materials

NASA Astrophysics Data System (ADS)

Stern, Eric C.

Ablative thermal protection system (TPS) materials play a vital role in the design of entry vehicles. Most simulation tools for ablative TPS in use today take a macroscopic approach to modeling, which involves heavy empiricism. Recent work has suggested improving the fidelity of the simulations by taking a multi-scale approach to the physics of ablation. In this work, a new approach for modeling ablative TPS at the microscale is proposed, and its feasibility and utility is assessed. This approach uses the Direct Simulation Monte Carlo (DSMC) method to simulate the gas flow through the microstructure, as well as the gas-surface interaction. Application of the DSMC method to this problem allows the gas phase dynamics---which are often rarefied---to be modeled to a high degree of fidelity. Furthermore this method allows for sophisticated gas-surface interaction models to be implemented. In order to test this approach for realistic materials, a method for generating artificial microstructures which emulate those found in spacecraft TPS is developed. Additionally, a novel approach for allowing the surface to move under the influence of chemical reactions at the surface is developed. This approach is shown to be efficient and robust for performing coupled simulation of the oxidation of carbon fibers. The microscale modeling approach is first applied to simulating the steady flow of gas through the porous medium. Predictions of Darcy permeability for an idealized microstructure agree with empirical correlations from the literature, as well as with predictions from computational fluid dynamics (CFD) when the continuum assumption is valid. Expected departures are observed for conditions at which the continuum assumption no longer holds. Comparisons of simulations using a fabricated microstructure to experimental data for a real spacecraft TPS material show good agreement when similar microstructural parameters are used to build the geometry. The approach is then applied to investigating the ablation of porous materials through oxidation. A simple gas surface interaction model is described, and an approach for coupling the surface reconstruction algorithm to the DSMC method is outlined. Simulations of single carbon fibers at representative conditions suggest this approach to be feasible for simulating the ablation of porous TPS materials at scale. Additionally, the effect of various simulation parameters on in-depth morphology is investigated for random fibrous microstructures.

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

Applicability of the Continuum-Shell Theories to the Mechanics of Carbon Nanotubes

NASA Technical Reports Server (NTRS)

Harik, V. M.; Gates, T. S.; Nemeth, M. P.

2002-01-01

Validity of the assumptions relating the applicability of continuum shell theories to the global mechanical behavior of carbon nanotubes is examined. The present study focuses on providing a basis that can be used to qualitatively assess the appropriateness of continuum-shell models for nanotubes. To address the effect of nanotube structure on their deformation, all nanotube geometries are divided into four major classes that require distinct models. Criteria for the applicability of continuum models are presented. The key parameters that control the buckling strains and deformation modes of these classes of nanotubes are determined. In an analogy with continuum mechanics, mechanical laws of geometric similitude are presented. A parametric map is constructed for a variety of nanotube geometries as a guide for the applicability of different models. The continuum assumptions made in representing a nanotube as a homogeneous thin shell are analyzed to identify possible limitations of applying shell theories and using their bifurcation-buckling equations at the nano-scale.

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

Considerations for the Development of a Substance-Related Care and Prevention Continuum Model

PubMed Central

Perlman, David C.; Jordan, Ashly E.

2017-01-01

There are significant gaps in the identification and engagement in care and prevention services of people who use illicit substances. Care continuum models have proven to be useful tools in the evaluation of care for HIV and other conditions; numerous issues in substance-related care and prevention resemble those identified in other continua models. Systems of care for substance misuse and substance use disorders (SUDs) can be viewed as consisting of a prevention and care continuum, reflecting incidence and prevalence of substance misuse and SUDs, screening and identification, medical and psychosocial evaluation for treatment, engagement in evidence-based treatment, treatment retention, relapse prevention, timeliness of step completion, and measures of overall and substance use-related specific morbidity and mortality. Care and prevention continuum models could potentially be applied at program, local, regional, state, and national levels. We discuss important lessons that can be drawn from applications of continuum models in other fields. The development and use of a substance-related care and prevention continuum may yield significant patient care, program evaluation and improvement, and population-level benefits. PMID:28770195

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

Smart Application of Direct Gas Injection using a new conceptual model on Coherent and Incoherent Flow: From Bench Scale to Field Scale.

NASA Astrophysics Data System (ADS)

Geistlinger, H.; Samani, S.; Pohlert, M.; Martienssen, M.; Engelmann, F.; Hüttmann, S.

2008-12-01

Within the framework of the OXYWALL field experiment we developed the direct gas injection (DGI) of oxygen as a remediation technology, which allows the cost-efficient and large-scale cleaning of groundwater contaminated with organic contaminants. That technology can be used as wide-banded, unselective remediation method for complex contaminant mixtures. Particularly, it could be proofed in field experiments that mineral oil hydrocarbons, aromatic hydrocarbons (BTEX), the rather persistent gasoline component Methyl tertiary-butyl ether (MTBE), and chlorinated aliphatic and aromatic hydrocarbons, like Trichloroethene and Monochlorobenzene, can be aerobically metabolized by autochthon microorganisms. Over the last 8 years the field site was investigated and a dense monitoring network was installed using Geoprobe direct- push technology and standard hydrogeological investigations were conducted, like EC-Logs, Injections-Logs, Gamma-Logs, TDR-probes, oxygen measurements with in-situ optodes, and tracer test with test gases SF6, Ar, and Oxygen. The key parameter for controling and regulating the DGI is the spatial and temporal distribution of the gas phase. High-resolution optical bench scale experiments were conducted in order to investigate local gas flow pattern and integral flow properties caused by point-like gas injection into water-saturated glass beads and natural sands. We observed a grain-size (dk)- and flow-rate (Q) dependent transition from incoherent to coherent flow. Conceptualizing the stationary tortuous gas flow as core-annulus flow and applying Hagen- Poiseuille flow for a straight capillary, we propose a flow-rate- and grain-size dependent stability criterion that could describe our experimental results and was used for classifying the experiments in a dk-Q-diagram (flow chart). Since DGI simulations are mainly based on continuum models, we also test the validity of the continuum approach for two-fluid flow in macroscopic homogeneous media by comparing our experimental flow pattern with the theoretical ones. It was found that a pulse-like function yields the best fit for the lateral gas saturation profile. This strange behaviour of a relatively sharp saturation transition is in contradiction to the widely anticipated picture of a smooth Gaussian-like transition, which is obtained by the continuum approach. Based on lab experiments, the proposed flow chart, and computer simulations the DGI-technology will be advanced and optimized at the field scale. A proper application of continuum models to direct gas injection should check, whether stable coherent flow is achieved; estimate the coherence length, and account for the channelized flow pattern by a realistic capillary pressure - saturation relationship. Further research is needed for modeling of direct gas injection to include appropriate stability criteria, the transition from coherent to incoherent flow, and bubble trapping. Geistlinger, H., Krauss, G., Lazik, D., and Luckner, L. (2006) Direct gas injection into saturated glass beads: transition from incoherent to coherent gas flow pattern. Water Resour. Res., 42 (7) W07403. Lazik, D., G. Krauss, H. Geistlinger, and H.-J. Vogel (2008) Multi-scale optical analyses of dynamic gas saturation during air sparging into glass beads, Transp. Porous Media. 74, 87-104.

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.

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.

Realistic Gamow shell model for resonance and continuum in atomic nuclei

NASA Astrophysics Data System (ADS)

Xu, F. R.; Sun, Z. H.; Wu, Q.; Hu, B. S.; Dai, S. J.

2018-02-01

The Gamow shell model can describe resonance and continuum for atomic nuclei. The model is established in the complex-moment (complex-k) plane of the Berggren coordinates in which bound, resonant and continuum states are treated on equal footing self-consistently. In the present work, the realistic nuclear force, CD Bonn, has been used. We have developed the full \\hat{Q}-box folded-diagram method to derive the realistic effective interaction in the model space which is nondegenerate and contains resonance and continuum channels. The CD-Bonn potential is renormalized using the V low-k method. With choosing 16O as the inert core, we have applied the Gamow shell model to oxygen isotopes.

Modeling Flow in Porous Media with Double Porosity/Permeability.

NASA Astrophysics Data System (ADS)

Seyed Joodat, S. H.; Nakshatrala, K. B.; Ballarini, R.

2016-12-01

Although several continuum models are available to study the flow of fluids in porous media with two pore-networks [1], they lack a firm theoretical basis. In this poster presentation, we will present a mathematical model with firm thermodynamic basis and a robust computational framework for studying flow in porous media that exhibit double porosity/permeability. The mathematical model will be derived by appealing to the maximization of rate of dissipation hypothesis, which ensures that the model is in accord with the second law of thermodynamics. We will also present important properties that the solutions under the model satisfy, along with an analytical solution procedure based on the Green's function method. On the computational front, a stabilized mixed finite element formulation will be derived based on the variational multi-scale formalism. The equal-order interpolation, which is computationally the most convenient, is stable under this formulation. The performance of this formulation will be demonstrated using patch tests, numerical convergence study, and representative problems. It will be shown that the pressure and velocity profiles under the double porosity/permeability model are qualitatively and quantitatively different from the corresponding ones under the classical Darcy equations. Finally, it will be illustrated that the surface pore-structure is not sufficient in characterizing the flow through a complex porous medium, which pitches a case for using advanced characterization tools like micro-CT. References [1] G. I. Barenblatt, I. P. Zheltov, and I. N. Kochina, "Basic concepts in the theory of seepage of homogeneous liquids in fissured rocks [strata]," Journal of Applied Mathematics and Mechanics, vol. 24, pp. 1286-1303, 1960.

Using Non-linear Homogenization to Improve the Performance of Macroscopic Damage Models of Trabecular Bone.

PubMed

Levrero-Florencio, Francesc; Pankaj, Pankaj

2018-01-01

Realistic macro-level finite element simulations of the mechanical behavior of trabecular bone, a cellular anisotropic material, require a suitable constitutive model; a model that incorporates the mechanical response of bone for complex loading scenarios and includes post-elastic phenomena, such as plasticity (permanent deformations) and damage (permanent stiffness reduction), which bone is likely to experience. Some such models have been developed by conducting homogenization-based multiscale finite element simulations on bone micro-structure. While homogenization has been fairly successful in the elastic regime and, to some extent, in modeling the macroscopic plastic response, it has remained a challenge with respect to modeling damage. This study uses a homogenization scheme to upscale the damage behavior from the tissue level (microscale) to the organ level (macroscale) and assesses the suitability of different damage constitutive laws. Ten cubic specimens were each subjected to 21 strain-controlled load cases for a small range of macroscopic post-elastic strains. Isotropic and anisotropic criteria were considered, density and fabric relationships were used in the formulation of the damage law, and a combined isotropic/anisotropic law with tension/compression asymmetry was formulated, based on the homogenized results, as a possible alternative to the currently used single scalar damage criterion. This computational study enhances the current knowledge on the macroscopic damage behavior of trabecular bone. By developing relationships of damage progression with bone's micro-architectural indices (density and fabric) the study also provides an aid for the creation of more precise macroscale continuum models, which are likely to improve clinical predictions.

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...

Hybrid plasma modeling.

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

Hopkins, Matthew Morgan; DeChant, Lawrence Justin.; Piekos, Edward Stanley

2009-02-01

This report summarizes the work completed during FY2007 and FY2008 for the LDRD project ''Hybrid Plasma Modeling''. The goal of this project was to develop hybrid methods to model plasmas across the non-continuum-to-continuum collisionality spectrum. The primary methodology to span these regimes was to couple a kinetic method (e.g., Particle-In-Cell) in the non-continuum regions to a continuum PDE-based method (e.g., finite differences) in continuum regions. The interface between the two would be adjusted dynamically ased on statistical sampling of the kinetic results. Although originally a three-year project, it became clear during the second year (FY2008) that there were not sufficientmore » resources to complete the project and it was terminated mid-year.« less

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.

Kinetic Monte Carlo simulation of self-organized pattern formation induced by ion beam sputtering using crater functions

NASA Astrophysics Data System (ADS)

Yang, Zhangcan; Lively, Michael A.; Allain, Jean Paul

2015-02-01

The production of self-organized nanostructures by ion beam sputtering has been of keen interest to researchers for many decades. Despite numerous experimental and theoretical efforts to understand ion-induced nanostructures, there are still many basic questions open to discussion, such as the role of erosion or curvature-dependent sputtering. In this work, a hybrid MD/kMC (molecular dynamics/kinetic Monte Carlo) multiscale atomistic model is developed to investigate these knowledge gaps, and its predictive ability is validated across the experimental parameter space. This model uses crater functions, which were obtained from MD simulations, to model the prompt mass redistribution due to single-ion impacts. Defect migration, which is missing from previous models that use crater functions, is treated by a kMC Arrhenius method. Using this model, a systematic study was performed for silicon bombarded by Ar+ ions of various energies (100 eV, 250 eV, 500 eV, 700 eV, and 1000 eV) at incidence angles of 0∘ to 80∘. The simulation results were compared with experimental findings, showing good agreement in many aspects of surface evolution, such as the phase diagram. The underestimation of the ripple wavelength by the simulations suggests that surface diffusion is not the main smoothening mechanism for ion-induced pattern formation. Furthermore, the simulated results were compared with moment-description continuum theory and found to give better results, as the simulation did not suffer from the same mathematical inconsistencies as the continuum model. The key finding was that redistributive effects are dominant in the formation of flat surfaces and parallel-mode ripples, but erosive effects are dominant at high angles when perpendicular-mode ripples are formed. Ion irradiation with simultaneous sample rotation was also simulated, resulting in arrays of square-ordered dots. The patterns obtained from sample rotation were strongly correlated to the rotation speed and to the pattern types formed without sample rotation, and a critical value of about 5 rpm was found between disordered ripples and square-ordered dots. Finally, simulations of dual-beam sputtering were performed, with the resulting patterns determined by the flux ratio of the two beams and the pattern types resulting from single-beam sputtering under the same conditions.

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

Discrete-to-continuum modelling of weakly interacting incommensurate two-dimensional lattices.

PubMed

Español, Malena I; Golovaty, Dmitry; Wilber, J Patrick

2018-01-01

In this paper, we derive a continuum variational model for a two-dimensional deformable lattice of atoms interacting with a two-dimensional rigid lattice. The starting point is a discrete atomistic model for the two lattices which are assumed to have slightly different lattice parameters and, possibly, a small relative rotation. This is a prototypical example of a three-dimensional system consisting of a graphene sheet suspended over a substrate. We use a discrete-to-continuum procedure to obtain the continuum model which recovers both qualitatively and quantitatively the behaviour observed in the corresponding discrete model. The continuum model predicts that the deformable lattice develops a network of domain walls characterized by large shearing, stretching and bending deformation that accommodates the misalignment and/or mismatch between the deformable and rigid lattices. Two integer-valued parameters, which can be identified with the components of a Burgers vector, describe the mismatch between the lattices and determine the geometry and the details of the deformation associated with the domain walls.

Materials-by-design: computation, synthesis, and characterization from atoms to structures

NASA Astrophysics Data System (ADS)

Yeo, Jingjie; Jung, Gang Seob; Martín-Martínez, Francisco J.; Ling, Shengjie; Gu, Grace X.; Qin, Zhao; Buehler, Markus J.

2018-05-01

In the 50 years that succeeded Richard Feynman’s exposition of the idea that there is ‘plenty of room at the bottom’ for manipulating individual atoms for the synthesis and manufacturing processing of materials, the materials-by-design paradigm is being developed gradually through synergistic integration of experimental material synthesis and characterization with predictive computational modeling and optimization. This paper reviews how this paradigm creates the possibility to develop materials according to specific, rational designs from the molecular to the macroscopic scale. We discuss promising techniques in experimental small-scale material synthesis and large-scale fabrication methods to manipulate atomistic or macroscale structures, which can be designed by computational modeling. These include recombinant protein technology to produce peptides and proteins with tailored sequences encoded by recombinant DNA, self-assembly processes induced by conformational transition of proteins, additive manufacturing for designing complex structures, and qualitative and quantitative characterization of materials at different length scales. We describe important material characterization techniques using numerous methods of spectroscopy and microscopy. We detail numerous multi-scale computational modeling techniques that complements these experimental techniques: DFT at the atomistic scale; fully atomistic and coarse-grain molecular dynamics at the molecular to mesoscale; continuum modeling at the macroscale. Additionally, we present case studies that utilize experimental and computational approaches in an integrated manner to broaden our understanding of the properties of two-dimensional materials and materials based on silk and silk-elastin-like proteins.

Predicting cell viability within tissue scaffolds under equiaxial strain: multi-scale finite element model of collagen-cardiomyocytes constructs.

PubMed

Elsaadany, Mostafa; Yan, Karen Chang; Yildirim-Ayan, Eda

2017-06-01

Successful tissue engineering and regenerative therapy necessitate having extensive knowledge about mechanical milieu in engineered tissues and the resident cells. In this study, we have merged two powerful analysis tools, namely finite element analysis and stochastic analysis, to understand the mechanical strain within the tissue scaffold and residing cells and to predict the cell viability upon applying mechanical strains. A continuum-based multi-length scale finite element model (FEM) was created to simulate the physiologically relevant equiaxial strain exposure on cell-embedded tissue scaffold and to calculate strain transferred to the tissue scaffold (macro-scale) and residing cells (micro-scale) upon various equiaxial strains. The data from FEM were used to predict cell viability under various equiaxial strain magnitudes using stochastic damage criterion analysis. The model validation was conducted through mechanically straining the cardiomyocyte-encapsulated collagen constructs using a custom-built mechanical loading platform (EQUicycler). FEM quantified the strain gradients over the radial and longitudinal direction of the scaffolds and the cells residing in different areas of interest. With the use of the experimental viability data, stochastic damage criterion, and the average cellular strains obtained from multi-length scale models, cellular viability was predicted and successfully validated. This methodology can provide a great tool to characterize the mechanical stimulation of bioreactors used in tissue engineering applications in providing quantification of mechanical strain and predicting cellular viability variations due to applied mechanical strain.