Intergranular Strain Evolution During Biaxial Loading: A Multiscale FE-FFT Approach

NASA Astrophysics Data System (ADS)

Upadhyay, M. V.; Capek, J.; Van Petegem, S.; Lebensohn, R. A.; Van Swygenhoven, H.

2017-05-01

Predicting the macroscopic and microscopic mechanical response of metals and alloys subjected to complex loading conditions necessarily requires a synergistic combination of multiscale material models and characterization techniques. This article focuses on the use of a multiscale approach to study the difference between intergranular lattice strain evolution for various grain families measured during in situ neutron diffraction on dog bone and cruciform 316L samples. At the macroscale, finite element simulations capture the complex coupling between applied forces and gauge stresses in cruciform geometries. The predicted gauge stresses are used as macroscopic boundary conditions to drive a mesoscale full-field elasto-viscoplastic fast Fourier transform crystal plasticity model. The results highlight the role of grain neighborhood on the intergranular strain evolution under uniaxial and equibiaxial loading.

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.

Introduction and application of the multiscale coefficient of variation analysis.

PubMed

Abney, Drew H; Kello, Christopher T; Balasubramaniam, Ramesh

2017-10-01

Quantifying how patterns of behavior relate across multiple levels of measurement typically requires long time series for reliable parameter estimation. We describe a novel analysis that estimates patterns of variability across multiple scales of analysis suitable for time series of short duration. The multiscale coefficient of variation (MSCV) measures the distance between local coefficient of variation estimates within particular time windows and the overall coefficient of variation across all time samples. We first describe the MSCV analysis and provide an example analytical protocol with corresponding MATLAB implementation and code. Next, we present a simulation study testing the new analysis using time series generated by ARFIMA models that span white noise, short-term and long-term correlations. The MSCV analysis was observed to be sensitive to specific parameters of ARFIMA models varying in the type of temporal structure and time series length. We then apply the MSCV analysis to short time series of speech phrases and musical themes to show commonalities in multiscale structure. The simulation and application studies provide evidence that the MSCV analysis can discriminate between time series varying in multiscale structure and length.

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 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

A Perspective on Coupled Multiscale Simulation and Validation in Nuclear Materials

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

M. P. Short; D. Gaston; C. R. Stanek

2014-01-01

The field of nuclear materials encompasses numerous opportunities to address and ultimately solve longstanding industrial problems by improving the fundamental understanding of materials through the integration of experiments with multiscale modeling and high-performance simulation. A particularly noteworthy example is an ongoing study of axial power distortions in a nuclear reactor induced by corrosion deposits, known as CRUD (Chalk River unidentified deposits). We describe how progress is being made toward achieving scientific advances and technological solutions on two fronts. Specifically, the study of thermal conductivity of CRUD phases has augmented missing data as well as revealed new mechanisms. Additionally, the developmentmore » of a multiscale simulation framework shows potential for the validation of a new capability to predict the power distribution of a reactor, in effect direct evidence of technological impact. The material- and system-level challenges identified in the study of CRUD are similar to other well-known vexing problems in nuclear materials, such as irradiation accelerated corrosion, stress corrosion cracking, and void swelling; they all involve connecting materials science fundamentals at the atomistic- and mesoscales to technology challenges at the macroscale.« less

Multiscale modeling of the human arterial tree on the TeraGrid.

NASA Astrophysics Data System (ADS)

Karniadakis, Gerorge

2009-03-01

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

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.

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

A multiscale approach to accelerate pore-scale simulation of porous electrodes

NASA Astrophysics Data System (ADS)

Zheng, Weibo; Kim, Seung Hyun

2017-04-01

A new method to accelerate pore-scale simulation of porous electrodes is presented. The method combines the macroscopic approach with pore-scale simulation by decomposing a physical quantity into macroscopic and local variations. The multiscale method is applied to the potential equation in pore-scale simulation of a Proton Exchange Membrane Fuel Cell (PEMFC) catalyst layer, and validated with the conventional approach for pore-scale simulation. Results show that the multiscale scheme substantially reduces the computational cost without sacrificing accuracy.

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

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.

Multiscale molecular dynamics simulations of rotary motor proteins.

PubMed

Ekimoto, Toru; Ikeguchi, Mitsunori

2018-04-01

Protein functions require specific structures frequently coupled with conformational changes. The scale of the structural dynamics of proteins spans from the atomic to the molecular level. Theoretically, all-atom molecular dynamics (MD) simulation is a powerful tool to investigate protein dynamics because the MD simulation is capable of capturing conformational changes obeying the intrinsically structural features. However, to study long-timescale dynamics, efficient sampling techniques and coarse-grained (CG) approaches coupled with all-atom MD simulations, termed multiscale MD simulations, are required to overcome the timescale limitation in all-atom MD simulations. Here, we review two examples of rotary motor proteins examined using free energy landscape (FEL) analysis and CG-MD simulations. In the FEL analysis, FEL is calculated as a function of reaction coordinates, and the long-timescale dynamics corresponding to conformational changes is described as transitions on the FEL surface. Another approach is the utilization of the CG model, in which the CG parameters are tuned using the fluctuation matching methodology with all-atom MD simulations. The long-timespan dynamics is then elucidated straightforwardly by using CG-MD 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.

Gyrokinetic predictions of multiscale transport in a DIII-D ITER baseline discharge

NASA Astrophysics Data System (ADS)

Holland, C.; Howard, N. T.; Grierson, B. A.

2017-06-01

New multiscale gyrokinetic simulations predict that electron energy transport in a DIII-D ITER baseline discharge with dominant electron heating and low input torque is multiscale in nature, with roughly equal amounts of the electron energy flux Q e coming from long wavelength ion-scale (k y ρ s  <  1) and short wavelength electron-scale (k y ρ s  >  1) fluctuations when the gyrokinetic results match independent power balance calculations. Corresponding conventional ion-scale simulations are able to match the power balance ion energy flux Q i, but systematically underpredict Q e when doing so. Significant nonlinear cross-scale couplings are observed in the multiscale simulations, but the exact simulation predictions are found to be extremely sensitive to variations of model input parameters within experimental uncertainties. Most notably, depending upon the exact value of the equilibrium E  ×  B shearing rate γ E×B used, either enhancement or suppression of the long-wavelength turbulence and transport levels in the multiscale simulations is observed relative to what is predicted by ion-scale simulations. While the enhancement of the long wavelength fluctuations by inclusion of the short wavelength turbulence was previously observed in similar multiscale simulations of an Alcator C-Mod L-mode discharge, these new results show for the first time a complete suppression of long-wavelength turbulence in a multiscale simulation, for parameters at which conventional ion-scale simulation predicts small but finite levels of low-k turbulence and transport consistent with the power balance Q i. Although computational resource limitations prevent a fully rigorous validation assessment of these new results, they provide significant new evidence that electron energy transport in burning plasmas is likely to have a strong multiscale character, with significant nonlinear cross-scale couplings that must be fully understood to predict the performance of those plasmas with confidence.

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

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

Dhakal, Tilak Raj

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

Multiscale Issues and Simulation-Based Science and Engineering for Materials-by-Design

DTIC Science & Technology

2010-05-15

planning and execution of programs to achieve the vision of ? material -by-design?. A key part of this effort has been to examine modeling at the mesoscale...15. SUBJECT TERMS Modelling & Simulation, Materials Design 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same as Report (SAR) 18...planning and execution of programs to achieve the vision of “ material -by-design”. A key part of this effort has been to examine modeling at the mesoscale. A

Multiscale Pressure-Balanced Structures in Three-dimensional Magnetohydrodynamic Turbulence

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

Yang, Liping; Zhang, Lei; Feng, Xueshang

2017-02-10

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

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

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Spatial adaptive sampling in multiscale simulation

NASA Astrophysics Data System (ADS)

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

2014-07-01

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

Multi-scale gyrokinetic simulations of an Alcator C-Mod, ELM-y H-mode plasma

NASA Astrophysics Data System (ADS)

Howard, N. T.; Holland, C.; White, A. E.; Greenwald, M.; Rodriguez-Fernandez, P.; Candy, J.; Creely, A. J.

2018-01-01

High fidelity, multi-scale gyrokinetic simulations capable of capturing both ion ({k}θ {ρ }s∼ { O }(1.0)) and electron-scale ({k}θ {ρ }e∼ { O }(1.0)) turbulence were performed in the core of an Alcator C-Mod ELM-y H-mode discharge which exhibits reactor-relevant characteristics. These simulations, performed with all experimental inputs and realistic ion to electron mass ratio ({({m}i/{m}e)}1/2=60.0) provide insight into the physics fidelity that may be needed for accurate simulation of the core of fusion reactor discharges. Three multi-scale simulations and series of separate ion and electron-scale simulations performed using the GYRO code (Candy and Waltz 2003 J. Comput. Phys. 186 545) are presented. As with earlier multi-scale results in L-mode conditions (Howard et al 2016 Nucl. Fusion 56 014004), both ion and multi-scale simulations results are compared with experimentally inferred ion and electron heat fluxes, as well as the measured values of electron incremental thermal diffusivities—indicative of the experimental electron temperature profile stiffness. Consistent with the L-mode results, cross-scale coupling is found to play an important role in the simulation of these H-mode conditions. Extremely stiff ion-scale transport is observed in these high-performance conditions which is shown to likely play and important role in the reproduction of measurements of perturbative transport. These results provide important insight into the role of multi-scale plasma turbulence in the core of reactor-relevant plasmas and establish important constraints on the the fidelity of models needed for predictive simulations.

Coupled numerical approach combining finite volume and lattice Boltzmann methods for multi-scale multi-physicochemical processes

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

Chen, Li; He, Ya-Ling; Kang, Qinjun

2013-12-15

A coupled (hybrid) simulation strategy spatially combining the finite volume method (FVM) and the lattice Boltzmann method (LBM), called CFVLBM, is developed to simulate coupled multi-scale multi-physicochemical processes. In the CFVLBM, computational domain of multi-scale problems is divided into two sub-domains, i.e., an open, free fluid region and a region filled with porous materials. The FVM and LBM are used for these two regions, respectively, with information exchanged at the interface between the two sub-domains. A general reconstruction operator (RO) is proposed to derive the distribution functions in the LBM from the corresponding macro scalar, the governing equation of whichmore » obeys the convection–diffusion equation. The CFVLBM and the RO are validated in several typical physicochemical problems and then are applied to simulate complex multi-scale coupled fluid flow, heat transfer, mass transport, and chemical reaction in a wall-coated micro reactor. The maximum ratio of the grid size between the FVM and LBM regions is explored and discussed. -- Highlights: •A coupled simulation strategy for simulating multi-scale phenomena is developed. •Finite volume method and lattice Boltzmann method are coupled. •A reconstruction operator is derived to transfer information at the sub-domains interface. •Coupled multi-scale multiple physicochemical processes in micro reactor are simulated. •Techniques to save computational resources and improve the efficiency are discussed.« less

Gyrokinetic predictions of multiscale transport in a DIII-D ITER baseline discharge

DOE PAGES

Holland, C.; Howard, N. T.; Grierson, B. A.

2017-05-08

New multiscale gyrokinetic simulations predict that electron energy transport in a DIII-D ITER baseline discharge with dominant electron heating and low input torque is multiscale in nature, with roughly equal amounts of the electron energy flux Q e coming from long wavelength ion-scale (k yρ s < 1) and short wavelength electron-scale (k yρ s > 1) fluctuations when the gyrokinetic results match independent power balance calculations. Corresponding conventional ion-scale simulations are able to match the power balance ion energy flux Q i, but systematically underpredict Q e when doing so. We observe significant nonlinear cross-scale couplings in the multiscalemore » simulations, but the exact simulation predictions are found to be extremely sensitive to variations of model input parameters within experimental uncertainties. Most notably, depending upon the exact value of the equilibrium E x B shearing rate γ E x B used, either enhancement or suppression of the long-wavelength turbulence and transport levels in the multiscale simulations is observed relative to what is predicted by ion-scale simulations. And while the enhancement of the long wavelength fluctuations by inclusion of the short wavelength turbulence was previously observed in similar multiscale simulations of an Alcator C-Mod L-mode discharge, these new results show for the first time a complete suppression of long-wavelength turbulence in a multiscale simulation, for parameters at which conventional ion-scale simulation predicts small but finite levels of low-k turbulence and transport consistent with the power balance Q i. Though computational resource limitations prevent a fully rigorous validation assessment of these new results, they provide significant new evidence that electron energy transport in burning plasmas is likely to have a strong multiscale character, with significant nonlinear cross-scale couplings that must be fully understood to predict the performance of those plasmas with confidence.« less

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

Roehm, Dominic; Pavel, Robert S.; Barros, Kipton

We present an adaptive sampling method supplemented by a distributed database and a prediction method for multiscale simulations using the Heterogeneous Multiscale Method. A finite-volume scheme integrates the macro-scale conservation laws for elastodynamics, which are closed by momentum and energy fluxes evaluated at the micro-scale. In the original approach, molecular dynamics (MD) simulations are launched for every macro-scale volume element. Our adaptive sampling scheme replaces a large fraction of costly micro-scale MD simulations with fast table lookup and prediction. The cloud database Redis provides the plain table lookup, and with locality aware hashing we gather input data for our predictionmore » scheme. For the latter we use kriging, which estimates an unknown value and its uncertainty (error) at a specific location in parameter space by using weighted averages of the neighboring points. We find that our adaptive scheme significantly improves simulation performance by a factor of 2.5 to 25, while retaining high accuracy for various choices of the algorithm parameters.« less

Distributed database kriging for adaptive sampling (D²KAS)

DOE PAGES

Roehm, Dominic; Pavel, Robert S.; Barros, Kipton; ...

2015-03-18

We present an adaptive sampling method supplemented by a distributed database and a prediction method for multiscale simulations using the Heterogeneous Multiscale Method. A finite-volume scheme integrates the macro-scale conservation laws for elastodynamics, which are closed by momentum and energy fluxes evaluated at the micro-scale. In the original approach, molecular dynamics (MD) simulations are launched for every macro-scale volume element. Our adaptive sampling scheme replaces a large fraction of costly micro-scale MD simulations with fast table lookup and prediction. The cloud database Redis provides the plain table lookup, and with locality aware hashing we gather input data for our predictionmore » scheme. For the latter we use kriging, which estimates an unknown value and its uncertainty (error) at a specific location in parameter space by using weighted averages of the neighboring points. We find that our adaptive scheme significantly improves simulation performance by a factor of 2.5 to 25, while retaining high accuracy for various choices of the algorithm parameters.« less

MULTISCALE AIR QUALITY SIMULATION PLATFORM (MAQSIP): INITIAL APPLICATIONS AND PERFORMANCE FOR TROPOSPHERIC OZONE AND PARTICULATE MATTER

EPA Science Inventory

This manuscript provides an overview of the formulation, process considerations, and performance for simulating tropospheric ozone and particulate matter distributions of the Multiscale Air Quality Simulation Platform (MAQSIP). MAQSIP is a comprehensive atmospheric chemistry/tran...

Multiscale simulation of molecular processes in cellular environments.

PubMed

Chiricotto, Mara; Sterpone, Fabio; Derreumaux, Philippe; Melchionna, Simone

2016-11-13

We describe the recent advances in studying biological systems via multiscale simulations. Our scheme is based on a coarse-grained representation of the macromolecules and a mesoscopic description of the solvent. The dual technique handles particles, the aqueous solvent and their mutual exchange of forces resulting in a stable and accurate methodology allowing biosystems of unprecedented size to be simulated.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2016 The Author(s).

Multiscale image-based modeling and simulation of gas flow and particle transport in the human lungs

PubMed Central

Tawhai, Merryn H; Hoffman, Eric A

2013-01-01

Improved understanding of structure and function relationships in the human lungs in individuals and sub-populations is fundamentally important to the future of pulmonary medicine. Image-based measures of the lungs can provide sensitive indicators of localized features, however to provide a better prediction of lung response to disease, treatment and environment, it is desirable to integrate quantifiable regional features from imaging with associated value-added high-level modeling. With this objective in mind, recent advances in computational fluid dynamics (CFD) of the bronchial airways - from a single bifurcation symmetric model to a multiscale image-based subject-specific lung model - will be reviewed. The interaction of CFD models with local parenchymal tissue expansion - assessed by image registration - allows new understanding of the interplay between environment, hot spots where inhaled aerosols could accumulate, and inflammation. To bridge ventilation function with image-derived central airway structure in CFD, an airway geometrical modeling method that spans from the model ‘entrance’ to the terminal bronchioles will be introduced. Finally, the effects of turbulent flows and CFD turbulence models on aerosol transport and deposition will be discussed. CFD simulation of airflow and particle transport in the human lung has been pursued by a number of research groups, whose interest has been in studying flow physics and airways resistance, improving drug delivery, or investigating which populations are most susceptible to inhaled pollutants. The three most important factors that need to be considered in airway CFD studies are lung structure, regional lung function, and flow characteristics. Their correct treatment is important because the transport of therapeutic or pollutant particles is dependent on the characteristics of the flow by which they are transported; and the airflow in the lungs is dependent on the geometry of the airways and how ventilation is distributed to the peripheral tissue. The human airway structure spans more than 20 generations, beginning with the extra-thoracic airways (oral or nasal cavity, and through the pharynx and larynx to the trachea), then the conducting airways, the respiratory airways, and to the alveoli. The airways in individuals and sub-populations (by gender, age, ethnicity, and normal vs. diseased states) may exhibit different dimensions, branching patterns and angles, and thickness and rigidity. At the local level, one would like to capture detailed flow characteristics, e.g. local velocity profiles, shear stress, and pressure, for prediction of particle transport in an airway (lung structure) model that is specific to the geometry of an individual, to understand how inter-subject variation in airway geometry (normal or pathological) influences the transport and deposition of particles. In a systems biology – or multiscale modeling – approach, these local flow characteristics can be further integrated with epithelial cell models for the study of mechanotransduction. At the global (organ) level, one would like to match regional ventilation (lung function) that is specific to the individual, thus ensuring that the flow that transports inhaled particles is appropriately distributed throughout the lung model. Computational models that do not account for realistic distribution of ventilation are not capable of predicting realistic particle distribution or targeted drug deposition. Furthermore, the flow in the human lung can be transitional or turbulent in the upper and proximal airways, and becomes laminar in the distal airways. The flows in the laminar, transitional and turbulent regimes have different temporal and spatial scales. Therefore, modeling airway structure and predicting gas flow and particle transport at both local and global levels require image-guided multiscale modeling strategies. In this article, we will review the aforementioned three key aspects of CFD studies of the human lungs: airway structure (conducting airways), lung function (regional ventilation and boundary conditions), and flow characteristics (modeling of turbulent flow and its effect on particle transport). For modeling airway structure, we will focus on the conducting airways, and review both symmetric vs. asymmetric airway models, idealized vs. CT-based airway models, and multiscale subject-specific airway models. Imposition of physiological subject-specific boundary conditions (BCs) in CFD is essential to match regional ventilation in individuals, which is also critical in studying preferential deposition of inhaled aerosols in sub-populations, e.g. normals vs. asthmatics that may exhibit different ventilation patterns. Subject-specific regional ventilation defines flow distributions and characteristics in airway segments and bifurcations, which subsequently determines the transport and deposition of aerosols in the entire lungs. Turbulence models are needed to capture the transient and turbulent nature of the gas flow in the human lungs. Thus, the advantages and disadvantages of different turbulence models as well as their effects on particle transport will be discussed. The ultimate goal of the development is to identify sensitive structural and functional variables in sub-populations of normal and diseased lungs for potential clinical applications. PMID:23843310

Exploring Beta-Amyloid Protein Transmembrane Insertion Behavior and Residue-Specific Lipid Interactions in Lipid Bilayers Using Multiscale MD Simulations

NASA Astrophysics Data System (ADS)

Qiu, Liming; Vaughn, Mark; Cheng, Kelvin

2013-03-01

Beta-amyloid (Abeta) interactions with neurons are linked to Alzheimer's. Using a multiscale MD simulation strategy that combines the high efficiency of phase space sampling of coarse-grained MD (CGD) and the high spatial resolution of Atomistic MD (AMD) simulations, we studied the Abeta insertion dynamics in cholesterol-enriched and -depleted lipid bilayers that mimic the neuronal membranes domains. Forward (AMD-CGD) and reverse (CGD-AMD) mappings were used. At the atomistic level, cholesterol promoted insertion of Abeta with high (folded) or low (unfolded) helical contents of the lipid insertion domain (Lys28-Ala42), and the insertions were stabilized by the Lys28 snorkeling and Ala42-anchoring to the polar lipid groups of the bilayer up to 200ns. After the forward mapping, the folded inserted state switched to a new extended inserted state with the Lys28 descended to the middle of the bilayer while the unfolded inserted state migrated to the membrane surface up to 4000ns. The two new states remained stable for 200ns at the atomistic scale after the reverse mapping. Our results suggested that different Abeta membrane-orientation states separated by free energy barriers can be explored by the multiscale MD more effectively than by Atomistic MD simulations alone. NIH RC1-GM090897-02

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

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.

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.

Mechanical response of stainless steel subjected to biaxial load path changes: Cruciform experiments and multi-scale modeling

DOE PAGES

Upadhyay, Manas V.; Patra, Anirban; Wen, Wei; ...

2018-05-08

In this paper, we propose a multi-scale modeling approach that can simulate the microstructural and mechanical behavior of metal or alloy parts with complex geometries subjected to multi-axial load path changes. The model is used to understand the biaxial load path change behavior of 316L stainless steel cruciform samples. At the macroscale, a finite element approach is used to simulate the cruciform geometry and numerically predict the gauge stresses, which are difficult to obtain analytically. At each material point in the finite element mesh, the anisotropic viscoplastic self-consistent model is used to simulate the role of texture evolution on themore » mechanical response. At the single crystal level, a dislocation density based hardening law that appropriately captures the role of multi-axial load path changes on slip activity is used. The combined approach is experimentally validated using cruciform samples subjected to uniaxial load and unload followed by different biaxial reloads in the angular range [27º, 90º]. Polycrystalline yield surfaces before and after load path changes are generated using the full-field elasto-viscoplastic fast Fourier transform model to study the influence of the deformation history and reloading direction on the mechanical response, including the Bauschinger effect, of these cruciform samples. Results reveal that the Bauschinger effect is strongly dependent on the first loading direction and strain, intergranular and macroscopic residual stresses after first load, and the reloading angle. The microstructural origins of the mechanical response are discussed.« less

Mechanical response of stainless steel subjected to biaxial load path changes: Cruciform experiments and multi-scale modeling

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

Upadhyay, Manas V.; Patra, Anirban; Wen, Wei

In this paper, we propose a multi-scale modeling approach that can simulate the microstructural and mechanical behavior of metal or alloy parts with complex geometries subjected to multi-axial load path changes. The model is used to understand the biaxial load path change behavior of 316L stainless steel cruciform samples. At the macroscale, a finite element approach is used to simulate the cruciform geometry and numerically predict the gauge stresses, which are difficult to obtain analytically. At each material point in the finite element mesh, the anisotropic viscoplastic self-consistent model is used to simulate the role of texture evolution on themore » mechanical response. At the single crystal level, a dislocation density based hardening law that appropriately captures the role of multi-axial load path changes on slip activity is used. The combined approach is experimentally validated using cruciform samples subjected to uniaxial load and unload followed by different biaxial reloads in the angular range [27º, 90º]. Polycrystalline yield surfaces before and after load path changes are generated using the full-field elasto-viscoplastic fast Fourier transform model to study the influence of the deformation history and reloading direction on the mechanical response, including the Bauschinger effect, of these cruciform samples. Results reveal that the Bauschinger effect is strongly dependent on the first loading direction and strain, intergranular and macroscopic residual stresses after first load, and the reloading angle. The microstructural origins of the mechanical response are discussed.« less

Physics-based multiscale coupling for full core nuclear reactor simulation

DOE PAGES

Gaston, Derek R.; Permann, Cody J.; Peterson, John W.; ...

2015-10-01

Numerical simulation of nuclear reactors is a key technology in the quest for improvements in efficiency, safety, and reliability of both existing and future reactor designs. Historically, simulation of an entire reactor was accomplished by linking together multiple existing codes that each simulated a subset of the relevant multiphysics phenomena. Recent advances in the MOOSE (Multiphysics Object Oriented Simulation Environment) framework have enabled a new approach: multiple domain-specific applications, all built on the same software framework, are efficiently linked to create a cohesive application. This is accomplished with a flexible coupling capability that allows for a variety of different datamore » exchanges to occur simultaneously on high performance parallel computational hardware. Examples based on the KAIST-3A benchmark core, as well as a simplified Westinghouse AP-1000 configuration, demonstrate the power of this new framework for tackling—in a coupled, multiscale manner—crucial reactor phenomena such as CRUD-induced power shift and fuel shuffle. 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-SA license« less

Multiscale pore structure and its effect on gas transport in organic-rich shale

NASA Astrophysics Data System (ADS)

Wu, Tianhao; Li, Xiang; Zhao, Junliang; Zhang, Dongxiao

2017-07-01

A systematic investigation of multiscale pore structure in organic-rich shale by means of the combination of various imaging techniques is presented, including the state-of-the-art Helium-Ion-Microscope (HIM). The study achieves insight into the major features at each scale and suggests the affordable techniques for specific objectives from the aspects of resolution, dimension, and cost. The pores, which appear to be isolated, are connected by smaller pores resolved by higher-resolution imaging. This observation provides valuable information, from the microscopic perspective of pore structure, for understanding how gas accumulates and transports from where it is generated. A comprehensive workflow is proposed based on the characteristics acquired from the multiscale pore structure analysis to simulate the gas transport process. The simulations are completed with three levels: the microscopic mechanisms should be taken into consideration at level I; the spatial distribution features of organic matter, inorganic matter, and macropores constitute the major issue at level II; and the microfracture orientation and topological structure are dominant factors at level III. The results of apparent permeability from simulations agree well with the values acquired from experiments. By means of the workflow, the impact of various gas transport mechanisms at different scales can be investigated more individually and precisely than conventional experiments.

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

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

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

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

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

DOE PAGES

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

2017-11-27

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

Sensitivities of simulated satellite views of clouds to subgrid-scale overlap and condensate heterogeneity

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

Hillman, Benjamin R.; Marchand, Roger T.; Ackerman, Thomas P.

Satellite simulators are often used to account for limitations in satellite retrievals of cloud properties in comparisons between models and satellite observations. The purpose of the simulator framework is to enable more robust evaluation of model cloud properties, so that di erences between models and observations can more con dently be attributed to model errors. However, these simulators are subject to uncertainties themselves. A fundamental uncertainty exists in connecting the spatial scales at which cloud properties are retrieved with those at which clouds are simulated in global models. In this study, we create a series of sensitivity tests using 4more » km global model output from the Multiscale Modeling Framework to evaluate the sensitivity of simulated satellite retrievals when applied to climate models whose grid spacing is many tens to hundreds of kilometers. In particular, we examine the impact of cloud and precipitation overlap and of condensate spatial variability. We find the simulated retrievals are sensitive to these assumptions. Specifically, using maximum-random overlap with homogeneous cloud and precipitation condensate, which is often used in global climate models, leads to large errors in MISR and ISCCP-simulated cloud cover and in CloudSat-simulated radar reflectivity. To correct for these errors, an improved treatment of unresolved clouds and precipitation is implemented for use with the simulator framework and is shown to substantially reduce the identified errors.« less

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

Multiscale Analysis of a Collapsible Respiratory Airway

NASA Astrophysics Data System (ADS)

Ghadiali, Samir; Bell, E. David; Swarts, J. Douglas

2006-11-01

The Eustachian tube (ET) is a collapsible respiratory airway that connects the nasopharynx with the middle ear (ME). The ET normally exists in a collapsed state and must be periodically opened to maintain a healthy and sterile ME. Although the inability to open the ET (i.e. ET dysfunction) is the primary etiology responsible for several common ME diseases (i.e. Otitis Media), the mechanisms responsible for ET dysfunction are not well established. To investigate these mechanisms, we developed a multi-scale model of airflow in the ET and correlated model results with experimental data obtained in healthy and diseased subjects. The computational models utilized finite-element methods to simulate fluid-structure interactions and molecular dynamics techniques to quantify the adhesive properties of mucus glycoproteins. Results indicate that airflow in the ET is highly sensitive to both the dynamics of muscle contraction and molecular adhesion forces within the ET lumen. In addition, correlation of model results with experimental data obtained in diseased subjects was used to identify the biomechanical mechanisms responsible for ET dysfunction.

Inferring multi-scale neural mechanisms with brain network modelling

PubMed Central

Schirner, Michael; McIntosh, Anthony Randal; Jirsa, Viktor; Deco, Gustavo

2018-01-01

The neurophysiological processes underlying non-invasive brain activity measurements are incompletely understood. Here, we developed a connectome-based brain network model that integrates individual structural and functional data with neural population dynamics to support multi-scale neurophysiological inference. Simulated populations were linked by structural connectivity and, as a novelty, driven by electroencephalography (EEG) source activity. Simulations not only predicted subjects' individual resting-state functional magnetic resonance imaging (fMRI) time series and spatial network topologies over 20 minutes of activity, but more importantly, they also revealed precise neurophysiological mechanisms that underlie and link six empirical observations from different scales and modalities: (1) resting-state fMRI oscillations, (2) functional connectivity networks, (3) excitation-inhibition balance, (4, 5) inverse relationships between α-rhythms, spike-firing and fMRI on short and long time scales, and (6) fMRI power-law scaling. These findings underscore the potential of this new modelling framework for general inference and integration of neurophysiological knowledge to complement empirical studies. PMID:29308767

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

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.

The Multiscale Robin Coupled Method for flows in porous media

NASA Astrophysics Data System (ADS)

Guiraldello, Rafael T.; Ausas, Roberto F.; Sousa, Fabricio S.; Pereira, Felipe; Buscaglia, Gustavo C.

2018-02-01

A multiscale mixed method aiming at the accurate approximation of velocity and pressure fields in heterogeneous porous media is proposed. The procedure is based on a new domain decomposition method in which the local problems are subject to Robin boundary conditions. The domain decomposition procedure is defined in terms of two independent spaces on the skeleton of the decomposition, corresponding to interface pressures and fluxes, that can be chosen with great flexibility to accommodate local features of the underlying permeability fields. The well-posedness of the new domain decomposition procedure is established and its connection with the method of Douglas et al. (1993) [12], is identified, also allowing us to reinterpret the known procedure as an optimized Schwarz (or Two-Lagrange-Multiplier) method. The multiscale property of the new domain decomposition method is indicated, and its relation with the Multiscale Mortar Mixed Finite Element Method (MMMFEM) and the Multiscale Hybrid-Mixed (MHM) Finite Element Method is discussed. Numerical simulations are presented aiming at illustrating several features of the new method. Initially we illustrate the possibility of switching from MMMFEM to MHM by suitably varying the Robin condition parameter in the new multiscale method. Then we turn our attention to realistic flows in high-contrast, channelized porous formations. We show that for a range of values of the Robin condition parameter our method provides better approximations for pressure and velocity than those computed with either the MMMFEM and the MHM. This is an indication that our method has the potential to produce more accurate velocity fields in the presence of rough, realistic permeability fields of petroleum reservoirs.

An Overview of the State of the Art in Atomistic and Multiscale Simulation of Fracture

NASA Technical Reports Server (NTRS)

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

2009-01-01

The emerging field of nanomechanics is providing a new focus in the study of the mechanics of materials, particularly in simulating fundamental atomic mechanisms involved in the initiation and evolution of damage. Simulating fundamental material processes using first principles in physics strongly motivates the formulation of computational multiscale methods to link macroscopic failure to the underlying atomic processes from which all material behavior originates. This report gives an overview of the state of the art in applying concurrent and sequential multiscale methods to analyze damage and failure mechanisms across length scales.

Validation of nonlinear gyrokinetic simulations of L- and I-mode plasmas on Alcator C-Mod

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

Creely, A. J.; Howard, N. T.; Rodriguez-Fernandez, P.

New validation of global, nonlinear, ion-scale gyrokinetic simulations (GYRO) is carried out for L- and I-mode plasmas on Alcator C-Mod, utilizing heat fluxes, profile stiffness, and temperature fluctuations. Previous work at C-Mod found that ITG/TEM-scale GYRO simulations can match both electron and ion heat fluxes within error bars in I-mode [White PoP 2015], suggesting that multi-scale (cross-scale coupling) effects [Howard PoP 2016] may be less important in I-mode than in L-mode. New results presented here, however, show that global, nonlinear, ion-scale GYRO simulations are able to match the experimental ion heat flux, but underpredict electron heat flux (at most radii),more » electron temperature fluctuations, and perturbative thermal diffusivity in both L- and I-mode. Linear addition of electron heat flux from electron scale runs does not resolve this discrepancy. These results indicate that single-scale simulations do not sufficiently describe the I-mode core transport, and that multi-scale (coupled electron- and ion-scale) transport models are needed. In conclusion a preliminary investigation with multi-scale TGLF, however, was unable to resolve the discrepancy between ion-scale GYRO and experimental electron heat fluxes and perturbative diffusivity, motivating further work with multi-scale GYRO simulations and a more comprehensive study with multi-scale TGLF.« less

Validation of nonlinear gyrokinetic simulations of L- and I-mode plasmas on Alcator C-Mod

DOE PAGES

Creely, A. J.; Howard, N. T.; Rodriguez-Fernandez, P.; ...

2017-03-02

New validation of global, nonlinear, ion-scale gyrokinetic simulations (GYRO) is carried out for L- and I-mode plasmas on Alcator C-Mod, utilizing heat fluxes, profile stiffness, and temperature fluctuations. Previous work at C-Mod found that ITG/TEM-scale GYRO simulations can match both electron and ion heat fluxes within error bars in I-mode [White PoP 2015], suggesting that multi-scale (cross-scale coupling) effects [Howard PoP 2016] may be less important in I-mode than in L-mode. New results presented here, however, show that global, nonlinear, ion-scale GYRO simulations are able to match the experimental ion heat flux, but underpredict electron heat flux (at most radii),more » electron temperature fluctuations, and perturbative thermal diffusivity in both L- and I-mode. Linear addition of electron heat flux from electron scale runs does not resolve this discrepancy. These results indicate that single-scale simulations do not sufficiently describe the I-mode core transport, and that multi-scale (coupled electron- and ion-scale) transport models are needed. In conclusion a preliminary investigation with multi-scale TGLF, however, was unable to resolve the discrepancy between ion-scale GYRO and experimental electron heat fluxes and perturbative diffusivity, motivating further work with multi-scale GYRO simulations and a more comprehensive study with multi-scale TGLF.« less

Fast online generalized multiscale finite element method using constraint energy minimization

NASA Astrophysics Data System (ADS)

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

2018-02-01

Local multiscale methods often construct multiscale basis functions in the offline stage without taking into account input parameters, such as source terms, boundary conditions, and so on. These basis functions are then used in the online stage with a specific input parameter to solve the global problem at a reduced computational cost. Recently, online approaches have been introduced, where multiscale basis functions are adaptively constructed in some regions to reduce the error significantly. In multiscale methods, it is desired to have only 1-2 iterations to reduce the error to a desired threshold. Using Generalized Multiscale Finite Element Framework [10], it was shown that by choosing sufficient number of offline basis functions, the error reduction can be made independent of physical parameters, such as scales and contrast. In this paper, our goal is to improve this. Using our recently proposed approach [4] and special online basis construction in oversampled regions, we show that the error reduction can be made sufficiently large by appropriately selecting oversampling regions. Our numerical results show that one can achieve a three order of magnitude error reduction, which is better than our previous methods. We also develop an adaptive algorithm and enrich in selected regions with large residuals. In our adaptive method, we show that the convergence rate can be determined by a user-defined parameter and we confirm this by numerical simulations. The analysis of the method is presented.

Evaluation of the Community Multi-scale Air Quality (CMAQ) ...

EPA Pesticide Factsheets

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 Protection Agency develops the CMAQ model and periodically releases new versions of the model that include bug fixes and various other improvements to the modeling system. In the fall of 2015, CMAQ version 5.1 was released. This new version of CMAQ will contain important bug fixes to several issues that were identified in CMAQv5.0.2 and additionally include updates to other portions of the code. Several annual, and numerous episodic, CMAQv5.1 simulations were performed to assess the impact of these improvements on the model results. These results will be presented, along with a base evaluation of the performance of the CMAQv5.1 modeling system against available surface and upper-air measurements available during the time period simulated. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, proces

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

NASA Technical Reports Server (NTRS)

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

Effects of Subscale Size and Shape on Global Energy Dissipation in a Multiscale Model of a Fiber-Reinforced Composite Exhibiting Post-Peak Strain Softening Using Abaqus and FEAMAC

NASA Technical Reports Server (NTRS)

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

2012-01-01

A mesh objective crack band model is implemented in the generalized method of cells (GMC) micromechanics model to predict failure of a composite repeating unit cell (RUC). The micromechanics calculations are achieved using the MAC/GMC core engine within the ImMAC suite of micromechanics codes, developed at the NASA Glenn Research Center. The microscale RUC is linked to a macroscale Abaqus/Standard finite element model using the FEAMAC multiscale framework (included in the ImMAC suite). The effects of the relationship between the characteristic length of the finite element and the size of the microscale RUC on the total energy dissipation of the multiscale model are investigated. A simple 2-D composite square subjected to uniaxial tension is used to demonstrate the effects of scaling the dimensions of the RUC such that the length of the sides of the RUC are equal to the characteristic length of the finite element. These results are compared to simulations where the size of the RUC is fixed, independent of the element size. Simulations are carried out for a variety of mesh densities and element shapes, including square and triangular. Results indicate that a consistent size and shape must be used to yield preserve energy dissipation across the scales.

EEMD-based multiscale ICA method for slewing bearing fault detection and diagnosis

NASA Astrophysics Data System (ADS)

Žvokelj, Matej; Zupan, Samo; Prebil, Ivan

2016-05-01

A novel multivariate and multiscale statistical process monitoring method is proposed with the aim of detecting incipient failures in large slewing bearings, where subjective influence plays a minor role. The proposed method integrates the strengths of the Independent Component Analysis (ICA) multivariate monitoring approach with the benefits of Ensemble Empirical Mode Decomposition (EEMD), which adaptively decomposes signals into different time scales and can thus cope with multiscale system dynamics. The method, which was named EEMD-based multiscale ICA (EEMD-MSICA), not only enables bearing fault detection but also offers a mechanism of multivariate signal denoising and, in combination with the Envelope Analysis (EA), a diagnostic tool. The multiscale nature of the proposed approach makes the method convenient to cope with data which emanate from bearings in complex real-world rotating machinery and frequently represent the cumulative effect of many underlying phenomena occupying different regions in the time-frequency plane. The efficiency of the proposed method was tested on simulated as well as real vibration and Acoustic Emission (AE) signals obtained through conducting an accelerated run-to-failure lifetime experiment on a purpose-built laboratory slewing bearing test stand. The ability to detect and locate the early-stage rolling-sliding contact fatigue failure of the bearing indicates that AE and vibration signals carry sufficient information on the bearing condition and that the developed EEMD-MSICA method is able to effectively extract it, thereby representing a reliable bearing fault detection and diagnosis strategy.

Computer Laboratory for Multi-scale Simulations of Novel Nanomaterials

DTIC Science & Technology

2014-09-15

schemes for multiscale modeling of polymers. Permselective ion-exchange membranes for protective clothing, fuel cells , and batteries are of special...polyelectrolyte membranes ( PEM ) with chemical warfare agents (CWA) and their simulants and (2) development of new simulation methods and computational...chemical potential using gauge cell method and calculation of density profiles. However, the code does not run in parallel environments. For mesoscale

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.

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

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

Zhang, Duan Z.; Dhakal, Tilak Raj

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

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

DOE PAGES

Zhang, Duan Z.; Dhakal, Tilak Raj

2017-01-17

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

Three-dimensional multi-scale model of deformable platelets adhesion to vessel wall in blood flow

PubMed Central

Wu, Ziheng; Xu, Zhiliang; Kim, Oleg; Alber, Mark

2014-01-01

When a blood vessel ruptures or gets inflamed, the human body responds by rapidly forming a clot to restrict the loss of blood. Platelets aggregation at the injury site of the blood vessel occurring via platelet–platelet adhesion, tethering and rolling on the injured endothelium is a critical initial step in blood clot formation. A novel three-dimensional multi-scale model is introduced and used in this paper to simulate receptor-mediated adhesion of deformable platelets at the site of vascular injury under different shear rates of blood flow. The novelty of the model is based on a new approach of coupling submodels at three biological scales crucial for the early clot formation: novel hybrid cell membrane submodel to represent physiological elastic properties of a platelet, stochastic receptor–ligand binding submodel to describe cell adhesion kinetics and lattice Boltzmann submodel for simulating blood flow. The model implementation on the GPU cluster significantly improved simulation performance. Predictive model simulations revealed that platelet deformation, interactions between platelets in the vicinity of the vessel wall as well as the number of functional GPIbα platelet receptors played significant roles in platelet adhesion to the injury site. Variation of the number of functional GPIbα platelet receptors as well as changes of platelet stiffness can represent effects of specific drugs reducing or enhancing platelet activity. Therefore, predictive simulations can improve the search for new drug targets and help to make treatment of thrombosis patient-specific. PMID:24982253

A novel method of multi-scale simulation of macro-scale deformation and microstructure evolution on metal forming

NASA Astrophysics Data System (ADS)

Huang, Shiquan; Yi, Youping; Li, Pengchuan

2011-05-01

In recent years, multi-scale simulation technique of metal forming is gaining significant attention for prediction of the whole deformation process and microstructure evolution of product. The advances of numerical simulation at macro-scale level on metal forming are remarkable and the commercial FEM software, such as Deform2D/3D, has found a wide application in the fields of metal forming. However, the simulation method of multi-scale has little application due to the non-linearity of microstructure evolution during forming and the difficulty of modeling at the micro-scale level. This work deals with the modeling of microstructure evolution and a new method of multi-scale simulation in forging process. The aviation material 7050 aluminum alloy has been used as example for modeling of microstructure evolution. The corresponding thermal simulated experiment has been performed on Gleeble 1500 machine. The tested specimens have been analyzed for modeling of dislocation density, nucleation and growth of recrystallization(DRX). The source program using cellular automaton (CA) method has been developed to simulate the grain nucleation and growth, in which the change of grain topology structure caused by the metal deformation was considered. The physical fields at macro-scale level such as temperature field, stress and strain fields, which can be obtained by commercial software Deform 3D, are coupled with the deformed storage energy at micro-scale level by dislocation model to realize the multi-scale simulation. This method was explained by forging process simulation of the aircraft wheel hub forging. Coupled the results of Deform 3D with CA results, the forging deformation progress and the microstructure evolution at any point of forging could be simulated. For verifying the efficiency of simulation, experiments of aircraft wheel hub forging have been done in the laboratory and the comparison of simulation and experiment result has been discussed in details.

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.

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 (...

All-Atom Multiscale Molecular Dynamics Theory and Simulation of Self-Assembly, Energy Transfer and Structural Transition in Nanosystems

NASA Astrophysics Data System (ADS)

Espinosa Duran, John Michael

The study of nanosystems and their emergent properties requires the development of multiscale computational models, theories and methods that preserve atomic and femtosecond resolution, to reveal details that cannot be resolved experimentally today. Considering this, three long time scale phenomena were studied using molecular dynamics and multiscale methods: self-assembly of organic molecules on graphite, energy transfer in nanosystems, and structural transition in vault nanoparticles. Molecular dynamics simulations of the self-assembly of alkoxybenzonitriles with different tail lengths on graphite were performed to learn about intermolecular interactions and phases exhibited by self-organized materials. This is important for the design of ordered self-assembled organic photovoltaic materials with greater efficiency than the disordered blends. Simulations revealed surface dynamical behaviors that cannot be resolved experimentally today due to the lack of spatiotemporal resolution. Atom-resolved structures predicted by simulations agreed with scanning tunneling microscopy images and unit cell measurements. Then, a multiscale theory based on the energy density as a field variable is developed to study energy transfer in nanoscale systems. For applications like photothermal microscopy or cancer phototherapy is required to understand how the energy is transferred to/from nanosystems. This multiscale theory could be applied in this context and here is tested for cubic nanoparticles immersed in water for energy being transferred to/from the nanoparticle. The theory predicts the energy transfer dynamics and reveals phenomena that cannot be described by current phenomenological theories. Finally, temperature-triggered structural transitions were revealed for vault nanoparticles using molecular dynamics and multiscale simulations. Vault is a football-shaped supramolecular assembly very distinct from the commonly observed icosahedral viruses. It has very promising applications in drug delivery and has been extensively studied experimentally. Sub-microsecond multiscale simulations at 310 K on the vault revealed the opening and closing of fractures near the shoulder while preserving the overall structure. This fracture mechanism could explain the uptake and release of small drugs while maintaining the overall structure. Higher temperature simulations show the generation of large fractures near the waist, which enables interaction of the external medium with the inner vault residues. Simulation results agreed with microscopy and spectroscopy measurements, and revealed new structures and mechanisms.

Experimental parameter identification of a multi-scale musculoskeletal model controlled by electrical stimulation: application to patients with spinal cord injury.

PubMed

Benoussaad, Mourad; Poignet, Philippe; Hayashibe, Mitsuhiro; Azevedo-Coste, Christine; Fattal, Charles; Guiraud, David

2013-06-01

We investigated the parameter identification of a multi-scale physiological model of skeletal muscle, based on Huxley's formulation. We focused particularly on the knee joint controlled by quadriceps muscles under electrical stimulation (ES) in subjects with a complete spinal cord injury. A noninvasive and in vivo identification protocol was thus applied through surface stimulation in nine subjects and through neural stimulation in one ES-implanted subject. The identification protocol included initial identification steps, which are adaptations of existing identification techniques to estimate most of the parameters of our model. Then we applied an original and safer identification protocol in dynamic conditions, which required resolution of a nonlinear programming (NLP) problem to identify the serial element stiffness of quadriceps. Each identification step and cross validation of the estimated model in dynamic condition were evaluated through a quadratic error criterion. The results highlighted good accuracy, the efficiency of the identification protocol and the ability of the estimated model to predict the subject-specific behavior of the musculoskeletal system. From the comparison of parameter values between subjects, we discussed and explored the inter-subject variability of parameters in order to select parameters that have to be identified in each patient.

Efficient Integration of Coupled Electrical-Chemical Systems in Multiscale Neuronal Simulations

PubMed Central

Brocke, Ekaterina; Bhalla, Upinder S.; Djurfeldt, Mikael; Hellgren Kotaleski, Jeanette; Hanke, Michael

2016-01-01

Multiscale modeling and simulations in neuroscience is gaining scientific attention due to its growing importance and unexplored capabilities. For instance, it can help to acquire better understanding of biological phenomena that have important features at multiple scales of time and space. This includes synaptic plasticity, memory formation and modulation, homeostasis. There are several ways to organize multiscale simulations depending on the scientific problem and the system to be modeled. One of the possibilities is to simulate different components of a multiscale system simultaneously and exchange data when required. The latter may become a challenging task for several reasons. First, the components of a multiscale system usually span different spatial and temporal scales, such that rigorous analysis of possible coupling solutions is required. Then, the components can be defined by different mathematical formalisms. For certain classes of problems a number of coupling mechanisms have been proposed and successfully used. However, a strict mathematical theory is missing in many cases. Recent work in the field has not so far investigated artifacts that may arise during coupled integration of different approximation methods. Moreover, in neuroscience, the coupling of widely used numerical fixed step size solvers may lead to unexpected inefficiency. In this paper we address the question of possible numerical artifacts that can arise during the integration of a coupled system. We develop an efficient strategy to couple the components comprising a multiscale test problem in neuroscience. We introduce an efficient coupling method based on the second-order backward differentiation formula (BDF2) numerical approximation. The method uses an adaptive step size integration with an error estimation proposed by Skelboe (2000). The method shows a significant advantage over conventional fixed step size solvers used in neuroscience for similar problems. We explore different coupling strategies that define the organization of computations between system components. We study the importance of an appropriate approximation of exchanged variables during the simulation. The analysis shows a substantial impact of these aspects on the solution accuracy in the application to our multiscale neuroscientific test problem. We believe that the ideas presented in the paper may essentially contribute to the development of a robust and efficient framework for multiscale brain modeling and simulations in neuroscience. PMID:27672364

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

PubMed

Brocke, Ekaterina; Bhalla, Upinder S; Djurfeldt, Mikael; Hellgren Kotaleski, Jeanette; Hanke, Michael

2016-01-01

Multiscale modeling and simulations in neuroscience is gaining scientific attention due to its growing importance and unexplored capabilities. For instance, it can help to acquire better understanding of biological phenomena that have important features at multiple scales of time and space. This includes synaptic plasticity, memory formation and modulation, homeostasis. There are several ways to organize multiscale simulations depending on the scientific problem and the system to be modeled. One of the possibilities is to simulate different components of a multiscale system simultaneously and exchange data when required. The latter may become a challenging task for several reasons. First, the components of a multiscale system usually span different spatial and temporal scales, such that rigorous analysis of possible coupling solutions is required. Then, the components can be defined by different mathematical formalisms. For certain classes of problems a number of coupling mechanisms have been proposed and successfully used. However, a strict mathematical theory is missing in many cases. Recent work in the field has not so far investigated artifacts that may arise during coupled integration of different approximation methods. Moreover, in neuroscience, the coupling of widely used numerical fixed step size solvers may lead to unexpected inefficiency. In this paper we address the question of possible numerical artifacts that can arise during the integration of a coupled system. We develop an efficient strategy to couple the components comprising a multiscale test problem in neuroscience. We introduce an efficient coupling method based on the second-order backward differentiation formula (BDF2) numerical approximation. The method uses an adaptive step size integration with an error estimation proposed by Skelboe (2000). The method shows a significant advantage over conventional fixed step size solvers used in neuroscience for similar problems. We explore different coupling strategies that define the organization of computations between system components. We study the importance of an appropriate approximation of exchanged variables during the simulation. The analysis shows a substantial impact of these aspects on the solution accuracy in the application to our multiscale neuroscientific test problem. We believe that the ideas presented in the paper may essentially contribute to the development of a robust and efficient framework for multiscale brain modeling and simulations in neuroscience.

Multiscale Simulation of Blood Flow in Brain Arteries with an Aneurysm

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

Leopold Grinberg; Vitali Morozov; Dmitry A. Fedosov

2013-04-24

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

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 ...

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...

Multi-Scale Simulation of High Energy Density Ionic Liquids

DTIC Science & Technology

2007-06-19

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

PROTO-PLASM: parallel language for adaptive and scalable modelling of biosystems.

PubMed

Bajaj, Chandrajit; DiCarlo, Antonio; Paoluzzi, Alberto

2008-09-13

This paper discusses the design goals and the first developments of PROTO-PLASM, a novel computational environment to produce libraries of executable, combinable and customizable computer models of natural and synthetic biosystems, aiming to provide a supporting framework for predictive understanding of structure and behaviour through multiscale geometric modelling and multiphysics simulations. Admittedly, the PROTO-PLASM platform is still in its infancy. Its computational framework--language, model library, integrated development environment and parallel engine--intends to provide patient-specific computational modelling and simulation of organs and biosystem, exploiting novel functionalities resulting from the symbolic combination of parametrized models of parts at various scales. PROTO-PLASM may define the model equations, but it is currently focused on the symbolic description of model geometry and on the parallel support of simulations. Conversely, CellML and SBML could be viewed as defining the behavioural functions (the model equations) to be used within a PROTO-PLASM program. Here we exemplify the basic functionalities of PROTO-PLASM, by constructing a schematic heart model. We also discuss multiscale issues with reference to the geometric and physical modelling of neuromuscular junctions.

Proto-Plasm: parallel language for adaptive and scalable modelling of biosystems

PubMed Central

Bajaj, Chandrajit; DiCarlo, Antonio; Paoluzzi, Alberto

2008-01-01

This paper discusses the design goals and the first developments of Proto-Plasm, a novel computational environment to produce libraries of executable, combinable and customizable computer models of natural and synthetic biosystems, aiming to provide a supporting framework for predictive understanding of structure and behaviour through multiscale geometric modelling and multiphysics simulations. Admittedly, the Proto-Plasm platform is still in its infancy. Its computational framework—language, model library, integrated development environment and parallel engine—intends to provide patient-specific computational modelling and simulation of organs and biosystem, exploiting novel functionalities resulting from the symbolic combination of parametrized models of parts at various scales. Proto-Plasm may define the model equations, but it is currently focused on the symbolic description of model geometry and on the parallel support of simulations. Conversely, CellML and SBML could be viewed as defining the behavioural functions (the model equations) to be used within a Proto-Plasm program. Here we exemplify the basic functionalities of Proto-Plasm, by constructing a schematic heart model. We also discuss multiscale issues with reference to the geometric and physical modelling of neuromuscular junctions. PMID:18559320

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

Ortoleva, Peter J.

Illustrative embodiments of systems and methods for the deductive multiscale simulation of macromolecules are disclosed. In one illustrative embodiment, a deductive multiscale simulation method may include (i) constructing a set of order parameters that model one or more structural characteristics of a macromolecule, (ii) simulating an ensemble of atomistic configurations for the macromolecule using instantaneous values of the set of order parameters, (iii) simulating thermal-average forces and diffusivities for the ensemble of atomistic configurations, and (iv) evolving the set of order parameters via Langevin dynamics using the thermal-average forces and diffusivities.

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.

Exploring total cardiac variability in healthy and pathophysiological subjects using improved refined multiscale entropy.

PubMed

Marwaha, Puneeta; Sunkaria, Ramesh Kumar

2017-02-01

Multiscale entropy (MSE) and refined multiscale entropy (RMSE) techniques are being widely used to evaluate the complexity of a time series across multiple time scales 't'. Both these techniques, at certain time scales (sometimes for the entire time scales, in the case of RMSE), assign higher entropy to the HRV time series of certain pathologies than that of healthy subjects, and to their corresponding randomized surrogate time series. This incorrect assessment of signal complexity may be due to the fact that these techniques suffer from the following limitations: (1) threshold value 'r' is updated as a function of long-term standard deviation and hence unable to explore the short-term variability as well as substantial variability inherited in beat-to-beat fluctuations of long-term HRV time series. (2) In RMSE, entropy values assigned to different filtered scaled time series are the result of changes in variance, but do not completely reflect the real structural organization inherited in original time series. In the present work, we propose an improved RMSE (I-RMSE) technique by introducing a new procedure to set the threshold value by taking into account the period-to-period variability inherited in a signal and evaluated it on simulated and real HRV database. The proposed I-RMSE assigns higher entropy to the age-matched healthy subjects than that of patients suffering from atrial fibrillation, congestive heart failure, sudden cardiac death and diabetes mellitus, for the entire time scales. The results strongly support the reduction in complexity of HRV time series in female group, old-aged, patients suffering from severe cardiovascular and non-cardiovascular diseases, and in their corresponding surrogate time series.

Multi-scale Finite Element Modeling of Eustachian Tube Function: Influence of Mucosal Adhesion

PubMed Central

Malik, J.E.; Swarts, J.D.; Ghadiali, S. N.

2017-01-01

The inability to open the collapsible Eustachian tube (ET) leads to the development of chronic Otitis Media (OM). Although mucosal inflammation during OM leads to increased mucin gene expression and elevated adhesion forces within the ET lumen, it is not known how changes in mucosal adhesion alter the biomechanical mechanisms of ET function. In this study, we developed a novel multi-scale finite element model of ET function in adults that utilizes adhesion spring elements to simulate changes in mucosal adhesion. Models were created for six adult subjects and dynamic patterns in muscle contraction were used to simulate the wave-like opening of the ET that occurs during swallowing. Results indicate that ET opening is highly sensitive to the level of mucosal adhesion and that exceeding a critical value of adhesion leads to rapid ET dysfunction. Parameter variation studies and sensitivity analysis indicate that increased mucosal adhesion alters the relative importance of several tissue biomechanical properties. For example, increases in mucosal adhesion reduced the sensitivity of ET function to tensor veli palatini muscle forces but did not alter the insensitivity of ET function to levator veli palatini muscle forces. Interestingly, although changes in cartilage stiffness did not significantly influence ET opening under low adhesion conditions, ET opening was highly sensitive to changes in cartilage stiffness under high adhesion conditions. Therefore, our multi-scale computational models indicate that changes in mucosal adhesion as would occur during inflammatory OM alter the biomechanical mechanisms of ET function. PMID:26891171

Multiscale equation-free algorithms for molecular dynamics

NASA Astrophysics Data System (ADS)

Abi Mansour, Andrew

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

Multiscale analysis of structure development in expanded starch snacks

NASA Astrophysics Data System (ADS)

van der Sman, R. G. M.; Broeze, J.

2014-11-01

In this paper we perform a multiscale analysis of the food structuring process of the expansion of starchy snack foods like keropok, which obtains a solid foam structure. In particular, we want to investigate the validity of the hypothesis of Kokini and coworkers, that expansion is optimal at the moisture content, where the glass transition and the boiling line intersect. In our analysis we make use of several tools, (1) time scale analysis from the field of physical transport phenomena, (2) the scale separation map (SSM) developed within a multiscale simulation framework of complex automata, (3) the supplemented state diagram (SSD), depicting phase transition and glass transition lines, and (4) a multiscale simulation model for the bubble expansion. Results of the time scale analysis are plotted in the SSD, and give insight into the dominant physical processes involved in expansion. Furthermore, the results of the time scale analysis are used to construct the SSM, which has aided us in the construction of the multiscale simulation model. Simulation results are plotted in the SSD. This clearly shows that the hypothesis of Kokini is qualitatively true, but has to be refined. Our results show that bubble expansion is optimal for moisture content, where the boiling line for gas pressure of 4 bars intersects the isoviscosity line of the critical viscosity 106 Pa.s, which runs parallel to the glass transition line.

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

Effects of multiscale phase-mixing and interior conductance in the lunar-like pickup ion plasma wake. First results from 3-D hybrid kinetic modeling

NASA Astrophysics Data System (ADS)

Lipatov, A. S.; Sarantos, M.; Farrell, W. M.; Cooper, J. F.

2018-07-01

The study of multiscale pickup ion phase-mixing in the lunar plasma wake with a hybrid model is the main subject of our investigation in this paper. Photoionization and charge exchange of protons with the lunar exosphere are the ionization processes included in our model. The computational model includes the self-consistent dynamics of the light (H+ or H2+ and He+), and heavy (Na+) pickup ions. The electrons are considered as a fluid. The lunar interior is considered as a weakly conducting body. In this paper we considered for the first time the cumulative effect of heavy neutrals in the lunar exosphere (e.g., Al, Ar), an effect which was simulated with one species of Na+ but with a tenfold increase in total production rates. We find that various species produce various types of plasma tail in the lunar plasma wake. Specifically, Na+ and He+ pickup ions form a cycloid-like tail, whereas the H+ or H2+ pickup ions form a tail with a high density core and saw-like periodic structures in the flank region. The length of these structures varies from 1.5RM to 3.3RM depending on the value of gyroradius for H+ or H2+ pickup ions. The light pickup ions produce more symmetrical jump in the density and magnetic field at the Mach cone which is mainly controlled by the conductivity of the interior, an effect previously unappreciated. Although other pickup ion species had little effect on the nature of the interaction of the Moon with the solar wind, the global structure of the lunar tail in these simulations appeared quite different when the H2+ production rate was high.

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

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

NASA Technical Reports Server (NTRS)

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

2008-01-01

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

Multiscale Poincaré plots for visualizing the structure of heartbeat time series.

PubMed

Henriques, Teresa S; Mariani, Sara; Burykin, Anton; Rodrigues, Filipa; Silva, Tiago F; Goldberger, Ary L

2016-02-09

Poincaré delay maps are widely used in the analysis of cardiac interbeat interval (RR) dynamics. To facilitate visualization of the structure of these time series, we introduce multiscale Poincaré (MSP) plots. Starting with the original RR time series, the method employs a coarse-graining procedure to create a family of time series, each of which represents the system's dynamics in a different time scale. Next, the Poincaré plots are constructed for the original and the coarse-grained time series. Finally, as an optional adjunct, color can be added to each point to represent its normalized frequency. We illustrate the MSP method on simulated Gaussian white and 1/f noise time series. The MSP plots of 1/f noise time series reveal relative conservation of the phase space area over multiple time scales, while those of white noise show a marked reduction in area. We also show how MSP plots can be used to illustrate the loss of complexity when heartbeat time series from healthy subjects are compared with those from patients with chronic (congestive) heart failure syndrome or with atrial fibrillation. This generalized multiscale approach to Poincaré plots may be useful in visualizing other types of time series.

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.

Multiscale Modeling of Structurally-Graded Materials Using Discrete Dislocation Plasticity Models and Continuum Crystal Plasticity Models

NASA Technical Reports Server (NTRS)

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

2012-01-01

A multiscale modeling methodology that combines the predictive capability of discrete dislocation plasticity and the computational efficiency of continuum crystal plasticity is developed. Single crystal configurations of different grain sizes modeled with periodic boundary conditions are analyzed using discrete dislocation plasticity (DD) to obtain grain size-dependent stress-strain predictions. These relationships are mapped into crystal plasticity parameters to develop a multiscale DD/CP model for continuum level simulations. A polycrystal model of a structurally-graded microstructure is developed, analyzed and used as a benchmark for comparison between the multiscale DD/CP model and the DD predictions. The multiscale DD/CP model follows the DD predictions closely up to an initial peak stress and then follows a strain hardening path that is parallel but somewhat offset from the DD predictions. The difference is believed to be from a combination of the strain rate in the DD simulation and the inability of the DD/CP model to represent non-monotonic material response.

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

Simulating Cancer Growth with Multiscale Agent-Based Modeling

PubMed Central

Wang, Zhihui; Butner, Joseph D.; Kerketta, Romica; Cristini, Vittorio; Deisboeck, Thomas S.

2014-01-01

There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models. PMID:24793698

Multiscale Universal Interface: A concurrent framework for coupling heterogeneous solvers

NASA Astrophysics Data System (ADS)

Tang, Yu-Hang; Kudo, Shuhei; Bian, Xin; Li, Zhen; Karniadakis, George Em

2015-09-01

Concurrently coupled numerical simulations using heterogeneous solvers are powerful tools for modeling multiscale phenomena. However, major modifications to existing codes are often required to enable such simulations, posing significant difficulties in practice. In this paper we present a C++ library, i.e. the Multiscale Universal Interface (MUI), which is capable of facilitating the coupling effort for a wide range of multiscale simulations. The library adopts a header-only form with minimal external dependency and hence can be easily dropped into existing codes. A data sampler concept is introduced, combined with a hybrid dynamic/static typing mechanism, to create an easily customizable framework for solver-independent data interpretation. The library integrates MPI MPMD support and an asynchronous communication protocol to handle inter-solver information exchange irrespective of the solvers' own MPI awareness. Template metaprogramming is heavily employed to simultaneously improve runtime performance and code flexibility. We validated the library by solving three different multiscale problems, which also serve to demonstrate the flexibility of the framework in handling heterogeneous models and solvers. In the first example, a Couette flow was simulated using two concurrently coupled Smoothed Particle Hydrodynamics (SPH) simulations of different spatial resolutions. In the second example, we coupled the deterministic SPH method with the stochastic Dissipative Particle Dynamics (DPD) method to study the effect of surface grafting on the hydrodynamics properties on the surface. In the third example, we consider conjugate heat transfer between a solid domain and a fluid domain by coupling the particle-based energy-conserving DPD (eDPD) method with the Finite Element Method (FEM).

Multiscale Universal Interface: A concurrent framework for coupling heterogeneous solvers

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

Tang, Yu-Hang, E-mail: yuhang_tang@brown.edu; Kudo, Shuhei, E-mail: shuhei-kudo@outlook.jp; Bian, Xin, E-mail: xin_bian@brown.edu

2015-09-15

Graphical abstract: - Abstract: Concurrently coupled numerical simulations using heterogeneous solvers are powerful tools for modeling multiscale phenomena. However, major modifications to existing codes are often required to enable such simulations, posing significant difficulties in practice. In this paper we present a C++ library, i.e. the Multiscale Universal Interface (MUI), which is capable of facilitating the coupling effort for a wide range of multiscale simulations. The library adopts a header-only form with minimal external dependency and hence can be easily dropped into existing codes. A data sampler concept is introduced, combined with a hybrid dynamic/static typing mechanism, to create anmore » easily customizable framework for solver-independent data interpretation. The library integrates MPI MPMD support and an asynchronous communication protocol to handle inter-solver information exchange irrespective of the solvers' own MPI awareness. Template metaprogramming is heavily employed to simultaneously improve runtime performance and code flexibility. We validated the library by solving three different multiscale problems, which also serve to demonstrate the flexibility of the framework in handling heterogeneous models and solvers. In the first example, a Couette flow was simulated using two concurrently coupled Smoothed Particle Hydrodynamics (SPH) simulations of different spatial resolutions. In the second example, we coupled the deterministic SPH method with the stochastic Dissipative Particle Dynamics (DPD) method to study the effect of surface grafting on the hydrodynamics properties on the surface. In the third example, we consider conjugate heat transfer between a solid domain and a fluid domain by coupling the particle-based energy-conserving DPD (eDPD) method with the Finite Element Method (FEM)« less

Coupling biomechanics to a cellular level model: an approach to patient-specific image driven multi-scale and multi-physics tumor simulation.

PubMed

May, Christian P; Kolokotroni, Eleni; Stamatakos, Georgios S; Büchler, Philippe

2011-10-01

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

Multiscale stochastic simulations for tensile testing of nanotube-based macroscopic cables.

PubMed

Pugno, Nicola M; Bosia, Federico; Carpinteri, Alberto

2008-08-01

Thousands of multiscale stochastic simulations are carried out in order to perform the first in-silico tensile tests of carbon nanotube (CNT)-based macroscopic cables with varying length. The longest treated cable is the space-elevator megacable but more realistic shorter cables are also considered in this bottom-up investigation. Different sizes, shapes, and concentrations of defects are simulated, resulting in cable macrostrengths not larger than approximately 10 GPa, which is much smaller than the theoretical nanotube strength (approximately 100 GPa). No best-fit parameters are present in the multiscale simulations: the input at level 1 is directly estimated from nanotensile tests of CNTs, whereas its output is considered as the input for the level 2, and so on up to level 5, corresponding to the megacable. Thus, five hierarchical levels are used to span lengths from that of a single nanotube (approximately 100 nm) to that of the space-elevator megacable (approximately 100 Mm).

Using CellML with OpenCMISS to Simulate Multi-Scale Physiology

PubMed Central

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

2014-01-01

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

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

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.

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.

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

PubMed

Hamdi, Mustapha

2009-12-02

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

Towards practical multiscale approach for analysis of reinforced concrete structures

NASA Astrophysics Data System (ADS)

Moyeda, Arturo; Fish, Jacob

2017-12-01

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

Melnikov's criteria, parametric control of chaos, and stationary chaos occurrence in systems with asymmetric potential subjected to multiscale type excitation.

PubMed

Kwuimy, C A Kitio; Nataraj, C; Litak, G

2011-12-01

We consider the problems of chaos and parametric control in nonlinear systems under an asymmetric potential subjected to a multiscale type excitation. The lower bound line for horseshoes chaos is analyzed using the Melnikov's criterion for a transition to permanent or transient nonperiodic motions, complement by the fractal or regular shape of the basin of attraction. Numerical simulations based on the basins of attraction, bifurcation diagrams, Poincaré sections, Lyapunov exponents, and phase portraits are used to show how stationary dissipative chaos occurs in the system. Our attention is focussed on the effects of the asymmetric potential term and the driven frequency. It is shown that the threshold amplitude ∣γ(c)∣ of the excitation decreases for small values of the driven frequency ω and increases for large values of ω. This threshold value decreases with the asymmetric parameter α and becomes constant for sufficiently large values of α. γ(c) has its maximum value for asymmetric load in comparison with the symmetric load. Finally, we apply the Melnikov theorem to the controlled system to explore the gain control parameter dependencies.

Turbulence and dissipation in a computational model of Luzon Strait

NASA Astrophysics Data System (ADS)

Jalali, Masoud; Sarkar, Sutanu

2014-11-01

Generation sites for topographic internal gravity waves can also be sites of intense turbulence. Bottom-intensified flow at critical slopes leads to convective instability and turbulent overturns [Gayen & Sarkar (2011)]. A steep ridge with small excursion number, Ex , but large super criticality can lead to nonlinear features according to observations [Klymak et al. (2008)] and numerical simulations [Legg & Klymak (2008)]. The present work uses high resolution 3-D LES to simulate flow over a model with multiscale topography patterned after a cross-section of Luzon Strait, a double-ridge generation site which was the subject of the recent IWISE experiment. A 1:100 scaling of topography was employed and environmental parameters were chosen to match the slope criticality and Fr number in the field. Several turbulent zones were identified including breaking lee waves, critical slope boundary layer, downslope jets, internal wave beams, and vortical valley flows. The multiscale model topography has subridges where a local Ex may be defined. Wave breaking and turbulence at these subridges can be understood if the local value of Ex is employed when using the Ex -based regimes identified by Jalali et al. (2014) in their DNS of oscillating flow over a single triangular obstacle.

Analysis of Gas-Particle Flows through Multi-Scale Simulations

NASA Astrophysics Data System (ADS)

Gu, Yile

Multi-scale structures are inherent in gas-solid flows, which render the modeling efforts challenging. On one hand, detailed simulations where the fine structures are resolved and particle properties can be directly specified can account for complex flow behaviors, but they are too computationally expensive to apply for larger systems. On the other hand, coarse-grained simulations demand much less computations but they necessitate constitutive models which are often not readily available for given particle properties. The present study focuses on addressing this issue, as it seeks to provide a general framework through which one can obtain the required constitutive models from detailed simulations. To demonstrate the viability of this general framework in which closures can be proposed for different particle properties, we focus on the van der Waals force of interaction between particles. We start with Computational Fluid Dynamics (CFD) - Discrete Element Method (DEM) simulations where the fine structures are resolved and van der Waals force between particles can be directly specified, and obtain closures for stress and drag that are required for coarse-grained simulations. Specifically, we develop a new cohesion model that appropriately accounts for van der Waals force between particles to be used for CFD-DEM simulations. We then validate this cohesion model and the CFD-DEM approach by showing that it can qualitatively capture experimental results where the addition of small particles to gas fluidization reduces bubble sizes. Based on the DEM and CFD-DEM simulation results, we propose stress models that account for the van der Waals force between particles. Finally, we apply machine learning, specifically neural networks, to obtain a drag model that captures the effects from fine structures and inter-particle cohesion. We show that this novel approach using neural networks, which can be readily applied for other closures other than drag here, can take advantage of the large amount of data generated from simulations, and therefore offer superior modeling performance over traditional approaches.

Three-Dimensional Visualization of Ozone Process Data.

DTIC Science & Technology

1997-06-18

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

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

A multi-scale model of the interplay between cell signalling and hormone transport in specifying the root meristem of Arabidopsis thaliana.

PubMed

Muraro, D; Larrieu, A; Lucas, M; Chopard, J; Byrne, H; Godin, C; King, J

2016-09-07

The growth of the root of Arabidopsis thaliana is sustained by the meristem, a region of cell proliferation and differentiation which is located in the root apex and generates cells which move shootwards, expanding rapidly to cause root growth. The balance between cell division and differentiation is maintained via a signalling network, primarily coordinated by the hormones auxin, cytokinin and gibberellin. Since these hormones interact at different levels of spatial organisation, we develop a multi-scale computational model which enables us to study the interplay between these signalling networks and cell-cell communication during the specification of the root meristem. We investigate the responses of our model to hormonal perturbations, validating the results of our simulations against experimental data. Our simulations suggest that one or more additional components are needed to explain the observed expression patterns of a regulator of cytokinin signalling, ARR1, in roots not producing gibberellin. By searching for novel network components, we identify two mutant lines that affect significantly both root length and meristem size, one of which also differentially expresses a central component of the interaction network (SHY2). More generally, our study demonstrates how a multi-scale investigation can provide valuable insight into the spatio-temporal dynamics of signalling networks in biological tissues. Copyright © 2016 Elsevier Ltd. All rights reserved.

Simulations of ecosystem hydrological processes using a unified multi-scale model

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

Yang, Xiaofan; Liu, Chongxuan; Fang, Yilin

2015-01-01

This paper presents a unified multi-scale model (UMSM) that we developed to simulate hydrological processes in an ecosystem containing both surface water and groundwater. The UMSM approach modifies the Navier–Stokes equation by adding a Darcy force term to formulate a single set of equations to describe fluid momentum and uses a generalized equation to describe fluid mass balance. The advantage of the approach is that the single set of the equations can describe hydrological processes in both surface water and groundwater where different models are traditionally required to simulate fluid flow. This feature of the UMSM significantly facilitates modelling ofmore » hydrological processes in ecosystems, especially at locations where soil/sediment may be frequently inundated and drained in response to precipitation, regional hydrological and climate changes. In this paper, the UMSM was benchmarked using WASH123D, a model commonly used for simulating coupled surface water and groundwater flow. Disney Wilderness Preserve (DWP) site at the Kissimmee, Florida, where active field monitoring and measurements are ongoing to understand hydrological and biogeochemical processes, was then used as an example to illustrate the UMSM modelling approach. The simulations results demonstrated that the DWP site is subject to the frequent changes in soil saturation, the geometry and volume of surface water bodies, and groundwater and surface water exchange. All the hydrological phenomena in surface water and groundwater components including inundation and draining, river bank flow, groundwater table change, soil saturation, hydrological interactions between groundwater and surface water, and the migration of surface water and groundwater interfaces can be simultaneously simulated using the UMSM. Overall, the UMSM offers a cross-scale approach that is particularly suitable to simulate coupled surface and ground water flow in ecosystems with strong surface water and groundwater interactions.« less

Multi-scale finite element modeling of Eustachian tube function: influence of mucosal adhesion.

PubMed

Malik, J E; Swarts, J D; Ghadiali, S N

2016-12-01

The inability to open the collapsible Eustachian tube (ET) leads to the development of chronic Otitis Media (OM). Although mucosal inflammation during OM leads to increased mucin gene expression and elevated adhesion forces within the ET lumen, it is not known how changes in mucosal adhesion alter the biomechanical mechanisms of ET function. In this study, we developed a novel multi-scale finite element model of ET function in adults that utilizes adhesion spring elements to simulate changes in mucosal adhesion. Models were created for six adult subjects, and dynamic patterns in muscle contraction were used to simulate the wave-like opening of the ET that occurs during swallowing. Results indicate that ET opening is highly sensitive to the level of mucosal adhesion and that exceeding a critical value of adhesion leads to rapid ET dysfunction. Parameter variation studies and sensitivity analysis indicate that increased mucosal adhesion alters the relative importance of several tissue biomechanical properties. For example, increases in mucosal adhesion reduced the sensitivity of ET function to tensor veli palatini muscle forces but did not alter the insensitivity of ET function to levator veli palatini muscle forces. Interestingly, although changes in cartilage stiffness did not significantly influence ET opening under low adhesion conditions, ET opening was highly sensitive to changes in cartilage stiffness under high adhesion conditions. Therefore, our multi-scale computational models indicate that changes in mucosal adhesion as would occur during inflammatory OM alter the biomechanical mechanisms of ET function. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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.

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.

Properties of Shocked Polymers: Mbar experiments on Z and multi-scale simulations

NASA Astrophysics Data System (ADS)

Mattsson, Thomas R.

2010-03-01

Significant progress has been made over the last few years in understanding properties of matter subject to strong shocks and other extreme conditions. High-accuracy multi-Mbar experiments and first-principles theoretical studies together provide detailed insights into the physics and chemistry of high energy-density matter. While comprehensive advances have been made for pure elements like deuterium, helium, and carbon, progress has been slower for equally important, albeit more challenging, materials like molecular crystals, polymers, and foams. Hydrocarbon based polymer foams are common materials and in particular they are used in designing shock- and inertial confinement fusion experiments. Depending on their initial density, foams shock to relatively higher pressure and temperature compared to shocked dense polymers/plastics. As foams and polymers are shocked, they exhibit both structural and chemical transitions. We will present experimental and theoretical results for shocked polymers in the Mbar regime. By shock impact of magnetically launched flyer plates on poly(4-methyl-1-pentene) foams, we create multi-Mbar pressures in a dense plasma mixture of hydrogen, carbon, at temperatures of several eV. Concurrently with executing experiments, we analyze the system by multi-scale simulations, from density functional theory to continuum magneto-hydrodynamics simulations. In particular, density functional theory (DFT) molecular dynamics (MD) and classical MD simulations of the principal shock Hugoniot will be presented in detail for two hydrocarbon polymers: polyethylene (PE) and poly(4-methyl-1-pentene) (PMP).

The Onset of Type 2 Diabetes: Proposal for a Multi-Scale Model

PubMed Central

Tieri, Paolo; De Graaf, Albert; Franceschi, Claudio; Liò, Pietro; Van Ommen, Ben; Mazzà, Claudia; Tuchel, Alexander; Bernaschi, Massimo; Samson, Clare; Colombo, Teresa; Castellani, Gastone C; Capri, Miriam; Garagnani, Paolo; Salvioli, Stefano; Nguyen, Viet Anh; Bobeldijk-Pastorova, Ivana; Krishnan, Shaji; Cappozzo, Aurelio; Sacchetti, Massimo; Morettini, Micaela; Ernst, Marc

2013-01-01

Background Type 2 diabetes mellitus (T2D) is a common age-related disease, and is a major health concern, particularly in developed countries where the population is aging, including Europe. The multi-scale immune system simulator for the onset of type 2 diabetes (MISSION-T2D) is a European Union-funded project that aims to develop and validate an integrated, multilevel, and patient-specific model, incorporating genetic, metabolic, and nutritional data for the simulation and prediction of metabolic and inflammatory processes in the onset and progression of T2D. The project will ultimately provide a tool for diagnosis and clinical decision making that can estimate the risk of developing T2D and predict its progression in response to possible therapies. Recent data showed that T2D and its complications, specifically in the heart, kidney, retina, and feet, should be considered a systemic disease that is sustained by a pervasive, metabolically-driven state of inflammation. Accordingly, there is an urgent need (1) to understand the complex mechanisms underpinning the onset of this disease, and (2) to identify early patient-specific diagnostic parameters and related inflammatory indicators. Objective We aim to accomplish this mission by setting up a multi-scale model to study the systemic interactions of the biological mechanisms involved in response to a variety of nutritional and metabolic stimuli and stressors. Methods Specifically, we will be studying the biological mechanisms of immunological/inflammatory processes, energy intake/expenditure ratio, and cell cycle rate. The overall architecture of the model will exploit an already established immune system simulator as well as several discrete and continuous mathematical methods for modeling of the processes critically involved in the onset and progression of T2D. We aim to validate the predictions of our models using actual biological and clinical data. Results This study was initiated in March 2013 and is expected to be completed by February 2016. Conclusions MISSION-T2D aims to pave the way for translating validated multilevel immune-metabolic models into the clinical setting of T2D. This approach will eventually generate predictive biomarkers for this disease from the integration of clinical data with metabolic, nutritional, immune/inflammatory, genetic, and gut microbiota profiles. Eventually, it should prove possible to translate these into cost-effective and mobile-based diagnostic tools. PMID:24176906

An open source platform for multi-scale spatially distributed simulations of microbial ecosystems

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

Segre, Daniel

2014-08-14

The goal of this project was to develop a tool for facilitating simulation, validation and discovery of multiscale dynamical processes in microbial ecosystems. This led to the development of an open-source software platform for Computation Of Microbial Ecosystems in Time and Space (COMETS). COMETS performs spatially distributed time-dependent flux balance based simulations of microbial metabolism. Our plan involved building the software platform itself, calibrating and testing it through comparison with experimental data, and integrating simulations and experiments to address important open questions on the evolution and dynamics of cross-feeding interactions between microbial species.

ProtoMD: A prototyping toolkit for multiscale molecular dynamics

NASA Astrophysics Data System (ADS)

Somogyi, Endre; Mansour, Andrew Abi; Ortoleva, Peter J.

2016-05-01

ProtoMD is a toolkit that facilitates the development of algorithms for multiscale molecular dynamics (MD) simulations. It is designed for multiscale methods which capture the dynamic transfer of information across multiple spatial scales, such as the atomic to the mesoscopic scale, via coevolving microscopic and coarse-grained (CG) variables. ProtoMD can be also be used to calibrate parameters needed in traditional CG-MD methods. The toolkit integrates 'GROMACS wrapper' to initiate MD simulations, and 'MDAnalysis' to analyze and manipulate trajectory files. It facilitates experimentation with a spectrum of coarse-grained variables, prototyping rare events (such as chemical reactions), or simulating nanocharacterization experiments such as terahertz spectroscopy, AFM, nanopore, and time-of-flight mass spectroscopy. ProtoMD is written in python and is freely available under the GNU General Public License from github.com/CTCNano/proto_md.

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

Scalable High-order Methods for Multi-Scale Problems: Analysis, Algorithms and Application

DTIC Science & Technology

2016-02-26

Karniadakis, “Resilient algorithms for reconstructing and simulating gappy flow fields in CFD ”, Fluid Dynamic Research, vol. 47, 051402, 2015. 2. Y. Yu, H...simulation, domain decomposition, CFD , gappy data, estimation theory, and gap-tooth algorithm. 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...objective of this project was to develop a general CFD framework for multifidelity simula- tions to target multiscale problems but also resilience in

Multiscale Macromolecular Simulation: Role of Evolving Ensembles

PubMed Central

Singharoy, A.; Joshi, H.; Ortoleva, P.J.

2013-01-01

Multiscale analysis provides an algorithm for the efficient simulation of macromolecular assemblies. This algorithm involves the coevolution of a quasiequilibrium probability density of atomic configurations and the Langevin dynamics of spatial coarse-grained variables denoted order parameters (OPs) characterizing nanoscale system features. In practice, implementation of the probability density involves the generation of constant OP ensembles of atomic configurations. Such ensembles are used to construct thermal forces and diffusion factors that mediate the stochastic OP dynamics. Generation of all-atom ensembles at every Langevin timestep is computationally expensive. Here, multiscale computation for macromolecular systems is made more efficient by a method that self-consistently folds in ensembles of all-atom configurations constructed in an earlier step, history, of the Langevin evolution. This procedure accounts for the temporal evolution of these ensembles, accurately providing thermal forces and diffusions. It is shown that efficiency and accuracy of the OP-based simulations is increased via the integration of this historical information. Accuracy improves with the square root of the number of historical timesteps included in the calculation. As a result, CPU usage can be decreased by a factor of 3-8 without loss of accuracy. The algorithm is implemented into our existing force-field based multiscale simulation platform and demonstrated via the structural dynamics of viral capsomers. PMID:22978601

Multiscale modeling for ferroelectric materials: identification of the phase-field model’s free energy for PZT from atomistic simulations

NASA Astrophysics Data System (ADS)

Völker, Benjamin; Landis, Chad M.; Kamlah, Marc

2012-03-01

Within a knowledge-based multiscale simulation approach for ferroelectric materials, the atomic level can be linked to the mesoscale by transferring results from first-principles calculations into a phase-field model. A recently presented routine (Völker et al 2011 Contin. Mech. Thermodyn. 23 435-51) for adjusting the Helmholtz free energy coefficients to intrinsic and extrinsic ferroelectric material properties obtained by DFT calculations and atomistic simulations was subject to certain limitations: caused by too small available degrees of freedom, an independent adjustment of the spontaneous strains and piezoelectric coefficients was not possible, and the elastic properties could only be considered in cubic instead of tetragonal symmetry. In this work we overcome such restrictions by expanding the formulation of the free energy function, i.e. by motivating and introducing new higher-order terms that have not appeared in the literature before. Subsequently we present an improved version of the adjustment procedure for the free energy coefficients that is solely based on input parameters from first-principles calculations performed by Marton and Elsässer, as documented in Völker et al (2011 Contin. Mech. Thermodyn. 23 435-51). Full sets of adjusted free energy coefficients for PbTiO3 and tetragonal Pb(Zr,Ti)O3 are presented, and the benefits of the newly introduced higher-order free energy terms are discussed.

Multiscale Data Assimilation

DTIC Science & Technology

2014-09-30

good test 3 case to study the multiscale data assimilation capabilities of our GMM-DO filter. We also performed stochastic simulations with our DO...Morakot and internal tides. The ignorance score and Kullback - Leibler divergence were employed to measure the skill of the multiscale pdf forecasts...read off from the posterior of the augmented state vector. We implemented this new smoother and tested it using a 2D-in-space stochastic flow exiting

Multiscale Simulation of Microbe Structure and Dynamics

PubMed Central

Joshi, Harshad; Singharoy, Abhishek; Sereda, Yuriy V.; Cheluvaraja, Srinath C.; Ortoleva, Peter J.

2012-01-01

A multiscale mathematical and computational approach is developed that captures the hierarchical organization of a microbe. It is found that a natural perspective for understanding a microbe is in terms of a hierarchy of variables at various levels of resolution. This hierarchy starts with the N -atom description and terminates with order parameters characterizing a whole microbe. This conceptual framework is used to guide the analysis of the Liouville equation for the probability density of the positions and momenta of the N atoms constituting the microbe and its environment. Using multiscale mathematical techniques, we derive equations for the co-evolution of the order parameters and the probability density of the N-atom state. This approach yields a rigorous way to transfer information between variables on different space-time scales. It elucidates the interplay between equilibrium and far-from-equilibrium processes underlying microbial behavior. It also provides framework for using coarse-grained nanocharacterization data to guide microbial simulation. It enables a methodical search for free-energy minimizing structures, many of which are typically supported by the set of macromolecules and membranes constituting a given microbe. This suite of capabilities provides a natural framework for arriving at a fundamental understanding of microbial behavior, the analysis of nanocharacterization data, and the computer-aided design of nanostructures for biotechnical and medical purposes. Selected features of the methodology are demonstrated using our multiscale bionanosystem simulator DeductiveMultiscaleSimulator. Systems used to demonstrate the approach are structural transitions in the cowpea chlorotic mosaic virus, RNA of satellite tobacco mosaic virus, virus-like particles related to human papillomavirus, and iron-binding protein lactoferrin. PMID:21802438

Aggregation of alpha-synuclein by a coarse-grained Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Farmer, Barry; Pandey, Ras

Alpha-synuclein, an intrinsic protein abundant in neurons, is believed to be a major cause of neurodegenerative diseases (e.g. Alzheimer, Parkinson's disease). Abnormal aggregation of ASN leads to Lewy bodies with specific morphologies. We investigate the self-organizing structures in a crowded environment of ASN proteins by a coarse-grained Monte Carlo simulation. ASN is a chain of 140 residues. Structure detail of residues is neglected but its specificity is captured via unique knowledge-based residue-residue interactions. Large-scale simulations are performed to analyze a number local and global physical quantities (e.g. mobility profile, contact map, radius of gyration, structure factor) as a function of temperature and protein concentration. Trend in multi-scale structural variations of the protein in a crowded environment is compared with that of a free protein chain.

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

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

A coupling method for a cardiovascular simulation model which includes the Kalman filter.

PubMed

Hasegawa, Yuki; Shimayoshi, Takao; Amano, Akira; Matsuda, Tetsuya

2012-01-01

Multi-scale models of the cardiovascular system provide new insight that was unavailable with in vivo and in vitro experiments. For the cardiovascular system, multi-scale simulations provide a valuable perspective in analyzing the interaction of three phenomenons occurring at different spatial scales: circulatory hemodynamics, ventricular structural dynamics, and myocardial excitation-contraction. In order to simulate these interactions, multiscale cardiovascular simulation systems couple models that simulate different phenomena. However, coupling methods require a significant amount of calculation, since a system of non-linear equations must be solved for each timestep. Therefore, we proposed a coupling method which decreases the amount of calculation by using the Kalman filter. In our method, the Kalman filter calculates approximations for the solution to the system of non-linear equations at each timestep. The approximations are then used as initial values for solving the system of non-linear equations. The proposed method decreases the number of iterations required by 94.0% compared to the conventional strong coupling method. When compared with a smoothing spline predictor, the proposed method required 49.4% fewer iterations.

Refined generalized multiscale entropy analysis for physiological signals

NASA Astrophysics Data System (ADS)

Liu, Yunxiao; Lin, Youfang; Wang, Jing; Shang, Pengjian

2018-01-01

Multiscale entropy analysis has become a prevalent complexity measurement and been successfully applied in various fields. However, it only takes into account the information of mean values (first moment) in coarse-graining procedure. Then generalized multiscale entropy (MSEn) considering higher moments to coarse-grain a time series was proposed and MSEσ2 has been implemented. However, the MSEσ2 sometimes may yield an imprecise estimation of entropy or undefined entropy, and reduce statistical reliability of sample entropy estimation as scale factor increases. For this purpose, we developed the refined model, RMSEσ2, to improve MSEσ2. Simulations on both white noise and 1 / f noise show that RMSEσ2 provides higher entropy reliability and reduces the occurrence of undefined entropy, especially suitable for short time series. Besides, we discuss the effect on RMSEσ2 analysis from outliers, data loss and other concepts in signal processing. We apply the proposed model to evaluate the complexity of heartbeat interval time series derived from healthy young and elderly subjects, patients with congestive heart failure and patients with atrial fibrillation respectively, compared to several popular complexity metrics. The results demonstrate that RMSEσ2 measured complexity (a) decreases with aging and diseases, and (b) gives significant discrimination between different physiological/pathological states, which may facilitate clinical application.

Multiscale simulation of red blood cell aggregation

NASA Astrophysics Data System (ADS)

Bagchi, P.; Popel, A. S.

2004-11-01

In humans and other mammals, aggregation of red blood cells (RBC) is a major determinant to blood viscosity in microcirculation under physiological and pathological conditions. Elevated levels of aggregation are often related to cardiovascular diseases, bacterial infection, diabetes, and obesity. Aggregation is a multiscale phenomenon that is governed by the molecular bond formation between adjacent cells, morphological and rheological properties of the cells, and the motion of the extra-cellular fluid in which the cells circulate. We have developed a simulation technique using front tracking methods for multiple fluids that includes the multiscale characteristics of aggregation. We will report the first-ever direct computer simulation of aggregation of deformable cells in shear flows. We will present results on the effect of shear rate, strength of the cross-bridging bonds, and the cell rheological properties on the rolling motion, deformation and subsequent breakage of an aggregate.

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.

A Comprehensive Specimen-Specific Multiscale Data Set for Anatomical and Mechanical Characterization of the Tibiofemoral Joint

PubMed Central

Chokhandre, Snehal; Colbrunn, Robb; Bennetts, Craig; Erdemir, Ahmet

2015-01-01

Understanding of tibiofemoral joint mechanics at multiple spatial scales is essential for developing effective preventive measures and treatments for both pathology and injury management. Currently, there is a distinct lack of specimen-specific biomechanical data at multiple spatial scales, e.g., joint, tissue, and cell scales. Comprehensive multiscale data may improve the understanding of the relationship between biomechanical and anatomical markers across various scales. Furthermore, specimen-specific multiscale data for the tibiofemoral joint may assist development and validation of specimen-specific computational models that may be useful for more thorough analyses of the biomechanical behavior of the joint. This study describes an aggregation of procedures for acquisition of multiscale anatomical and biomechanical data for the tibiofemoral joint. Magnetic resonance imaging was used to acquire anatomical morphology at the joint scale. A robotic testing system was used to quantify joint level biomechanical response under various loading scenarios. Tissue level material properties were obtained from the same specimen for the femoral and tibial articular cartilage, medial and lateral menisci, anterior and posterior cruciate ligaments, and medial and lateral collateral ligaments. Histology data were also obtained for all tissue types to measure specimen-specific cell scale information, e.g., cellular distribution. This study is the first of its kind to establish a comprehensive multiscale data set for a musculoskeletal joint and the presented data collection approach can be used as a general template to guide acquisition of specimen-specific comprehensive multiscale data for musculoskeletal joints. PMID:26381404

Multiscale stochastic simulations of chemical reactions with regulated scale separation

NASA Astrophysics Data System (ADS)

Koumoutsakos, Petros; Feigelman, Justin

2013-07-01

We present a coupling of multiscale frameworks with accelerated stochastic simulation algorithms for systems of chemical reactions with disparate propensities. The algorithms regulate the propensities of the fast and slow reactions of the system, using alternating micro and macro sub-steps simulated with accelerated algorithms such as τ and R-leaping. The proposed algorithms are shown to provide significant speedups in simulations of stiff systems of chemical reactions with a trade-off in accuracy as controlled by a regulating parameter. More importantly, the error of the methods exhibits a cutoff phenomenon that allows for optimal parameter choices. Numerical experiments demonstrate that hybrid algorithms involving accelerated stochastic simulations can be, in certain cases, more accurate while faster, than their corresponding stochastic simulation algorithm counterparts.

Growth of nitrogen-doped graphene on copper: Multiscale simulations

NASA Astrophysics Data System (ADS)

Gaillard, P.; Schoenhalz, A. L.; Moskovkin, P.; Lucas, S.; Henrard, L.

2016-02-01

We used multiscale simulations to model the growth of nitrogen-doped graphene on a copper substrate by chemical vapour deposition (CVD). Our simulations are based on ab-initio calculations of energy barriers for surface diffusion, which are complemented by larger scale Kinetic Monte Carlo (KMC) simulations. Our results indicate that the shape of grown doped graphene flakes depends on the temperature and deposition flux they are submitted during the process, but we found no significant effect of nitrogen doping on this shape. However, we show that nitrogen atoms have a preference for pyridine-like sites compared to graphite-like sites, as observed experimentally.

Enhanced Representation of Soil NO Emissions in the Community Multiscale Air Quality (CMAQ) Model Version 5.0.2

NASA Technical Reports Server (NTRS)

Rasool, Quazi Z.; Zhang, Rui; Lash, Benjamin; Cohan, Daniel S.; Cooter, Ellen J.; Bash, Jesse O.; Lamsal, Lok N.

2016-01-01

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions.

Simulating cancer growth with multiscale agent-based modeling.

PubMed

Wang, Zhihui; Butner, Joseph D; Kerketta, Romica; Cristini, Vittorio; Deisboeck, Thomas S

2015-02-01

There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Multi-scale modeling of Arabidopsis thaliana response to different CO2 conditions: From gene expression to metabolic flux.

PubMed

Liu, Lin; Shen, Fangzhou; Xin, Changpeng; Wang, Zhuo

2016-01-01

Multi-scale investigation from gene transcript level to metabolic activity is important to uncover plant response to environment perturbation. Here we integrated a genome-scale constraint-based metabolic model with transcriptome data to explore Arabidopsis thaliana response to both elevated and low CO2 conditions. The four condition-specific models from low to high CO2 concentrations show differences in active reaction sets, enriched pathways for increased/decreased fluxes, and putative post-transcriptional regulation, which indicates that condition-specific models are necessary to reflect physiological metabolic states. The simulated CO2 fixation flux at different CO2 concentrations is consistent with the measured Assimilation-CO2intercellular curve. Interestingly, we found that reactions in primary metabolism are affected most significantly by CO2 perturbation, whereas secondary metabolic reactions are not influenced a lot. The changes predicted in key pathways are consistent with existing knowledge. Another interesting point is that Arabidopsis is required to make stronger adjustment on metabolism to adapt to the more severe low CO2 stress than elevated CO2 . The challenges of identifying post-transcriptional regulation could also be addressed by the integrative model. In conclusion, this innovative application of multi-scale modeling in plants demonstrates potential to uncover the mechanisms of metabolic response to different conditions. © 2015 Institute of Botany, Chinese Academy of Sciences.

CR softcopy display presets based on optimum visualization of specific findings

NASA Astrophysics Data System (ADS)

Andriole, Katherine P.; Gould, Robert G.; Webb, W. R.

1999-07-01

The purpose of this research is to assess the utility of providing presets for computed radiography (CR) softcopy display, based not on the window/level settings, but on image processing applied to the image based on optimization for visualization of specific findings, pathologies, etc. Clinical chest images are acquired using an Agfa ADC 70 CR scanner, and transferred over the PACS network to an image processing station which has the capability to perform multiscale contrast equalization. The optimal image processing settings per finding are developed in conjunction with a thoracic radiologist by manipulating the multiscale image contrast amplification algorithm parameters. Softcopy display of images processed with finding-specific settings are compared with the standard default image presentation for fifty cases of each category. Comparison is scored using a five point scale with positive one and two denoting the standard presentation is preferred over the finding-specific presets, negative one and two denoting the finding-specific preset is preferred over the standard presentation, and zero denoting no difference. Presets have been developed for pneumothorax and clinical cases are currently being collected in preparation for formal clinical trials. Subjective assessments indicate a preference for the optimized-preset presentation of images over the standard default, particularly by inexperienced radiology residents and referring clinicians.

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

Non-Invasive Electrical Impedance Tomography for Multi-Scale Detection of Liver Fat Content

PubMed Central

Luo, Yuan; Abiri, Parinaz; Zhang, Shell; Chang, Chih-Chiang; Kaboodrangi, Amir H.; Li, Rongsong; Sahib, Ashish K.; Bui, Alex; Kumar, Rajesh; Woo, Mary; Li, Zhaoping; Packard, René R. Sevag; Tai, Yu-Chong; Hsiai, Tzung K.

2018-01-01

Introduction: Obesity is associated with an increased risk of nonalcoholic fatty liver disease (NAFLD). While Magnetic Resonance Imaging (MRI) is a non-invasive gold standard to detect fatty liver, we demonstrate a low-cost and portable electrical impedance tomography (EIT) approach with circumferential abdominal electrodes for liver conductivity measurements. Methods and Results: A finite element model (FEM) was established to simulate decremental liver conductivity in response to incremental liver lipid content. To validate the FEM simulation, we performed EIT imaging on an ex vivo porcine liver in a non-conductive tank with 32 circumferentially-embedded electrodes, demonstrating a high-resolution output given a priori information on location and geometry. To further examine EIT capacity in fatty liver detection, we performed EIT measurements in age- and gender-matched New Zealand White rabbits (3 on normal, 3 on high-fat diets). Liver conductivity values were significantly distinct following the high-fat diet (p = 0.003 vs. normal diet, n=3), accompanied by histopathological evidence of hepatic fat accumulation. We further assessed EIT imaging in human subjects with MRI quantification for fat volume fraction based on Dixon procedures, demonstrating average liver conductivity of 0.331 S/m for subjects with low Body-Mass Index (BMI < 25 kg/m²) and 0.286 S/m for high BMI (> 25 kg/m²). Conclusion: We provide both the theoretical and experimental framework for a multi-scale EIT strategy to detect liver lipid content. Our preliminary studies pave the way to enhance the spatial resolution of EIT as a marker for fatty liver disease and metabolic syndrome. PMID:29556346

Patient-specific models of cardiac biomechanics

NASA Astrophysics Data System (ADS)

Krishnamurthy, Adarsh; Villongco, Christopher T.; Chuang, Joyce; Frank, Lawrence R.; Nigam, Vishal; Belezzuoli, Ernest; Stark, Paul; Krummen, David E.; Narayan, Sanjiv; Omens, Jeffrey H.; McCulloch, Andrew D.; Kerckhoffs, Roy C. P.

2013-07-01

Patient-specific models of cardiac function have the potential to improve diagnosis and management of heart disease by integrating medical images with heterogeneous clinical measurements subject to constraints imposed by physical first principles and prior experimental knowledge. We describe new methods for creating three-dimensional patient-specific models of ventricular biomechanics in the failing heart. Three-dimensional bi-ventricular geometry is segmented from cardiac CT images at end-diastole from patients with heart failure. Human myofiber and sheet architecture is modeled using eigenvectors computed from diffusion tensor MR images from an isolated, fixed human organ-donor heart and transformed to the patient-specific geometric model using large deformation diffeomorphic mapping. Semi-automated methods were developed for optimizing the passive material properties while simultaneously computing the unloaded reference geometry of the ventricles for stress analysis. Material properties of active cardiac muscle contraction were optimized to match ventricular pressures measured by cardiac catheterization, and parameters of a lumped-parameter closed-loop model of the circulation were estimated with a circulatory adaptation algorithm making use of information derived from echocardiography. These components were then integrated to create a multi-scale model of the patient-specific heart. These methods were tested in five heart failure patients from the San Diego Veteran's Affairs Medical Center who gave informed consent. The simulation results showed good agreement with measured echocardiographic and global functional parameters such as ejection fraction and peak cavity pressures.

Hybrid Multiscale Simulation of Hydrologic and Biogeochemical Processes in the River-Groundwater Interaction Zone

NASA Astrophysics Data System (ADS)

Yang, X.; Scheibe, T. D.; Chen, X.; Hammond, G. E.; Song, X.

2015-12-01

The zone in which river water and groundwater mix plays an important role in natural ecosystems as it regulates the mixing of nutrients that control biogeochemical transformations. Subsurface heterogeneity leads to local hotspots of microbial activity that are important to system function yet difficult to resolve computationally. To address this challenge, we are testing a hybrid multiscale approach that couples models at two distinct scales, based on field research at the U. S. Department of Energy's Hanford Site. The region of interest is a 400 x 400 x 20 m macroscale domain that intersects the aquifer and the river and contains a contaminant plume. However, biogeochemical activity is high in a thin zone (mud layer, <1 m thick) immediately adjacent to the river. This microscale domain is highly heterogeneous and requires fine spatial resolution to adequately represent the effects of local mixing on reactions. It is not computationally feasible to resolve the full macroscale domain at the fine resolution needed in the mud layer, and the reaction network needed in the mud layer is much more complex than that needed in the rest of the macroscale domain. Hence, a hybrid multiscale approach is used to efficiently and accurately predict flow and reactive transport at both scales. In our simulations, models at both scales are simulated using the PFLOTRAN code. Multiple microscale simulations in dynamically defined sub-domains (fine resolution, complex reaction network) are executed and coupled with a macroscale simulation over the entire domain (coarse resolution, simpler reaction network). The objectives of the research include: 1) comparing accuracy and computing cost of the hybrid multiscale simulation with a single-scale simulation; 2) identifying hot spots of microbial activity; and 3) defining macroscopic quantities such as fluxes, residence times and effective reaction rates.

Multi-scale gyrokinetic simulation of Alcator C-Mod tokamak discharges

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

Howard, N. T., E-mail: nthoward@psfc.mit.edu; White, A. E.; Greenwald, M.

2014-03-15

Alcator C-Mod tokamak discharges have been studied with nonlinear gyrokinetic simulation simultaneously spanning both ion and electron spatiotemporal scales. These multi-scale simulations utilized the gyrokinetic model implemented by GYRO code [J. Candy and R. E. Waltz, J. Comput. Phys. 186, 545 (2003)] and the approximation of reduced electron mass (μ = (m{sub D}/m{sub e}){sup .5} = 20.0) to qualitatively study a pair of Alcator C-Mod discharges: a low-power discharge, previously demonstrated (using realistic mass, ion-scale simulation) to display an under-prediction of the electron heat flux and a high-power discharge displaying agreement with both ion and electron heat flux channels [N. T. Howard et al.,more » Nucl. Fusion 53, 123011 (2013)]. These multi-scale simulations demonstrate the importance of electron-scale turbulence in the core of conventional tokamak discharges and suggest it is a viable candidate for explaining the observed under-prediction of electron heat flux. In this paper, we investigate the coupling of turbulence at the ion (k{sub θ}ρ{sub s}∼O(1.0)) and electron (k{sub θ}ρ{sub e}∼O(1.0)) scales for experimental plasma conditions both exhibiting strong (high-power) and marginally stable (low-power) low-k (k{sub θ}ρ{sub s} < 1.0) turbulence. It is found that reduced mass simulation of the plasma exhibiting marginally stable low-k turbulence fails to provide even qualitative insight into the turbulence present in the realistic plasma conditions. In contrast, multi-scale simulation of the plasma condition exhibiting strong turbulence provides valuable insight into the coupling of the ion and electron scales.« less

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.

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

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.

A Computational Cluster for Multiscale Simulations of Ionic Liquids

DTIC Science & Technology

2008-09-16

AND SUBTITLE DURIP: A Computational Cluster for Multiscale Simulations of Ionic Liquids 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA955007-1-0512 5c...AVAILABILITY STATEMENT ZO\\5oc\\\\%1>^ 13. SUPPLEMENTARY NOTES 14. ABSTRACT The focus of this project was to acquire and use computer cluster nodes...by ANSI Std. Z39.18 Adobe Professional 7.0 Comprehensive Final Report: Gregory A. Voth, PI Contract/Grant Title: DURIP: A Computational Cluster for

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

DOE PAGES

Borovikov, Sergey; Heerikhuisen, Jacob; Pogorelov, Nikolai

2013-04-01

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

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.

Time irreversibility of financial time series based on higher moments and multiscale Kullback-Leibler divergence

NASA Astrophysics Data System (ADS)

Li, Jinyang; Shang, Pengjian

2018-07-01

Irreversibility is an important property of time series. In this paper, we propose the higher moments and multiscale Kullback-Leibler divergence to analyze time series irreversibility. The higher moments Kullback-Leibler divergence (HMKLD) can amplify irreversibility and make the irreversibility variation more obvious. Therefore, many time series whose irreversibility is hard to be found are also able to show the variations. We employ simulated data and financial stock data to test and verify this method, and find that HMKLD of stock data is growing in the form of fluctuations. As for multiscale Kullback-Leibler divergence (MKLD), it is very complex in the dynamic system, so that exploring the law of simulation and stock system is difficult. In conventional multiscale entropy method, the coarse-graining process is non-overlapping, however we apply a different coarse-graining process and obtain a surprising discovery. The result shows when the scales are 4 and 5, their entropy is nearly similar, which demonstrates MKLD is efficient to display characteristics of time series irreversibility.

Data fusion of multi-scale representations for structural damage detection

NASA Astrophysics Data System (ADS)

Guo, Tian; Xu, Zili

2018-01-01

Despite extensive researches into structural health monitoring (SHM) in the past decades, there are few methods that can detect multiple slight damage in noisy environments. Here, we introduce a new hybrid method that utilizes multi-scale space theory and data fusion approach for multiple damage detection in beams and plates. A cascade filtering approach provides multi-scale space for noisy mode shapes and filters the fluctuations caused by measurement noise. In multi-scale space, a series of amplification and data fusion algorithms are utilized to search the damage features across all possible scales. We verify the effectiveness of the method by numerical simulation using damaged beams and plates with various types of boundary conditions. Monte Carlo simulations are conducted to illustrate the effectiveness and noise immunity of the proposed method. The applicability is further validated via laboratory cases studies focusing on different damage scenarios. Both results demonstrate that the proposed method has a superior noise tolerant ability, as well as damage sensitivity, without knowing material properties or boundary conditions.

A numerical homogenization method for heterogeneous, anisotropic elastic media based on multiscale theory

DOE PAGES

Gao, Kai; Chung, Eric T.; Gibson, Richard L.; ...

2015-06-05

The development of reliable methods for upscaling fine scale models of elastic media has long been an important topic for rock physics and applied seismology. Several effective medium theories have been developed to provide elastic parameters for materials such as finely layered media or randomly oriented or aligned fractures. In such cases, the analytic solutions for upscaled properties can be used for accurate prediction of wave propagation. However, such theories cannot be applied directly to homogenize elastic media with more complex, arbitrary spatial heterogeneity. We therefore propose a numerical homogenization algorithm based on multiscale finite element methods for simulating elasticmore » wave propagation in heterogeneous, anisotropic elastic media. Specifically, our method used multiscale basis functions obtained from a local linear elasticity problem with appropriately defined boundary conditions. Homogenized, effective medium parameters were then computed using these basis functions, and the approach applied a numerical discretization that is similar to the rotated staggered-grid finite difference scheme. Comparisons of the results from our method and from conventional, analytical approaches for finely layered media showed that the homogenization reliably estimated elastic parameters for this simple geometry. Additional tests examined anisotropic models with arbitrary spatial heterogeneity where the average size of the heterogeneities ranged from several centimeters to several meters, and the ratio between the dominant wavelength and the average size of the arbitrary heterogeneities ranged from 10 to 100. Comparisons to finite-difference simulations proved that the numerical homogenization was equally accurate for these complex cases.« less

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

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 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

In silico analysis of the anti-hypertensive drugs impact on myocardial oxygen balance.

PubMed

Guala, A; Leone, D; Milan, A; Ridolfi, L

2017-06-01

Hypertension is a very common pathology, and its clinical treatment largely relies on different drugs. Some of these drugs exhibit specific protective functions in addition to those resulting from blood pressure reduction. In this work, we study the impact of commonly used anti-hypertensive drugs (RAAS, [Formula: see text] and calcium channel blockers) on myocardial oxygen supply-consumption balance, which plays a crucial role in type 2 myocardial infarction. To this aim, 42 wash-out hypertensive patients were selected, a number of measured data were used to set a validated multi-scale cardiovascular model to subject-specific conditions, and the administration of different drugs was suitably simulated. Our results ascribe the well-known major cardioprotective efficiency of [Formula: see text] blockers compared to other drugs to a positive change of myocardial oxygen balance due to the concomitant: (1) reduction in aortic systolic, diastolic and pulse pressures, (2) decrease in left ventricular work, diastolic cavity pressure and oxygen consumption, (3) increase in coronary flow and (4) ejection efficiency improvement. RAAS blockers share several positive outcomes with [Formula: see text] blockers, although to a reduced extent. In contrast, calcium channel blockers seem to induce some potentially negative effects on the myocardial oxygen balance.

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...

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...

Using Multi-scale Dynamic Rupture Models to Improve Ground Motion Estimates: ALCF-2 Early Science Program Technical Report

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

Ely, Geoffrey P.

2013-10-31

This project uses dynamic rupture simulations to investigate high-frequency seismic energy generation. The relevant phenomena (frictional breakdown, shear heating, effective normal-stress fluctuations, material damage, etc.) controlling rupture are strongly interacting and span many orders of magnitude in spatial scale, requiring highresolution simulations that couple disparate physical processes (e.g., elastodynamics, thermal weakening, pore-fluid transport, and heat conduction). Compounding the computational challenge, we know that natural faults are not planar, but instead have roughness that can be approximated by power laws potentially leading to large, multiscale fluctuations in normal stress. The capacity to perform 3D rupture simulations that couple these processes willmore » provide guidance for constructing appropriate source models for high-frequency ground motion simulations. The improved rupture models from our multi-scale dynamic rupture simulations will be used to conduct physicsbased (3D waveform modeling-based) probabilistic seismic hazard analysis (PSHA) for California. These calculation will provide numerous important seismic hazard results, including a state-wide extended earthquake rupture forecast with rupture variations for all significant events, a synthetic seismogram catalog for thousands of scenario events and more than 5000 physics-based seismic hazard curves for California.« less

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

Asymptotic-Preserving methods and multiscale models for plasma physics

NASA Astrophysics Data System (ADS)

Degond, Pierre; Deluzet, Fabrice

2017-05-01

The purpose of the present paper is to provide an overview of Asymptotic-Preserving methods for multiscale plasma simulations by addressing three singular perturbation problems. First, the quasi-neutral limit of fluid and kinetic models is investigated in the framework of non-magnetized as well as magnetized plasmas. Second, the drift limit for fluid descriptions of thermal plasmas under large magnetic fields is addressed. Finally efficient numerical resolutions of anisotropic elliptic or diffusion equations arising in magnetized plasma simulation are reviewed.

Active learning of constitutive relation from mesoscopic dynamics for macroscopic modeling of non-Newtonian flows

NASA Astrophysics Data System (ADS)

Zhao, Lifei; Li, Zhen; Caswell, Bruce; Ouyang, Jie; Karniadakis, George Em

2018-06-01

We simulate complex fluids by means of an on-the-fly coupling of the bulk rheology to the underlying microstructure dynamics. In particular, a continuum model of polymeric fluids is constructed without a pre-specified constitutive relation, but instead it is actively learned from mesoscopic simulations where the dynamics of polymer chains is explicitly computed. To couple the bulk rheology of polymeric fluids and the microscale dynamics of polymer chains, the continuum approach (based on the finite volume method) provides the transient flow field as inputs for the (mesoscopic) dissipative particle dynamics (DPD), and in turn DPD returns an effective constitutive relation to close the continuum equations. In this multiscale modeling procedure, we employ an active learning strategy based on Gaussian process regression (GPR) to minimize the number of expensive DPD simulations, where adaptively selected DPD simulations are performed only as necessary. Numerical experiments are carried out for flow past a circular cylinder of a non-Newtonian fluid, modeled at the mesoscopic level by bead-spring chains. The results show that only five DPD simulations are required to achieve an effective closure of the continuum equations at Reynolds number Re = 10. Furthermore, when Re is increased to 100, only one additional DPD simulation is required for constructing an extended GPR-informed model closure. Compared to traditional message-passing multiscale approaches, applying an active learning scheme to multiscale modeling of non-Newtonian fluids can significantly increase the computational efficiency. Although the method demonstrated here obtains only a local viscosity from the polymer dynamics, it can be extended to other multiscale models of complex fluids whose macro-rheology is unknown.

A Machine Learning Method for the Prediction of Receptor Activation in the Simulation of Synapses

PubMed Central

Montes, Jesus; Gomez, Elena; Merchán-Pérez, Angel; DeFelipe, Javier; Peña, Jose-Maria

2013-01-01

Chemical synaptic transmission involves the release of a neurotransmitter that diffuses in the extracellular space and interacts with specific receptors located on the postsynaptic membrane. Computer simulation approaches provide fundamental tools for exploring various aspects of the synaptic transmission under different conditions. In particular, Monte Carlo methods can track the stochastic movements of neurotransmitter molecules and their interactions with other discrete molecules, the receptors. However, these methods are computationally expensive, even when used with simplified models, preventing their use in large-scale and multi-scale simulations of complex neuronal systems that may involve large numbers of synaptic connections. We have developed a machine-learning based method that can accurately predict relevant aspects of the behavior of synapses, such as the percentage of open synaptic receptors as a function of time since the release of the neurotransmitter, with considerably lower computational cost compared with the conventional Monte Carlo alternative. The method is designed to learn patterns and general principles from a corpus of previously generated Monte Carlo simulations of synapses covering a wide range of structural and functional characteristics. These patterns are later used as a predictive model of the behavior of synapses under different conditions without the need for additional computationally expensive Monte Carlo simulations. This is performed in five stages: data sampling, fold creation, machine learning, validation and curve fitting. The resulting procedure is accurate, automatic, and it is general enough to predict synapse behavior under experimental conditions that are different to the ones it has been trained on. Since our method efficiently reproduces the results that can be obtained with Monte Carlo simulations at a considerably lower computational cost, it is suitable for the simulation of high numbers of synapses and it is therefore an excellent tool for multi-scale simulations. PMID:23894367

Full-scale fatigue tests of CX-100 wind turbine blades. Part II: analysis

NASA Astrophysics Data System (ADS)

Taylor, Stuart G.; Jeong, Hyomi; Jang, Jae Kyeong; Park, Gyuhae; Farinholt, Kevin M.; Todd, Michael D.; Ammerman, Curtt M.

2012-04-01

This paper presents the initial analysis results of several structural health monitoring (SHM) methods applied to two 9- meter CX-100 wind turbine blades subjected to fatigue loading at the National Renewable Energy Laboratory's (NREL) National Wind Technology Center (NWTC). The first blade was a pristine blade, manufactured to standard CX-100 design specifications. The second blade was manufactured for the University of Massachusetts, Lowell (UMass), with intentional simulated defects within the fabric layup. Each blade was instrumented with a variety of sensors on its surface. The blades were subject to harmonic excitation at their first natural frequency with steadily increasing loading until ultimately reaching failure. Data from the sensors were collected between and during fatigue loading sessions. The data were measured at multi-scale frequency ranges using a variety of data acquisition equipment, including off-the-shelf systems and prototype data acquisition hardware. The data were analyzed to identify fatigue damage initiation and to assess damage progression. Modal response, diffuse wave-field transfer functions in time and frequency domains, and wave propagation methods were applied to assess the condition of the turbine blade. The analysis methods implemented were evaluated in conjunction with hardware-specific performance for their efficacy in enabling the assessment of damage progression in the blade. The results of this assessment will inform the selection of specific data to be collected and analysis methods to be implemented for a CX-100 flight test to be conducted in collaboration with Sandia National Laboratory at the U.S. Department of Agriculture's (USDA) Conservation and Production Research Laboratory (CPRL) in Bushland, Texas.

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

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...

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...

Patient-specific biomechanical model of hypoplastic left heart to predict post-operative cardio-circulatory behaviour.

PubMed

Cutrì, Elena; Meoli, Alessio; Dubini, Gabriele; Migliavacca, Francesco; Hsia, Tain-Yen; Pennati, Giancarlo

2017-09-01

Hypoplastic left heart syndrome is a complex congenital heart disease characterised by the underdevelopment of the left ventricle normally treated with a three-stage surgical repair. In this study, a multiscale closed-loop cardio-circulatory model is created to reproduce the pre-operative condition of a patient suffering from such pathology and virtual surgery is performed. Firstly, cardio-circulatory parameters are estimated using a fully closed-loop cardio-circulatory lumped parameter model. Secondly, a 3D standalone FEA model is build up to obtain active and passive ventricular characteristics and unloaded reference state. Lastly, the 3D model of the single ventricle is coupled to the lumped parameter model of the circulation obtaining a multiscale closed-loop pre-operative model. Lacking any information on the fibre orientation, two cases were simulated: (i) fibre distributed as in the physiological right ventricle and (ii) fibre as in the physiological left ventricle. Once the pre-operative condition is satisfactorily simulated for the two cases, virtual surgery is performed. The post-operative results in the two cases highlighted similar hemodynamic behaviour but different local mechanics. This finding suggests that the knowledge of the patient-specific fibre arrangement is important to correctly estimate the single ventricle's working condition and consequently can be valuable to support clinical decision. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

A Computational Systems Biology Software Platform for Multiscale Modeling and Simulation: Integrating Whole-Body Physiology, Disease Biology, and Molecular Reaction Networks

PubMed Central

Eissing, Thomas; Kuepfer, Lars; Becker, Corina; Block, Michael; Coboeken, Katrin; Gaub, Thomas; Goerlitz, Linus; Jaeger, Juergen; Loosen, Roland; Ludewig, Bernd; Meyer, Michaela; Niederalt, Christoph; Sevestre, Michael; Siegmund, Hans-Ulrich; Solodenko, Juri; Thelen, Kirstin; Telle, Ulrich; Weiss, Wolfgang; Wendl, Thomas; Willmann, Stefan; Lippert, Joerg

2011-01-01

Today, in silico studies and trial simulations already complement experimental approaches in pharmaceutical R&D and have become indispensable tools for decision making and communication with regulatory agencies. While biology is multiscale by nature, project work, and software tools usually focus on isolated aspects of drug action, such as pharmacokinetics at the organism scale or pharmacodynamic interaction on the molecular level. We present a modeling and simulation software platform consisting of PK-Sim® and MoBi® capable of building and simulating models that integrate across biological scales. A prototypical multiscale model for the progression of a pancreatic tumor and its response to pharmacotherapy is constructed and virtual patients are treated with a prodrug activated by hepatic metabolization. Tumor growth is driven by signal transduction leading to cell cycle transition and proliferation. Free tumor concentrations of the active metabolite inhibit Raf kinase in the signaling cascade and thereby cell cycle progression. In a virtual clinical study, the individual therapeutic outcome of the chemotherapeutic intervention is simulated for a large population with heterogeneous genomic background. Thereby, the platform allows efficient model building and integration of biological knowledge and prior data from all biological scales. Experimental in vitro model systems can be linked with observations in animal experiments and clinical trials. The interplay between patients, diseases, and drugs and topics with high clinical relevance such as the role of pharmacogenomics, drug–drug, or drug–metabolite interactions can be addressed using this mechanistic, insight driven multiscale modeling approach. PMID:21483730

Simulation model of a gear synchronisation unit for application in a real-time HiL environment

NASA Astrophysics Data System (ADS)

Kirchner, Markus; Eberhard, Peter

2017-05-01

Gear shifting simulations using the multibody system approach and the finite-element method are standard in the development of transmissions. However, the corresponding models are typically large due to the complex geometries and numerous contacts, which causes long calculation times. The present work sets itself apart from these detailed shifting simulations by proposing a much simpler but powerful synchronisation model which can be computed in real-time while it is still more realistic than a pure rigid multibody model. Therefore, the model is even used as part of a Hardware-in-the-Loop (HiL) test rig. The proposed real-time capable synchronization model combines the rigid multibody system approach with a multiscale simulation approach. The multibody system approach is suitable for the description of the large motions. The multiscale simulation approach is using also the finite-element method suitable for the analysis of the contact processes. An efficient contact search for the claws of a car transmission synchronisation unit is described in detail which shortens the required calculation time of the model considerably. To further shorten the calculation time, the use of a complex pre-synchronisation model with a nonlinear contour is presented. The model has to provide realistic results with the time-step size of the HiL test rig. To reach this specification, a particularly adapted multirate method for the synchronisation model is shown. Measured results of test rigs of the real-time capable synchronisation model are verified on plausibility. The simulation model is then also used in the HiL test rig for a transmission control unit.

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

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

NASA Astrophysics Data System (ADS)

Lockerby, Duncan; Borg, Matthew; Reese, Jason

2012-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Multiscale modeling for SiO2 atomic layer deposition for high-aspect-ratio hole patterns

NASA Astrophysics Data System (ADS)

Miyano, Yumiko; Narasaki, Ryota; Ichikawa, Takashi; Fukumoto, Atsushi; Aiso, Fumiki; Tamaoki, Naoki

2018-06-01

A multiscale simulation model is developed for optimizing the parameters of SiO2 plasma-enhanced atomic layer deposition of high-aspect-ratio hole patterns in three-dimensional (3D) stacked memory. This model takes into account the diffusion of a precursor in a reactor, that in holes, and the adsorption onto the wafer. It is found that the change in the aperture ratio of the holes on the wafer affects the concentration of the precursor near the top of the wafer surface, hence the deposition profile in the hole. The simulation results reproduced well the experimental results of the deposition thickness for the various hole aperture ratios. By this multiscale simulation, we can predict the deposition profile in a high-aspect-ratio hole pattern in 3D stacked memory. The atomic layer deposition parameters for conformal deposition such as precursor feeding time and partial pressure of precursor for wafers with various hole aperture ratios can be estimated.

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.

Blood Flow: Multi-scale Modeling and Visualization (July 2011)

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

None

2011-01-01

Multi-scale modeling of arterial blood flow can shed light on the interaction between events happening at micro- and meso-scales (i.e., adhesion of red blood cells to the arterial wall, clot formation) and at macro-scales (i.e., change in flow patterns due to the clot). Coupled numerical simulations of such multi-scale flow require state-of-the-art computers and algorithms, along with techniques for multi-scale visualizations. This animation presents early results of two studies used in the development of a multi-scale visualization methodology. The fisrt illustrates a flow of healthy (red) and diseased (blue) blood cells with a Dissipative Particle Dynamics (DPD) method. Each bloodmore » cell is represented by a mesh, small spheres show a sub-set of particles representing the blood plasma, while instantaneous streamlines and slices represent the ensemble average velocity. In the second we investigate the process of thrombus (blood clot) formation, which may be responsible for the rupture of aneurysms, by concentrating on the platelet blood cells, observing as they aggregate on the wall of an aneruysm. Simulation was performed on Kraken at the National Institute for Computational Sciences. Visualization was produced using resources of the Argonne Leadership Computing Facility at Argonne National Laboratory.« less

A 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

Seafloor identification in sonar imagery via simulations of Helmholtz equations and discrete optimization

NASA Astrophysics Data System (ADS)

Engquist, Björn; Frederick, Christina; Huynh, Quyen; Zhou, Haomin

2017-06-01

We present a multiscale approach for identifying features in ocean beds by solving inverse problems in high frequency seafloor acoustics. The setting is based on Sound Navigation And Ranging (SONAR) imaging used in scientific, commercial, and military applications. The forward model incorporates multiscale simulations, by coupling Helmholtz equations and geometrical optics for a wide range of spatial scales in the seafloor geometry. This allows for detailed recovery of seafloor parameters including material type. Simulated backscattered data is generated using numerical microlocal analysis techniques. In order to lower the computational cost of the large-scale simulations in the inversion process, we take advantage of a pre-computed library of representative acoustic responses from various seafloor parameterizations.

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<...

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.

Multiscale Reactive Molecular Dynamics

DTIC Science & Technology

2012-08-15

biology cannot be described without considering electronic and nuclear-level dynamics and their coupling to slower, cooperative motions of the system ...coupling to slower, cooperative motions of the system . These inherently multiscale problems require computationally efficient and accurate methods to...condensed phase systems with computational efficiency orders of magnitudes greater than currently possible with ab initio simulation methods, thus

Free-Energy Landscape of Protein-Ligand Interactions Coupled with Protein Structural Changes.

PubMed

Moritsugu, Kei; Terada, Tohru; Kidera, Akinori

2017-02-02

Protein-ligand interactions are frequently coupled with protein structural changes. Focusing on the coupling, we present the free-energy surface (FES) of the ligand-binding process for glutamine-binding protein (GlnBP) and its ligand, glutamine, in which glutamine binding accompanies large-scale domain closure. All-atom simulations were performed in explicit solvents by multiscale enhanced sampling (MSES), which adopts a multicopy and multiscale scheme to achieve enhanced sampling of systems with a large number of degrees of freedom. The structural ensemble derived from the MSES simulation yielded the FES of the coupling, described in terms of both the ligand's and protein's degrees of freedom at atomic resolution, and revealed the tight coupling between the two degrees of freedom. The derived FES led to the determination of definite structural states, which suggested the dominant pathways of glutamine binding to GlnBP: first, glutamine migrates via diffusion to form a dominant encounter complex with Arg75 on the large domain of GlnBP, through strong polar interactions. Subsequently, the closing motion of GlnBP occurs to form ligand interactions with the small domain, finally completing the native-specific complex structure. The formation of hydrogen bonds between glutamine and the small domain is considered to be a rate-limiting step, inducing desolvation of the protein-ligand interface to form the specific native complex. The key interactions to attain high specificity for glutamine, the "door keeper" existing between the two domains (Asp10-Lys115) and the "hydrophobic sandwich" formed between the ligand glutamine and Phe13/Phe50, have been successfully mapped on the pathway derived from the FES.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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.

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.

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.

A multiscale quantum mechanics/electromagnetics method for device simulations.

PubMed

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

2015-04-07

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

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

Hyperlipidemia affects multiscale structure and strength of murine femur.

PubMed

Ascenzi, Maria-Grazia; Lutz, Andre; Du, Xia; Klimecky, Laureen; Kawas, Neal; Hourany, Talia; Jahng, Joelle; Chin, Jesse; Tintut, Yin; Nackenhors, Udo; Keyak, Joyce

2014-07-18

To improve bone strength prediction beyond limitations of assessment founded solely on the bone mineral component, we investigated the effect of hyperlipidemia, present in more than 40% of osteoporotic patients, on multiscale structure of murine bone. Our overarching purpose is to estimate bone strength accurately, to facilitate mitigating fracture morbidity and mortality in patients. Because (i) orientation of collagen type I affects, independently of degree of mineralization, cortical bone׳s micro-structural strength; and, (ii) hyperlipidemia affects collagen orientation and μCT volumetric tissue mineral density (vTMD) in murine cortical bone, we have constructed the first multiscale finite element (mFE), mouse-specific femoral model to study the effect of collagen orientation and vTMD on strength in Ldlr(-/-), a mouse model of hyperlipidemia, and its control wild type, on either high fat diet or normal diet. Each µCT scan-based mFE model included either element-specific elastic orthotropic properties calculated from collagen orientation and vTMD (collagen-density model) by experimentally validated formulation, or usual element-specific elastic isotropic material properties dependent on vTMD-only (density-only model). We found that collagen orientation, assessed by circularly polarized light and confocal microscopies, and vTMD, differed among groups and that microindentation results strongly correlate with elastic modulus of collagen-density models (r(2)=0.85, p=10(-5)). Collagen-density models yielded (1) larger strains, and therefore lower strength, in simulations of 3-point bending and physiological loading; and (2) higher correlation between mFE-predicted strength and 3-point bending experimental strength, than density-only models. This novel method supports ongoing translational research to achieve the as yet elusive goal of accurate bone strength prediction. Copyright © 2014 Elsevier Ltd. All rights reserved.

Design of a framework for modeling, integration and simulation of physiological models.

PubMed

Erson, E Zeynep; Cavuşoğlu, M Cenk

2012-09-01

Multiscale modeling and integration of physiological models carry challenges due to the complex nature of physiological processes. High coupling within and among scales present a significant challenge in constructing and integrating multiscale physiological models. In order to deal with such challenges in a systematic way, there is a significant need for an information technology framework together with related analytical and computational tools that will facilitate integration of models and simulations of complex biological systems. Physiological Model Simulation, Integration and Modeling Framework (Phy-SIM) is an information technology framework providing the tools to facilitate development, integration and simulation of integrated models of human physiology. Phy-SIM brings software level solutions to the challenges raised by the complex nature of physiological systems. The aim of Phy-SIM, and this paper is to lay some foundation with the new approaches such as information flow and modular representation of the physiological models. The ultimate goal is to enhance the development of both the models and the integration approaches of multiscale physiological processes and thus this paper focuses on the design approaches that would achieve such a goal. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

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

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

PubMed

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

2015-12-01

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

Multiscale 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.

Nonlinear intrinsic variables and state reconstruction in multiscale simulations

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

Dsilva, Carmeline J., E-mail: cdsilva@princeton.edu; Talmon, Ronen, E-mail: ronen.talmon@yale.edu; Coifman, Ronald R., E-mail: coifman@math.yale.edu

2013-11-14

Finding informative low-dimensional descriptions of high-dimensional simulation data (like the ones arising in molecular dynamics or kinetic Monte Carlo simulations of physical and chemical processes) is crucial to understanding physical phenomena, and can also dramatically assist in accelerating the simulations themselves. In this paper, we discuss and illustrate the use of nonlinear intrinsic variables (NIV) in the mining of high-dimensional multiscale simulation data. In particular, we focus on the way NIV allows us to functionally merge different simulation ensembles, and different partial observations of these ensembles, as well as to infer variables not explicitly measured. The approach relies on certainmore » simple features of the underlying process variability to filter out measurement noise and systematically recover a unique reference coordinate frame. We illustrate the approach through two distinct sets of atomistic simulations: a stochastic simulation of an enzyme reaction network exhibiting both fast and slow time scales, and a molecular dynamics simulation of alanine dipeptide in explicit water.« less

Nonlinear intrinsic variables and state reconstruction in multiscale simulations

NASA Astrophysics Data System (ADS)

Dsilva, Carmeline J.; Talmon, Ronen; Rabin, Neta; Coifman, Ronald R.; Kevrekidis, Ioannis G.

2013-11-01

Finding informative low-dimensional descriptions of high-dimensional simulation data (like the ones arising in molecular dynamics or kinetic Monte Carlo simulations of physical and chemical processes) is crucial to understanding physical phenomena, and can also dramatically assist in accelerating the simulations themselves. In this paper, we discuss and illustrate the use of nonlinear intrinsic variables (NIV) in the mining of high-dimensional multiscale simulation data. In particular, we focus on the way NIV allows us to functionally merge different simulation ensembles, and different partial observations of these ensembles, as well as to infer variables not explicitly measured. The approach relies on certain simple features of the underlying process variability to filter out measurement noise and systematically recover a unique reference coordinate frame. We illustrate the approach through two distinct sets of atomistic simulations: a stochastic simulation of an enzyme reaction network exhibiting both fast and slow time scales, and a molecular dynamics simulation of alanine dipeptide in explicit water.

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.;

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 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 (...

Multiscale Modeling of Grain-Boundary Fracture: Cohesive Zone Models Parameterized From Atomistic Simulations

NASA Technical Reports Server (NTRS)

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

2006-01-01

A multiscale modeling strategy is developed to study grain boundary fracture in polycrystalline aluminum. Atomistic simulation is used to model fundamental nanoscale deformation and fracture mechanisms and to develop a constitutive relationship for separation along a grain boundary interface. The nanoscale constitutive relationship is then parameterized within a cohesive zone model to represent variations in grain boundary properties. These variations arise from the presence of vacancies, intersticies, and other defects in addition to deviations in grain boundary angle from the baseline configuration considered in the molecular dynamics simulation. The parameterized cohesive zone models are then used to model grain boundaries within finite element analyses of aluminum polycrystals.

Dislocation dynamics: simulation of plastic flow of bcc metals

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

Lassila, D H

This is the final report for the LDRD strategic initiative entitled ''Dislocation Dynamic: Simulation of Plastic Flow of bcc Metals'' (tracking code: 00-SI-011). This report is comprised of 6 individual sections. The first is an executive summary of the project and describes the overall project goal, which is to establish an experimentally validated 3D dislocation dynamics simulation. This first section also gives some information of LLNL's multi-scale modeling efforts associated with the plasticity of bcc metals, and the role of this LDRD project in the multiscale modeling program. The last five sections of this report are journal articles that weremore » produced during the course of the FY-2000 efforts.« less

ESCOMPTE 2001: multi-scale modelling and experimental validation

NASA Astrophysics Data System (ADS)

Cousin, F.; Tulet, P.; Rosset, R.

2003-04-01

ESCOMPTE is a European pollution field experiment located in the Marseille / Fos-Berre area in the summer 2001.This Mediterranean area, with frequent pollution peaks, is characterized by a complex topography subject to sea breeze regimes, together with intense localized urban, industrial and biogenic sources. Four POI have been selected, the most significant being POI2a / b, a 6-day pollution episode extensively documented for dynamics, radiation, gas phase and aerosols, with surface measurements (including measurements at sea in the gulf of Genoa, on board instrumented ferries between Marseille and Corsica), 7 aircrafts, lidar, radar and constant-level flight balloon soundings. The two-way mesoscale model MESO-NH-C (MNH-C), with horizontal resolutions of 9 and 3 km and high vertical resolution (up to 40 levels in the first 2 km), embedded in the global CTM Mocage, has been run for all POIs, with a focus here on POI2b (June 24-27,2001), a typical high pollution episode. The multi-scale modelling system MNH-C+MOCAGE allows to simulate local and regional pollution issued from emission sources in the Marseille / Fos-Berre area as well as from remote sources (e.g. the Po Valley and / or western Mediterranean sources) and their associated transboundary pollution fluxes. Detailed dynamical, chemical and aerosol (both modal and sectional spectra with organics and inorganics) simulations generally favorably compare to surface(continental and on ships), lidar and along-flight aircraft measurements.

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

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.

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.

Simulated shift work in rats perturbs multiscale regulation of locomotor activity

PubMed Central

Hsieh, Wan-Hsin; Escobar, Carolina; Yugay, Tatiana; Lo, Men-Tzung; Pittman-Polletta, Benjamin; Salgado-Delgado, Roberto; Scheer, Frank A. J. L.; Shea, Steven A.; Buijs, Ruud M.; Hu, Kun

2014-01-01

Motor activity possesses a multiscale regulation that is characterized by fractal activity fluctuations with similar structure across a wide range of timescales spanning minutes to hours. Fractal activity patterns are disturbed in animals after ablating the master circadian pacemaker (suprachiasmatic nucleus, SCN) and in humans with SCN dysfunction as occurs with aging and in dementia, suggesting the crucial role of the circadian system in the multiscale activity regulation. We hypothesized that the normal synchronization between behavioural cycles and the SCN-generated circadian rhythms is required for multiscale activity regulation. To test the hypothesis, we studied activity fluctuations of rats in a simulated shift work protocol that was designed to force animals to be active during the habitual resting phase of the circadian/daily cycle. We found that these animals had gradually decreased mean activity level and reduced 24-h activity rhythm amplitude, indicating disturbed circadian and behavioural cycles. Moreover, these animals had disrupted fractal activity patterns as characterized by more random activity fluctuations at multiple timescales from 4 to 12 h. Intriguingly, these activity disturbances exacerbated when the shift work schedule lasted longer and persisted even in the normal days (without forced activity) following the shift work. The disrupted circadian and fractal patterns resemble those of SCN-lesioned animals and of human patients with dementia, suggesting a detrimental impact of shift work on multiscale activity regulation. PMID:24829282

Simulation of atmospheric oxidation capacity in Houston, Texas

EPA Science Inventory

Air quality model simulations are performed and evaluated for Houston using the Community Multiscale Air Quality (CMAQ) model. The simulations use two different emissions estimates: the EPA 2005 National Emissions Inventory (NEI) and the Texas Commission on Environmental Quality ...

Recent Advances in Transferable Coarse-Grained Modeling of Proteins

PubMed Central

Kar, Parimal; Feig, Michael

2017-01-01

Computer simulations are indispensable tools for studying the structure and dynamics of biological macromolecules. Biochemical processes occur on different scales of length and time. Atomistic simulations cannot cover the relevant spatiotemporal scales at which the cellular processes occur. To address this challenge, coarse-grained (CG) modeling of the biological systems are employed. Over the last few years, many CG models for proteins continue to be developed. However, many of them are not transferable with respect to different systems and different environments. In this review, we discuss those CG protein models that are transferable and that retain chemical specificity. We restrict ourselves to CG models of soluble proteins only. We also briefly review recent progress made in the multi-scale hybrid all-atom/coarse-grained simulations of proteins. PMID:25443957

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

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.

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.

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.

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

Enabling Predictive Simulation and UQ of Complex Multiphysics PDE Systems by the Development of Goal-Oriented Variational Sensitivity Analysis and a-Posteriori Error Estimation Methods

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

Estep, Donald

2015-11-30

This project addressed the challenge of predictive computational analysis of strongly coupled, highly nonlinear multiphysics systems characterized by multiple physical phenomena that span a large range of length- and time-scales. Specifically, the project was focused on computational estimation of numerical error and sensitivity analysis of computational solutions with respect to variations in parameters and data. In addition, the project investigated the use of accurate computational estimates to guide efficient adaptive discretization. The project developed, analyzed and evaluated new variational adjoint-based techniques for integration, model, and data error estimation/control and sensitivity analysis, in evolutionary multiphysics multiscale simulations.

RACER a Coarse-Grained RNA Model for Capturing Folding Free Energy in Molecular Dynamics Simulations

NASA Astrophysics Data System (ADS)

Cheng, Sara; Bell, David; Ren, Pengyu

RACER is a coarse-grained RNA model that can be used in molecular dynamics simulations to predict native structures and sequence-specific variation of free energy of various RNA structures. RACER is capable of accurate prediction of native structures of duplexes and hairpins (average RMSD of 4.15 angstroms), and RACER can capture sequence-specific variation of free energy in excellent agreement with experimentally measured stabilities (r-squared =0.98). The RACER model implements a new effective non-bonded potential and re-parameterization of hydrogen bond and Debye-Huckel potentials. Insights from the RACER model include the importance of treating pairing and stacking interactions separately in order to distinguish folded an unfolded states and identification of hydrogen-bonding, base stacking, and electrostatic interactions as essential driving forces for RNA folding. Future applications of the RACER model include predicting free energy landscapes of more complex RNA structures and use of RACER for multiscale simulations.

A multi-scale model for geared transmission aero-thermodynamics

NASA Astrophysics Data System (ADS)

McIntyre, Sean M.

A multi-scale, multi-physics computational tool for the simulation of high-per- formance gearbox aero-thermodynamics was developed and applied to equilibrium and pathological loss-of-lubrication performance simulation. The physical processes at play in these systems include multiphase compressible ow of the air and lubricant within the gearbox, meshing kinematics and tribology, as well as heat transfer by conduction, and free and forced convection. These physics are coupled across their representative space and time scales in the computational framework developed in this dissertation. These scales span eight orders of magnitude, from the thermal response of the full gearbox O(100 m; 10 2 s), through effects at the tooth passage time scale O(10-2 m; 10-4 s), down to tribological effects on the meshing gear teeth O(10-6 m; 10-6 s). Direct numerical simulation of these coupled physics and scales is intractable. Accordingly, a scale-segregated simulation strategy was developed by partitioning and treating the contributing physical mechanisms as sub-problems, each with associated space and time scales, and appropriate coupling mechanisms. These are: (1) the long time scale thermal response of the system, (2) the multiphase (air, droplets, and film) aerodynamic flow and convective heat transfer within the gearbox, (3) the high-frequency, time-periodic thermal effects of gear tooth heating while in mesh and its subsequent cooling through the rest of rotation, (4) meshing effects including tribology and contact mechanics. The overarching goal of this dissertation was to develop software and analysis procedures for gearbox loss-of-lubrication performance. To accommodate these four physical effects and their coupling, each is treated in the CFD code as a sub problem. These physics modules are coupled algorithmically. Specifically, the high- frequency conduction analysis derives its local heat transfer coefficient and near-wall air temperature boundary conditions from a quasi-steady cyclic-symmetric simulation of the internal flow. This high-frequency conduction solution is coupled directly with a model for the meshing friction, developed by a collaborator, which was adapted for use in a finite-volume CFD code. The local surface heat flux on solid surfaces is calculated by time-averaging the heat flux in the high-frequency analysis. This serves as a fixed-flux boundary condition in the long time scale conduction module. The temperature distribution from this long time scale heat transfer calculation serves as a boundary condition for the internal convection simulation, and as the initial condition for the high-frequency heat transfer module. Using this multi-scale model, simulations were performed for equilibrium and loss-of-lubrication operation of the NASA Glenn Research Center test stand. Results were compared with experimental measurements. In addition to the multi-scale model itself, several other specific contributions were made. Eulerian models for droplets and wall-films were developed and im- plemented in the CFD code. A novel approach to retaining liquid film on the solid surfaces, and strategies for its mass exchange with droplets, were developed and verified. Models for interfacial transfer between droplets and wall-film were implemented, and include the effects of droplet deposition, splashing, bouncing, as well as film breakup. These models were validated against airfoil data. To mitigate the observed slow convergence of CFD simulations of the enclosed aerodynamic flows within gearboxes, Fourier stability analysis was applied to the SIMPLE-C fractional-step algorithm. From this, recommendations to accelerate the convergence rate through enhanced pressure-velocity coupling were made. These were shown to be effective. A fast-running finite-volume reduced-order-model of the gearbox aero-thermo- dynamics was developed, and coupled with the tribology model to investigate the sensitivity of loss-of-lubrication predictions to various model and physical param- eters. This sensitivity study was instrumental in guiding efforts toward improving the accuracy of the multi-scale model without undue increase in computational cost. In addition, the reduced-order model is now used extensively by a collaborator in tribology model development and testing. Experimental measurements of high-speed gear windage in partially and fully- shrouded configurations were performed to supplement the paucity of available validation data. This measurement program provided measurements of windage loss for a gear of design-relevant size and operating speed, as well as guidance for increasing the accuracy of future measurements.

An integrated approach to patient-specific predictive modeling for single ventricle heart palliation.

PubMed

Corsini, Chiara; Baker, Catriona; Kung, Ethan; Schievano, Silvia; Arbia, Gregory; Baretta, Alessia; Biglino, Giovanni; Migliavacca, Francesco; Dubini, Gabriele; Pennati, Giancarlo; Marsden, Alison; Vignon-Clementel, Irene; Taylor, Andrew; Hsia, Tain-Yen; Dorfman, Adam

2014-01-01

In patients with congenital heart disease and a single ventricle (SV), ventricular support of the circulation is inadequate, and staged palliative surgery (usually 3 stages) is needed for treatment. In the various palliative surgical stages individual differences in the circulation are important and patient-specific surgical planning is ideal. In this study, an integrated approach between clinicians and engineers has been developed, based on patient-specific multi-scale models, and is here applied to predict stage 2 surgical outcomes. This approach involves four distinct steps: (1) collection of pre-operative clinical data from a patient presenting for SV palliation, (2) construction of the pre-operative model, (3) creation of feasible virtual surgical options which couple a three-dimensional model of the surgical anatomy with a lumped parameter model (LPM) of the remainder of the circulation and (4) performance of post-operative simulations to aid clinical decision making. The pre-operative model is described, agreeing well with clinical flow tracings and mean pressures. Two surgical options (bi-directional Glenn and hemi-Fontan operations) are virtually performed and coupled to the pre-operative LPM, with the hemodynamics of both options reported. Results are validated against postoperative clinical data. Ultimately, this work represents the first patient-specific predictive modeling of stage 2 palliation using virtual surgery and closed-loop multi-scale modeling.

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

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

Chacon, Luis; Chen, Guangye; Knoll, Dana Alan

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

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

DOE PAGES

Chacon, Luis; Chen, Guangye; Knoll, Dana Alan; ...

2016-11-11

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

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

PubMed

Grebenkov, Denis S

2011-02-01

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

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 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

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.

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

Reaction-Infiltration Instabilities in Fractured and Porous Rocks

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

Ladd, Anthony

In this project we are developing a multiscale analysis of the evolution of fracture permeability, using numerical simulations and linear stability analysis. Our simulations include fully three-dimensional simulations of the fracture topography, fluid flow, and reactant transport, two-dimensional simulations based on aperture models, and linear stability analysis.

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.

Noise and poise: Enhancement of postural complexity in the elderly with a stochastic-resonance based therapy

NASA Astrophysics Data System (ADS)

Costa, M.; Priplata, A. A.; Lipsitz, L. A.; Wu, Z.; Huang, N. E.; Goldberger, A. L.; Peng, C.-K.

2007-03-01

Pathologic states are associated with a loss of dynamical complexity. Therefore, therapeutic interventions that increase physiologic complexity may enhance health status. Using multiscale entropy analysis, we show that the postural sway dynamics of healthy young and healthy elderly subjects are more complex than that of elderly subjects with a history of falls. Application of subsensory noise to the feet has been demonstrated to improve postural stability in the elderly. We next show that this therapy significantly increases the multiscale complexity of sway fluctuations in healthy elderly subjects. Quantification of changes in dynamical complexity of biologic variability may be the basis of a new approach to assessing risk and to predicting the efficacy of clinical interventions, including noise-based therapies.

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.

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.

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.

A tool for multi-scale modelling of the renal nephron

PubMed Central

Nickerson, David P.; Terkildsen, Jonna R.; Hamilton, Kirk L.; Hunter, Peter J.

2011-01-01

We present the development of a tool, which provides users with the ability to visualize and interact with a comprehensive description of a multi-scale model of the renal nephron. A one-dimensional anatomical model of the nephron has been created and is used for visualization and modelling of tubule transport in various nephron anatomical segments. Mathematical models of nephron segments are embedded in the one-dimensional model. At the cellular level, these segment models use models encoded in CellML to describe cellular and subcellular transport kinetics. A web-based presentation environment has been developed that allows the user to visualize and navigate through the multi-scale nephron model, including simulation results, at the different spatial scales encompassed by the model description. The Zinc extension to Firefox is used to provide an interactive three-dimensional view of the tubule model and the native Firefox rendering of scalable vector graphics is used to present schematic diagrams for cellular and subcellular scale models. The model viewer is embedded in a web page that dynamically presents content based on user input. For example, when viewing the whole nephron model, the user might be presented with information on the various embedded segment models as they select them in the three-dimensional model view. Alternatively, the user chooses to focus the model viewer on a cellular model located in a particular nephron segment in order to view the various membrane transport proteins. Selecting a specific protein may then present the user with a description of the mathematical model governing the behaviour of that protein—including the mathematical model itself and various simulation experiments used to validate the model against the literature. PMID:22670210

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.

Multi-scale spectrally resolved quantitative fluorescence imaging system: towards neurosurgical guidance in glioma resection

NASA Astrophysics Data System (ADS)

Xie, Yijing; Thom, Maria; Miserocchi, Anna; McEvoy, Andrew W.; Desjardins, Adrien; Ourselin, Sebastien; Vercauteren, Tom

2017-02-01

In glioma resection surgery, the detection of tumour is often guided by using intraoperative fluorescence imaging notably with 5-ALA-PpIX, providing fluorescent contrast between normal brain tissue and the gliomas tissue to achieve improved tumour delineation and prolonged patient survival compared with the conventional white-light guided resection. However, the commercially available fluorescence imaging system relies on surgeon's eyes to visualise and distinguish the fluorescence signals, which unfortunately makes the resection subjective. In this study, we developed a novel multi-scale spectrally-resolved fluorescence imaging system and a computational model for quantification of PpIX concentration. The system consisted of a wide-field spectrally-resolved quantitative imaging device and a fluorescence endomicroscopic imaging system enabling optical biopsy. Ex vivo animal tissue experiments as well as human tumour sample studies demonstrated that the system was capable of specifically detecting the PpIX fluorescent signal and estimate the true concentration of PpIX in brain specimen.

A multi-scale model for hair follicles reveals heterogeneous domains driving rapid spatiotemporal hair growth patterning.

PubMed

Wang, Qixuan; Oh, Ji Won; Lee, Hye-Lim; Dhar, Anukriti; Peng, Tao; Ramos, Raul; Guerrero-Juarez, Christian Fernando; Wang, Xiaojie; Zhao, Ran; Cao, Xiaoling; Le, Jonathan; Fuentes, Melisa A; Jocoy, Shelby C; Rossi, Antoni R; Vu, Brian; Pham, Kim; Wang, Xiaoyang; Mali, Nanda Maya; Park, Jung Min; Choi, June-Hyug; Lee, Hyunsu; Legrand, Julien M D; Kandyba, Eve; Kim, Jung Chul; Kim, Moonkyu; Foley, John; Yu, Zhengquan; Kobielak, Krzysztof; Andersen, Bogi; Khosrotehrani, Kiarash; Nie, Qing; Plikus, Maksim V

2017-07-11

The control principles behind robust cyclic regeneration of hair follicles (HFs) remain unclear. Using multi-scale modeling, we show that coupling inhibitors and activators with physical growth of HFs is sufficient to drive periodicity and excitability of hair regeneration. Model simulations and experimental data reveal that mouse skin behaves as a heterogeneous regenerative field, composed of anatomical domains where HFs have distinct cycling dynamics. Interactions between fast-cycling chin and ventral HFs and slow-cycling dorsal HFs produce bilaterally symmetric patterns. Ear skin behaves as a hyper-refractory domain with HFs in extended rest phase. Such hyper-refractivity relates to high levels of BMP ligands and WNT antagonists, in part expressed by ear-specific cartilage and muscle. Hair growth stops at the boundaries with hyper-refractory ears and anatomically discontinuous eyelids, generating wave-breaking effects. We posit that similar mechanisms for coupled regeneration with dominant activator, hyper-refractory, and wave-breaker regions can operate in other actively renewing organs.

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.

Science based integrated approach to advanced nuclear fuel development - integrated multi-scale multi-physics hierarchical modeling and simulation framework Part III: cladding

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

Tome, Carlos N; Caro, J A; Lebensohn, R A

2010-01-01

Advancing the performance of Light Water Reactors, Advanced Nuclear Fuel Cycles, and Advanced Reactors, such as the Next Generation Nuclear Power Plants, requires enhancing our fundamental understanding of fuel and materials behavior under irradiation. The capability to accurately model the nuclear fuel systems to develop predictive tools is critical. Not only are fabrication and performance models needed to understand specific aspects of the nuclear fuel, fully coupled fuel simulation codes are required to achieve licensing of specific nuclear fuel designs for operation. The backbone of these codes, models, and simulations is a fundamental understanding and predictive capability for simulating themore » phase and microstructural behavior of the nuclear fuel system materials and matrices. In this paper we review the current status of the advanced modeling and simulation of nuclear reactor cladding, with emphasis on what is available and what is to be developed in each scale of the project, how we propose to pass information from one scale to the next, and what experimental information is required for benchmarking and advancing the modeling at each scale level.« 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

Simulated shift work in rats perturbs multiscale regulation of locomotor activity.

PubMed

Hsieh, Wan-Hsin; Escobar, Carolina; Yugay, Tatiana; Lo, Men-Tzung; Pittman-Polletta, Benjamin; Salgado-Delgado, Roberto; Scheer, Frank A J L; Shea, Steven A; Buijs, Ruud M; Hu, Kun

2014-07-06

Motor activity possesses a multiscale regulation that is characterized by fractal activity fluctuations with similar structure across a wide range of timescales spanning minutes to hours. Fractal activity patterns are disturbed in animals after ablating the master circadian pacemaker (suprachiasmatic nucleus, SCN) and in humans with SCN dysfunction as occurs with aging and in dementia, suggesting the crucial role of the circadian system in the multiscale activity regulation. We hypothesized that the normal synchronization between behavioural cycles and the SCN-generated circadian rhythms is required for multiscale activity regulation. To test the hypothesis, we studied activity fluctuations of rats in a simulated shift work protocol that was designed to force animals to be active during the habitual resting phase of the circadian/daily cycle. We found that these animals had gradually decreased mean activity level and reduced 24-h activity rhythm amplitude, indicating disturbed circadian and behavioural cycles. Moreover, these animals had disrupted fractal activity patterns as characterized by more random activity fluctuations at multiple timescales from 4 to 12 h. Intriguingly, these activity disturbances exacerbated when the shift work schedule lasted longer and persisted even in the normal days (without forced activity) following the shift work. The disrupted circadian and fractal patterns resemble those of SCN-lesioned animals and of human patients with dementia, suggesting a detrimental impact of shift work on multiscale activity regulation. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

The topology of the cosmic web in terms of persistent Betti numbers

NASA Astrophysics Data System (ADS)

Pranav, Pratyush; Edelsbrunner, Herbert; van de Weygaert, Rien; Vegter, Gert; Kerber, Michael; Jones, Bernard J. T.; Wintraecken, Mathijs

2017-03-01

We introduce a multiscale topological description of the Megaparsec web-like cosmic matter distribution. Betti numbers and topological persistence offer a powerful means of describing the rich connectivity structure of the cosmic web and of its multiscale arrangement of matter and galaxies. Emanating from algebraic topology and Morse theory, Betti numbers and persistence diagrams represent an extension and deepening of the cosmologically familiar topological genus measure and the related geometric Minkowski functionals. In addition to a description of the mathematical background, this study presents the computational procedure for computing Betti numbers and persistence diagrams for density field filtrations. The field may be computed starting from a discrete spatial distribution of galaxies or simulation particles. The main emphasis of this study concerns an extensive and systematic exploration of the imprint of different web-like morphologies and different levels of multiscale clustering in the corresponding computed Betti numbers and persistence diagrams. To this end, we use Voronoi clustering models as templates for a rich variety of web-like configurations and the fractal-like Soneira-Peebles models exemplify a range of multiscale configurations. We have identified the clear imprint of cluster nodes, filaments, walls, and voids in persistence diagrams, along with that of the nested hierarchy of structures in multiscale point distributions. We conclude by outlining the potential of persistent topology for understanding the connectivity structure of the cosmic web, in large simulations of cosmic structure formation and in the challenging context of the observed galaxy distribution in large galaxy surveys.

A domain-specific analysis system for examining nuclear reactor simulation data for light-water and sodium-cooled fast reactors

DOE PAGES

Billings, Jay Jay; Deyton, Jordan H.; Forest Hull, S.; ...

2015-07-17

Building new fission reactors in the United States presents many technical and regulatory challenges. Chief among the technical challenges is the need to share and present results from new high- fidelity, high- performance simulations in an easily consumable way. In light of the modern multi-scale, multi-physics simulations can generate petabytes of data, this will require the development of new techniques and methods to reduce the data to familiar quantities of interest with a more reasonable resolution and size. Furthermore, some of the results from these simulations may be new quantities for which visualization and analysis techniques are not immediately availablemore » in the community and need to be developed. Our paper describes a new system for managing high-performance simulation results in a domain-specific way that naturally exposes quantities of interest for light water and sodium-cooled fast reactors. It enables easy qualitative and quantitative comparisons between simulation results with a graphical user interface and cross-platform, multi-language input- output libraries for use by developers to work with the data. One example comparing results from two different simulation suites for a single assembly in a light-water reactor is presented along with a detailed discussion of the system s requirements and design.« less

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.

A Computational Framework for Efficient Low Temperature Plasma Simulations

NASA Astrophysics Data System (ADS)

Verma, Abhishek Kumar; Venkattraman, Ayyaswamy

2016-10-01

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

SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

PubMed

Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

2010-01-01

Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

Scale-specific effects: A report on multiscale analysis of acupunctured EEG in entropy and power

NASA Astrophysics Data System (ADS)

Song, Zhenxi; Deng, Bin; Wei, Xile; Cai, Lihui; Yu, Haitao; Wang, Jiang; Wang, Ruofan; Chen, Yingyuan

2018-02-01

Investigating acupuncture effects contributes to improving clinical application and understanding neuronal dynamics under external stimulation. In this report, we recorded electroencephalography (EEG) signals evoked by acupuncture at ST36 acupoint with three stimulus frequencies of 50, 100 and 200 times per minutes, and selected non-acupuncture EEGs as the control group. Multiscale analyses were introduced to investigate the possible acupuncture effects on complexity and power in multiscale level. Using multiscale weighted-permutation entropy, we found the significant effects on increased complexity degree in EEG signals induced by acupuncture. The comparison of three stimulation manipulations showed that 100 times/min generated most obvious effects, and affected most cortical regions. By estimating average power spectral density, we found decreased power induced by acupuncture. The joint distribution of entropy and power indicated an inverse correlation, and this relationship was weakened by acupuncture effects, especially under the manipulation of 100 times/min frequency. Above findings are more evident and stable in large scales than small scales, which suggests that multiscale analysis allows evaluating significant effects in specific scale and enables to probe the inherent characteristics underlying physiological signals.

Multi-scale simulations of space problems with iPIC3D

NASA Astrophysics Data System (ADS)

Lapenta, Giovanni; Bettarini, Lapo; Markidis, Stefano

The implicit Particle-in-Cell method for the computer simulation of space plasma, and its im-plementation in a three-dimensional parallel code, called iPIC3D, are presented. The implicit integration in time of the Vlasov-Maxwell system removes the numerical stability constraints and enables kinetic plasma simulations at magnetohydrodynamics scales. Simulations of mag-netic reconnection in plasma are presented to show the effectiveness of the algorithm. In particular we will show a number of simulations done for large scale 3D systems using the physical mass ratio for Hydrogen. Most notably one simulation treats kinetically a box of tens of Earth radii in each direction and was conducted using about 16000 processors of the Pleiades NASA computer. The work is conducted in collaboration with the MMS-IDS theory team from University of Colorado (M. Goldman, D. Newman and L. Andersson). Reference: Stefano Markidis, Giovanni Lapenta, Rizwan-uddin Multi-scale simulations of plasma with iPIC3D Mathematics and Computers in Simulation, Available online 17 October 2009, http://dx.doi.org/10.1016/j.matcom.2009.08.038

A combined molecular dynamics/micromechanics/finite element approach for multiscale constitutive modeling of nanocomposites with interface effects

NASA Astrophysics Data System (ADS)

Yang, B. J.; Shin, H.; Lee, H. K.; Kim, H.

2013-12-01

We introduce a multiscale framework based on molecular dynamic (MD) simulation, micromechanics, and finite element method (FEM). A micromechanical model, which considers influences of the interface properties, nanoparticle (NP) size, and microcracks, is developed. Then, we perform MD simulations to characterize the mechanical properties of the nanocomposite system (silica/nylon 6) with varying volume fraction and size of NPs. By comparing the MD with micromechanics results, intrinsic physical properties at interfacial region are derived. Finally, we implement the developed model in the FEM code with the derived interfacial parameters, and predict the mechanical behavior of the nanocomposite at the macroscopic scale.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Multi-Scale Impact and Compression-After-Impact Modeling of Reinforced Benzoxazine/Epoxy Composites using Micromechanics Approach

NASA Astrophysics Data System (ADS)

Montero, Marc Villa; Barjasteh, Ehsan; Baid, Harsh K.; Godines, Cody; Abdi, Frank; Nikbin, Kamran

A multi-scale micromechanics approach along with finite element (FE) model predictive tool is developed to analyze low-energy-impact damage footprint and compression-after-impact (CAI) of composite laminates which is also tested and verified with experimental data. Effective fiber and matrix properties were reverse-engineered from lamina properties using an optimization algorithm and used to assess damage at the micro-level during impact and post-impact FE simulations. Progressive failure dynamic analysis (PFDA) was performed for a two step-process simulation. Damage mechanisms at the micro-level were continuously evaluated during the analyses. Contribution of each failure mode was tracked during the simulations and damage and delamination footprint size and shape were predicted to understand when, where and why failure occurred during both impact and CAI events. The composite laminate was manufactured by the vacuum infusion of the aero-grade toughened Benzoxazine system into the fabric preform. Delamination footprint was measured using C-scan data from the impacted panels and compared with the predicated values obtained from proposed multi-scale micromechanics coupled with FE analysis. Furthermore, the residual strength was predicted from the load-displacement curve and compared with the experimental values as well.

A multi-scale network method for two-phase flow in porous media

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

Khayrat, Karim, E-mail: khayratk@ifd.mavt.ethz.ch; Jenny, Patrick

Pore-network models of porous media are useful in the study of pore-scale flow in porous media. In order to extract macroscopic properties from flow simulations in pore-networks, it is crucial the networks are large enough to be considered representative elementary volumes. However, existing two-phase network flow solvers are limited to relatively small domains. For this purpose, a multi-scale pore-network (MSPN) method, which takes into account flow-rate effects and can simulate larger domains compared to existing methods, was developed. In our solution algorithm, a large pore network is partitioned into several smaller sub-networks. The algorithm to advance the fluid interfaces withinmore » each subnetwork consists of three steps. First, a global pressure problem on the network is solved approximately using the multiscale finite volume (MSFV) method. Next, the fluxes across the subnetworks are computed. Lastly, using fluxes as boundary conditions, a dynamic two-phase flow solver is used to advance the solution in time. Simulation results of drainage scenarios at different capillary numbers and unfavourable viscosity ratios are presented and used to validate the MSPN method against solutions obtained by an existing dynamic network flow solver.« less

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

EPA Pesticide Factsheets

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 Protection Agency develops the CMAQ model and periodically releases new versions of the model that include bug fixes and various other improvements to the modeling system. In the fall of 2016, CMAQ version 5.1.1 will be released. This new version of CMAQ will contain important bug fixes to several issues that were identified in CMAQv5.1 (the current public release version of the CMAQ model), and additionally include updates to other portions of the code. Some specific model updates include a new implementation of the wind-blown dust calculation in CMAQv5.1.1 which fixes several bugs that were identified in the current implementation of wind-blown dust in CMAQv5.1. Several other major updates to the model include an update to the calculation of aerosols; implementation of full halogen chemistry (CMAQv5.1 contains a partial implementation of halogen chemistry), which is particularly important for hemispheric applications of the CMAQ model, as halogen chemistry is need to accurately simulation the destruction of ozone over the ocean; and the new carbon bond 6 (CB6) chemical mechanism. Several annual, and numerous episodic, CMAQv5.1.1 simulations will be performed to assess the impact of these

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

From Solidification Processing to Microstructure to Mechanical Properties: A Multi-scale X-ray Study of an Al-Cu Alloy Sample

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

Tourret, D.; Mertens, J. C. E.; Lieberman, E.

We follow an Al-12 at. pct Cu alloy sample from the liquid state to mechanical failure, using in situ X-ray radiography during directional solidification and tensile testing, as well as three-dimensional computed tomography of the microstructure before and after mechanical testing. The solidification processing stage is simulated with a multi-scale dendritic needle network model, and the micromechanical behavior of the solidified microstructure is simulated using voxelized tomography data and an elasto-viscoplastic fast Fourier transform model. This study demonstrates the feasibility of direct in situ monitoring of a metal alloy microstructure from the liquid processing stage up to its mechanical failure,more » supported by quantitative simulations of microstructure formation and its mechanical behavior.« less

Multiscale Approach For Simulating Nonlinear Wave Propagation In Materials with Localized Microdamage

NASA Astrophysics Data System (ADS)

Vanaverbeke, Sigfried; Van Den Abeele, Koen

2006-05-01

A multiscale model for the simulation of two-dimensional nonlinear wave propagation in microcracked materials exhibiting hysteretic nonlinearity is presented. We use trigger-like elements with a two state nonlinear stress-strain relation to simulate microcracks at the microlevel. A generalized Preisach space approach, based on the eigenstress-eigenstrain formulation, upscales the microscopic state relation to the mesoscopic level. The macroscopic response of the sample to an arbitrary excitation signal is then predicted using a staggered grid Elastodynamic Finite Integration Technique (EFIT) formalism. We apply the model to investigate spectral changes of a pulsed signal traversing a localized microdamaged region with hysteretic nonlinearity in a plate, and to study the influence of a superficial region with hysteretic nonlinearity on the nonlinear Rayleigh wave propagation.

From Solidification Processing to Microstructure to Mechanical Properties: A Multi-scale X-ray Study of an Al-Cu Alloy Sample

DOE PAGES

Tourret, D.; Mertens, J. C. E.; Lieberman, E.; ...

2017-09-13

We follow an Al-12 at. pct Cu alloy sample from the liquid state to mechanical failure, using in situ X-ray radiography during directional solidification and tensile testing, as well as three-dimensional computed tomography of the microstructure before and after mechanical testing. The solidification processing stage is simulated with a multi-scale dendritic needle network model, and the micromechanical behavior of the solidified microstructure is simulated using voxelized tomography data and an elasto-viscoplastic fast Fourier transform model. This study demonstrates the feasibility of direct in situ monitoring of a metal alloy microstructure from the liquid processing stage up to its mechanical failure,more » supported by quantitative simulations of microstructure formation and its mechanical behavior.« less

From Solidification Processing to Microstructure to Mechanical Properties: A Multi-scale X-ray Study of an Al-Cu Alloy Sample

NASA Astrophysics Data System (ADS)

Tourret, D.; Mertens, J. C. E.; Lieberman, E.; Imhoff, S. D.; Gibbs, J. W.; Henderson, K.; Fezzaa, K.; Deriy, A. L.; Sun, T.; Lebensohn, R. A.; Patterson, B. M.; Clarke, A. J.

2017-11-01

We follow an Al-12 at. pct Cu alloy sample from the liquid state to mechanical failure, using in situ X-ray radiography during directional solidification and tensile testing, as well as three-dimensional computed tomography of the microstructure before and after mechanical testing. The solidification processing stage is simulated with a multi-scale dendritic needle network model, and the micromechanical behavior of the solidified microstructure is simulated using voxelized tomography data and an elasto-viscoplastic fast Fourier transform model. This study demonstrates the feasibility of direct in situ monitoring of a metal alloy microstructure from the liquid processing stage up to its mechanical failure, supported by quantitative simulations of microstructure formation and its mechanical behavior.

A multiple-fan active control wind tunnel for outdoor wind speed and direction simulation

NASA Astrophysics Data System (ADS)

Wang, Jia-Ying; Meng, Qing-Hao; Luo, Bing; Zeng, Ming

2018-03-01

This article presents a new type of active controlled multiple-fan wind tunnel. The wind tunnel consists of swivel plates and arrays of direct current fans, and the rotation speed of each fan and the shaft angle of each swivel plate can be controlled independently for simulating different kinds of outdoor wind fields. To measure the similarity between the simulated wind field and the outdoor wind field, wind speed and direction time series of two kinds of wind fields are recorded by nine two-dimensional ultrasonic anemometers, and then statistical properties of the wind signals in different time scales are analyzed based on the empirical mode decomposition. In addition, the complexity of wind speed and direction time series is also investigated using multiscale entropy and multivariate multiscale entropy. Results suggest that the simulated wind field in the multiple-fan wind tunnel has a high degree of similarity with the outdoor wind field.

Adaptive resolution simulation of oligonucleotides

NASA Astrophysics Data System (ADS)

Netz, Paulo A.; Potestio, Raffaello; Kremer, Kurt

2016-12-01

Nucleic acids are characterized by a complex hierarchical structure and a variety of interaction mechanisms with other molecules. These features suggest the need of multiscale simulation methods in order to grasp the relevant physical properties of deoxyribonucleic acid (DNA) and RNA using in silico experiments. Here we report an implementation of a dual-resolution modeling of a DNA oligonucleotide in physiological conditions; in the presented setup only the nucleotide molecule and the solvent and ions in its proximity are described at the atomistic level; in contrast, the water molecules and ions far from the DNA are represented as computationally less expensive coarse-grained particles. Through the analysis of several structural and dynamical parameters, we show that this setup reliably reproduces the physical properties of the DNA molecule as observed in reference atomistic simulations. These results represent a first step towards a realistic multiscale modeling of nucleic acids and provide a quantitatively solid ground for their simulation using dual-resolution methods.

An extended algebraic variational multiscale-multigrid-multifractal method (XAVM4) for large-eddy simulation of turbulent two-phase flow

NASA Astrophysics Data System (ADS)

Rasthofer, U.; Wall, W. A.; Gravemeier, V.

2018-04-01

A novel and comprehensive computational method, referred to as the eXtended Algebraic Variational Multiscale-Multigrid-Multifractal Method (XAVM4), is proposed for large-eddy simulation of the particularly challenging problem of turbulent two-phase flow. The XAVM4 involves multifractal subgrid-scale modeling as well as a Nitsche-type extended finite element method as an approach for two-phase flow. The application of an advanced structural subgrid-scale modeling approach in conjunction with a sharp representation of the discontinuities at the interface between two bulk fluids promise high-fidelity large-eddy simulation of turbulent two-phase flow. The high potential of the XAVM4 is demonstrated for large-eddy simulation of turbulent two-phase bubbly channel flow, that is, turbulent channel flow carrying a single large bubble of the size of the channel half-width in this particular application.

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.

Simulation of dilute polymeric fluids in a three-dimensional contraction using a multiscale FENE model

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

Griebel, M., E-mail: griebel@ins.uni-bonn.de, E-mail: ruettgers@ins.uni-bonn.de; Rüttgers, A., E-mail: griebel@ins.uni-bonn.de, E-mail: ruettgers@ins.uni-bonn.de

The multiscale FENE model is applied to a 3D square-square contraction flow problem. For this purpose, the stochastic Brownian configuration field method (BCF) has been coupled with our fully parallelized three-dimensional Navier-Stokes solver NaSt3DGPF. The robustness of the BCF method enables the numerical simulation of high Deborah number flows for which most macroscopic methods suffer from stability issues. The results of our simulations are compared with that of experimental measurements from literature and show a very good agreement. In particular, flow phenomena such as a strong vortex enhancement, streamline divergence and a flow inversion for highly elastic flows are reproduced.more » Due to their computational complexity, our simulations require massively parallel computations. Using a domain decomposition approach with MPI, the implementation achieves excellent scale-up results for up to 128 processors.« less

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

A novel and versatile “bottom-up” approach is developed to estimate the radiobiological effect of clinic radiotherapy. The model consists of multi-scale Monte Carlo simulations from organ to cell levels. At cellular level, accumulated damages are computed using a spectrum-based accumulation algorithm and predefined cellular damage database. The damage repair mechanism is modeled by an expanded reaction-rate two-lesion kinetic model, which were calibrated through replicating a radiobiological experiment. Multi-scale modeling is then performed on a lung cancer patient under conventional fractionated irradiation. The cell killing effects of two representative voxels (isocenter and peripheral voxel of the tumor) are computed and compared. At microscopic level, the nucleus dose and damage yields vary among all nucleuses within the voxels. Slightly larger percentage of cDSB yield is observed for the peripheral voxel (55.0%) compared to the isocenter one (52.5%). For isocenter voxel, survival fraction increase monotonically at reduced oxygen environment. Under an extreme anoxic condition (0.001%), survival fraction is calculated to be 80% and the hypoxia reduction factor reaches a maximum value of 2.24. In conclusion, with biological-related variations, the proposed multi-scale approach is more versatile than the existing approaches for evaluating personalized radiobiological effects in radiotherapy.

Real-Time Nonlocal Means-Based Despeckling.

PubMed

Breivik, Lars Hofsoy; Snare, Sten Roar; Steen, Erik Normann; Solberg, Anne H Schistad

2017-06-01

In this paper, we propose a multiscale nonlocal means-based despeckling method for medical ultrasound. The multiscale approach leads to large computational savings and improves despeckling results over single-scale iterative approaches. We present two variants of the method. The first, denoted multiscale nonlocal means (MNLM), yields uniform robust filtering of speckle both in structured and homogeneous regions. The second, denoted unnormalized MNLM (UMNLM), is more conservative in regions of structure assuring minimal disruption of salient image details. Due to the popularity of anisotropic diffusion-based methods in the despeckling literature, we review the connection between anisotropic diffusion and iterative variants of NLM. These iterative variants in turn relate to our multiscale variant. As part of our evaluation, we conduct a simulation study making use of ground truth phantoms generated from clinical B-mode ultrasound images. We evaluate our method against a set of popular methods from the despeckling literature on both fine and coarse speckle noise. In terms of computational efficiency, our method outperforms the other considered methods. Quantitatively on simulations and on a tissue-mimicking phantom, our method is found to be competitive with the state-of-the-art. On clinical B-mode images, our method is found to effectively smooth speckle while preserving low-contrast and highly localized salient image detail.

Predicting Silk Fiber Mechanical Properties through Multiscale Simulation and Protein Design.

PubMed

Rim, Nae-Gyune; Roberts, Erin G; Ebrahimi, Davoud; Dinjaski, Nina; Jacobsen, Matthew M; Martín-Moldes, Zaira; Buehler, Markus J; Kaplan, David L; Wong, Joyce Y

2017-08-14

Silk is a promising material for biomedical applications, and much research is focused on how application-specific, mechanical properties of silk can be designed synthetically through proper amino acid sequences and processing parameters. This protocol describes an iterative process between research disciplines that combines simulation, genetic synthesis, and fiber analysis to better design silk fibers with specific mechanical properties. Computational methods are used to assess the protein polymer structure as it forms an interconnected fiber network through shearing and how this process affects fiber mechanical properties. Model outcomes are validated experimentally with the genetic design of protein polymers that match the simulation structures, fiber fabrication from these polymers, and mechanical testing of these fibers. Through iterative feedback between computation, genetic synthesis, and fiber mechanical testing, this protocol will enable a priori prediction capability of recombinant material mechanical properties via insights from the resulting molecular architecture of the fiber network based entirely on the initial protein monomer composition. This style of protocol may be applied to other fields where a research team seeks to design a biomaterial with biomedical application-specific properties. This protocol highlights when and how the three research groups (simulation, synthesis, and engineering) should be interacting to arrive at the most effective method for predictive design of their material.

Scalability Test of Multiscale Fluid-Platelet Model for Three Top Supercomputers

PubMed Central

Zhang, Peng; Zhang, Na; Gao, Chao; Zhang, Li; Gao, Yuxiang; Deng, Yuefan; Bluestein, Danny

2016-01-01

We have tested the scalability of three supercomputers: the Tianhe-2, Stampede and CS-Storm with multiscale fluid-platelet simulations, in which a highly-resolved and efficient numerical model for nanoscale biophysics of platelets in microscale viscous biofluids is considered. Three experiments involving varying problem sizes were performed: Exp-S: 680,718-particle single-platelet; Exp-M: 2,722,872-particle 4-platelet; and Exp-L: 10,891,488-particle 16-platelet. Our implementations of multiple time-stepping (MTS) algorithm improved the performance of single time-stepping (STS) in all experiments. Using MTS, our model achieved the following simulation rates: 12.5, 25.0, 35.5 μs/day for Exp-S and 9.09, 6.25, 14.29 μs/day for Exp-M on Tianhe-2, CS-Storm 16-K80 and Stampede K20. The best rate for Exp-L was 6.25 μs/day for Stampede. Utilizing current advanced HPC resources, the simulation rates achieved by our algorithms bring within reach performing complex multiscale simulations for solving vexing problems at the interface of biology and engineering, such as thrombosis in blood flow which combines millisecond-scale hematology with microscale blood flow at resolutions of micro-to-nanoscale cellular components of platelets. This study of testing the performance characteristics of supercomputers with advanced computational algorithms that offer optimal trade-off to achieve enhanced computational performance serves to demonstrate that such simulations are feasible with currently available HPC resources. PMID:27570250

The Effect of Lateral Boundary Values on Atmospheric Mercury Simulations with the CMAQ Model

EPA Science Inventory

Simulation results from three global-scale models of atmospheric mercury have been used to define three sets of initial condition and boundary condition (IC/BC) data for regional-scale model simulations over North America using the Community Multi-scale Air Quality (CMAQ) model. ...

Dynamic evaluation of two decades of WRF-CMAQ ozone simulations over the contiguous United States

EPA Science Inventory

Dynamic evaluation of the fully coupled Weather Research and Forecasting (WRF)– Community Multi-scale Air Quality (CMAQ) model ozone simulations over the contiguous United States (CONUS) using two decades of simulations covering the period from 1990 to 2010 is conducted to ...

Dynamic evaluation of two decades of WRF-CMAQ ozone simulations over the contiguous United States

EPA Science Inventory

Dynamic evaluation of the fully coupled Weather Research and Forecasting (WRF)– Community Multi-scale Air Quality (CMAQ) model ozone simulations over the contiguous United States (CONUS) using two decades of simulations covering the period from 1990 to 2010 is conducted to assess...

Bridging scales through multiscale modeling: a case study on protein kinase A.

PubMed

Boras, Britton W; Hirakis, Sophia P; Votapka, Lane W; Malmstrom, Robert D; Amaro, Rommie E; McCulloch, Andrew D

2015-01-01

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

Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations

NASA Astrophysics Data System (ADS)

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

2017-12-01

Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely resolved (e.g., molecular dynamics) and coarse-grained (e.g., continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 084115 (2016)], simulated using a particle-based continuum method known as smoothed dissipative particle dynamics. An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.

Understanding the interfacial behavior of lysozyme on Au (111) surfaces with multiscale simulations

NASA Astrophysics Data System (ADS)

Samieegohar, Mohammadreza; Ma, Heng; Sha, Feng; Jahan Sajib, Md Symon; Guerrero-García, G. Iván; Wei, Tao

2017-02-01

The understanding of the adsorption and interfacial behavior of proteins is crucial to the development of novel biosensors and biomaterials. By using bottom-up atomistic multiscale simulations, we study here the adsorption of lysozyme on Au(111) surfaces in an aqueous environment. Atomistic simulations are used to calculate the inhomogeneous polarization of the gold surface, which is induced by the protein adsorption, and by the presence of an interfacial layer of water molecules and monovalent salts. The corresponding potential of mean force between the protein and the gold surface including polarization effects is used in Langevin Dynamics simulations to study the time dependent behavior of proteins at finite concentration. These simulations display a rapid adsorption and formation of a first-layer of proteins at the interface. Proteins are initially adsorbed directly on the gold surface due to the strong protein-surface attractive interaction. A subsequent interfacial weak aggregation of proteins leading to multilayer build-up is also observed at long times.

Challenge toward the prediction of typhoon behaviour and down pour

NASA Astrophysics Data System (ADS)

Takahashi, K.; Onishi, R.; Baba, Y.; Kida, S.; Matsuda, K.; Goto, K.; Fuchigami, H.

2013-08-01

Mechanisms of interactions among different scale phenomena play important roles for forecasting of weather and climate. Multi-scale Simulator for the Geoenvironment (MSSG), which deals with multi-scale multi-physics phenomena, is a coupled non-hydrostatic atmosphere-ocean model designed to be run efficiently on the Earth Simulator. We present simulation results with the world-highest 1.9km horizontal resolution for the entire globe and regional heavy rain with 1km horizontal resolution and 5m horizontal/vertical resolution for urban area simulation. To gain high performance by exploiting the system capabilities, we propose novel performance evaluation metrics introduced in previous studies that incorporate the effects of the data caching mechanism between CPU and memory. With a useful code optimization guideline based on such metrics, we demonstrate that MSSG can achieve an excellent peak performance ratio of 32.2% on the Earth Simulator with the single-core performance found to be a key to a reduced time-to-solution.

A multi-scale model for correlation in B cell VDJ usage of zebrafish

NASA Astrophysics Data System (ADS)

Pan, Keyao; Deem, Michael W.

2011-10-01

The zebrafish (Danio rerio) is one of the model animals used for the study of immunology because the dynamics in the adaptive immune system of zebrafish are similar to that in higher animals. In this work, we built a multi-scale model to simulate the dynamics of B cells in the primary and secondary immune responses of zebrafish. We use this model to explain the reported correlation between VDJ usage of B cell repertoires in individual zebrafish. We use a delay ordinary differential equation (ODE) system to model the immune responses in the 6-month lifespan of a zebrafish. This mean field theory gives the number of high-affinity B cells as a function of time during an infection. The sequences of those B cells are then taken from a distribution calculated by a 'microscopic' random energy model. This generalized NK model shows that mature B cells specific to one antigen largely possess a single VDJ recombination. The model allows first-principle calculation of the probability, p, that two zebrafish responding to the same antigen will select the same VDJ recombination. This probability p increases with the B cell population size and the B cell selection intensity. The probability p decreases with the B cell hypermutation rate. The multi-scale model predicts correlations in the immune system of the zebrafish that are highly similar to that from experiment.

Enhancement of low visibility aerial images using histogram truncation and an explicit Retinex representation for balancing contrast and color consistency

NASA Astrophysics Data System (ADS)

Liu, Changjiang; Cheng, Irene; Zhang, Yi; Basu, Anup

2017-06-01

This paper presents an improved multi-scale Retinex (MSR) based enhancement for ariel images under low visibility. For traditional multi-scale Retinex, three scales are commonly employed, which limits its application scenarios. We extend our research to a general purpose enhanced method, and design an MSR with more than three scales. Based on the mathematical analysis and deductions, an explicit multi-scale representation is proposed that balances image contrast and color consistency. In addition, a histogram truncation technique is introduced as a post-processing strategy to remap the multi-scale Retinex output to the dynamic range of the display. Analysis of experimental results and comparisons with existing algorithms demonstrate the effectiveness and generality of the proposed method. Results on image quality assessment proves the accuracy of the proposed method with respect to both objective and subjective criteria.

A Micromechanics-Based Method for Multiscale Fatigue Prediction

NASA Astrophysics Data System (ADS)

Moore, John Allan

An estimated 80% of all structural failures are due to mechanical fatigue, often resulting in catastrophic, dangerous and costly failure events. However, an accurate model to predict fatigue remains an elusive goal. One of the major challenges is that fatigue is intrinsically a multiscale process, which is dependent on a structure's geometric design as well as its material's microscale morphology. The following work begins with a microscale study of fatigue nucleation around non- metallic inclusions. Based on this analysis, a novel multiscale method for fatigue predictions is developed. This method simulates macroscale geometries explicitly while concurrently calculating the simplified response of microscale inclusions. Thus, providing adequate detail on multiple scales for accurate fatigue life predictions. The methods herein provide insight into the multiscale nature of fatigue, while also developing a tool to aid in geometric design and material optimization for fatigue critical devices such as biomedical stents and artificial heart valves.

Multiscale Modelling of the 2011 Tohoku Tsunami with Fluidity: Coastal Inundation and Run-up.

NASA Astrophysics Data System (ADS)

Hill, J.; Martin-Short, R.; Piggott, M. D.; Candy, A. S.

2014-12-01

Tsunami-induced flooding represents one of the most dangerous natural hazards to coastal communities around the world, as exemplified by Tohoku tsunami of March 2011. In order to further understand this hazard and to design appropriate mitigation it is necessary to develop versatile, accurate software capable of simulating large scale tsunami propagation and interaction with coastal geomorphology on a local scale. One such software package is Fluidity, an open source, finite element, multiscale, code that is capable of solving the fully three dimensional Navier-Stokes equations on unstructured meshes. Such meshes are significantly better at representing complex coastline shapes than structured meshes and have the advantage of allowing variation in element size across a domain. Furthermore, Fluidity incorporates a novel wetting and drying algorithm, which enables accurate, efficient simulation of tsunami run-up over complex, multiscale, topography. Fluidity has previously been demonstrated to accurately simulate the 2011 Tohoku tsunami (Oishi et al 2013) , but its wetting and drying facility has not yet been tested on a geographical scale. This study makes use of Fluidity to simulate the 2011 Tohoku tsunami and its interaction with Japan's eastern shoreline, including coastal flooding. The results are validated against observations made by survey teams, aerial photographs and previous modelling efforts in order to evaluate Fluidity's current capabilities and suggest methods of future improvement. The code is shown to perform well at simulating flooding along the topographically complex Tohoku coast of Japan, with major deviations between model and observation arising mainly due to limitations imposed by bathymetry resolution, which could be improved in future. In theory, Fluidity is capable of full multiscale tsunami modelling, thus enabling researchers to understand both wave propagation across ocean basins and flooding of coastal landscapes down to interaction with individual defence structures. This makes the code an exciting candidate for use in future studies aiming to investigate tsunami risk elsewhere in the world. Oishi, Y. et al. Three-dimensional tsunami propagation simulations using an unstructured mesh finite element model. J. Geophys. Res. [Solid Earth] 118, 2998-3018 (2013).

Hierarchical Multiscale Modeling of Macromolecules and their Assemblies

PubMed Central

Ortoleva, P.; Singharoy, A.; Pankavich, S.

2013-01-01

Soft materials (e.g., enveloped viruses, liposomes, membranes and supercooled liquids) simultaneously deform or display collective behaviors, while undergoing atomic scale vibrations and collisions. While the multiple space-time character of such systems often makes traditional molecular dynamics simulation impractical, a multiscale approach has been presented that allows for long-time simulation with atomic detail based on the co-evolution of slowly-varying order parameters (OPs) with the quasi-equilibrium probability density of atomic configurations. However, this approach breaks down when the structural change is extreme, or when nearest-neighbor connectivity of atoms is not maintained. In the current study, a self-consistent approach is presented wherein OPs and a reference structure co-evolve slowly to yield long-time simulation for dynamical soft-matter phenomena such as structural transitions and self-assembly. The development begins with the Liouville equation for N classical atoms and an ansatz on the form of the associated N-atom probability density. Multiscale techniques are used to derive Langevin equations for the coupled OP-configurational dynamics. The net result is a set of equations for the coupled stochastic dynamics of the OPs and centers of mass of the subsystems that constitute a soft material body. The theory is based on an all-atom methodology and an interatomic force field, and therefore enables calibration-free simulations of soft matter, such as macromolecular assemblies. PMID:23671457

Multi-scale structures of turbulent magnetic reconnection

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

Nakamura, T. K. M., E-mail: takuma.nakamura@oeaw.ac.at; Nakamura, R.; Narita, Y.

2016-05-15

We have analyzed data from a series of 3D fully kinetic simulations of turbulent magnetic reconnection with a guide field. A new concept of the guide filed reconnection process has recently been proposed, in which the secondary tearing instability and the resulting formation of oblique, small scale flux ropes largely disturb the structure of the primary reconnection layer and lead to 3D turbulent features [W. Daughton et al., Nat. Phys. 7, 539 (2011)]. In this paper, we further investigate the multi-scale physics in this turbulent, guide field reconnection process by introducing a wave number band-pass filter (k-BPF) technique in whichmore » modes for the small scale (less than ion scale) fluctuations and the background large scale (more than ion scale) variations are separately reconstructed from the wave number domain to the spatial domain in the inverse Fourier transform process. Combining with the Fourier based analyses in the wave number domain, we successfully identify spatial and temporal development of the multi-scale structures in the turbulent reconnection process. When considering a strong guide field, the small scale tearing mode and the resulting flux ropes develop over a specific range of oblique angles mainly along the edge of the primary ion scale flux ropes and reconnection separatrix. The rapid merging of these small scale modes leads to a smooth energy spectrum connecting ion and electron scales. When the guide field is sufficiently weak, the background current sheet is strongly kinked and oblique angles for the small scale modes are widely scattered at the kinked regions. Similar approaches handling both the wave number and spatial domains will be applicable to the data from multipoint, high-resolution spacecraft observations such as the NASA magnetospheric multiscale (MMS) mission.« less

Multi-scale structures of turbulent magnetic reconnection

NASA Astrophysics Data System (ADS)

Nakamura, T. K. M.; Nakamura, R.; Narita, Y.; Baumjohann, W.; Daughton, W.

2016-05-01

We have analyzed data from a series of 3D fully kinetic simulations of turbulent magnetic reconnection with a guide field. A new concept of the guide filed reconnection process has recently been proposed, in which the secondary tearing instability and the resulting formation of oblique, small scale flux ropes largely disturb the structure of the primary reconnection layer and lead to 3D turbulent features [W. Daughton et al., Nat. Phys. 7, 539 (2011)]. In this paper, we further investigate the multi-scale physics in this turbulent, guide field reconnection process by introducing a wave number band-pass filter (k-BPF) technique in which modes for the small scale (less than ion scale) fluctuations and the background large scale (more than ion scale) variations are separately reconstructed from the wave number domain to the spatial domain in the inverse Fourier transform process. Combining with the Fourier based analyses in the wave number domain, we successfully identify spatial and temporal development of the multi-scale structures in the turbulent reconnection process. When considering a strong guide field, the small scale tearing mode and the resulting flux ropes develop over a specific range of oblique angles mainly along the edge of the primary ion scale flux ropes and reconnection separatrix. The rapid merging of these small scale modes leads to a smooth energy spectrum connecting ion and electron scales. When the guide field is sufficiently weak, the background current sheet is strongly kinked and oblique angles for the small scale modes are widely scattered at the kinked regions. Similar approaches handling both the wave number and spatial domains will be applicable to the data from multipoint, high-resolution spacecraft observations such as the NASA magnetospheric multiscale (MMS) mission.

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.

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.

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

Fractal analysis of multiscale spatial autocorrelation among point data

USGS Publications Warehouse

De Cola, L.

1991-01-01

The analysis of spatial autocorrelation among point-data quadrats is a well-developed technique that has made limited but intriguing use of the multiscale aspects of pattern. In this paper are presented theoretical and algorithmic approaches to the analysis of aggregations of quadrats at or above a given density, in which these sets are treated as multifractal regions whose fractal dimension, D, may vary with phenomenon intensity, scale, and location. The technique is illustrated with Matui's quadrat house-count data, which yield measurements consistent with a nonautocorrelated simulated Poisson process but not with an orthogonal unit-step random walk. The paper concludes with a discussion of the implications of such analysis for multiscale geographic analysis systems. -Author

Inverse Coarse-Graining: A New Tool for Molecular Design

DTIC Science & Technology

2010-12-16

simulations. When compared with the more general multiscale coarse-graining (MS-CG) method, the EF-CG method retains the transferable part of the CG...Y.; Yan, T.; Voth, G. A., A Multiscale coarse-graining study of liquid/vacuum interface of room-temperature ionic liquids with alkyl substituents of...Energetic Room Temperature Ionic Liquid 1-Hydroxyethyl-4Amino-1, 2, 4-Triazolium Nitrate (HEATN). J. Phys. Chem. B 2008, 112, 3121-3131. 6. Liu, P

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.

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

Detection of feigned mental disorders on the personality assessment inventory: a discriminant analysis.

PubMed

Rogers, R; Sewell, K W; Morey, L C; Ustad, K L

1996-12-01

Psychological assessment with multiscale inventories is largely dependent on the honesty and forthrightness of those persons evaluated. We investigated the effectiveness of the Personality Assessment Inventory (PAI) in detecting participants feigning three specific disorders: schizophrenia, major depression, and generalized anxiety disorder. With a simulation design, we tested the PAI validity scales on 166 naive (undergraduates with minimal preparation) and 80 sophisticated (doctoral psychology students with 1 week preparation) participants. We compared their results to persons with the designated disorders: schizophrenia (n = 45), major depression (n = 136), and generalized anxiety disorder (n = 40). Although moderately effective with naive simulators, the validity scales evidenced only modest positive predictive power with their sophisticated counterparts. Therefore, we performed a two-stage discriminant analysis that yielded a moderately high hit rate (> 80%) that was maintained in the cross-validation sample, irrespective of the feigned disorder or the sophistication of the simulators.

SpineCreator: a Graphical User Interface for the Creation of Layered Neural Models.

PubMed

Cope, A J; Richmond, P; James, S S; Gurney, K; Allerton, D J

2017-01-01

There is a growing requirement in computational neuroscience for tools that permit collaborative model building, model sharing, combining existing models into a larger system (multi-scale model integration), and are able to simulate models using a variety of simulation engines and hardware platforms. Layered XML model specification formats solve many of these problems, however they are difficult to write and visualise without tools. Here we describe a new graphical software tool, SpineCreator, which facilitates the creation and visualisation of layered models of point spiking neurons or rate coded neurons without requiring the need for programming. We demonstrate the tool through the reproduction and visualisation of published models and show simulation results using code generation interfaced directly into SpineCreator. As a unique application for the graphical creation of neural networks, SpineCreator represents an important step forward for neuronal modelling.

Multi-scale modeling of microstructure dependent intergranular brittle fracture using a quantitative phase-field based method

DOE PAGES

Chakraborty, Pritam; Zhang, Yongfeng; Tonks, Michael R.

2015-12-07

In this study, the fracture behavior of brittle materials is strongly influenced by their underlying microstructure that needs explicit consideration for accurate prediction of fracture properties and the associated scatter. In this work, a hierarchical multi-scale approach is pursued to model microstructure sensitive brittle fracture. A quantitative phase-field based fracture model is utilized to capture the complex crack growth behavior in the microstructure and the related parameters are calibrated from lower length scale atomistic simulations instead of engineering scale experimental data. The workability of this approach is demonstrated by performing porosity dependent intergranular fracture simulations in UO 2 and comparingmore » the predictions with experiments.« less

Hybrid codes with finite electron mass

NASA Astrophysics Data System (ADS)

Lipatov, A. S.

This report is devoted to the current status of the hybrid multiscale simulation technique. The different aspects of modeling are discussed. In particular, we consider the different level for description of the plasma model, however, the main attention will be paid to conventional hybrid models. We discuss the main steps of time integration the Vlasov/Maxwell system of equations. The main attention will be paid to the models with finite electron mass. Such model may allow us to explore the plasma system with multiscale phenomena ranging from ion to electron scales. As an application of hybrid modeling technique we consider the simulation of the plasma processes at the collisionless shocks and very shortly ther magnetic field reconnection processes.

Multi-scale modeling of microstructure dependent intergranular brittle fracture using a quantitative phase-field based method

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

Chakraborty, Pritam; Zhang, Yongfeng; Tonks, Michael R.

In this study, the fracture behavior of brittle materials is strongly influenced by their underlying microstructure that needs explicit consideration for accurate prediction of fracture properties and the associated scatter. In this work, a hierarchical multi-scale approach is pursued to model microstructure sensitive brittle fracture. A quantitative phase-field based fracture model is utilized to capture the complex crack growth behavior in the microstructure and the related parameters are calibrated from lower length scale atomistic simulations instead of engineering scale experimental data. The workability of this approach is demonstrated by performing porosity dependent intergranular fracture simulations in UO 2 and comparingmore » the predictions with experiments.« less

Multiscale Simulations of ALD in Cross Flow Reactors

DOE PAGES

Yanguas-Gil, Angel; Libera, Joseph A.; Elam, Jeffrey W.

2014-08-13

In this study, we have developed a multiscale simulation code that allows us to study the impact of surface chemistry on the coating of large area substrates with high surface area/high aspect-ratio features. Our code, based on open-source libraries, takes advantage of the ALD surface chemistry to achieve an extremely efficient two-way coupling between reactor and feature length scales, and it can provide simulated quartz crystal microbalance and mass spectrometry data at any point of the reactor. By combining experimental surface characterization with simple analysis of growth profiles in a tubular cross flow reactor, we are able to extract amore » minimal set of reactions to effectively model the surface chemistry, including the presence of spurious CVD, to evaluate the impact of surface chemistry on the coating of large, high surface area substrates.« less

NEAMS FPL M2 Milestone Report: Development of a UO₂ Grain Size Model using Multicale Modeling and Simulation

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

Tonks, Michael R; Zhang, Yongfeng; Bai, Xianming

2014-06-01

This report summarizes development work funded by the Nuclear Energy Advanced Modeling Simulation program's Fuels Product Line (FPL) to develop a mechanistic model for the average grain size in UO₂ fuel. The model is developed using a multiscale modeling and simulation approach involving atomistic simulations, as well as mesoscale simulations using INL's MARMOT code.

Shingle 2.0: generalising self-consistent and automated domain discretisation for multi-scale geophysical models

NASA Astrophysics Data System (ADS)

Candy, Adam S.; Pietrzak, Julie D.

2018-01-01

The approaches taken to describe and develop spatial discretisations of the domains required for geophysical simulation models are commonly ad hoc, model- or application-specific, and under-documented. This is particularly acute for simulation models that are flexible in their use of multi-scale, anisotropic, fully unstructured meshes where a relatively large number of heterogeneous parameters are required to constrain their full description. As a consequence, it can be difficult to reproduce simulations, to ensure a provenance in model data handling and initialisation, and a challenge to conduct model intercomparisons rigorously. This paper takes a novel approach to spatial discretisation, considering it much like a numerical simulation model problem of its own. It introduces a generalised, extensible, self-documenting approach to carefully describe, and necessarily fully, the constraints over the heterogeneous parameter space that determine how a domain is spatially discretised. This additionally provides a method to accurately record these constraints, using high-level natural language based abstractions that enable full accounts of provenance, sharing, and distribution. Together with this description, a generalised consistent approach to unstructured mesh generation for geophysical models is developed that is automated, robust and repeatable, quick-to-draft, rigorously verified, and consistent with the source data throughout. This interprets the description above to execute a self-consistent spatial discretisation process, which is automatically validated to expected discrete characteristics and metrics. Library code, verification tests, and examples available in the repository at https://github.com/shingleproject/Shingle. Further details of the project presented at http://shingleproject.org.

Multiscale Computer Simulation of Tensile and Compressive Strain in Polymer- Coated Silica Aerogels

NASA Technical Reports Server (NTRS)

Good, Brian

2009-01-01

While the low thermal conductivities of silica aerogels have made them of interest to the aerospace community as lightweight thermal insulation, the application of conformal polymer coatings to these gels increases their strength significantly, making them potentially useful as structural materials as well. In this work we perform multiscale computer simulations to investigate the tensile and compressive strain behavior of silica and polymer-coated silica aerogels. Aerogels are made up of clusters of interconnected particles of amorphous silica of less than bulk density. We simulate gel nanostructure using a Diffusion Limited Cluster Aggregation (DLCA) procedure, which produces aggregates that exhibit fractal dimensions similar to those observed in real aerogels. We have previously found that model gels obtained via DLCA exhibited stress-strain curves characteristic of the experimentally observed brittle failure. However, the strain energetics near the expected point of failure were not consistent with such failure. This shortcoming may be due to the fact that the DLCA process produces model gels that are lacking in closed-loop substructures, compared with real gels. Our model gels therefore contain an excess of dangling strands, which tend to unravel under tensile strain, producing non-brittle failure. To address this problem, we have incorporated a modification to the DLCA algorithm that specifically produces closed loops in the model gels. We obtain the strain energetics of interparticle connections via atomistic molecular statics, and abstract the collective energy of the atomic bonds into a Morse potential scaled to describe gel particle interactions. Polymer coatings are similarly described. We apply repeated small uniaxial strains to DLCA clusters, and allow relaxation of the center eighty percent of the cluster between strains. The simulations produce energetics and stress-strain curves for looped and nonlooped clusters, for a variety of densities and interaction parameters.

Tackling some of the most intricate geophysical challenges via high-performance computing

NASA Astrophysics Data System (ADS)

Khosronejad, A.

2016-12-01

Recently, world has been witnessing significant enhancements in computing power of supercomputers. Computer clusters in conjunction with the advanced mathematical algorithms has set the stage for developing and applying powerful numerical tools to tackle some of the most intricate geophysical challenges that today`s engineers face. One such challenge is to understand how turbulent flows, in real-world settings, interact with (a) rigid and/or mobile complex bed bathymetry of waterways and sea-beds in the coastal areas; (b) objects with complex geometry that are fully or partially immersed; and (c) free-surface of waterways and water surface waves in the coastal area. This understanding is especially important because the turbulent flows in real-world environments are often bounded by geometrically complex boundaries, which dynamically deform and give rise to multi-scale and multi-physics transport phenomena, and characterized by multi-lateral interactions among various phases (e.g. air/water/sediment phases). Herein, I present some of the multi-scale and multi-physics geophysical fluid mechanics processes that I have attempted to study using an in-house high-performance computational model, the so-called VFS-Geophysics. More specifically, I will present the simulation results of turbulence/sediment/solute/turbine interactions in real-world settings. Parts of the simulations I present are performed to gain scientific insights into the processes such as sand wave formation (A. Khosronejad, and F. Sotiropoulos, (2014), Numerical simulation of sand waves in a turbulent open channel flow, Journal of Fluid Mechanics, 753:150-216), while others are carried out to predict the effects of climate change and large flood events on societal infrastructures ( A. Khosronejad, et al., (2016), Large eddy simulation of turbulence and solute transport in a forested headwater stream, Journal of Geophysical Research:, doi: 10.1002/2014JF003423).

Multiscale optical simulation settings: challenging applications handled with an iterative ray-tracing FDTD interface method.

PubMed

Leiner, Claude; Nemitz, Wolfgang; Schweitzer, Susanne; Kuna, Ladislav; Wenzl, Franz P; Hartmann, Paul; Satzinger, Valentin; Sommer, Christian

2016-03-20

We show that with an appropriate combination of two optical simulation techniques-classical ray-tracing and the finite difference time domain method-an optical device containing multiple diffractive and refractive optical elements can be accurately simulated in an iterative simulation approach. We compare the simulation results with experimental measurements of the device to discuss the applicability and accuracy of our iterative simulation procedure.

A Reduced Form Model for Ozone Based on Two Decades of CMAQ Simulations for the Continental United States

EPA Science Inventory

A Reduced Form Model (RFM) is a mathematical relationship between the inputs and outputs of an air quality model, permitting estimation of additional modeling without costly new regional-scale simulations. A 21-year Community Multiscale Air Quality (CMAQ) simulation for the con...

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 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.

Prediction of protein loop conformations using multiscale modeling methods with physical energy scoring functions.

PubMed

Olson, Mark A; Feig, Michael; Brooks, Charles L

2008-04-15

This article examines ab initio methods for the prediction of protein loops by a computational strategy of multiscale conformational sampling and physical energy scoring functions. Our approach consists of initial sampling of loop conformations from lattice-based low-resolution models followed by refinement using all-atom simulations. To allow enhanced conformational sampling, the replica exchange method was implemented. Physical energy functions based on CHARMM19 and CHARMM22 parameterizations with generalized Born (GB) solvent models were applied in scoring loop conformations extracted from the lattice simulations and, in the case of all-atom simulations, the ensemble of conformations were generated and scored with these models. Predictions are reported for 25 loop segments, each eight residues long and taken from a diverse set of 22 protein structures. We find that the simulations generally sampled conformations with low global root-mean-square-deviation (RMSD) for loop backbone coordinates from the known structures, whereas clustering conformations in RMSD space and scoring detected less favorable loop structures. Specifically, the lattice simulations sampled basins that exhibited an average global RMSD of 2.21 +/- 1.42 A, whereas clustering and scoring the loop conformations determined an RMSD of 3.72 +/- 1.91 A. Using CHARMM19/GB to refine the lattice conformations improved the sampling RMSD to 1.57 +/- 0.98 A and detection to 2.58 +/- 1.48 A. We found that further improvement could be gained from extending the upper temperature in the all-atom refinement from 400 to 800 K, where the results typically yield a reduction of approximately 1 A or greater in the RMSD of the detected loop. Overall, CHARMM19 with a simple pairwise GB solvent model is more efficient at sampling low-RMSD loop basins than CHARMM22 with a higher-resolution modified analytical GB model; however, the latter simulation method provides a more accurate description of the all-atom energy surface, yet demands a much greater computational cost. (c) 2007 Wiley Periodicals, Inc.

Characterizing the SEMG patterns with myofascial pain using a multi-scale wavelet model through machine learning approaches.

PubMed

Lin, Yu-Ching; Yu, Nan-Ying; Jiang, Ching-Fen; Chang, Shao-Hsia

2018-06-02

In this paper, we introduce a newly developed multi-scale wavelet model for the interpretation of surface electromyography (SEMG) signals and validate the model's capability to characterize changes in neuromuscular activation in cases with myofascial pain syndrome (MPS) via machine learning methods. The SEMG data collected from normal (N = 30; 27 women, 3 men) and MPS subjects (N = 26; 22 women, 4 men) were adopted for this retrospective analysis. SMEGs were measured from the taut-band loci on both sides of the trapezius muscle on the upper back while he/she conducted a cyclic bilateral backward shoulder extension movement within 1 min. Classification accuracy of the SEMG model to differentiate MPS patients from normal subjects was 77% using template matching and 60% using K-means clustering. Classification consistency between the two machine learning methods was 87% in the normal group and 93% in the MPS group. The 2D feature graphs derived from the proposed multi-scale model revealed distinct patterns between normal subjects and MPS patients. The classification consistency using template matching and K-means clustering suggests the potential of using the proposed model to characterize interference pattern changes induced by MPS. Copyright © 2018. Published by Elsevier Ltd.

Quadrantal multi-scale distribution entropy analysis of heartbeat interval series based on a modified Poincaré plot

NASA Astrophysics Data System (ADS)

Huo, Chengyu; Huang, Xiaolin; Zhuang, Jianjun; Hou, Fengzhen; Ni, Huangjing; Ning, Xinbao

2013-09-01

The Poincaré plot is one of the most important approaches in human cardiac rhythm analysis. However, further investigations are still needed to concentrate on techniques that can characterize the dispersion of the points displayed by a Poincaré plot. Based on a modified Poincaré plot, we provide a novel measurement named distribution entropy (DE) and propose a quadrantal multi-scale distribution entropy analysis (QMDE) for the quantitative descriptions of the scatter distribution patterns in various regions and temporal scales. We apply this method to the heartbeat interval series derived from healthy subjects and congestive heart failure (CHF) sufferers, respectively, and find that the discriminations between them are most significant in the first quadrant, which implies significant impacts on vagal regulation brought about by CHF. We also investigate the day-night differences of young healthy people, and it is shown that the results present a clearly circadian rhythm, especially in the first quadrant. In addition, the multi-scale analysis indicates that the results of healthy subjects and CHF sufferers fluctuate in different trends with variation of the scale factor. The same phenomenon also appears in circadian rhythm investigations of young healthy subjects, which implies that the cardiac dynamic system is affected differently in various temporal scales by physiological or pathological factors.

The role of zonal flows in the saturation of multi-scale gyrokinetic turbulence

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

Staebler, G. M.; Candy, J.; Howard, N. T.

2016-06-15

The 2D spectrum of the saturated electric potential from gyrokinetic turbulence simulations that include both ion and electron scales (multi-scale) in axisymmetric tokamak geometry is analyzed. The paradigm that the turbulence is saturated when the zonal (axisymmetic) ExB flow shearing rate competes with linear growth is shown to not apply to the electron scale turbulence. Instead, it is the mixing rate by the zonal ExB velocity spectrum with the turbulent distribution function that competes with linear growth. A model of this mechanism is shown to be able to capture the suppression of electron-scale turbulence by ion-scale turbulence and the thresholdmore » for the increase in electron scale turbulence when the ion-scale turbulence is reduced. The model computes the strength of the zonal flow velocity and the saturated potential spectrum from the linear growth rate spectrum. The model for the saturated electric potential spectrum is applied to a quasilinear transport model and shown to accurately reproduce the electron and ion energy fluxes of the non-linear gyrokinetic multi-scale simulations. The zonal flow mixing saturation model is also shown to reproduce the non-linear upshift in the critical temperature gradient caused by zonal flows in ion-scale gyrokinetic simulations.« less

The role of zonal flows in the saturation of multi-scale gyrokinetic turbulence

DOE PAGES

Staebler, Gary M.; Candy, John; Howard, Nathan T.; ...

2016-06-29

The 2D spectrum of the saturated electric potential from gyrokinetic turbulence simulations that include both ion and electron scales (multi-scale) in axisymmetric tokamak geometry is analyzed. The paradigm that the turbulence is saturated when the zonal (axisymmetic) ExB flow shearing rate competes with linear growth is shown to not apply to the electron scale turbulence. Instead, it is the mixing rate by the zonal ExB velocity spectrum with the turbulent distribution function that competes with linear growth. A model of this mechanism is shown to be able to capture the suppression of electron-scale turbulence by ion-scale turbulence and the thresholdmore » for the increase in electron scale turbulence when the ion-scale turbulence is reduced. The model computes the strength of the zonal flow velocity and the saturated potential spectrum from the linear growth rate spectrum. The model for the saturated electric potential spectrum is applied to a quasilinear transport model and shown to accurately reproduce the electron and ion energy fluxes of the non-linear gyrokinetic multi-scale simulations. Finally, the zonal flow mixing saturation model is also shown to reproduce the non-linear upshift in the critical temperature gradient caused by zonal flows in ionscale gyrokinetic simulations.« less

Simulating multi-scale oceanic processes around Taiwan on unstructured grids

NASA Astrophysics Data System (ADS)

Yu, Hao-Cheng; Zhang, Yinglong J.; Yu, Jason C. S.; Terng, C.; Sun, Weiling; Ye, Fei; Wang, Harry V.; Wang, Zhengui; Huang, Hai

2017-11-01

We validate a 3D unstructured-grid (UG) model for simulating multi-scale processes as occurred in Northwestern Pacific around Taiwan using recently developed new techniques (Zhang et al., Ocean Modeling, 102, 64-81, 2016) that require no bathymetry smoothing even for this region with prevalent steep bottom slopes and many islands. The focus is on short-term forecast for several months instead of long-term variability. Compared with satellite products, the errors for the simulated Sea-surface Height (SSH) and Sea-surface Temperature (SST) are similar to a reference data-assimilated global model. In the nearshore region, comparison with 34 tide gauges located around Taiwan indicates an average RMSE of 13 cm for the tidal elevation. The average RMSE for SST at 6 coastal buoys is 1.2 °C. The mean transport and eddy kinetic energy compare reasonably with previously published values and the reference model used to provide boundary and initial conditions. The model suggests ∼2-day interruption of Kuroshio east of Taiwan during a typhoon period. The effect of tidal mixing is shown to be significant nearshore. The multi-scale model is easily extendable to target regions of interest due to its UG framework and a flexible vertical gridding system, which is shown to be superior to terrain-following coordinates.

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

Persistence of initial conditions in continental scale air quality simulations

EPA Science Inventory

This study investigates the effect of initial conditions (IC) for pollutant concentrations in the atmosphere and soil on simulated air quality for two continental-scale Community Multiscale Air Quality (CMAQ) model applications. One of these applications was performed for springt...

Statistical CT noise reduction with multiscale decomposition and penalized weighted least squares in the projection domain

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

Tang Shaojie; Tang Xiangyang; School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi 710121

2012-09-15

Purposes: The suppression of noise in x-ray computed tomography (CT) imaging is of clinical relevance for diagnostic image quality and the potential for radiation dose saving. Toward this purpose, statistical noise reduction methods in either the image or projection domain have been proposed, which employ a multiscale decomposition to enhance the performance of noise suppression while maintaining image sharpness. Recognizing the advantages of noise suppression in the projection domain, the authors propose a projection domain multiscale penalized weighted least squares (PWLS) method, in which the angular sampling rate is explicitly taken into consideration to account for the possible variation ofmore » interview sampling rate in advanced clinical or preclinical applications. Methods: The projection domain multiscale PWLS method is derived by converting an isotropic diffusion partial differential equation in the image domain into the projection domain, wherein a multiscale decomposition is carried out. With adoption of the Markov random field or soft thresholding objective function, the projection domain multiscale PWLS method deals with noise at each scale. To compensate for the degradation in image sharpness caused by the projection domain multiscale PWLS method, an edge enhancement is carried out following the noise reduction. The performance of the proposed method is experimentally evaluated and verified using the projection data simulated by computer and acquired by a CT scanner. Results: The preliminary results show that the proposed projection domain multiscale PWLS method outperforms the projection domain single-scale PWLS method and the image domain multiscale anisotropic diffusion method in noise reduction. In addition, the proposed method can preserve image sharpness very well while the occurrence of 'salt-and-pepper' noise and mosaic artifacts can be avoided. Conclusions: Since the interview sampling rate is taken into account in the projection domain multiscale decomposition, the proposed method is anticipated to be useful in advanced clinical and preclinical applications where the interview sampling rate varies.« less

Validation and Calibration of Nuclear Thermal Hydraulics Multiscale Multiphysics Models - Subcooled Flow Boiling Study

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

Anh Bui; Nam Dinh; Brian Williams

In addition to validation data plan, development of advanced techniques for calibration and validation of complex multiscale, multiphysics nuclear reactor simulation codes are a main objective of the CASL VUQ plan. Advanced modeling of LWR systems normally involves a range of physico-chemical models describing multiple interacting phenomena, such as thermal hydraulics, reactor physics, coolant chemistry, etc., which occur over a wide range of spatial and temporal scales. To a large extent, the accuracy of (and uncertainty in) overall model predictions is determined by the correctness of various sub-models, which are not conservation-laws based, but empirically derived from measurement data. Suchmore » sub-models normally require extensive calibration before the models can be applied to analysis of real reactor problems. This work demonstrates a case study of calibration of a common model of subcooled flow boiling, which is an important multiscale, multiphysics phenomenon in LWR thermal hydraulics. The calibration process is based on a new strategy of model-data integration, in which, all sub-models are simultaneously analyzed and calibrated using multiple sets of data of different types. Specifically, both data on large-scale distributions of void fraction and fluid temperature and data on small-scale physics of wall evaporation were simultaneously used in this work’s calibration. In a departure from traditional (or common-sense) practice of tuning/calibrating complex models, a modern calibration technique based on statistical modeling and Bayesian inference was employed, which allowed simultaneous calibration of multiple sub-models (and related parameters) using different datasets. Quality of data (relevancy, scalability, and uncertainty) could be taken into consideration in the calibration process. This work presents a step forward in the development and realization of the “CIPS Validation Data Plan” at the Consortium for Advanced Simulation of LWRs to enable quantitative assessment of the CASL modeling of Crud-Induced Power Shift (CIPS) phenomenon, in particular, and the CASL advanced predictive capabilities, in general. This report is prepared for the Department of Energy’s Consortium for Advanced Simulation of LWRs program’s VUQ Focus Area.« less

Multiscale entropy analysis of human gait dynamics

NASA Astrophysics Data System (ADS)

Costa, M.; Peng, C.-K.; L. Goldberger, Ary; Hausdorff, Jeffrey M.

2003-12-01

We compare the complexity of human gait time series from healthy subjects under different conditions. Using the recently developed multiscale entropy algorithm, which provides a way to measure complexity over a range of scales, we observe that normal spontaneous walking has the highest complexity when compared to slow and fast walking and also to walking paced by a metronome. These findings have implications for modeling locomotor control and for quantifying gait dynamics in physiologic and pathologic states.

Development of a Renormalization Group Approach to Multi-Scale Plasma Physics Computation

DTIC Science & Technology

2012-03-28

with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1...NUMBER(S) 12. DISTRIBUTION/AVAILABILITY STATEMENT 13. SUPPLEMENTARY NOTES 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: a . REPORT...code) 29-12-2008 Final Technical Report From 29-12-2008 To 16-95-2011 (STTR PHASE II) DEVELOPMENT OF A RENORMALIZATION GROUP APPROACH TO MULTI-SCALE

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

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

Multiscale power analysis for heart rate variability

NASA Astrophysics Data System (ADS)

Zeng, Peng; Liu, Hongxing; Ni, Huangjing; Zhou, Jing; Xia, Lan; Ning, Xinbao

2015-06-01

We first introduce multiscale power (MSP) method to assess the power distribution of physiological signals on multiple time scales. Simulation on synthetic data and experiments on heart rate variability (HRV) are tested to support the approach. Results show that both physical and psychological changes influence power distribution significantly. A quantitative parameter, termed power difference (PD), is introduced to evaluate the degree of power distribution alteration. We find that dynamical correlation of HRV will be destroyed completely when PD>0.7.

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

EPA Pesticide Factsheets

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

Wavelet-based multiscale analysis of minimum toe clearance variability in the young and elderly during walking.

PubMed

Khandoker, Ahsan H; Karmakar, Chandan K; Begg, Rezaul K; Palaniswami, Marimuthu

2007-01-01

As humans age or are influenced by pathology of the neuromuscular system, gait patterns are known to adjust, accommodating for reduced function in the balance control system. The aim of this study was to investigate the effectiveness of a wavelet based multiscale analysis of a gait variable [minimum toe clearance (MTC)] in deriving indexes for understanding age-related declines in gait performance and screening of balance impairments in the elderly. MTC during walking on a treadmill for 30 healthy young, 27 healthy elderly and 10 falls risk elderly subjects with a history of tripping falls were analyzed. The MTC signal from each subject was decomposed to eight detailed signals at different wavelet scales by using the discrete wavelet transform. The variances of detailed signals at scales 8 to 1 were calculated. The multiscale exponent (beta) was then estimated from the slope of the variance progression at successive scales. The variance at scale 5 was significantly (p<0.01) different between young and healthy elderly group. Results also suggest that the Beta between scales 1 to 2 are effective for recognizing falls risk gait patterns. Results have implication for quantifying gait dynamics in normal, ageing and pathological conditions. Early detection of gait pattern changes due to ageing and balance impairments using wavelet-based multiscale analysis might provide the opportunity to initiate preemptive measures to be undertaken to avoid injurious falls.

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

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.

Antipsychotics reverse abnormal EEG complexity in drug-naïve schizophrenia: A multiscale entropy analysis

PubMed Central

Takahashi, Tetsuya; Cho, Raymond Y.; Mizuno, Tomoyuki; Kikuchi, Mitsuru; Murata, Tetsuhito; Takahashi, Koichi; Wada, Yuji

2010-01-01

Multiscale entropy (MSE) analysis is a novel entropy-based approach for measuring dynamical complexity in physiological systems over a range of temporal scales. To evaluate this analytic approach as an aid to elucidating the pathophysiologic mechanisms in schizophrenia, we examined MSE in EEG activity in drug-naïve schizophrenia subjects pre- and post-treatment with antipsychotics in comparison with traditional EEG analysis. We recorded eyes-closed resting state EEG from frontal, temporal, parietal and occipital regions in drug-naïve 22 schizophrenia and 24 age-matched healthy control subjects. Fifteen patients were re-evaluated within 2–8 weeks after the initiation of antipsychotic treatment. For each participant, MSE was calculated on one continuous 60 second epoch for each experimental session. Schizophrenia subjects showed significantly higher complexity at higher time scales (lower frequencies), than that of healthy controls in fronto-centro-temporal, but not in parieto-occipital regions. Post-treatment, this higher complexity decreased to healthy control subject levels selectively in fronto-central regions, while the increased complexity in temporal sites remained higher. Comparative power analysis identified spectral slowing in frontal regions in pre-treatment schizophrenia subjects, consistent with previous findings, whereas no antipsychotic treatment effect was observed. In summary, multiscale entropy measures identified abnormal dynamical EEG signal complexity in anterior brain areas in schizophrenia that normalized selectively in fronto-central areas with antipsychotic treatment. These findings show that entropy-based analytic methods may serve as a novel approach for characterizing and understanding abnormal cortical dynamics in schizophrenia, and elucidating the therapeutic mechanisms of antipsychotics. PMID:20149880

Thermo-Oxidative Induced Damage in Polymer Composites: Microstructure Image-Based Multi-Scale Modeling and Experimental Validation

NASA Astrophysics Data System (ADS)

Hussein, Rafid M.; Chandrashekhara, K.

2017-11-01

A multi-scale modeling approach is presented to simulate and validate thermo-oxidation shrinkage and cracking damage of a high temperature polymer composite. The multi-scale approach investigates coupled transient diffusion-reaction and static structural at macro- to micro-scale. The micro-scale shrinkage deformation and cracking damage are simulated and validated using 2D and 3D simulations. Localized shrinkage displacement boundary conditions for the micro-scale simulations are determined from the respective meso- and macro-scale simulations, conducted for a cross-ply laminate. The meso-scale geometrical domain and the micro-scale geometry and mesh are developed using the object oriented finite element (OOF). The macro-scale shrinkage and weight loss are measured using unidirectional coupons and used to build the macro-shrinkage model. The cross-ply coupons are used to validate the macro-shrinkage model by the shrinkage profiles acquired using scanning electron images at the cracked surface. The macro-shrinkage model deformation shows a discrepancy when the micro-scale image-based cracking is computed. The local maximum shrinkage strain is assumed to be 13 times the maximum macro-shrinkage strain of 2.5 × 10-5, upon which the discrepancy is minimized. The microcrack damage of the composite is modeled using a static elastic analysis with extended finite element and cohesive surfaces by considering the modulus spatial evolution. The 3D shrinkage displacements are fed to the model using node-wise boundary/domain conditions of the respective oxidized region. Microcrack simulation results: length, meander, and opening are closely matched to the crack in the area of interest for the scanning electron images.

Hybrid stochastic simplifications for multiscale gene networks.

PubMed

Crudu, Alina; Debussche, Arnaud; Radulescu, Ovidiu

2009-09-07

Stochastic simulation of gene networks by Markov processes has important applications in molecular biology. The complexity of exact simulation algorithms scales with the number of discrete jumps to be performed. Approximate schemes reduce the computational time by reducing the number of simulated discrete events. Also, answering important questions about the relation between network topology and intrinsic noise generation and propagation should be based on general mathematical results. These general results are difficult to obtain for exact models. We propose a unified framework for hybrid simplifications of Markov models of multiscale stochastic gene networks dynamics. We discuss several possible hybrid simplifications, and provide algorithms to obtain them from pure jump processes. In hybrid simplifications, some components are discrete and evolve by jumps, while other components are continuous. Hybrid simplifications are obtained by partial Kramers-Moyal expansion [1-3] which is equivalent to the application of the central limit theorem to a sub-model. By averaging and variable aggregation we drastically reduce simulation time and eliminate non-critical reactions. Hybrid and averaged simplifications can be used for more effective simulation algorithms and for obtaining general design principles relating noise to topology and time scales. The simplified models reproduce with good accuracy the stochastic properties of the gene networks, including waiting times in intermittence phenomena, fluctuation amplitudes and stationary distributions. The methods are illustrated on several gene network examples. Hybrid simplifications can be used for onion-like (multi-layered) approaches to multi-scale biochemical systems, in which various descriptions are used at various scales. Sets of discrete and continuous variables are treated with different methods and are coupled together in a physically justified approach.

Projected 2050 Model Simulations for the Chesapeake Bay ...

EPA Pesticide Factsheets

The Chesapeake Bay Program as has been tasked with assessing how changes in climate systems are expected to alter key variables and processes within the Watershed in concurrence with land use changes. EPA’s Office of Research and Development will be conducting historic and future, 2050, Weather Research and Forecast (WRF) metrological and Community Multiscale Air Quality (CMAQ) chemical transport model simulations to provide meteorological and nutrient deposition estimates for inclusion of the Chesapeake Bay Program’s assessment of how climate and land use change may impact water quality and ecosystem health. This presentation will present the timeline and research updates. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Mesoscale modeling of solute precipitation and radiation damage

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

Zhang, Yongfeng; Schwen, Daniel; Ke, Huibin

2015-09-01

This report summarizes the low length scale effort during FY 2014 in developing mesoscale capabilities for microstructure evolution in reactor pressure vessels. During operation, reactor pressure vessels are subject to hardening and embrittlement caused by irradiation-induced defect accumulation and irradiation-enhanced solute precipitation. Both defect production and solute precipitation start from the atomic scale, and manifest their eventual effects as degradation in engineering-scale properties. To predict the property degradation, multiscale modeling and simulation are needed to deal with the microstructure evolution, and to link the microstructure feature to material properties. In this report, the development of mesoscale capabilities for defect accumulationmore » and solute precipitation are summarized. Atomic-scale efforts that supply information for the mesoscale capabilities are also included.« less

Iterative Self-Dual Reconstruction on Radar Image Recovery

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

Martins, Charles; Medeiros, Fatima; Ushizima, Daniela

2010-05-21

Imaging systems as ultrasound, sonar, laser and synthetic aperture radar (SAR) are subjected to speckle noise during image acquisition. Before analyzing these images, it is often necessary to remove the speckle noise using filters. We combine properties of two mathematical morphology filters with speckle statistics to propose a signal-dependent noise filter to multiplicative noise. We describe a multiscale scheme that preserves sharp edges while it smooths homogeneous areas, by combining local statistics with two mathematical morphology filters: the alternating sequential and the self-dual reconstruction algorithms. The experimental results show that the proposed approach is less sensitive to varying window sizesmore » when applied to simulated and real SAR images in comparison with standard filters.« less

Multi-scale heterogeneity of the 2011 Great Tohoku-oki Earthquake from dynamic simulations

NASA Astrophysics Data System (ADS)

Aochi, H.; Ide, S.

2011-12-01

In order to explain the scaling issues of earthquakes of different sizes, multi-scale heterogeneity conception is necessary to characterize earthquake faulting property (Ide and Aochi, JGR, 2005; Aochi and Ide, JGR, 2009).The 2011 Great Tohoku-oki earthquake (M9) is characterized by a slow initial phase of about M7, a M8 class deep rupture, and a M9 main rupture with quite large slip near the trench (e.g. Ide et al., Science, 2011) as well as the presence of foreshocks. We dynamically model these features based on the multi-scale conception. We suppose a significantly large fracture energy (corresponding to slip-weakening distance of 3.2 m) in most of the fault dimension to represent the M9 rupture. However we give local heterogeneity with relatively small circular patches of smaller fracture energy, by assuming the linear scaling relation between the radius and fracture energy. The calculation is carried out using 3D Boundary Integral Equation Method. We first begin only with the mainshock (Aochi and Ide, EPS, 2011), but later we find it important to take into account of a series of foreshocks since the 9th March (M7.4). The smaller patches including the foreshock area are necessary to launch the M9 rupture area of large fracture energy. We then simulate the ground motion in low frequencies using Finite Difference Method. Qualitatively, the observed tendency is consistent with our simulations, in the meaning of the transition from the central part to the southern part in low frequencies (10 - 20 sec). At higher frequencies (1-10 sec), further small asperities are inferred in the observed signals, and this feature matches well with our multi-scale conception.

Low-Frequency Oscillations and Transport Processes Induced by Multiscale Transverse Structures in the Polar Wind Outflow: A Three-Dimensional Simulation

NASA Technical Reports Server (NTRS)

Ganguli, Supriya B.; Gavrishchaka, Valeriy V.

1999-01-01

Multiscale transverse structures in the magnetic-field-aligned flows have been frequently observed in the auroral region by FAST and Freja satellites. A number of multiscale processes, such as broadband low-frequency oscillations and various cross-field transport effects are well correlated with these structures. To study these effects, we have used our three-dimensional multifluid model with multiscale transverse inhomogeneities in the initial velocity profile. Self-consistent-frequency mode driven by local transverse gradients in the generation of the low field-aligned ion flow and associated transport processes were simulated. Effects of particle interaction with the self-consistent time-dependent three-dimensional wave potential have been modeled using a distribution of test particles. For typical polar wind conditions it has been found that even large-scale (approximately 50 - 100 km) transverse inhomogeneities in the flow can generate low-frequency oscillations that lead to significant flow modifications, cross-field particle diffusion, and other transport effects. It has also been shown that even small-amplitude (approximately 10 - 20%) short-scale (approximately 10 km) modulations of the original large-scale flow profile significantly increases low-frequency mode generation and associated cross-field transport, not only at the local spatial scales imposed by the modulations but also on global scales. Note that this wave-induced cross-field transport is not included in any of the global numerical models of the ionosphere, ionosphere-thermosphere, or ionosphere-polar wind. The simulation results indicate that the wave-induced cross-field transport not only affects the ion outflow rates but also leads to a significant broadening of particle phase-space distribution and transverse particle diffusion.

How well do the GCMs/RCMs capture the multi-scale temporal variability of precipitation in the Southwestern United States?

NASA Astrophysics Data System (ADS)

Jiang, Peng; Gautam, Mahesh R.; Zhu, Jianting; Yu, Zhongbo

2013-02-01

SummaryMulti-scale temporal variability of precipitation has an established relationship with floods and droughts. In this paper, we present the diagnostics on the ability of 16 General Circulation Models (GCMs) from Bias Corrected and Downscaled (BCSD) World Climate Research Program's (WCRP's) Coupled Model Inter-comparison Project Phase 3 (CMIP3) projections and 10 Regional Climate Models (RCMs) that participated in the North American Regional Climate Change Assessment Program (NARCCAP) to represent multi-scale temporal variability determined from the observed station data. Four regions (Los Angeles, Las Vegas, Tucson, and Cimarron) in the Southwest United States are selected as they represent four different precipitation regions classified by clustering method. We investigate how storm properties and seasonal, inter-annual, and decadal precipitation variabilities differed between GCMs/RCMs and observed records in these regions. We find that current GCMs/RCMs tend to simulate longer storm duration and lower storm intensity compared to those from observed records. Most GCMs/RCMs fail to produce the high-intensity summer storms caused by local convective heat transport associated with the summer monsoon. Both inter-annual and decadal bands are present in the GCM/RCM-simulated precipitation time series; however, these do not line up to the patterns of large-scale ocean oscillations such as El Nino/La Nina Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Our results show that the studied GCMs/RCMs can capture long-term monthly mean as the examined data is bias-corrected and downscaled, but fail to simulate the multi-scale precipitation variability including flood generating extreme events, which suggests their inadequacy for studies on floods and droughts that are strongly associated with multi-scale temporal precipitation variability.

Multiscale Modeling of Novel Carbon Nanotube/Copper-Composite Material Used in Microelectronics

NASA Astrophysics Data System (ADS)

Awad, Ibrahim; Ladani, Leila

2016-06-01

Current carrying capacity is one of the elements that hinders further miniaturization of Copper (Cu) interconnects. Therefore, there is a need to propose new materials with higher ampacity (current carrying capacity) that have the potential to replace Cu. Experimental observations have shown that Carbon Nanotube (CNT)/Cu-composite material has a hundredfold ampacity of Cu, which makes it a good candidate to replace Cu. However, sufficient information about the mechanical behavior of the novel CNT/Cu-composite is not available. In the current paper, the CNT/Cu-composite is utilized to construct Through Silicon Via (TSV). The mechanical behavior, specifically the fatigue life, of the CNT/Cu-TSV is evaluated by applying a multiscale modeling approach. Molecular Dynamics (MD) simulations are conducted to evaluate the tensile strength and the coefficient of thermal expansion of CNTs. MD simulation is also used to determine the interface behavior between CNTs and Cu. MD simulation results are integrated into Finite Element analysis at the micro-level to estimate the fatigue life of the CNT/Cu-TSV. A comparison is made with base material; Cu. CNTs addition has redistributed the plastic deformation in Cu to occur at two different locations (Si/Cu interface and Cu/CNT interface) instead of only one location (Si/Cu interface) in the case of Cu-only-TSV. Thus, the maximum equivalent plastic strain has been alleviated in the CNT/Cu-TSV. Accordingly, CNT/Cu-TSV has shown a threefold increase in the fatigue life. This is a solid indication of the improvement in the fatigue life that is attributed to the addition of CNTs.

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

Next generation multi-scale biophysical characterization of high precision cancer particle radiotherapy using clinical proton, helium-, carbon- and oxygen ion beams

PubMed Central

Niklas, Martin; Zimmermann, Ferdinand; Chaudhri, Naved; Krunic, Damir; Tessonnier, Thomas; Ferrari, Alfredo; Parodi, Katia; Jäkel, Oliver; Debus, Jürgen; Haberer, Thomas; Abdollahi, Amir

2016-01-01

The growing number of particle therapy facilities worldwide landmarks a novel era of precision oncology. Implementation of robust biophysical readouts is urgently needed to assess the efficacy of different radiation qualities. This is the first report on biophysical evaluation of Monte Carlo simulated predictive models of prescribed dose for four particle qualities i.e., proton, helium-, carbon- or oxygen ions using raster-scanning technology and clinical therapy settings at HIT. A high level of agreement was found between the in silico simulations, the physical dosimetry and the clonogenic tumor cell survival. The cell fluorescence ion track hybrid detector (Cell-Fit-HD) technology was employed to detect particle traverse per cell nucleus. Across a panel of radiobiological surrogates studied such as late ROS accumulation and apoptosis (caspase 3/7 activation), the relative biological effectiveness (RBE) chiefly correlated with the radiation species-specific spatio-temporal pattern of DNA double strand break (DSB) formation and repair kinetic. The size and the number of residual nuclear γ-H2AX foci increased as a function of linear energy transfer (LET) and RBE, reminiscent of enhanced DNA-damage complexity and accumulation of non-repairable DSB. These data confirm the high relevance of complex DSB formation as a central determinant of cell fate and reliable biological surrogates for cell survival/RBE. The multi-scale simulation, physical and radiobiological characterization of novel clinical quality beams presented here constitutes a first step towards development of high precision biologically individualized radiotherapy. PMID:27494855

Analysis of surface EMG baseline for detection of hidden muscle activity

NASA Astrophysics Data System (ADS)

Zhang, Xu; Zhou, Ping

2014-02-01

Objective. This study explored the feasibility of detecting hidden muscle activity in surface electromyogram (EMG) baseline. Approach. Power spectral density (PSD) analysis and multi-scale entropy (MSE) analysis were used. Both analyses were applied to computer simulations of surface EMG baseline with the presence (representing activity data) or absence (representing reference data) of hidden muscle activity, as well as surface electrode array EMG baseline recordings of healthy control and amyotrophic lateral sclerosis (ALS) subjects. Main results. Although the simulated reference data and the activity data yielded no distinguishable difference in the time domain, they demonstrated a significant difference in the frequency and signal complexity domains with the PSD and MSE analyses. For a comparison using pooled data, such a difference was also observed when the PSD and MSE analyses were applied to surface electrode array EMG baseline recordings of healthy control and ALS subjects, which demonstrated no distinguishable difference in the time domain. Compared with the PSD analysis, the MSE analysis appeared to be more sensitive for detecting the difference in surface EMG baselines between the two groups. Significance. The findings implied the presence of a hidden muscle activity in surface EMG baseline recordings from the ALS subjects. To promote the presented analysis as a useful diagnostic or investigatory tool, future studies are necessary to assess the pathophysiological nature or origins of the hidden muscle activity, as well as the baseline difference at the individual subject level.

Analysis of Surface EMG Baseline for Detection of Hidden Muscle Activity

PubMed Central

Zhang, Xu; Zhou, Ping

2014-01-01

Objective This study explored the feasibility of detecting hidden muscle activity in surface electromyogram (EMG) baseline. Approach Power spectral density (PSD) analysis and multi-scale entropy (MSE) analysis were used respectively. Both analyses were applied to computer simulations of surface EMG baseline with presence (representing activity data) or absence (representing reference data) of hidden muscle activity, as well as surface electrode array EMG baseline recordings of healthy control and amyotrophic lateral sclerosis (ALS) subjects. Main results Although the simulated reference data and the activity data yielded no distinguishable difference in the time domain, they demonstrated a significant difference in the frequency and signal complexity domains with the PSD and MSE analyses. For a comparison using pooled data, such a difference was also observed when the PSD and MSE analyses were applied to surface electrode array EMG baseline recordings of healthy control and ALS subjects, which demonstrated no distinguishable difference in the time domain. Compared with the PSD analysis, the MSE analysis appeared to be more sensitive for detecting the difference in surface EMG baselines between the two groups. Significance The findings implied presence of hidden muscle activity in surface EMG baseline recordings from the ALS subjects. To promote the presented analysis as a useful diagnostic or investigatory tool, future studies are necessary to assess the pathophysiological nature or origins of the hidden muscle activity, as well as the baseline difference at the individual subject level. PMID:24445526

Cluster-guided imaging-based CFD analysis of airflow and particle deposition in asthmatic human lungs

NASA Astrophysics Data System (ADS)

Choi, Jiwoong; Leblanc, Lawrence; Choi, Sanghun; Haghighi, Babak; Hoffman, Eric; Lin, Ching-Long

2017-11-01

The goal of this study is to assess inter-subject variability in delivery of orally inhaled drug products to small airways in asthmatic lungs. A recent multiscale imaging-based cluster analysis (MICA) of computed tomography (CT) lung images in an asthmatic cohort identified four clusters with statistically distinct structural and functional phenotypes associating with unique clinical biomarkers. Thus, we aimed to address inter-subject variability via inter-cluster variability. We selected a representative subject from each of the 4 asthma clusters as well as 1 male and 1 female healthy controls, and performed computational fluid and particle simulations on CT-based airway models of these subjects. The results from one severe and one non-severe asthmatic cluster subjects characterized by segmental airway constriction had increased particle deposition efficiency, as compared with the other two cluster subjects (one non-severe and one severe asthmatics) without airway constriction. Constriction-induced jets impinging on distal bifurcations led to excessive particle deposition. The results emphasize the impact of airway constriction on regional particle deposition rather than disease severity, demonstrating the potential of using cluster membership to tailor drug delivery. NIH Grants U01HL114494 and S10-RR022421, and FDA Grant U01FD005837. XSEDE.

“Skin-Core-Skin” Structure of Polymer Crystallization Investigated by Multiscale Simulation

PubMed Central

Ruan, Chunlei

2018-01-01

“Skin-core-skin” structure is a typical crystal morphology in injection products. Previous numerical works have rarely focused on crystal evolution; rather, they have mostly been based on the prediction of temperature distribution or crystallization kinetics. The aim of this work was to achieve the “skin-core-skin” structure and investigate the role of external flow and temperature fields on crystal morphology. Therefore, the multiscale algorithm was extended to the simulation of polymer crystallization in a pipe flow. The multiscale algorithm contains two parts: a collocated finite volume method at the macroscopic level and a morphological Monte Carlo method at the microscopic level. The SIMPLE (semi-implicit method for pressure linked equations) algorithm was used to calculate the polymeric model at the macroscopic level, while the Monte Carlo method with stochastic birth-growth process of spherulites and shish-kebabs was used at the microscopic level. Results show that our algorithm is valid to predict “skin-core-skin” structure, and the initial melt temperature and the maximum velocity of melt at the inlet mainly affects the morphology of shish-kebabs. PMID:29659516

Towards a new multiscale air quality transport model using the fully unstructured anisotropic adaptive mesh technology of Fluidity (version 4.1.9)

NASA Astrophysics Data System (ADS)

Zheng, J.; Zhu, J.; Wang, Z.; Fang, F.; Pain, C. C.; Xiang, J.

2015-10-01

An integrated method of advanced anisotropic hr-adaptive mesh and discretization numerical techniques has been, for first time, applied to modelling of multiscale advection-diffusion problems, which is based on a discontinuous Galerkin/control volume discretization on unstructured meshes. Over existing air quality models typically based on static-structured grids using a locally nesting technique, the advantage of the anisotropic hr-adaptive model has the ability to adapt the mesh according to the evolving pollutant distribution and flow features. That is, the mesh resolution can be adjusted dynamically to simulate the pollutant transport process accurately and effectively. To illustrate the capability of the anisotropic adaptive unstructured mesh model, three benchmark numerical experiments have been set up for two-dimensional (2-D) advection phenomena. Comparisons have been made between the results obtained using uniform resolution meshes and anisotropic adaptive resolution meshes. Performance achieved in 3-D simulation of power plant plumes indicates that this new adaptive multiscale model has the potential to provide accurate air quality modelling solutions effectively.

Complexity and multifractal behaviors of multiscale-continuum percolation financial system for Chinese stock markets

NASA Astrophysics Data System (ADS)

Zeng, Yayun; Wang, Jun; Xu, Kaixuan

2017-04-01

A new financial agent-based time series model is developed and investigated by multiscale-continuum percolation system, which can be viewed as an extended version of continuum percolation system. In this financial model, for different parameters of proportion and density, two Poisson point processes (where the radii of points represent the ability of receiving or transmitting information among investors) are applied to model a random stock price process, in an attempt to investigate the fluctuation dynamics of the financial market. To validate its effectiveness and rationality, we compare the statistical behaviors and the multifractal behaviors of the simulated data derived from the proposed model with those of the real stock markets. Further, the multiscale sample entropy analysis is employed to study the complexity of the returns, and the cross-sample entropy analysis is applied to measure the degree of asynchrony of return autocorrelation time series. The empirical results indicate that the proposed financial model can simulate and reproduce some significant characteristics of the real stock markets to a certain extent.

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.

A multi-scale model for hair follicles reveals heterogeneous domains driving rapid spatiotemporal hair growth patterning

PubMed Central

Wang, Qixuan; Oh, Ji Won; Lee, Hye-Lim; Dhar, Anukriti; Peng, Tao; Ramos, Raul; Guerrero-Juarez, Christian Fernando; Wang, Xiaojie; Zhao, Ran; Cao, Xiaoling; Le, Jonathan; Fuentes, Melisa A; Jocoy, Shelby C; Rossi, Antoni R; Vu, Brian; Pham, Kim; Wang, Xiaoyang; Mali, Nanda Maya; Park, Jung Min; Choi, June-Hyug; Lee, Hyunsu; Legrand, Julien M D; Kandyba, Eve; Kim, Jung Chul; Kim, Moonkyu; Foley, John; Yu, Zhengquan; Kobielak, Krzysztof; Andersen, Bogi; Khosrotehrani, Kiarash; Nie, Qing; Plikus, Maksim V

2017-01-01

The control principles behind robust cyclic regeneration of hair follicles (HFs) remain unclear. Using multi-scale modeling, we show that coupling inhibitors and activators with physical growth of HFs is sufficient to drive periodicity and excitability of hair regeneration. Model simulations and experimental data reveal that mouse skin behaves as a heterogeneous regenerative field, composed of anatomical domains where HFs have distinct cycling dynamics. Interactions between fast-cycling chin and ventral HFs and slow-cycling dorsal HFs produce bilaterally symmetric patterns. Ear skin behaves as a hyper-refractory domain with HFs in extended rest phase. Such hyper-refractivity relates to high levels of BMP ligands and WNT antagonists, in part expressed by ear-specific cartilage and muscle. Hair growth stops at the boundaries with hyper-refractory ears and anatomically discontinuous eyelids, generating wave-breaking effects. We posit that similar mechanisms for coupled regeneration with dominant activator, hyper-refractory, and wave-breaker regions can operate in other actively renewing organs. DOI: http://dx.doi.org/10.7554/eLife.22772.001 PMID:28695824

Multi-Scale Modeling and the Eddy-Diffusivity/Mass-Flux (EDMF) Parameterization

NASA Astrophysics Data System (ADS)

Teixeira, J.

2015-12-01

Turbulence and convection play a fundamental role in many key weather and climate science topics. Unfortunately, current atmospheric models cannot explicitly resolve most turbulent and convective flow. Because of this fact, turbulence and convection in the atmosphere has to be parameterized - i.e. equations describing the dynamical evolution of the statistical properties of turbulence and convection motions have to be devised. Recently a variety of different models have been developed that attempt at simulating the atmosphere using variable resolution. A key problem however is that parameterizations are in general not explicitly aware of the resolution - the scale awareness problem. In this context, we will present and discuss a specific approach, the Eddy-Diffusivity/Mass-Flux (EDMF) parameterization, that not only is in itself a multi-scale parameterization but it is also particularly well suited to deal with the scale-awareness problems that plague current variable-resolution models. It does so by representing small-scale turbulence using a classic Eddy-Diffusivity (ED) method, and the larger-scale (boundary layer and tropospheric-scale) eddies as a variety of plumes using the Mass-Flux (MF) concept.

Three steps to gold: mechanism of protein adsorption revealed by Brownian and molecular dynamics simulations.

PubMed

Ozboyaci, M; Kokh, D B; Wade, R C

2016-04-21

The addition of three N-terminal histidines to β-lactamase inhibitor protein was shown experimentally to increase its binding potency to an Au(111) surface substantially but the binding mechanism was not resolved. Here, we propose a complete adsorption mechanism for this fusion protein by means of a multi-scale simulation approach and free energy calculations. We find that adsorption is a three-step process: (i) recognition of the surface predominantly by the histidine fusion peptide and formation of an encounter complex facilitated by a reduced dielectric screening of water in the interfacial region, (ii) adsorption of the protein on the surface and adoption of a specific binding orientation, and (iii) adaptation of the protein structure on the metal surface accompanied by induced fit. We anticipate that the mechanistic features of protein adsorption to an Au(111) surface revealed here can be extended to other inorganic surfaces and proteins and will therefore aid the design of specific protein-surface interactions.

ATMOSPHERIC MERCURY SIMULATION USING THE CMAQ MODEL: FORMULATION DESCRIPTION AND ANALYSIS OF WET DEPOSITION RESULTS

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) modeling system has recently been adapted to simulate the emission, transport, transformation and deposition of atmospheric mercury in three distinct forms; elemental mercury gas, reactive gaseous mercury, and particulate mercury. Emis...

Modeling Solar Wind Flow with the Multi-Scale Fluid-Kinetic Simulation Suite

DOE PAGES

Pogorelov, N.V.; Borovikov, S. N.; Bedford, M. C.; ...

2013-04-01

Multi-Scale Fluid-Kinetic Simulation Suite (MS-FLUKSS) is a package of numerical codes capable of performing adaptive mesh refinement simulations of complex plasma flows in the presence of discontinuities and charge exchange between ions and neutral atoms. The flow of the ionized component is described with the ideal MHD equations, while the transport of atoms is governed either by the Boltzmann equation or multiple Euler gas dynamics equations. We have enhanced the code with additional physical treatments for the transport of turbulence and acceleration of pickup ions in the interplanetary space and at the termination shock. In this article, we present themore » results of our numerical simulation of the solar wind (SW) interaction with the local interstellar medium (LISM) in different time-dependent and stationary formulations. Numerical results are compared with the Ulysses, Voyager, and OMNI observations. Finally, the SW boundary conditions are derived from in-situ spacecraft measurements and remote observations.« less

Molecular origin of differences in hole and electron mobility in amorphous Alq3--a multiscale simulation study.

PubMed

Fuchs, Andreas; Steinbrecher, Thomas; Mommer, Mario S; Nagata, Yuki; Elstner, Marcus; Lennartz, Christian

2012-03-28

In order to determine the molecular origin of the difference in electron and hole mobilities of amorphous thin films of Alq(3) (meridional Alq(3) (tris(8-hydroxyquinoline) aluminium)) we performed multiscale simulations covering quantum mechanics, molecular mechanics and lattice models. The study includes realistic disordered morphologies, polarized site energies to describe diagonal disorder, quantum chemically calculated transfer integrals for the off-diagonal disorder, inner sphere reorganization energies and an approximative scheme for outer sphere reorganization energies. Intermolecular transfer rates were calculated via Marcus-theory and mobilities were simulated via kinetic Monte Carlo simulations and by a Master Equation approach. The difference in electron and hole mobility originates from the different localization of charge density in the radical anion (more delocalized) compared to the radical cation (more confined). This results in higher diagonal disorder for holes and less favourable overlap properties for the hole transfer integrals leading to an overall higher electron mobility.

Realistic Modeling of Multi-Scale MHD Dynamics of the Solar Atmosphere

NASA Technical Reports Server (NTRS)

Kitiashvili, Irina; Mansour, Nagi N.; Wray, Alan; Couvidat, Sebastian; Yoon, Seokkwan; Kosovichev, Alexander

2014-01-01

Realistic 3D radiative MHD simulations open new perspectives for understanding the turbulent dynamics of the solar surface, its coupling to the atmosphere, and the physical mechanisms of generation and transport of non-thermal energy. Traditionally, plasma eruptions and wave phenomena in the solar atmosphere are modeled by prescribing artificial driving mechanisms using magnetic or gas pressure forces that might arise from magnetic field emergence or reconnection instabilities. In contrast, our 'ab initio' simulations provide a realistic description of solar dynamics naturally driven by solar energy flow. By simulating the upper convection zone and the solar atmosphere, we can investigate in detail the physical processes of turbulent magnetoconvection, generation and amplification of magnetic fields, excitation of MHD waves, and plasma eruptions. We present recent simulation results of the multi-scale dynamics of quiet-Sun regions, and energetic effects in the atmosphere and compare with observations. For the comparisons we calculate synthetic spectro-polarimetric data to model observational data of SDO, Hinode, and New Solar Telescope.

An evaluation of noise reduction algorithms for particle-based fluid simulations in multi-scale applications

NASA Astrophysics Data System (ADS)

Zimoń, M. J.; Prosser, R.; Emerson, D. R.; Borg, M. K.; Bray, D. J.; Grinberg, L.; Reese, J. M.

2016-11-01

Filtering of particle-based simulation data can lead to reduced computational costs and enable more efficient information transfer in multi-scale modelling. This paper compares the effectiveness of various signal processing methods to reduce numerical noise and capture the structures of nano-flow systems. In addition, a novel combination of these algorithms is introduced, showing the potential of hybrid strategies to improve further the de-noising performance for time-dependent measurements. The methods were tested on velocity and density fields, obtained from simulations performed with molecular dynamics and dissipative particle dynamics. Comparisons between the algorithms are given in terms of performance, quality of the results and sensitivity to the choice of input parameters. The results provide useful insights on strategies for the analysis of particle-based data and the reduction of computational costs in obtaining ensemble solutions.

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

PubMed Central

Mathur, Rohit; Xing, Jia; Gilliam, Robert; Sarwar, Golam; Hogrefe, Christian; Pleim, Jonathan; Pouliot, George; Roselle, Shawn; Spero, Tanya L.; Wong, David C.; Young, Jeffrey

2018-01-01

The Community Multiscale Air Quality (CMAQ) modeling system is extended to simulate ozone, particulate matter, and related precursor distributions throughout the Northern Hemisphere. Modelled processes were examined and enhanced to suitably represent the extended space and time scales for such applications. Hemispheric scale simulations with CMAQ and the Weather Research and Forecasting (WRF) model are performed for multiple years. Model capabilities for a range of applications including episodic long-range pollutant transport, long-term trends in air pollution across the Northern Hemisphere, and air pollution-climate interactions are evaluated through detailed comparison with available surface, aloft, and remotely sensed observations. The expansion of CMAQ to simulate the hemispheric scales provides a framework to examine interactions between atmospheric processes occurring at various spatial and temporal scales with physical, chemical, and dynamical consistency. PMID:29681922

On multiscale moving contact line theory.

PubMed

Li, Shaofan; Fan, Houfu

2015-07-08

In this paper, a multiscale moving contact line (MMCL) theory is presented and employed to simulate liquid droplet spreading and capillary motion. The proposed MMCL theory combines a coarse-grained adhesive contact model with a fluid interface membrane theory, so that it can couple molecular scale adhesive interaction and surface tension with hydrodynamics of microscale flow. By doing so, the intermolecular force, the van der Waals or double layer force, separates and levitates the liquid droplet from the supporting solid substrate, which avoids the shear stress singularity caused by the no-slip condition in conventional hydrodynamics theory of moving contact line. Thus, the MMCL allows the difference of the surface energies and surface stresses to drive droplet spreading naturally. To validate the proposed MMCL theory, we have employed it to simulate droplet spreading over various elastic substrates. The numerical simulation results obtained by using MMCL are in good agreement with the molecular dynamics results reported in the literature.

Multi-scale Modeling of Radiation Damage: Large Scale Data Analysis

NASA Astrophysics Data System (ADS)

Warrier, M.; Bhardwaj, U.; Bukkuru, S.

2016-10-01

Modification of materials in nuclear reactors due to neutron irradiation is a multiscale problem. These neutrons pass through materials creating several energetic primary knock-on atoms (PKA) which cause localized collision cascades creating damage tracks, defects (interstitials and vacancies) and defect clusters depending on the energy of the PKA. These defects diffuse and recombine throughout the whole duration of operation of the reactor, thereby changing the micro-structure of the material and its properties. It is therefore desirable to develop predictive computational tools to simulate the micro-structural changes of irradiated materials. In this paper we describe how statistical averages of the collision cascades from thousands of MD simulations are used to provide inputs to Kinetic Monte Carlo (KMC) simulations which can handle larger sizes, more defects and longer time durations. Use of unsupervised learning and graph optimization in handling and analyzing large scale MD data will be highlighted.

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.

Regional variations in growth plate chondrocyte deformation as predicted by three-dimensional multi-scale simulations.

PubMed

Gao, Jie; Roan, Esra; Williams, John L

2015-01-01

The physis, or growth plate, is a complex disc-shaped cartilage structure that is responsible for longitudinal bone growth. In this study, a multi-scale computational approach was undertaken to better understand how physiological loads are experienced by chondrocytes embedded inside chondrons when subjected to moderate strain under instantaneous compressive loading of the growth plate. Models of representative samples of compressed bone/growth-plate/bone from a 0.67 mm thick 4-month old bovine proximal tibial physis were subjected to a prescribed displacement equal to 20% of the growth plate thickness. At the macroscale level, the applied compressive deformation resulted in an overall compressive strain across the proliferative-hypertrophic zone of 17%. The microscale model predicted that chondrocytes sustained compressive height strains of 12% and 6% in the proliferative and hypertrophic zones, respectively, in the interior regions of the plate. This pattern was reversed within the outer 300 μm region at the free surface where cells were compressed by 10% in the proliferative and 26% in the hypertrophic zones, in agreement with experimental observations. This work provides a new approach to study growth plate behavior under compression and illustrates the need for combining computational and experimental methods to better understand the chondrocyte mechanics in the growth plate cartilage. While the current model is relevant to fast dynamic events, such as heel strike in walking, we believe this approach provides new insight into the mechanical factors that regulate bone growth at the cell level and provides a basis for developing models to help interpret experimental results at varying time scales.

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

Regional Variations in Growth Plate Chondrocyte Deformation as Predicted By Three-Dimensional Multi-Scale Simulations

PubMed Central

Gao, Jie; Roan, Esra; Williams, John L.

2015-01-01

The physis, or growth plate, is a complex disc-shaped cartilage structure that is responsible for longitudinal bone growth. In this study, a multi-scale computational approach was undertaken to better understand how physiological loads are experienced by chondrocytes embedded inside chondrons when subjected to moderate strain under instantaneous compressive loading of the growth plate. Models of representative samples of compressed bone/growth-plate/bone from a 0.67 mm thick 4-month old bovine proximal tibial physis were subjected to a prescribed displacement equal to 20% of the growth plate thickness. At the macroscale level, the applied compressive deformation resulted in an overall compressive strain across the proliferative-hypertrophic zone of 17%. The microscale model predicted that chondrocytes sustained compressive height strains of 12% and 6% in the proliferative and hypertrophic zones, respectively, in the interior regions of the plate. This pattern was reversed within the outer 300 μm region at the free surface where cells were compressed by 10% in the proliferative and 26% in the hypertrophic zones, in agreement with experimental observations. This work provides a new approach to study growth plate behavior under compression and illustrates the need for combining computational and experimental methods to better understand the chondrocyte mechanics in the growth plate cartilage. While the current model is relevant to fast dynamic events, such as heel strike in walking, we believe this approach provides new insight into the mechanical factors that regulate bone growth at the cell level and provides a basis for developing models to help interpret experimental results at varying time scales. PMID:25885547

Multiscale simulation of DC corona discharge and ozone generation from nanostructures

NASA Astrophysics Data System (ADS)

Wang, Pengxiang

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

Three-Dimensional Multiscale Modeling of Dendritic Spacing Selection During Al-Si Directional Solidification

NASA Astrophysics Data System (ADS)

Tourret, Damien; Clarke, Amy J.; Imhoff, Seth D.; Gibbs, Paul J.; Gibbs, John W.; Karma, Alain

2015-08-01

We present a three-dimensional extension of the multiscale dendritic needle network (DNN) model. This approach enables quantitative simulations of the unsteady dynamics of complex hierarchical networks in spatially extended dendritic arrays. We apply the model to directional solidification of Al-9.8 wt.%Si alloy and directly compare the model predictions with measurements from experiments with in situ x-ray imaging. We focus on the dynamical selection of primary spacings over a range of growth velocities, and the influence of sample geometry on the selection of spacings. Simulation results show good agreement with experiments. The computationally efficient DNN model opens new avenues for investigating the dynamics of large dendritic arrays at scales relevant to solidification experiments and processes.

W and X Photoluminescence Centers in Crystalline Si: Chasing Candidates at Atomic Level Through Multiscale Simulations

NASA Astrophysics Data System (ADS)

Aboy, María; Santos, Iván; López, Pedro; Marqués, Luis A.; Pelaz, Lourdes

2018-04-01

Several atomistic techniques have been combined to identify the structure of defects responsible for X and W photoluminescence lines in crystalline Si. We used kinetic Monte Carlo simulations to reproduce irradiation and annealing conditions used in photoluminescence experiments. We found that W and X radiative centers are related to small Si self-interstitial clusters but coexist with larger Si self-interstitials clusters that can act as nonradiative centers. We used molecular dynamics simulations to explore the many different configurations of small Si self-interstitial clusters, and selected those having symmetry compatible with W and X photoluminescence centers. Using ab initio simulations, we calculated their formation energy, donor levels, and energy of local vibrational modes. On the basis of photoluminescence experiments and our multiscale theoretical calculations, we discuss the possible atomic configurations responsible for W and X photoluminescence centers in Si. Our simulations also reveal that the intensity of photoluminescence lines is the result of competition between radiative centers and nonradiative competitors, which can explain the experimental quenching of W and X lines even in the presence of the photoluminescence centers.

Refined composite multivariate generalized multiscale fuzzy entropy: A tool for complexity analysis of multichannel signals

NASA Astrophysics Data System (ADS)

Azami, Hamed; Escudero, Javier

2017-01-01

Multiscale entropy (MSE) is an appealing tool to characterize the complexity of time series over multiple temporal scales. Recent developments in the field have tried to extend the MSE technique in different ways. Building on these trends, we propose the so-called refined composite multivariate multiscale fuzzy entropy (RCmvMFE) whose coarse-graining step uses variance (RCmvMFEσ2) or mean (RCmvMFEμ). We investigate the behavior of these multivariate methods on multichannel white Gaussian and 1/ f noise signals, and two publicly available biomedical recordings. Our simulations demonstrate that RCmvMFEσ2 and RCmvMFEμ lead to more stable results and are less sensitive to the signals' length in comparison with the other existing multivariate multiscale entropy-based methods. The classification results also show that using both the variance and mean in the coarse-graining step offers complexity profiles with complementary information for biomedical signal analysis. We also made freely available all the Matlab codes used in this paper.

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.

Part I: Steady States in Two-Species Particle Aggregation. Part II: Sparse Representations for Multiscale PDE

DTIC Science & Technology

2015-03-01

University of California Los Angeles Part I: Steady States in Two-Species Particle Aggregation Part II: Sparse Representations for Multiscale PDE A ...Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a ...penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE MAR 2015

Diagnostic Analysis of Ozone Concentrations Simulated by Two Regional-Scale Air Quality Models

EPA Science Inventory

Since the Community Multiscale Air Quality modeling system (CMAQ) and the Weather Research and Forecasting with Chemistry model (WRF/Chem) use different approaches to simulate the interaction of meteorology and chemistry, this study compares the CMAQ and WRF/Chem air quality simu...

Individual-specific multi-scale finite element simulation of cortical bone of human proximal femur

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

Ascenzi, Maria-Grazia, E-mail: mgascenzi@mednet.ucla.edu; Kawas, Neal P., E-mail: nealkawas@ucla.edu; Lutz, Andre, E-mail: andre.lutz@hotmail.de

2013-07-01

We present an innovative method to perform multi-scale finite element analyses of the cortical component of the femur using the individual’s (1) computed tomography scan; and (2) a bone specimen obtained in conjunction with orthopedic surgery. The method enables study of micro-structural characteristics regulating strains and stresses under physiological loading conditions. The analysis of the micro-structural scenarios that cause variation of strain and stress is the first step in understanding the elevated strains and stresses in bone tissue, which are indicative of higher likelihood of micro-crack formation in bone, implicated in consequent remodeling or macroscopic bone fracture. Evidence that micro-structuremore » varies with clinical history and contributes in significant, but poorly understood, ways to bone function, motivates the method’s development, as does need for software tools to investigate relationships between macroscopic loading and micro-structure. Three applications – varying region of interest, bone mineral density, and orientation of collagen type I, illustrate the method. We show, in comparison between physiological loading and simple compression of a patient’s femur, that strains computed at the multi-scale model’s micro-level: (i) differ; and (ii) depend on local collagen-apatite orientation and degree of calcification. Our findings confirm the strain concentration role of osteocyte lacunae, important for mechano-transduction. We hypothesize occurrence of micro-crack formation, leading either to remodeling or macroscopic fracture, when the computed strains exceed the elastic range observed in micro-structural testing.« less

Impact of model complexity and multi-scale data integration on the estimation of hydrogeological parameters in a dual-porosity aquifer

NASA Astrophysics Data System (ADS)

Tamayo-Mas, Elena; Bianchi, Marco; Mansour, Majdi

2018-03-01

This study investigates the impact of model complexity and multi-scale prior hydrogeological data on the interpretation of pumping test data in a dual-porosity aquifer (the Chalk aquifer in England, UK). In order to characterize the hydrogeological properties, different approaches ranging from a traditional analytical solution (Theis approach) to more sophisticated numerical models with automatically calibrated input parameters are applied. Comparisons of results from the different approaches show that neither traditional analytical solutions nor a numerical model assuming a homogenous and isotropic aquifer can adequately explain the observed drawdowns. A better reproduction of the observed drawdowns in all seven monitoring locations is instead achieved when medium and local-scale prior information about the vertical hydraulic conductivity (K) distribution is used to constrain the model calibration process. In particular, the integration of medium-scale vertical K variations based on flowmeter measurements lead to an improvement in the goodness-of-fit of the simulated drawdowns of about 30%. Further improvements (up to 70%) were observed when a simple upscaling approach was used to integrate small-scale K data to constrain the automatic calibration process of the numerical model. Although the analysis focuses on a specific case study, these results provide insights about the representativeness of the estimates of hydrogeological properties based on different interpretations of pumping test data, and promote the integration of multi-scale data for the characterization of heterogeneous aquifers in complex hydrogeological settings.

Modeling the dust cycle from sand dunes to haboobs

NASA Astrophysics Data System (ADS)

Kallos, George; Patlakas, Platon; Bartsotas, Nikolaos; Spyrou, Christos; Qahtani, Jumaan Al; Alexiou, Ioannis; Bar, Ayman M.

2017-04-01

The dust cycle is a rather complicated mechanism depending on various factors. The most important factors affecting dust production is soil characteristics (soil composi-tion, physical and chemical properties, water content, temperature etc). The most known production mechanism at small scale is the saltation-bombardment. This mechanism is able to accurately predict uptake of dust particles up to about 10 μm. Larger dust particles are heavier and fall relatively fast due to the gravitational influ-ence. The other controlling factors of dust uptake and transport are wind speed (to be above a threshold) and turbulence. Weather conditions affecting dust produc-tion/transport/deposition are of multi-scale ranging from small surface inhomoge-neities to mesoscale and large-scale systems. While the typical dust transport mech-anism is related to wind conditions near the surface, larger scale systems play an important role on dust production. Such systems are associated with mesoscale phenomena typical of the specific regions. Usually they are associated with deep convection and strong downdrafts and are known as haboobs. Density currents are formed in the surface with strong winds and turbulence. Density currents can be considered as dust sources by themselves due to high productivity of dust. In this presentation we will discuss characteristics of the dust production mechanisms at multiscale over the Arabian Peninsula by utilizing the RAMS/ICLAMS multiscale model. A series of simulations at small-scale have been performed and mitigation actions will be explored.

Multi-Scale Modeling, Surrogate-Based Analysis, and Optimization of Lithium-Ion Batteries for Vehicle Applications

NASA Astrophysics Data System (ADS)

Du, Wenbo

A common attribute of electric-powered aerospace vehicles and systems such as unmanned aerial vehicles, hybrid- and fully-electric aircraft, and satellites is that their performance is usually limited by the energy density of their batteries. Although lithium-ion batteries offer distinct advantages such as high voltage and low weight over other battery technologies, they are a relatively new development, and thus significant gaps in the understanding of the physical phenomena that govern battery performance remain. As a result of this limited understanding, batteries must often undergo a cumbersome design process involving many manual iterations based on rules of thumb and ad-hoc design principles. A systematic study of the relationship between operational, geometric, morphological, and material-dependent properties and performance metrics such as energy and power density is non-trivial due to the multiphysics, multiphase, and multiscale nature of the battery system. To address these challenges, two numerical frameworks are established in this dissertation: a process for analyzing and optimizing several key design variables using surrogate modeling tools and gradient-based optimizers, and a multi-scale model that incorporates more detailed microstructural information into the computationally efficient but limited macro-homogeneous model. In the surrogate modeling process, multi-dimensional maps for the cell energy density with respect to design variables such as the particle size, ion diffusivity, and electron conductivity of the porous cathode material are created. A combined surrogate- and gradient-based approach is employed to identify optimal values for cathode thickness and porosity under various operating conditions, and quantify the uncertainty in the surrogate model. The performance of multiple cathode materials is also compared by defining dimensionless transport parameters. The multi-scale model makes use of detailed 3-D FEM simulations conducted at the particle-level. A monodisperse system of ellipsoidal particles is used to simulate the effective transport coefficients and interfacial reaction current density within the porous microstructure. Microscopic simulation results are shown to match well with experimental measurements, while differing significantly from homogenization approximations used in the macroscopic model. Global sensitivity analysis and surrogate modeling tools are applied to couple the two length scales and complete the multi-scale model.

Parameters Selection for Bivariate Multiscale Entropy Analysis of Postural Fluctuations in Fallers and Non-Fallers Older Adults.

PubMed

Ramdani, Sofiane; Bonnet, Vincent; Tallon, Guillaume; Lagarde, Julien; Bernard, Pierre Louis; Blain, Hubert

2016-08-01

Entropy measures are often used to quantify the regularity of postural sway time series. Recent methodological developments provided both multivariate and multiscale approaches allowing the extraction of complexity features from physiological signals; see "Dynamical complexity of human responses: A multivariate data-adaptive framework," in Bulletin of Polish Academy of Science and Technology, vol. 60, p. 433, 2012. The resulting entropy measures are good candidates for the analysis of bivariate postural sway signals exhibiting nonstationarity and multiscale properties. These methods are dependant on several input parameters such as embedding parameters. Using two data sets collected from institutionalized frail older adults, we numerically investigate the behavior of a recent multivariate and multiscale entropy estimator; see "Multivariate multiscale entropy: A tool for complexity analysis of multichannel data," Physics Review E, vol. 84, p. 061918, 2011. We propose criteria for the selection of the input parameters. Using these optimal parameters, we statistically compare the multivariate and multiscale entropy values of postural sway data of non-faller subjects to those of fallers. These two groups are discriminated by the resulting measures over multiple time scales. We also demonstrate that the typical parameter settings proposed in the literature lead to entropy measures that do not distinguish the two groups. This last result confirms the importance of the selection of appropriate input parameters.

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.

A point-by-point multi-scale surface temperature reconstruction method and tests by pseudo proxy experiments

NASA Astrophysics Data System (ADS)

Chen, X.

2016-12-01

This study present a multi-scale approach combining Mode Decomposition and Variance Matching (MDVM) method and basic process of Point-by-Point Regression (PPR) method. Different from the widely applied PPR method, the scanning radius for each grid box, were re-calculated considering the impact from topography (i.e. mean altitudes and fluctuations). Thus, appropriate proxy records were selected to be candidates for reconstruction. The results of this multi-scale methodology could not only provide the reconstructed gridded temperature, but also the corresponding uncertainties of the four typical timescales. In addition, this method can bring in another advantage that spatial distribution of the uncertainty for different scales could be quantified. To interpreting the necessity of scale separation in calibration, with proxy records location over Eastern Asia, we perform two sets of pseudo proxy experiments (PPEs) based on different ensembles of climate model simulation. One consist of 7 simulated results by 5 models (BCC-CSM1-1, CSIRO-MK3L-1-2, HadCM3, MPI-ESM-P, and Giss-E2-R) of the "past1000" simulation from Coupled Model Intercomparison Project Phase 5. The other is based on the simulations of Community Earth System Model Last Millennium Ensemble (CESM-LME). The pseudo-records network were obtained by adding the white noise with signal-to-noise ratio (SNR) increasing from 0.1 to 1.0 to the simulated true state and the locations mainly followed the PAGES-2k network in Asia. Totally, 400 years (1601-2000) simulation was used for calibration and 600 years (1001-1600) for verification. The reconstructed results were evaluated by three metrics 1) root mean squared error (RMSE), 2) correlation and 3) reduction of error (RE) score. The PPE verification results have shown that, in comparison with ordinary linear calibration method (variance matching), the RMSE and RE score of PPR-MDVM are improved, especially for the area with sparse proxy records. To be noted, in some periods with large volcanic activities, the RMSE of MDVM get larger than VM for higher SNR cases. It should be inferred that the volcanic eruptions might blur the intrinsic characteristics of multi-scales variabilities of the climate system and the MDVM method would show less advantage in that case.

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.

Sensitivity of air quality simulation to smoke plume rise

Treesearch

Yongqiang Liu; Gary Achtemeier; Scott Goodrick

2008-01-01

Plume rise is the height smoke plumes can reach. This information is needed by air quality models such as the Community Multiscale Air Quality (CMAQ) model to simulate physical and chemical processes of point-source fire emissions. This study seeks to understand the importance of plume rise to CMAQ air quality simulation of prescribed burning to plume rise. CMAQ...

The Virtual Liver Project: Modeling Tissue Response To Chemicals Through Multiscale Simulation

EPA Science Inventory

The US EPA Virtual Liver Project is aimed at simulating the risk of toxic effects from environmental chemicals in silico. The computational systems model of organ injury due to chronic chemical exposure is based on: (i) the dynamics of perturbed molecular pathways, (ii) their lin...

SENSITIVITY OF THE CMAQ MERCURY MODEL TO GAS-PHASE OXIDATION CHEMISTRY

EPA Science Inventory

Simulations of the Community Multi-scale Air Quality (CMAQ) model for mercury have shown the vast majority of the mercury deposited in the United States to be in the form of oxidized mercury. However, most of this simulated oxidized mercury was the result of atmospheric oxidatio...

Predicting agricultural impacts of large-scale drought: 2012 and the case for better modeling

USDA-ARS?s Scientific Manuscript database

We present an example of a simulation-based forecast for the 2012 U.S. maize growing season produced as part of a high-resolution, multi-scale, predictive mechanistic modeling study designed for decision support, risk management, and counterfactual analysis. The simulations undertaken for this analy...

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.

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

Hybrid stochastic simplifications for multiscale gene networks

PubMed Central

Crudu, Alina; Debussche, Arnaud; Radulescu, Ovidiu

2009-01-01

Background Stochastic simulation of gene networks by Markov processes has important applications in molecular biology. The complexity of exact simulation algorithms scales with the number of discrete jumps to be performed. Approximate schemes reduce the computational time by reducing the number of simulated discrete events. Also, answering important questions about the relation between network topology and intrinsic noise generation and propagation should be based on general mathematical results. These general results are difficult to obtain for exact models. Results We propose a unified framework for hybrid simplifications of Markov models of multiscale stochastic gene networks dynamics. We discuss several possible hybrid simplifications, and provide algorithms to obtain them from pure jump processes. In hybrid simplifications, some components are discrete and evolve by jumps, while other components are continuous. Hybrid simplifications are obtained by partial Kramers-Moyal expansion [1-3] which is equivalent to the application of the central limit theorem to a sub-model. By averaging and variable aggregation we drastically reduce simulation time and eliminate non-critical reactions. Hybrid and averaged simplifications can be used for more effective simulation algorithms and for obtaining general design principles relating noise to topology and time scales. The simplified models reproduce with good accuracy the stochastic properties of the gene networks, including waiting times in intermittence phenomena, fluctuation amplitudes and stationary distributions. The methods are illustrated on several gene network examples. Conclusion Hybrid simplifications can be used for onion-like (multi-layered) approaches to multi-scale biochemical systems, in which various descriptions are used at various scales. Sets of discrete and continuous variables are treated with different methods and are coupled together in a physically justified approach. PMID:19735554

Multi-scale image segmentation and numerical modeling in carbonate rocks

NASA Astrophysics Data System (ADS)

Alves, G. C.; Vanorio, T.

2016-12-01

Numerical methods based on computational simulations can be an important tool in estimating physical properties of rocks. These can complement experimental results, especially when time constraints and sample availability are a problem. However, computational models created at different scales can yield conflicting results with respect to the physical laboratory. This problem is exacerbated in carbonate rocks due to their heterogeneity at all scales. We developed a multi-scale approach performing segmentation of the rock images and numerical modeling across several scales, accounting for those heterogeneities. As a first step, we measured the porosity and the elastic properties of a group of carbonate samples with varying micrite content. Then, samples were imaged by Scanning Electron Microscope (SEM) as well as optical microscope at different magnifications. We applied three different image segmentation techniques to create numerical models from the SEM images and performed numerical simulations of the elastic wave-equation. Our results show that a multi-scale approach can efficiently account for micro-porosities in tight micrite-supported samples, yielding acoustic velocities comparable to those obtained experimentally. Nevertheless, in high-porosity samples characterized by larger grain/micrite ratio, results show that SEM scale images tend to overestimate velocities, mostly due to their inability to capture macro- and/or intragranular- porosity. This suggests that, for high-porosity carbonate samples, optical microscope images would be more suited for numerical simulations.

A multiscale MDCT image-based breathing lung model with time-varying regional ventilation

PubMed Central

Yin, Youbing; Choi, Jiwoong; Hoffman, Eric A.; Tawhai, Merryn H.; Lin, Ching-Long

2012-01-01

A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C1 continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung. PMID:23794749

Modeling Materials: Design for Planetary Entry, Electric Aircraft, and Beyond

NASA Technical Reports Server (NTRS)

Thompson, Alexander; Lawson, John W.

2014-01-01

NASA missions push the limits of what is possible. The development of high-performance materials must keep pace with the agency's demanding, cutting-edge applications. Researchers at NASA's Ames Research Center are performing multiscale computational modeling to accelerate development times and further the design of next-generation aerospace materials. Multiscale modeling combines several computationally intensive techniques ranging from the atomic level to the macroscale, passing output from one level as input to the next level. These methods are applicable to a wide variety of materials systems. For example: (a) Ultra-high-temperature ceramics for hypersonic aircraft-we utilized the full range of multiscale modeling to characterize thermal protection materials for faster, safer air- and spacecraft, (b) Planetary entry heat shields for space vehicles-we computed thermal and mechanical properties of ablative composites by combining several methods, from atomistic simulations to macroscale computations, (c) Advanced batteries for electric aircraft-we performed large-scale molecular dynamics simulations of advanced electrolytes for ultra-high-energy capacity batteries to enable long-distance electric aircraft service; and (d) Shape-memory alloys for high-efficiency aircraft-we used high-fidelity electronic structure calculations to determine phase diagrams in shape-memory transformations. Advances in high-performance computing have been critical to the development of multiscale materials modeling. We used nearly one million processor hours on NASA's Pleiades supercomputer to characterize electrolytes with a fidelity that would be otherwise impossible. For this and other projects, Pleiades enables us to push the physics and accuracy of our calculations to new levels.

Subject specific finite element modeling of periprosthetic femoral fracture using element deactivation to simulate bone failure.

PubMed

Miles, Brad; Kolos, Elizabeth; Walter, William L; Appleyard, Richard; Shi, Angela; Li, Qing; Ruys, Andrew J

2015-06-01

Subject-specific finite element (FE) modeling methodology could predict peri-prosthetic femoral fracture (PFF) for cementless hip arthoplasty in the early postoperative period. This study develops methodology for subject-specific finite element modeling by using the element deactivation technique to simulate bone failure and validate with experimental testing, thereby predicting peri-prosthetic femoral fracture in the early postoperative period. Material assignments for biphasic and triphasic models were undertaken. Failure modeling with the element deactivation feature available in ABAQUS 6.9 was used to simulate a crack initiation and propagation in the bony tissue based upon a threshold of fracture strain. The crack mode for the biphasic models was very similar to the experimental testing crack mode, with a similar shape and path of the crack. The fracture load is sensitive to the friction coefficient at the implant-bony interface. The development of a novel technique to simulate bone failure by element deactivation of subject-specific finite element models could aid prediction of fracture load in addition to fracture risk characterization for PFF. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

A global multiscale mathematical model for the human circulation with emphasis on the venous system.

PubMed

Müller, Lucas O; Toro, Eleuterio F

2014-07-01

We present a global, closed-loop, multiscale mathematical model for the human circulation including the arterial system, the venous system, the heart, the pulmonary circulation and the microcirculation. A distinctive feature of our model is the detailed description of the venous system, particularly for intracranial and extracranial veins. Medium to large vessels are described by one-dimensional hyperbolic systems while the rest of the components are described by zero-dimensional models represented by differential-algebraic equations. Robust, high-order accurate numerical methodology is implemented for solving the hyperbolic equations, which are adopted from a recent reformulation that includes variable material properties. Because of the large intersubject variability of the venous system, we perform a patient-specific characterization of major veins of the head and neck using MRI data. Computational results are carefully validated using published data for the arterial system and most regions of the venous system. For head and neck veins, validation is carried out through a detailed comparison of simulation results against patient-specific phase-contrast MRI flow quantification data. A merit of our model is its global, closed-loop character; the imposition of highly artificial boundary conditions is avoided. Applications in mind include a vast range of medical conditions. Of particular interest is the study of some neurodegenerative diseases, whose venous haemodynamic connection has recently been identified by medical researchers. Copyright © 2014 John Wiley & Sons, Ltd.

Advanced Aerospace Materials by Design

NASA Technical Reports Server (NTRS)

Srivastava, Deepak; Djomehri, Jahed; Wei, Chen-Yu

2004-01-01

The advances in the emerging field of nanophase thermal and structural composite materials; materials with embedded sensors and actuators for morphing structures; light-weight composite materials for energy and power storage; and large surface area materials for in-situ resource generation and waste recycling, are expected to :revolutionize the capabilities of virtually every system comprising of future robotic and :human moon and mars exploration missions. A high-performance multiscale simulation platform, including the computational capabilities and resources of Columbia - the new supercomputer, is being developed to discover, validate, and prototype next generation (of such advanced materials. This exhibit will describe the porting and scaling of multiscale 'physics based core computer simulation codes for discovering and designing carbon nanotube-polymer composite materials for light-weight load bearing structural and 'thermal protection applications.

Three-dimensional multiscale modeling of dendritic spacing selection during Al-Si directional solidification

DOE PAGES

Tourret, Damien; Clarke, Amy J.; Imhoff, Seth D.; ...

2015-05-27

We present a three-dimensional extension of the multiscale dendritic needle network (DNN) model. This approach enables quantitative simulations of the unsteady dynamics of complex hierarchical networks in spatially extended dendritic arrays. We apply the model to directional solidification of Al-9.8 wt.%Si alloy and directly compare the model predictions with measurements from experiments with in situ x-ray imaging. The focus is on the dynamical selection of primary spacings over a range of growth velocities, and the influence of sample geometry on the selection of spacings. Simulation results show good agreement with experiments. The computationally efficient DNN model opens new avenues formore » investigating the dynamics of large dendritic arrays at scales relevant to solidification experiments and processes.« less

Multiscale simulations of the early stages of the growth of graphene on copper

NASA Astrophysics Data System (ADS)

Gaillard, P.; Chanier, T.; Henrard, L.; Moskovkin, P.; Lucas, S.

2015-07-01

We have performed multiscale simulations of the growth of graphene on defect-free copper (111) in order to model the nucleation and growth of graphene flakes during chemical vapour deposition and potentially guide future experimental work. Basic activation energies for atomic surface diffusion were determined by ab initio calculations. Larger scale growth was obtained within a kinetic Monte Carlo approach (KMC) with parameters based on the ab initio results. The KMC approach counts the first and second neighbours to determine the probability of surface diffusion. We report qualitative results on the size and shape of the graphene islands as a function of deposition flux. The dominance of graphene zigzag edges for low deposition flux, also observed experimentally, is explained by its larger dynamical stability that the present model fully reproduced.

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...

Effects of polymer graft properties on protein adsorption and transport in ion exchange chromatography: a multiscale modeling study.

PubMed

Basconi, Joseph E; Carta, Giorgio; Shirts, Michael R

2015-04-14

Multiscale simulation is used to study the adsorption of lysozyme onto ion exchangers obtained by grafting charged polymers into a porous matrix, in systems with various polymer properties and strengths of electrostatic interaction. Molecular dynamics simulations show that protein partitioning into the polymer-filled pore space increases with the overall charge content of the polymers, while the diffusivity in the pore space decreases. However, the combination of greatly increased partitioning and modestly decreased diffusion results in macroscopic transport rates that increase as a function of charge content, as the large concentration driving force due to enhanced pore space partitioning outweighs the reduction in the pore space diffusivity. Matrices having greater charge associated with the grafted polymers also exhibit more diffuse intraparticle concentration profiles during transient adsorption. In systems with a high charge content per polymer and a low protein loading, the polymers preferentially partition toward the surface due to favorable interactions with the surface-bound protein. These results demonstrate the potential of multiscale modeling to illuminate qualitative trends between molecular properties and the adsorption equilibria and kinetic properties observable on macroscopic scales.

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.

Blast and the Consequences on Traumatic Brain Injury-Multiscale Mechanical Modeling of Brain

DTIC Science & Technology

2011-02-17

blast simulation. LS-DYNA as an explicit FE code has been employed to simulate this multi- material fluid –structure interaction problem. The 3-D head...formulation is implemented to model the air-blast simulation. LS-DYNA as an explicit FE code has been employed to simulate this multi-material fluid ...Biomechanics Study of Influencing Parameters for brain under Impact ............................... 12 5.1 The Impact of Cerebrospinal Fluid

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.

Simulation Platform: a cloud-based online simulation environment.

PubMed

Yamazaki, Tadashi; Ikeno, Hidetoshi; Okumura, Yoshihiro; Satoh, Shunji; Kamiyama, Yoshimi; Hirata, Yutaka; Inagaki, Keiichiro; Ishihara, Akito; Kannon, Takayuki; Usui, Shiro

2011-09-01

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called "Simulation Platform". Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software. Copyright © 2011 Elsevier Ltd. All rights reserved.

Reprint of: Simulation Platform: a cloud-based online simulation environment.

PubMed

Yamazaki, Tadashi; Ikeno, Hidetoshi; Okumura, Yoshihiro; Satoh, Shunji; Kamiyama, Yoshimi; Hirata, Yutaka; Inagaki, Keiichiro; Ishihara, Akito; Kannon, Takayuki; Usui, Shiro

2011-11-01

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called "Simulation Platform". Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software. Copyright © 2011 Elsevier Ltd. All rights reserved.

The Diurnal Cycle of Clouds and Precipitation at the ARM SGP Site: An Atmospheric State-Based Analysis and Error Decomposition of a Multiscale Modeling Framework Simulation

NASA Astrophysics Data System (ADS)

Zhao, Wei; Marchand, Roger; Fu, Qiang

2017-12-01

Long-term reflectivity data collected by a millimeter cloud radar at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site are used to examine the diurnal cycle of clouds and precipitation and are compared with the diurnal cycle simulated by a Multiscale Modeling Framework (MMF) climate model. The study uses a set of atmospheric states that were created specifically for the SGP and for the purpose of investigating under what synoptic conditions models compare well with observations on a statistical basis (rather than using case studies or seasonal or longer time scale averaging). Differences in the annual mean diurnal cycle between observations and the MMF are decomposed into differences due to the relative frequency of states, the daily mean vertical profile of hydrometeor occurrence, and the (normalized) diurnal variation of hydrometeors in each state. Here the hydrometeors are classified as cloud or precipitation based solely on the reflectivity observed by a millimeter radar or generated by a radar simulator. The results show that the MMF does not capture the diurnal variation of low clouds well in any of the states but does a reasonable job capturing the diurnal variations of high clouds and precipitation in some states. In particular, the diurnal variations in states that occur during summer are reasonably captured by the MMF, while the diurnal variations in states that occur during the transition seasons (spring and fall) are not well captured. Overall, the errors in the annual composite are due primarily to errors in the daily mean of hydrometeor occurrence (rather than diurnal variations), but errors in the state frequency (that is, the distribution of weather states in the model) also play a significant role.

Multiscale Magnetic Underdense Regions on the Solar Surface: Granular and Mesogranular Scales

NASA Astrophysics Data System (ADS)

Berrilli, F.; Scardigli, S.; Giordano, S.

2013-02-01

The Sun is a non-equilibrium, dissipative system subject to an energy flow that originates in its core. Convective overshooting motions create temperature and velocity structures that show a temporal and spatial multiscale evolution. As a result, photospheric structures are generally considered to be a direct manifestation of convective plasma motions. The plasma flows in the photosphere govern the motion of single magnetic elements. These elements are arranged in typical patterns, which are observed as a variety of multiscale magnetic patterns. High-resolution magnetograms of the quiet solar surface revealed the presence of multiscale magnetic underdense regions in the solar photosphere, commonly called voids, which may be considered to be a signature of the underlying convective structure. The analysis of such patterns paves the way for the investigation of all turbulent convective scales, from granular to global. In order to address the question of magnetic structures driven by turbulent convection at granular and mesogranular scales, we used a voids-detection method. The computed distribution of void length scales shows an exponential behavior at scales between 2 and 10 Mm and the absence of features at mesogranular scales. The absence of preferred scales of organization in the 2 - 10 Mm range supports the multiscale nature of flows on the solar surface and the absence of a mesogranular convective scale.

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.

Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement

PubMed Central

Han, Zhenyu; Sun, Shouzheng; Fu, Hongya; Fu, Yunzhong

2017-01-01

Automated fiber placement (AFP) process includes a variety of energy forms and multi-scale effects. This contribution proposes a novel multi-scale low-entropy method aiming at optimizing processing parameters in an AFP process, where multi-scale effect, energy consumption, energy utilization efficiency and mechanical properties of micro-system could be taken into account synthetically. Taking a carbon fiber/epoxy prepreg as an example, mechanical properties of macro–meso–scale are obtained by Finite Element Method (FEM). A multi-scale energy transfer model is then established to input the macroscopic results into the microscopic system as its boundary condition, which can communicate with different scales. Furthermore, microscopic characteristics, mainly micro-scale adsorption energy, diffusion coefficient entropy–enthalpy values, are calculated under different processing parameters based on molecular dynamics method. Low-entropy region is then obtained in terms of the interrelation among entropy–enthalpy values, microscopic mechanical properties (interface adsorbability and matrix fluidity) and processing parameters to guarantee better fluidity, stronger adsorption, lower energy consumption and higher energy quality collaboratively. Finally, nine groups of experiments are carried out to verify the validity of the simulation results. The results show that the low-entropy optimization method can reduce void content effectively, and further improve the mechanical properties of laminates. PMID:28869520

Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement.

PubMed

Han, Zhenyu; Sun, Shouzheng; Fu, Hongya; Fu, Yunzhong

2017-09-03

Automated fiber placement (AFP) process includes a variety of energy forms and multi-scale effects. This contribution proposes a novel multi-scale low-entropy method aiming at optimizing processing parameters in an AFP process, where multi-scale effect, energy consumption, energy utilization efficiency and mechanical properties of micro-system could be taken into account synthetically. Taking a carbon fiber/epoxy prepreg as an example, mechanical properties of macro-meso-scale are obtained by Finite Element Method (FEM). A multi-scale energy transfer model is then established to input the macroscopic results into the microscopic system as its boundary condition, which can communicate with different scales. Furthermore, microscopic characteristics, mainly micro-scale adsorption energy, diffusion coefficient entropy-enthalpy values, are calculated under different processing parameters based on molecular dynamics method. Low-entropy region is then obtained in terms of the interrelation among entropy-enthalpy values, microscopic mechanical properties (interface adsorbability and matrix fluidity) and processing parameters to guarantee better fluidity, stronger adsorption, lower energy consumption and higher energy quality collaboratively. Finally, nine groups of experiments are carried out to verify the validity of the simulation results. The results show that the low-entropy optimization method can reduce void content effectively, and further improve the mechanical properties of laminates.

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.

Investigation of Effects of Varying Model Inputs on Mercury Deposition Estimates in the Southwest US

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) model version 4.7.1 was used to simulate mercury wet and dry deposition for a domain covering the continental United States (US). The simulations used MM5-derived meteorological input fields and the US Environmental Protection Agency (E...

Assessment of long-term WRF–CMAQ simulations for understanding direct aerosol effects on radiation "brightening" in the United States

EPA Science Inventory

Long-term simulations with the coupled WRF–CMAQ (Weather Research and Forecasting–Community Multi-scale Air Quality) model have been conducted to systematically investigate the changes in anthropogenic emissions of SO2 and NOx over the past 16 years (1995–2010) ...

Air pollution and climate response to aerosol direct radiative effects: A modeling study of decadal trends across the northern hemisphere

EPA Science Inventory

Decadal hemispheric Weather Research and Forecast-Community Multiscale Air Quality simulations from 1990 to 2010 were conducted to examine the meteorology and air quality responses to the aerosol direct radiative effects. The model's performance for the simulation of hourly surfa...

Interdisciplinary Modeling and Dynamics of Archipelago Straits

DTIC Science & Technology

2009-01-01

modeling, tidal modeling and multi-dynamics nested domains and non-hydrostatic modeling WORK COMPLETED Realistic Multiscale Simulations, Real-time...six state variables (chlorophyll, nitrate , ammonium, detritus, phytoplankton, and zooplankton) were needed to initialize simulations. Using biological...parameters from literature, climatology from World Ocean Atlas data for nitrate and chlorophyll profiles extracted from satellite data, a first

RESULTS OF PHOTOCHEMICAL SIMULATIONS OF SUBGRID SCALE POINT SOURCE EMISSIONS WITH THE MODELS-3 CMAQ MODELING SYSTEM

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) / Plume-in-Grid (PinG) model was applied on a domain encompassing the greater Nashville, Tennessee region. Model simulations were performed for selected days in July 1995 during the Southern Oxidant Study (SOS) field study program wh...

Dynamic Evaluation of Two Decades of WRF-CMAQ Ozone Simulations over the Contiguous United States (2017 CMAS)

EPA Science Inventory

Weather Research and Forecasting (WRF)–Community Multi-scale Air Quality (CMAQ) model over the contiguous United States is conducted to assess how well the changes in observed ozone air quality are simulated by the model. The changes induced by variations in meteorology and...

Dynamic Evaluation of Two Decades of WRF-CMAQ Ozone Simulations over the Contiguous United States (2017 MAC-MAQ Conference Presentation)

EPA Science Inventory

Dynamic evaluation of two decades of ozone simulations performed with the fully coupled Weather Research and Forecasting (WRF)–Community Multi-scale Air Quality (CMAQ) model over the contiguous United States is conducted to assess how well the changes in observed ozone air ...

Application of Watershed Deposition Tool to Estimate from CMAQ Simulations of the Atmospheric Deposition of Nitrogen to Tampa Bay and Its Watershed

EPA Science Inventory

The USEPA has developed Watershed Deposition Tool (WDT) to calculate from the Community Multiscale Air Quality (CMAQ) model output the nitrogen, sulfur, and mercury deposition rates to watersheds and their sub-basins. The CMAQ model simulates from first principles the transport, ...

Multiscale predictions of aviation-attributable PM2.5 for US ...

EPA Pesticide Factsheets

Aviation activities represent an important and unique mode of transportation, but also impact air quality. In this study, we aim to quantify the impact of aircraft on air quality, focusing on aviation-attributable PM2.5 at scales ranging from local (a few kilometers) to continental (spanning hundreds of kilometers) using the Community Multiscale Air Quality-Advanced Plume Treatment (CMAQ-APT) model. In our CMAQ-APT simulations, a plume scale treatment is applied to aircraft emissions from 99 major U.S. airports over the contiguous U.S. in January and July 2005. In addition to the plume scale treatment, we account for the formation of non-traditional secondary organic aerosols (NTSOA) from the oxidation of semivolatile and intermediate volatility organic compounds (S/IVOCs) emitted from aircraft, and utilize alternative emission estimates from the Aerosol Dynamics Simulation Code (ADSC). ADSC is a 1-D plume scale model that estimates engine specific PM and S/IVOC emissions at ambient conditions, accounting for relative humidity and temperature. We estimated monthly and contiguous U.S. average aviation-attributable PM2.5 to be 2.7 ng m−3 in January and 2.6 ng m−3 in July using CMAQ-APT with ADSC emissions. This represents an increase of 40% and 12% in January and July, respectively, over impacts using traditional modeling approaches (traditional emissions without APT). The maximum fine scale (subgrid scale) hourly impacts at a major airport were 133.6 μg m−

A self-consistent first-principle based approach to model carrier mobility in organic materials

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

Meded, Velimir; Friederich, Pascal; Symalla, Franz

2015-12-31

Transport through thin organic amorphous films, utilized in OLEDs and OPVs, has been a challenge to model by using ab-initio methods. Charge carrier mobility depends strongly on the disorder strength and reorganization energy, both of which are significantly affected by the details in environment of each molecule. Here we present a multi-scale approach to describe carrier mobility in which the materials morphology is generated using DEPOSIT, a Monte Carlo based atomistic simulation approach, or, alternatively by molecular dynamics calculations performed with GROMACS. From this morphology we extract the material specific hopping rates, as well as the on-site energies using amore » fully self-consistent embedding approach to compute the electronic structure parameters, which are then used in an analytic expression for the carrier mobility. We apply this strategy to compute the carrier mobility for a set of widely studied molecules and obtain good agreement between experiment and theory varying over several orders of magnitude in the mobility without any freely adjustable parameters. The work focuses on the quantum mechanical step of the multi-scale workflow, explains the concept along with the recently published workflow optimization, which combines density functional with semi-empirical tight binding approaches. This is followed by discussion on the analytic formula and its agreement with established percolation fits as well as kinetic Monte Carlo numerical approaches. Finally, we skatch an unified multi-disciplinary approach that integrates materials science simulation and high performance computing, developed within EU project MMM@HPC.« less

Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations

DOE PAGES

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

2017-12-21

Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely-resolved (e.g. molecular dynamics) and coarse-grained (e.g. continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 84115 (2016)], simulatedmore » using a particle-based continuum method known as smoothed dissipative particle dynamics (SDPD). An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.« less

Simulation of Degraded Properties of 2D plain Woven C/SiC Composites under Preloading Oxidation Atmosphere

NASA Astrophysics Data System (ADS)

Chen, Xihui; Sun, Zhigang; Sun, Jianfen; Song, Yingdong

2017-12-01

In this paper, a numerical model which incorporates the oxidation damage model and the finite element model of 2D plain woven composites is presented for simulation of the oxidation behaviors of 2D plain woven C/SiC composite under preloading oxidation atmosphere. The equal proportional reduction method is firstly proposed to calculate the residual moduli and strength of unidirectional C/SiC composite. The multi-scale method is developed to simulate the residual elastic moduli and strength of 2D plain woven C/SiC composite. The multi-scale method is able to accurately predict the residual elastic modulus and strength of the composite. Besides, the simulated residual elastic moduli and strength of 2D plain woven C/SiC composites under preloading oxidation atmosphere show good agreements with experimental results. Furthermore, the preload, oxidation time, temperature and fiber volume fractions of the composite are investigated to show their influences upon the residual elastic modulus and strength of 2D plain woven C/SiC composites.

A Novel Multi-scale Simulation Strategy for Turbulent Reacting Flows

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

James, Sutherland C.

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

Progress in fast, accurate multi-scale climate simulations

DOE PAGES

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

2015-06-01

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

Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations

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

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

Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely-resolved (e.g. molecular dynamics) and coarse-grained (e.g. continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 84115 (2016)], simulatedmore » using a particle-based continuum method known as smoothed dissipative particle dynamics (SDPD). An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.« less

Predicting variation in subject thermal response during transcranial magnetic resonance guided focused ultrasound surgery: Comparison in seventeen subject datasets.

PubMed

Vyas, Urvi; Ghanouni, Pejman; Halpern, Casey H; Elias, Jeff; Pauly, Kim Butts

2016-09-01

In transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) treatments, the acoustic and spatial heterogeneity of the skull cause reflection, absorption, and scattering of the acoustic beams. These effects depend on skull-specific parameters and can lead to patient-specific thermal responses to the same transducer power. In this work, the authors develop a simulation tool to help predict these different experimental responses using 3D heterogeneous tissue models based on the subject CT images. The authors then validate and compare the predicted skull efficiencies to an experimental metric based on the subject thermal responses during tcMRgFUS treatments in a dataset of seventeen human subjects. Seventeen human head CT scans were used to create tissue acoustic models, simulating the effects of reflection, absorption, and scattering of the acoustic beam as it propagates through a heterogeneous skull. The hybrid angular spectrum technique was used to model the acoustic beam propagation of the InSightec ExAblate 4000 head transducer for each subject, yielding maps of the specific absorption rate (SAR). The simulation assumed the transducer was geometrically focused to the thalamus of each subject, and the focal SAR at the target was used as a measure of the simulated skull efficiency. Experimental skull efficiency for each subject was calculated using the thermal temperature maps from the tcMRgFUS treatments. Axial temperature images (with no artifacts) were reconstructed with a single baseline, corrected using a referenceless algorithm. The experimental skull efficiency was calculated by dividing the reconstructed temperature rise 8.8 s after sonication by the applied acoustic power. The simulated skull efficiency using individual-specific heterogeneous models predicts well (R(2) = 0.84) the experimental energy efficiency. This paper presents a simulation model to predict the variation in thermal responses measured in clinical ctMRGFYS treatments while being computationally feasible.

Predicting variation in subject thermal response during transcranial magnetic resonance guided focused ultrasound surgery: Comparison in seventeen subject datasets

PubMed Central

Vyas, Urvi; Ghanouni, Pejman; Halpern, Casey H.; Elias, Jeff; Pauly, Kim Butts

2016-01-01

Purpose: In transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) treatments, the acoustic and spatial heterogeneity of the skull cause reflection, absorption, and scattering of the acoustic beams. These effects depend on skull-specific parameters and can lead to patient-specific thermal responses to the same transducer power. In this work, the authors develop a simulation tool to help predict these different experimental responses using 3D heterogeneous tissue models based on the subject CT images. The authors then validate and compare the predicted skull efficiencies to an experimental metric based on the subject thermal responses during tcMRgFUS treatments in a dataset of seventeen human subjects. Methods: Seventeen human head CT scans were used to create tissue acoustic models, simulating the effects of reflection, absorption, and scattering of the acoustic beam as it propagates through a heterogeneous skull. The hybrid angular spectrum technique was used to model the acoustic beam propagation of the InSightec ExAblate 4000 head transducer for each subject, yielding maps of the specific absorption rate (SAR). The simulation assumed the transducer was geometrically focused to the thalamus of each subject, and the focal SAR at the target was used as a measure of the simulated skull efficiency. Experimental skull efficiency for each subject was calculated using the thermal temperature maps from the tcMRgFUS treatments. Axial temperature images (with no artifacts) were reconstructed with a single baseline, corrected using a referenceless algorithm. The experimental skull efficiency was calculated by dividing the reconstructed temperature rise 8.8 s after sonication by the applied acoustic power. Results: The simulated skull efficiency using individual-specific heterogeneous models predicts well (R2 = 0.84) the experimental energy efficiency. Conclusions: This paper presents a simulation model to predict the variation in thermal responses measured in clinical ctMRGFYS treatments while being computationally feasible. PMID:27587047

Predicting variation in subject thermal response during transcranial magnetic resonance guided focused ultrasound surgery: Comparison in seventeen subject datasets

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

Vyas, Urvi, E-mail: urvi.vyas@gmail.com; Ghanouni,

Purpose: In transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) treatments, the acoustic and spatial heterogeneity of the skull cause reflection, absorption, and scattering of the acoustic beams. These effects depend on skull-specific parameters and can lead to patient-specific thermal responses to the same transducer power. In this work, the authors develop a simulation tool to help predict these different experimental responses using 3D heterogeneous tissue models based on the subject CT images. The authors then validate and compare the predicted skull efficiencies to an experimental metric based on the subject thermal responses during tcMRgFUS treatments in a dataset of seventeen humanmore » subjects. Methods: Seventeen human head CT scans were used to create tissue acoustic models, simulating the effects of reflection, absorption, and scattering of the acoustic beam as it propagates through a heterogeneous skull. The hybrid angular spectrum technique was used to model the acoustic beam propagation of the InSightec ExAblate 4000 head transducer for each subject, yielding maps of the specific absorption rate (SAR). The simulation assumed the transducer was geometrically focused to the thalamus of each subject, and the focal SAR at the target was used as a measure of the simulated skull efficiency. Experimental skull efficiency for each subject was calculated using the thermal temperature maps from the tcMRgFUS treatments. Axial temperature images (with no artifacts) were reconstructed with a single baseline, corrected using a referenceless algorithm. The experimental skull efficiency was calculated by dividing the reconstructed temperature rise 8.8 s after sonication by the applied acoustic power. Results: The simulated skull efficiency using individual-specific heterogeneous models predicts well (R{sup 2} = 0.84) the experimental energy efficiency. Conclusions: This paper presents a simulation model to predict the variation in thermal responses measured in clinical ctMRGFYS treatments while being computationally feasible.« less

Simulation of blood flow in deformable vessels using subject-specific geometry and spatially varying wall properties

PubMed Central

Xiong, Guanglei; Figueroa, C. Alberto; Xiao, Nan; Taylor, Charles A.

2011-01-01

SUMMARY Simulation of blood flow using image-based models and computational fluid dynamics has found widespread application to quantifying hemodynamic factors relevant to the initiation and progression of cardiovascular diseases and for planning interventions. Methods for creating subject-specific geometric models from medical imaging data have improved substantially in the last decade but for many problems, still require significant user interaction. In addition, while fluid–structure interaction methods are being employed to model blood flow and vessel wall dynamics, tissue properties are often assumed to be uniform. In this paper, we propose a novel workflow for simulating blood flow using subject-specific geometry and spatially varying wall properties. The geometric model construction is based on 3D segmentation and geometric processing. Variable wall properties are assigned to the model based on combining centerline-based and surface-based methods. We finally demonstrate these new methods using an idealized cylindrical model and two subject-specific vascular models with thoracic and cerebral aneurysms. PMID:21765984

The Geometric Factor of Electrostatic Plasma Analyzers: A Case Study from the Fast Plasma Investigation for the Magnetospheric Multiscale mission

NASA Technical Reports Server (NTRS)

Collinson, Glyn A.; Dorelli, John Charles; Avanov, Leon A.; Lewis, Gethyn R.; Moore, Thomas E.; Pollock, Craig; Kataria, Dhiren O.; Bedington, Robert; Arridge, Chris S.; Chornay, Dennis J.;

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

NASA Astrophysics Data System (ADS)

Liu, Yushi; Poh, Hee Joo

2014-11-01

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

Multiscale limited penetrable horizontal visibility graph for analyzing nonlinear time series

NASA Astrophysics Data System (ADS)

Gao, Zhong-Ke; Cai, Qing; Yang, Yu-Xuan; Dang, Wei-Dong; Zhang, Shan-Shan

2016-10-01

Visibility graph has established itself as a powerful tool for analyzing time series. We in this paper develop a novel multiscale limited penetrable horizontal visibility graph (MLPHVG). We use nonlinear time series from two typical complex systems, i.e., EEG signals and two-phase flow signals, to demonstrate the effectiveness of our method. Combining MLPHVG and support vector machine, we detect epileptic seizures from the EEG signals recorded from healthy subjects and epilepsy patients and the classification accuracy is 100%. In addition, we derive MLPHVGs from oil-water two-phase flow signals and find that the average clustering coefficient at different scales allows faithfully identifying and characterizing three typical oil-water flow patterns. These findings render our MLPHVG method particularly useful for analyzing nonlinear time series from the perspective of multiscale network analysis.

Biological materials by design.

PubMed

Qin, Zhao; Dimas, Leon; Adler, David; Bratzel, Graham; Buehler, Markus J

2014-02-19

In this topical review we discuss recent advances in the use of physical insight into the way biological materials function, to design novel engineered materials 'from scratch', or from the level of fundamental building blocks upwards and by using computational multiscale methods that link chemistry to material function. We present studies that connect advances in multiscale hierarchical material structuring with material synthesis and testing, review case studies of wood and other biological materials, and illustrate how engineered fiber composites and bulk materials are designed, modeled, and then synthesized and tested experimentally. The integration of experiment and simulation in multiscale design opens new avenues to explore the physics of materials from a fundamental perspective, and using complementary strengths from models and empirical techniques. Recent developments in this field illustrate a new paradigm by which complex material functionality is achieved through hierarchical structuring in spite of simple material constituents.

Global sensitivity analysis of multiscale properties of porous materials

NASA Astrophysics Data System (ADS)

Um, Kimoon; Zhang, Xuan; Katsoulakis, Markos; Plechac, Petr; Tartakovsky, Daniel M.

2018-02-01

Ubiquitous uncertainty about pore geometry inevitably undermines the veracity of pore- and multi-scale simulations of transport phenomena in porous media. It raises two fundamental issues: sensitivity of effective material properties to pore-scale parameters and statistical parameterization of Darcy-scale models that accounts for pore-scale uncertainty. Homogenization-based maps of pore-scale parameters onto their Darcy-scale counterparts facilitate both sensitivity analysis (SA) and uncertainty quantification. We treat uncertain geometric characteristics of a hierarchical porous medium as random variables to conduct global SA and to derive probabilistic descriptors of effective diffusion coefficients and effective sorption rate. Our analysis is formulated in terms of solute transport diffusing through a fluid-filled pore space, while sorbing to the solid matrix. Yet it is sufficiently general to be applied to other multiscale porous media phenomena that are amenable to homogenization.

Multi-scale symbolic transfer entropy analysis of EEG

NASA Astrophysics Data System (ADS)

Yao, Wenpo; Wang, Jun

2017-10-01

From both global and local perspectives, we symbolize two kinds of EEG and analyze their dynamic and asymmetrical information using multi-scale transfer entropy. Multi-scale process with scale factor from 1 to 199 and step size of 2 is applied to EEG of healthy people and epileptic patients, and then the permutation with embedding dimension of 3 and global approach are used to symbolize the sequences. The forward and reverse symbol sequences are taken as the inputs of transfer entropy. Scale factor intervals of permutation and global way are (37, 57) and (65, 85) where the two kinds of EEG have satisfied entropy distinctions. When scale factor is 67, transfer entropy of the healthy and epileptic subjects of permutation, 0.1137 and 0.1028, have biggest difference. And the corresponding values of the global symbolization is 0.0641 and 0.0601 which lies in the scale factor of 165. Research results show that permutation which takes contribution of local information has better distinction and is more effectively applied to our multi-scale transfer entropy analysis of EEG.

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.

Multi-Scale Modeling of an Integrated 3D Braided Composite with Applications to Helicopter Arm

NASA Astrophysics Data System (ADS)

Zhang, Diantang; Chen, Li; Sun, Ying; Zhang, Yifan; Qian, Kun

2017-10-01

A study is conducted with the aim of developing multi-scale analytical method for designing the composite helicopter arm with three-dimensional (3D) five-directional braided structure. Based on the analysis of 3D braided microstructure, the multi-scale finite element modeling is developed. Finite element analysis on the load capacity of 3D five-directional braided composites helicopter arm is carried out using the software ABAQUS/Standard. The influences of the braiding angle and loading condition on the stress and strain distribution of the helicopter arm are simulated. The results show that the proposed multi-scale method is capable of accurately predicting the mechanical properties of 3D braided composites, validated by the comparison the stress-strain curves of meso-scale RVCs. Furthermore, it is found that the braiding angle is an important factor affecting the mechanical properties of 3D five-directional braided composite helicopter arm. Based on the optimized structure parameters, the nearly net-shaped composite helicopter arm is fabricated using a novel resin transfer mould (RTM) process.

A 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

Multiscale analysis of information dynamics for linear multivariate processes.

PubMed

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

2016-08-01

In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving average (MA) component, we describe how to represent the resulting VARMA process using statespace (SS) models and how to exploit the SS model parameters to compute analytical measures of information storage and information transfer for the original and rescaled processes. The framework is then used to quantify multiscale information dynamics for simulated unidirectionally and bidirectionally coupled VAR processes, showing that rescaling may lead to insightful patterns of information storage and transfer but also to potentially misleading behaviors.

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

PubMed

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

2018-01-28

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

Multiscale investigation of chemical interference in proteins

NASA Astrophysics Data System (ADS)

Samiotakis, Antonios; Homouz, Dirar; Cheung, Margaret S.

2010-05-01

We developed a multiscale approach (MultiSCAAL) that integrates the potential of mean force obtained from all-atomistic molecular dynamics simulations with a knowledge-based energy function for coarse-grained molecular simulations in better exploring the energy landscape of a small protein under chemical interference such as chemical denaturation. An excessive amount of water molecules in all-atomistic molecular dynamics simulations often negatively impacts the sampling efficiency of some advanced sampling techniques such as the replica exchange method and it makes the investigation of chemical interferences on protein dynamics difficult. Thus, there is a need to develop an effective strategy that focuses on sampling structural changes in protein conformations rather than solvent molecule fluctuations. In this work, we address this issue by devising a multiscale simulation scheme (MultiSCAAL) that bridges the gap between all-atomistic molecular dynamics simulation and coarse-grained molecular simulation. The two key features of this scheme are the Boltzmann inversion and a protein atomistic reconstruction method we previously developed (SCAAL). Using MultiSCAAL, we were able to enhance the sampling efficiency of proteins solvated by explicit water molecules. Our method has been tested on the folding energy landscape of a small protein Trp-cage with explicit solvent under 8M urea using both the all-atomistic replica exchange molecular dynamics and MultiSCAAL. We compared computational analyses on ensemble conformations of Trp-cage with its available experimental NOE distances. The analysis demonstrated that conformations explored by MultiSCAAL better agree with the ones probed in the experiments because it can effectively capture the changes in side-chain orientations that can flip out of the hydrophobic pocket in the presence of urea and water molecules. In this regard, MultiSCAAL is a promising and effective sampling scheme for investigating chemical interference which presents a great challenge when modeling protein interactions in vivo.

Development of a Patient-Specific Multi-Scale Model to Understand Atherosclerosis and Calcification Locations: Comparison with In vivo Data in an Aortic Dissection

PubMed Central

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

2016-01-01

Vascular calcification results in stiffening of the aorta and is associated with hypertension and atherosclerosis. Atherogenesis is a complex, multifactorial, and systemic process; the result of a number of factors, each operating simultaneously at several spatial and temporal scales. The ability to predict sites of atherogenesis would be of great use to clinicians in order to improve diagnostic and treatment planning. In this paper, we present a mathematical model as a tool to understand why atherosclerotic plaque and calcifications occur in specific locations. This model is then used to analyze vascular calcification and atherosclerotic areas in an aortic dissection patient using a mechanistic, multi-scale modeling approach, coupling patient-specific, fluid-structure interaction simulations with a model of endothelial mechanotransduction. A number of hemodynamic factors based on state-of-the-art literature are used as inputs to the endothelial permeability model, in order to investigate plaque and calcification distributions, which are compared with clinical imaging data. A significantly improved correlation between elevated hydraulic conductivity or volume flux and the presence of calcification and plaques was achieved by using a shear index comprising both mean and oscillatory shear components (HOLMES) and a non-Newtonian viscosity model as inputs, as compared to widely used hemodynamic indicators. The proposed approach shows promise as a predictive tool. The improvements obtained using the combined biomechanical/biochemical modeling approach highlight the benefits of mechanistic modeling as a powerful tool to understand complex phenomena and provides insight into the relative importance of key hemodynamic parameters. PMID:27445834

Bayesian Multiscale Modeling of Closed Curves in Point Clouds

PubMed Central

Gu, Kelvin; Pati, Debdeep; Dunson, David B.

2014-01-01

Modeling object boundaries based on image or point cloud data is frequently necessary in medical and scientific applications ranging from detecting tumor contours for targeted radiation therapy, to the classification of organisms based on their structural information. In low-contrast images or sparse and noisy point clouds, there is often insufficient data to recover local segments of the boundary in isolation. Thus, it becomes critical to model the entire boundary in the form of a closed curve. To achieve this, we develop a Bayesian hierarchical model that expresses highly diverse 2D objects in the form of closed curves. The model is based on a novel multiscale deformation process. By relating multiple objects through a hierarchical formulation, we can successfully recover missing boundaries by borrowing structural information from similar objects at the appropriate scale. Furthermore, the model’s latent parameters help interpret the population, indicating dimensions of significant structural variability and also specifying a ‘central curve’ that summarizes the collection. Theoretical properties of our prior are studied in specific cases and efficient Markov chain Monte Carlo methods are developed, evaluated through simulation examples and applied to panorex teeth images for modeling teeth contours and also to a brain tumor contour detection problem. PMID:25544786

Effect of stenosis eccentricity on the functionality of coronary bifurcation lesions-a numerical study.

PubMed

Pagiatakis, Catherine; Tardif, Jean-Claude; L'Allier, Philippe L; Mongrain, Rosaire

2017-12-01

Interventional cardiologists still rely heavily on angiography for the evaluation of coronary lesion severity, despite its poor correlation with the presence of ischemia. In order to improve the accuracy of the current diagnostic procedures, an understanding of the relative influence of geometric characteristics on the induction of ischemia is required. This idea is especially important for coronary bifurcation lesions (CBLs), whose treatment is complex and is associated with high rates of peri- and post-procedural clinical events. Overall, it is unclear which geometric and morphological parameters of CBLs influence the onset of ischemia. More specifically, the effect of stenosis eccentricity is unknown. Computational fluid dynamic simulations, under a geometric multiscale framework, were executed for seven CBL configurations within the left main coronary artery bifurcation. Both concentric and eccentric stenosis profiles of mild to severe constriction were considered. By using a geometric multiscale framework, the fractional flow reserve, which is the gold-standard clinical diagnostic index, could be calculated and was compared between the eccentric and concentric profiles for each case. The results suggested that for configurations where the supplying vessel is stenosed, eccentricity could have a notable effect on and therefore be an important factor that influences configuration functionality.

Multi-scale individual-based model of microbial and bioconversion dynamics in aerobic granular sludge.

PubMed

Xavier, Joao B; De Kreuk, Merle K; Picioreanu, Cristian; Van Loosdrecht, Mark C M

2007-09-15

Aerobic granular sludge is a novel compact biological wastewater treatment technology for integrated removal of COD (chemical oxygen demand), nitrogen, and phosphate charges. We present here a multiscale model of aerobic granular sludge sequencing batch reactors (GSBR) describing the complex dynamics of populations and nutrient removal. The macro scale describes bulk concentrations and effluent composition in six solutes (oxygen, acetate, ammonium, nitrite, nitrate, and phosphate). A finer scale, the scale of one granule (1.1 mm of diameter), describes the two-dimensional spatial arrangement of four bacterial groups--heterotrophs, ammonium oxidizers, nitrite oxidizers, and phosphate accumulating organisms (PAO)--using individual based modeling (IbM) with species-specific kinetic models. The model for PAO includes three internal storage compounds: polyhydroxyalkanoates (PHA), poly phosphate, and glycogen. Simulations of long-term reactor operation show how the microbial population and activity depends on the operating conditions. Short-term dynamics of solute bulk concentrations are also generated with results comparable to experimental data from lab scale reactors. Our results suggest that N-removal in GSBR occurs mostly via alternating nitrification/denitrification rather than simultaneous nitrification/denitrification, supporting an alternative strategy to improve N-removal in this promising wastewater treatment process.

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

Chacón, L., E-mail: chacon@lanl.gov; Chen, G.; Knoll, D.A.

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

Influences of coupled fire-atmosphere interaction on wildfire behavior

NASA Astrophysics Data System (ADS)

Linn, R.; Winterkamp, J.; Jonko, A. K.; Runde, I.; Canfield, J.; Parsons, R.; Sieg, C.

2017-12-01

Two-way interactions between fire and the environment affect fire behavior at scales ranging from buoyancy-induced mixing and turbulence to fire-scale circulations that retard or increase fire spread. Advances in computing have created new opportunities for the exploration of coupled fire-atmosphere behavior using numerical models that represent interactions between the dominant processes driving wildfire behavior, including convective and radiative heat transfer, aerodynamic drag and buoyant response of the atmosphere to heat released by the fire. Such models are not practical for operational, faster-than-real-time fire prediction due to their computational and data requirements. However, they are valuable tools for exploring influences of fire-atmosphere feedbacks on fire behavior as they explicitly simulate atmospheric motions surrounding fires from meter to kilometer scales. We use the coupled fire-atmosphere model FIRETEC to gain new insights into aspects of fire behavior that have been observed in the field and laboratory, to carry out sensitivity analysis that is impractical through observations and to pose new hypotheses that can be tested experimentally. Specifically, we use FIRETEC to study the following multi-scale coupled fire-atmosphere interactions: 1) 3D fire-atmosphere interaction that dictates multi-scale fire line dynamics; 2) influence of vegetation heterogeneity and variability in wind fields on predictability of fire spread; 3) fundamental impacts of topography on fire spread. These numerical studies support new conceptual models for the dominant roles of multi-scale fluid dynamics in determining fire spread, including the roles of crosswind fire line-intensity variations on heat transfer to unburned fuels and the role of fire line depth expansion in upslope acceleration of fires.

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

Air Pollution and Preterm Birth in the U.S. State of Georgia (2002-2006): Associations with Concentrations of 11 Ambient Air Pollutants Estimated by Combining Community Multiscale Air Quality Model (CMAQ) Simulations with Stationary Monitor Measurements.

PubMed

Hao, Hua; Chang, Howard H; Holmes, Heather A; Mulholland, James A; Klein, Mitch; Darrow, Lyndsey A; Strickland, Matthew J

2016-06-01

Previous epidemiologic studies suggest associations between preterm birth and ambient air pollution. We investigated associations between 11 ambient air pollutants, estimated by combining Community Multiscale Air Quality model (CMAQ) simulations with measurements from stationary monitors, and risk of preterm birth (< 37 weeks of gestation) in the U.S. state of Georgia. Birth records for singleton births ≥ 27 weeks of gestation with complete covariate information and estimated dates of conception between 1 January 2002 and 28 February 2006 were obtained from the Office of Health Indicators for Planning, Georgia Department of Public Health (n = 511,658 births). Daily pollutant concentrations at 12-km resolution were estimated for 11 ambient air pollutants. We used logistic regression with county-level fixed effects to estimate associations between preterm birth and average pollutant concentrations during the first and second trimester. Discrete-time survival models were used to estimate third-trimester and total pregnancy associations. Effect modification was investigated by maternal education, race, census tract poverty level, and county-level urbanicity. Trimester-specific and total pregnancy associations (p < 0.05) were observed for several pollutants. All the traffic-related pollutants (carbon monoxide, nitrogen dioxide, PM2.5 elemental carbon) were associated with preterm birth [e.g., odds ratios for interquartile range increases in carbon monoxide during the first, second, and third trimesters and total pregnancy were 1.005 (95% CI: 1.001, 1.009), 1.007 (95% CI: 1.002, 1.011), 1.010 (95% CI: 1.006, 1.014), and 1.011 (95% CI: 1.006, 1.017)]. Associations tended to be higher for mothers with low educational attainment and African American mothers. Several ambient air pollutants were associated with preterm birth; associations were observed in all exposure windows. Hao H, Chang HH, Holmes HA, Mulholland JA, Klein M, Darrow LA, Strickland MJ. 2016. Air pollution and preterm birth in the U.S. state of Georgia (2002-2006): associations with concentrations of 11 ambient air pollutants estimated by combining Community Multiscale Air Quality Model (CMAQ) simulations with stationary monitor measurements. Environ Health Perspect 124:875-880; http://dx.doi.org/10.1289/ehp.1409651.

Air Pollution and Preterm Birth in the U.S. State of Georgia (2002–2006): Associations with Concentrations of 11 Ambient Air Pollutants Estimated by Combining Community Multiscale Air Quality Model (CMAQ) Simulations with Stationary Monitor Measurements

PubMed Central

Hao, Hua; Chang, Howard H.; Holmes, Heather A.; Mulholland, James A.; Klein, Mitch; Darrow, Lyndsey A.; Strickland, Matthew J.

2015-01-01

Background: Previous epidemiologic studies suggest associations between preterm birth and ambient air pollution. Objective: We investigated associations between 11 ambient air pollutants, estimated by combining Community Multiscale Air Quality model (CMAQ) simulations with measurements from stationary monitors, and risk of preterm birth (< 37 weeks of gestation) in the U.S. state of Georgia. Methods: Birth records for singleton births ≥ 27 weeks of gestation with complete covariate information and estimated dates of conception between 1 January 2002 and 28 February 2006 were obtained from the Office of Health Indicators for Planning, Georgia Department of Public Health (n = 511,658 births). Daily pollutant concentrations at 12-km resolution were estimated for 11 ambient air pollutants. We used logistic regression with county-level fixed effects to estimate associations between preterm birth and average pollutant concentrations during the first and second trimester. Discrete-time survival models were used to estimate third-trimester and total pregnancy associations. Effect modification was investigated by maternal education, race, census tract poverty level, and county-level urbanicity. Results: Trimester-specific and total pregnancy associations (p < 0.05) were observed for several pollutants. All the traffic-related pollutants (carbon monoxide, nitrogen dioxide, PM2.5 elemental carbon) were associated with preterm birth [e.g., odds ratios for interquartile range increases in carbon monoxide during the first, second, and third trimesters and total pregnancy were 1.005 (95% CI: 1.001, 1.009), 1.007 (95% CI: 1.002, 1.011), 1.010 (95% CI: 1.006, 1.014), and 1.011 (95% CI: 1.006, 1.017)]. Associations tended to be higher for mothers with low educational attainment and African American mothers. Conclusion: Several ambient air pollutants were associated with preterm birth; associations were observed in all exposure windows. Citation: Hao H, Chang HH, Holmes HA, Mulholland JA, Klein M, Darrow LA, Strickland MJ. 2016. Air pollution and preterm birth in the U.S. state of Georgia (2002–2006): associations with concentrations of 11 ambient air pollutants estimated by combining Community Multiscale Air Quality Model (CMAQ) simulations with stationary monitor measurements. Environ Health Perspect 124:875–880; http://dx.doi.org/10.1289/ehp.1409651 PMID:26485731

Automated Pathogenesis-Based Diagnosis of Lumbar Neural Foraminal Stenosis via Deep Multiscale Multitask Learning.

PubMed

Han, Zhongyi; Wei, Benzheng; Leung, Stephanie; Nachum, Ilanit Ben; Laidley, David; Li, Shuo

2018-02-15

Pathogenesis-based diagnosis is a key step to prevent and control lumbar neural foraminal stenosis (LNFS). It conducts both early diagnosis and comprehensive assessment by drawing crucial pathological links between pathogenic factors and LNFS. Automated pathogenesis-based diagnosis would simultaneously localize and grade multiple spinal organs (neural foramina, vertebrae, intervertebral discs) to diagnose LNFS and discover pathogenic factors. The automated way facilitates planning optimal therapeutic schedules and relieving clinicians from laborious workloads. However, no successful work has been achieved yet due to its extreme challenges since 1) multiple targets: each lumbar spine has at least 17 target organs, 2) multiple scales: each type of target organ has structural complexity and various scales across subjects, and 3) multiple tasks, i.e., simultaneous localization and diagnosis of all lumbar organs, are extremely difficult than individual tasks. To address these huge challenges, we propose a deep multiscale multitask learning network (DMML-Net) integrating a multiscale multi-output learning and a multitask regression learning into a fully convolutional network. 1) DMML-Net merges semantic representations to reinforce the salience of numerous target organs. 2) DMML-Net extends multiscale convolutional layers as multiple output layers to boost the scale-invariance for various organs. 3) DMML-Net joins a multitask regression module and a multitask loss module to prompt the mutual benefit between tasks. Extensive experimental results demonstrate that DMML-Net achieves high performance (0.845 mean average precision) on T1/T2-weighted MRI scans from 200 subjects. This endows our method an efficient tool for clinical LNFS diagnosis.

Key Factors Influencing the Energy Absorption of Dual-Phase Steels: Multiscale Material Model Approach and Microstructural Optimization

NASA Astrophysics Data System (ADS)

Belgasam, Tarek M.; Zbib, Hussein M.

2018-06-01

The increase in use of dual-phase (DP) steel grades by vehicle manufacturers to enhance crash resistance and reduce body car weight requires the development of a clear understanding of the effect of various microstructural parameters on the energy absorption in these materials. Accordingly, DP steelmakers are interested in predicting the effect of various microscopic factors as well as optimizing microstructural properties for application in crash-relevant components of vehicle bodies. This study presents a microstructure-based approach using a multiscale material and structure model. In this approach, Digimat and LS-DYNA software were coupled and employed to provide a full micro-macro multiscale material model, which is then used to simulate tensile tests. Microstructures with varied ferrite grain sizes, martensite volume fractions, and carbon content in DP steels were studied. The impact of these microstructural features at different strain rates on energy absorption characteristics of DP steels is investigated numerically using an elasto-viscoplastic constitutive model. The model is implemented in a multiscale finite-element framework. A comprehensive statistical parametric study using response surface methodology is performed to determine the optimum microstructural features for a required tensile toughness at different strain rates. The simulation results are validated using experimental data found in the literature. The developed methodology proved to be effective for investigating the influence and interaction of key microscopic properties on the energy absorption characteristics of DP steels. Furthermore, it is shown that this method can be used to identify optimum microstructural conditions at different strain-rate conditions.

Key Factors Influencing the Energy Absorption of Dual-Phase Steels: Multiscale Material Model Approach and Microstructural Optimization

NASA Astrophysics Data System (ADS)

Belgasam, Tarek M.; Zbib, Hussein M.

2018-03-01

The increase in use of dual-phase (DP) steel grades by vehicle manufacturers to enhance crash resistance and reduce body car weight requires the development of a clear understanding of the effect of various microstructural parameters on the energy absorption in these materials. Accordingly, DP steelmakers are interested in predicting the effect of various microscopic factors as well as optimizing microstructural properties for application in crash-relevant components of vehicle bodies. This study presents a microstructure-based approach using a multiscale material and structure model. In this approach, Digimat and LS-DYNA software were coupled and employed to provide a full micro-macro multiscale material model, which is then used to simulate tensile tests. Microstructures with varied ferrite grain sizes, martensite volume fractions, and carbon content in DP steels were studied. The impact of these microstructural features at different strain rates on energy absorption characteristics of DP steels is investigated numerically using an elasto-viscoplastic constitutive model. The model is implemented in a multiscale finite-element framework. A comprehensive statistical parametric study using response surface methodology is performed to determine the optimum microstructural features for a required tensile toughness at different strain rates. The simulation results are validated using experimental data found in the literature. The developed methodology proved to be effective for investigating the influence and interaction of key microscopic properties on the energy absorption characteristics of DP steels. Furthermore, it is shown that this method can be used to identify optimum microstructural conditions at different strain-rate conditions.

A multiscale method for a robust detection of the default mode network

NASA Astrophysics Data System (ADS)

Baquero, Katherine; Gómez, Francisco; Cifuentes, Christian; Guldenmund, Pieter; Demertzi, Athena; Vanhaudenhuyse, Audrey; Gosseries, Olivia; Tshibanda, Jean-Flory; Noirhomme, Quentin; Laureys, Steven; Soddu, Andrea; Romero, Eduardo

2013-11-01

The Default Mode Network (DMN) is a resting state network widely used for the analysis and diagnosis of mental disorders. It is normally detected in fMRI data, but for its detection in data corrupted by motion artefacts or low neuronal activity, the use of a robust analysis method is mandatory. In fMRI it has been shown that the signal-to-noise ratio (SNR) and the detection sensitivity of neuronal regions is increased with di erent smoothing kernels sizes. Here we propose to use a multiscale decomposition based of a linear scale-space representation for the detection of the DMN. Three main points are proposed in this methodology: rst, the use of fMRI data at di erent smoothing scale-spaces, second, detection of independent neuronal components of the DMN at each scale by using standard preprocessing methods and ICA decomposition at scale-level, and nally, a weighted contribution of each scale by the Goodness of Fit measurement. This method was applied to a group of control subjects and was compared with a standard preprocesing baseline. The detection of the DMN was improved at single subject level and at group level. Based on these results, we suggest to use this methodology to enhance the detection of the DMN in data perturbed with artefacts or applied to subjects with low neuronal activity. Furthermore, the multiscale method could be extended for the detection of other resting state neuronal networks.

A multi-scale residual-based anti-hourglass control for compatible staggered Lagrangian hydrodynamics

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

Kucharik, M.; Scovazzi, Guglielmo; Shashkov, Mikhail Jurievich

Hourglassing is a well-known pathological numerical artifact affecting the robustness and accuracy of Lagrangian methods. There exist a large number of hourglass control/suppression strategies. In the community of the staggered compatible Lagrangian methods, the approach of sub-zonal pressure forces is among the most widely used. However, this approach is known to add numerical strength to the solution, which can cause potential problems in certain types of simulations, for instance in simulations of various instabilities. To avoid this complication, we have adapted the multi-scale residual-based stabilization typically used in the finite element approach for staggered compatible framework. In this study, wemore » describe two discretizations of the new approach and demonstrate their properties and compare with the method of sub-zonal pressure forces on selected numerical problems.« less

Geophysics and Nanosciences: Nano to Micro to Meso to Macro Scale Swelling Soils

NASA Astrophysics Data System (ADS)

Cushman, J.

2003-04-01

We use statistical mechanical simulations of nanoporous materials to motivate a choice of independent constitutive variables for a multiscale mixture theory of swelling soils. A video will illustrate the structural behavior of fluids in nanopores when they are adsorbed from a bulk phase vapor to form capillaries on the nanoscale. These simulations suggest that when a swelling soil is very dry, the full strain tensor for the liquid phase should be included in the list of independent variables in any mixture theory. We use this information to develop a three-scale (micro, meso, macro) mixture theory for swelling soils. For a simplified case, we present the underlying multiscale field equations and constitutive theory, solve the resultant well posed system numerically, and present some graphical results for a drying and shrinking body.

Lattice Boltzmann Modeling of Complex Flows for Engineering Applications

NASA Astrophysics Data System (ADS)

Montessori, Andrea; Falcucci, Giacomo

2018-01-01

Nature continuously presents a huge number of complex and multiscale phenomena, which in many cases, involve the presence of one or more fluids flowing, merging and evolving around us. Since the very first years of the third millennium, the Lattice Boltzmann method (LB) has seen an exponential growth of applications, especially in the fields connected with the simulation of complex and soft matter flows. LB, in fact, has shown a remarkable versatility in different fields of applications from nanoactive materials, free surface flows, and multiphase and reactive flows to the simulation of the processes inside engines and fluid machinery. In this book, the authors present the most recent advances of the application of the LB to complex flow phenomena of scientific and technical interest with focus on the multiscale modeling of heterogeneous catalysis within nano-porous media and multiphase, multicomponent flows.

Multiscale atomistic simulation of metal-oxygen surface interactions: Methodological development, theoretical investigation, and correlation with experiment

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

Yang, Judith C.

The purpose of this grant is to develop the multi-scale theoretical methods to describe the nanoscale oxidation of metal thin films, as the PI (Yang) extensive previous experience in the experimental elucidation of the initial stages of Cu oxidation by primarily in situ transmission electron microscopy methods. Through the use and development of computational tools at varying length (and time) scales, from atomistic quantum mechanical calculation, force field mesoscale simulations, to large scale Kinetic Monte Carlo (KMC) modeling, the fundamental underpinings of the initial stages of Cu oxidation have been elucidated. The development of computational modeling tools allows for acceleratedmore » materials discovery. The theoretical tools developed from this program impact a wide range of technologies that depend on surface reactions, including corrosion, catalysis, and nanomaterials fabrication.« less

A multi-scale residual-based anti-hourglass control for compatible staggered Lagrangian hydrodynamics

DOE PAGES

Kucharik, M.; Scovazzi, Guglielmo; Shashkov, Mikhail Jurievich; ...

2017-10-28

Hourglassing is a well-known pathological numerical artifact affecting the robustness and accuracy of Lagrangian methods. There exist a large number of hourglass control/suppression strategies. In the community of the staggered compatible Lagrangian methods, the approach of sub-zonal pressure forces is among the most widely used. However, this approach is known to add numerical strength to the solution, which can cause potential problems in certain types of simulations, for instance in simulations of various instabilities. To avoid this complication, we have adapted the multi-scale residual-based stabilization typically used in the finite element approach for staggered compatible framework. In this study, wemore » describe two discretizations of the new approach and demonstrate their properties and compare with the method of sub-zonal pressure forces on selected numerical problems.« less

Investigating ice nucleation in cirrus clouds with an aerosol-enabled Multiscale Modeling Framework

DOE PAGES

Zhang, Chengzhu; Wang, Minghuai; Morrison, H.; ...

2014-11-06

In this study, an aerosol-dependent ice nucleation scheme [Liu and Penner, 2005] has been implemented in an aerosol-enabled multi-scale modeling framework (PNNL MMF) to study ice formation in upper troposphere cirrus clouds through both homogeneous and heterogeneous nucleation. The MMF model represents cloud scale processes by embedding a cloud-resolving model (CRM) within each vertical column of a GCM grid. By explicitly linking ice nucleation to aerosol number concentration, CRM-scale temperature, relative humidity and vertical velocity, the new MMF model simulates the persistent high ice supersaturation and low ice number concentration (10 to 100/L) at cirrus temperatures. The low ice numbermore » is attributed to the dominance of heterogeneous nucleation in ice formation. The new model simulates the observed shift of the ice supersaturation PDF towards higher values at low temperatures following homogeneous nucleation threshold. The MMF models predict a higher frequency of midlatitude supersaturation in the Southern hemisphere and winter hemisphere, which is consistent with previous satellite and in-situ observations. It is shown that compared to a conventional GCM, the MMF is a more powerful model to emulate parameters that evolve over short time scales such as supersaturation. Sensitivity tests suggest that the simulated global distribution of ice clouds is sensitive to the ice nucleation schemes and the distribution of sulfate and dust aerosols. Simulations are also performed to test empirical parameters related to auto-conversion of ice crystals to snow. Results show that with a value of 250 μm for the critical diameter, Dcs, that distinguishes ice crystals from snow, the model can produce good agreement to the satellite retrieved products in terms of cloud ice water path and ice water content, while the total ice water is not sensitive to the specification of Dcs value.« less

Modelling an industrial anaerobic granular reactor using a multi-scale approach.

PubMed

Feldman, H; Flores-Alsina, X; Ramin, P; Kjellberg, K; Jeppsson, U; Batstone, D J; Gernaey, K V

2017-12-01

The objective of this paper is to show the results of an industrial project dealing with modelling of anaerobic digesters. A multi-scale mathematical approach is developed to describe reactor hydrodynamics, granule growth/distribution and microbial competition/inhibition for substrate/space within the biofilm. The main biochemical and physico-chemical processes in the model are based on the Anaerobic Digestion Model No 1 (ADM1) extended with the fate of phosphorus (P), sulfur (S) and ethanol (Et-OH). Wastewater dynamic conditions are reproduced and data frequency increased using the Benchmark Simulation Model No 2 (BSM2) influent generator. All models are tested using two plant data sets corresponding to different operational periods (#D1, #D2). Simulation results reveal that the proposed approach can satisfactorily describe the transformation of organics, nutrients and minerals, the production of methane, carbon dioxide and sulfide and the potential formation of precipitates within the bulk (average deviation between computer simulations and measurements for both #D1, #D2 is around 10%). Model predictions suggest a stratified structure within the granule which is the result of: 1) applied loading rates, 2) mass transfer limitations and 3) specific (bacterial) affinity for substrate. Hence, inerts (X I ) and methanogens (X ac ) are situated in the inner zone, and this fraction lowers as the radius increases favouring the presence of acidogens (X su ,X aa , X fa ) and acetogens (X c4 ,X pro ). Additional simulations show the effects on the overall process performance when operational (pH) and loading (S:COD) conditions are modified. Lastly, the effect of intra-granular precipitation on the overall organic/inorganic distribution is assessed at: 1) different times; and, 2) reactor heights. Finally, the possibilities and opportunities offered by the proposed approach for conducting engineering optimization projects are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

TGLF Recalibration for ITER Standard Case Parameters FY2015: Theory and Simulation Performance Target Final Report

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

Candy, J.

2015-12-01

This work was motivated by the observation, as early as 2008, that GYRO simulations of some ITER operating scenarios exhibited nonlinear zonal-flow generation large enough to effectively quench turbulence inside r /a ~ 0.5. This observation of flow-dominated, low-transport states persisted even as more accurate and comprehensive predictions of ITER profiles were made using the state-of-the-art TGLF transport model. This core stabilization is in stark contrast to GYRO-TGLF comparisons for modern-day tokamaks, for which GYRO and TGLF are typically in very close agreement. So, we began to suspect that TGLF needed to be generalized to include the effect of zonal-flowmore » stabilization in order to be more accurate for the conditions of reactor simulations. While the precise cause of the GYRO-TGLF discrepancy for ITER parameters was not known, it was speculated that closeness to threshold in the absence of driven rotation, as well as electromagnetic stabilization, created conditions more sensitive the self-generated zonal-flow stabilization than in modern tokamaks. Need for nonlinear zonal-flow stabilization: To explore the inclusion of a zonal-flow stabilization mechanism in TGLF, we started with a nominal ITER profile predicted by TGLF, and then performed linear and nonlinear GYRO simulations to characterize the behavior at and slightly above the nominal temperature gradients for finite levels of energy transport. Then, we ran TGLF on these cases to see where the discrepancies were largest. The predicted ITER profiles were indeed near to the TGLF threshold over most of the plasma core in the hybrid discharge studied (weak magnetic shear, q > 1). Scanning temperature gradients above the TGLF power balance values also showed that TGLF overpredicted the electron energy transport in the low-collisionality ITER plasma. At first (in Q3), a model of only the zonal-flow stabilization (Dimits shift) was attempted. Although we were able to construct an ad hoc model of the zonal flows that fit the GYRO simulations, the parameters of the model had to be tuned to each case. A physics basis for the zonal flow model was lacking. Electron energy transport at short wavelength: A secondary issue – the high-k electron energy flux – was initially assumed to be independent of the zonal flow effect. However, detailed studies of the fluctuation spectra from recent multiscale (electron and ion scale) GYRO simulations provided a critical new insight into the role of zonal flows. The multiscale simulations suggested that advection by the zonal flows strongly suppressed electron-scale turbulence. Radial shear of the zonal E×B fluctuation could not compete with the large electron-scale linear growth rate, but the k x-mixing rate of the E×B advection could. This insight led to a preliminary new model for the way zonal flows saturate both electron- and ion-scale turbulence. It was also discovered that the strength of the zonal E×B velocity could be computed from the linear growth rate spectrum. The new saturation model (SAT1), which replaces the original model (SAT0), was fit to the multiscale GYRO simulations as well as the ion-scale GYRO simulations used to calibrate the original SAT0 model. Thus, SAT1 captures the physics of both multiscale electron transport and zonal-flow stabilization. In future work, the SAT1 model will require significant further testing and (expensive) calibration with nonlinear multiscale gyrokinetic simulations over a wider variety of plasma conditions – certainly more than the small set of scans about a single C-Mod L-mode discharge. We believe the SAT1 model holds great promise as a physics-based model of the multiscale turbulent transport in fusion devices. Correction to ITER performance predictions: Finally, the impact of the SAT1model on the ITER hybrid case is mixed. Without the electron-scale contribution to the fluxes, the Dimits shift makes a significant improvement in the predicted fusion power as originally posited. Alas, including the high-k electron transport reduces the improvement, yielding a modest net increase in predicted fusion power compared to the TGLF prediction with the original SAT0 model.« less

Subject-specific computer simulation model for determining elbow loading in one-handed tennis backhand groundstrokes.

PubMed

King, Mark A; Glynn, Jonathan A; Mitchell, Sean R

2011-11-01

A subject-specific angle-driven computer model of a tennis player, combined with a forward dynamics, equipment-specific computer model of tennis ball-racket impacts, was developed to determine the effect of ball-racket impacts on loading at the elbow for one-handed backhand groundstrokes. Matching subject-specific computer simulations of a typical topspin/slice one-handed backhand groundstroke performed by an elite tennis player were done with root mean square differences between performance and matching simulations of < 0.5 degrees over a 50 ms period starting from ball impact. Simulation results suggest that for similar ball-racket impact conditions, the difference in elbow loading for a topspin and slice one-handed backhand groundstroke is relatively small. In this study, the relatively small differences in elbow loading may be due to comparable angle-time histories at the wrist and elbow joints with the major kinematic differences occurring at the shoulder. Using a subject-specific angle-driven computer model combined with a forward dynamics, equipment-specific computer model of tennis ball-racket impacts allows peak internal loading, net impulse, and shock due to ball-racket impact to be calculated which would not otherwise be possible without impractical invasive techniques. This study provides a basis for further investigation of the factors that may increase elbow loading during tennis strokes.

Multiscale Modeling of Polycrystalline NiTi Shape Memory Alloy under Various Plastic Deformation Conditions by Coupling Microstructure Evolution and Macroscopic Mechanical Response

PubMed Central

Jiang, Shuyong; Zhou, Tao; Tu, Jian; Shi, Laixin; Chen, Qiang; Yang, Mingbo

2017-01-01

Numerical modeling of microstructure evolution in various regions during uniaxial compression and canning compression of NiTi shape memory alloy (SMA) are studied through combined macroscopic and microscopic finite element simulation in order to investigate plastic deformation of NiTi SMA at 400 °C. In this approach, the macroscale material behavior is modeled with a relatively coarse finite element mesh, and then the corresponding deformation history in some selected regions in this mesh is extracted by the sub-model technique of finite element code ABAQUS and subsequently used as boundary conditions for the microscale simulation by means of crystal plasticity finite element method (CPFEM). Simulation results show that NiTi SMA exhibits an inhomogeneous plastic deformation at the microscale. Moreover, regions that suffered canning compression sustain more homogeneous plastic deformation by comparison with the corresponding regions subjected to uniaxial compression. The mitigation of inhomogeneous plastic deformation contributes to reducing the statistically stored dislocation (SSD) density in polycrystalline aggregation and also to reducing the difference of stress level in various regions of deformed NiTi SMA sample, and therefore sustaining large plastic deformation in the canning compression process. PMID:29027925

Multiscale Modeling of Polycrystalline NiTi Shape Memory Alloy under Various Plastic Deformation Conditions by Coupling Microstructure Evolution and Macroscopic Mechanical Response.

PubMed

Hu, Li; Jiang, Shuyong; Zhou, Tao; Tu, Jian; Shi, Laixin; Chen, Qiang; Yang, Mingbo

2017-10-13

Numerical modeling of microstructure evolution in various regions during uniaxial compression and canning compression of NiTi shape memory alloy (SMA) are studied through combined macroscopic and microscopic finite element simulation in order to investigate plastic deformation of NiTi SMA at 400 °C. In this approach, the macroscale material behavior is modeled with a relatively coarse finite element mesh, and then the corresponding deformation history in some selected regions in this mesh is extracted by the sub-model technique of finite element code ABAQUS and subsequently used as boundary conditions for the microscale simulation by means of crystal plasticity finite element method (CPFEM). Simulation results show that NiTi SMA exhibits an inhomogeneous plastic deformation at the microscale. Moreover, regions that suffered canning compression sustain more homogeneous plastic deformation by comparison with the corresponding regions subjected to uniaxial compression. The mitigation of inhomogeneous plastic deformation contributes to reducing the statistically stored dislocation (SSD) density in polycrystalline aggregation and also to reducing the difference of stress level in various regions of deformed NiTi SMA sample, and therefore sustaining large plastic deformation in the canning compression process.

Evaluation of the Community Multiscale Air Quality (CMAQ) Model Version 5.1

EPA Science Inventory

The AMAD will performed two CMAQ model simulations, one with the current publically available version of the CMAQ model (v5.0.2) and the other with the new version of the CMAQ model (v5.1). The results of each model simulation are compared to observations and the performance of t...

Preliminary Evaluation of the Community Multiscale Air Quality (CMAQ) Model Version 5.1

EPA Science Inventory

The AMAD will perform two annual CMAQ model simulations, one with the current publically available version of the CMAQ model (v5.0.2) and the other with the beta version of the new model (v5.1). The results of each model simulation will then be compared to observations and the pe...

A Novel Probabilistic Multi-Scale Modeling and Sensing Framework for Fatigue Life Prediction of Aerospace Structures and Materials: DCT Project

DTIC Science & Technology

2012-08-25

Accel- erated Crystal Plasticity FEM Simulations (submitted). 5. M. Anahid, M. Samal and S. Ghosh, Dwell fatigue crack nucleation model based on using...4] M. Anahid, M. K. Samal , and S. Ghosh. Dwell fatigue crack nucleation model based on crystal plasticity finite element simulations of

Modeling multi-scale aerosol dynamics and micro-environmental air quality near a large highway intersection using the CTAG model.

PubMed

Wang, Yan Jason; Nguyen, Monica T; Steffens, Jonathan T; Tong, Zheming; Wang, Yungang; Hopke, Philip K; Zhang, K Max

2013-01-15

A new methodology, referred to as the multi-scale structure, integrates "tailpipe-to-road" (i.e., on-road domain) and "road-to-ambient" (i.e., near-road domain) simulations to elucidate the environmental impacts of particulate emissions from traffic sources. The multi-scale structure is implemented in the CTAG model to 1) generate process-based on-road emission rates of ultrafine particles (UFPs) by explicitly simulating the effects of exhaust properties, traffic conditions, and meteorological conditions and 2) to characterize the impacts of traffic-related emissions on micro-environmental air quality near a highway intersection in Rochester, NY. The performance of CTAG, evaluated against with the field measurements, shows adequate agreement in capturing the dispersion of carbon monoxide (CO) and the number concentrations of UFPs in the near road micro-environment. As a proof-of-concept case study, we also apply CTAG to separate the relative impacts of the shutdown of a large coal-fired power plant (CFPP) and the adoption of the ultra-low-sulfur diesel (ULSD) on UFP concentrations in the intersection micro-environment. Although CTAG is still computationally expensive compared to the widely-used parameterized dispersion models, it has the potential to advance our capability to predict the impacts of UFP emissions and spatial/temporal variations of air pollutants in complex environments. Furthermore, for the on-road simulations, CTAG can serve as a process-based emission model; Combining the on-road and near-road simulations, CTAG becomes a "plume-in-grid" model for mobile emissions. The processed emission profiles can potentially improve regional air quality and climate predictions accordingly. Copyright © 2012 Elsevier B.V. All rights reserved.

Relaxation dynamics of internal segments of DNA chains in nanochannels

NASA Astrophysics Data System (ADS)

Jain, Aashish; Muralidhar, Abhiram; Dorfman, Kevin; Dorfman Group Team

We will present relaxation dynamics of internal segments of a DNA chain confined in nanochannel. The results have direct application in genome mapping technology, where long DNA molecules containing sequence-specific fluorescent probes are passed through an array of nanochannels to linearize them, and then the distances between these probes (the so-called ``DNA barcode'') are measured. The relaxation dynamics of internal segments set the experimental error due to dynamic fluctuations. We developed a multi-scale simulation algorithm, combining a Pruned-Enriched Rosenbluth Method (PERM) simulation of a discrete wormlike chain model with hard spheres with Brownian dynamics (BD) simulations of a bead-spring chain. Realistic parameters such as the bead friction coefficient and spring force law parameters are obtained from PERM simulations and then mapped onto the bead-spring model. The BD simulations are carried out to obtain the extension autocorrelation functions of various segments, which furnish their relaxation times. Interestingly, we find that (i) corner segments relax faster than the center segments and (ii) relaxation times of corner segments do not depend on the contour length of DNA chain, whereas the relaxation times of center segments increase linearly with DNA chain size.

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

Savic, Vesna; Hector, Louis G.; Ezzat, Hesham

This paper presents an overview of a four-year project focused on development of an integrated computational materials engineering (ICME) toolset for third generation advanced high-strength steels (3GAHSS). Following a brief look at ICME as an emerging discipline within the Materials Genome Initiative, technical tasks in the ICME project will be discussed. Specific aims of the individual tasks are multi-scale, microstructure-based material model development using state-of-the-art computational and experimental techniques, forming, toolset assembly, design optimization, integration and technical cost modeling. The integrated approach is initially illustrated using a 980 grade transformation induced plasticity (TRIP) steel, subject to a two-step quenching andmore » partitioning (Q&P) heat treatment, as an example.« less

Musculoskeletal Simulation Model Generation from MRI Data Sets and Motion Capture Data

NASA Astrophysics Data System (ADS)

Schmid, Jérôme; Sandholm, Anders; Chung, François; Thalmann, Daniel; Delingette, Hervé; Magnenat-Thalmann, Nadia

Today computer models and computer simulations of the musculoskeletal system are widely used to study the mechanisms behind human gait and its disorders. The common way of creating musculoskeletal models is to use a generic musculoskeletal model based on data derived from anatomical and biomechanical studies of cadaverous specimens. To adapt this generic model to a specific subject, the usual approach is to scale it. This scaling has been reported to introduce several errors because it does not always account for subject-specific anatomical differences. As a result, a novel semi-automatic workflow is proposed that creates subject-specific musculoskeletal models from magnetic resonance imaging (MRI) data sets and motion capture data. Based on subject-specific medical data and a model-based automatic segmentation approach, an accurate modeling of the anatomy can be produced while avoiding the scaling operation. This anatomical model coupled with motion capture data, joint kinematics information, and muscle-tendon actuators is finally used to create a subject-specific musculoskeletal model.

Multiscale model of a freeze–thaw process for tree sap exudation

PubMed Central

Graf, Isabell; Ceseri, Maurizio; Stockie, John M.

2015-01-01

Sap transport in trees has long fascinated scientists, and a vast literature exists on experimental and modelling studies of trees during the growing season when large negative stem pressures are generated by transpiration from leaves. Much less attention has been paid to winter months when trees are largely dormant but nonetheless continue to exhibit interesting flow behaviour. A prime example is sap exudation, which refers to the peculiar ability of sugar maple (Acer saccharum) and related species to generate positive stem pressure while in a leafless state. Experiments demonstrate that ambient temperatures must oscillate about the freezing point before significantly heightened stem pressures are observed, but the precise causes of exudation remain unresolved. The prevailing hypothesis attributes exudation to a physical process combining freeze–thaw and osmosis, which has some support from experimental studies but remains a subject of active debate. We address this knowledge gap by developing the first mathematical model for exudation, while also introducing several essential modifications to this hypothesis. We derive a multiscale model consisting of a nonlinear system of differential equations governing phase change and transport within wood cells, coupled to a suitably homogenized equation for temperature on the macroscale. Numerical simulations yield stem pressures that are consistent with experiments and provide convincing evidence that a purely physical mechanism is capable of capturing exudation. PMID:26400199

Multiscale model of a freeze-thaw process for tree sap exudation.

PubMed

Graf, Isabell; Ceseri, Maurizio; Stockie, John M

2015-10-06

Sap transport in trees has long fascinated scientists, and a vast literature exists on experimental and modelling studies of trees during the growing season when large negative stem pressures are generated by transpiration from leaves. Much less attention has been paid to winter months when trees are largely dormant but nonetheless continue to exhibit interesting flow behaviour. A prime example is sap exudation, which refers to the peculiar ability of sugar maple (Acer saccharum) and related species to generate positive stem pressure while in a leafless state. Experiments demonstrate that ambient temperatures must oscillate about the freezing point before significantly heightened stem pressures are observed, but the precise causes of exudation remain unresolved. The prevailing hypothesis attributes exudation to a physical process combining freeze-thaw and osmosis, which has some support from experimental studies but remains a subject of active debate. We address this knowledge gap by developing the first mathematical model for exudation, while also introducing several essential modifications to this hypothesis. We derive a multiscale model consisting of a nonlinear system of differential equations governing phase change and transport within wood cells, coupled to a suitably homogenized equation for temperature on the macroscale. Numerical simulations yield stem pressures that are consistent with experiments and provide convincing evidence that a purely physical mechanism is capable of capturing exudation. © 2015 The Author(s).

77 FR 37684 - National Institute of Biomedical Imaging and Bioengineering; Notice of Closed Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-22

... Imaging and Bioengineering Special Emphasis Panel; Center for Multiscale Simulations in the Human....D., Scientific Review Officer, 6707 Democracy Boulevard, Room 959, Bethesda, MD 20892, 301-451- 3398...

Foreword to 'Multiscale structural biology: biophysical principles and mechanisms underlying the action of bio-nanomachines', a special issue in Honour of Fumio Arisaka's 70th birthday.

PubMed

Hall, Damien; Takagi, Junichi; Nakamura, Haruki

2018-04-01

This issue of Biophysical Reviews, titled 'Multiscale structural biology: biophysical principles and mechanisms underlying the action of bio-nanomachines', is a collection of articles dedicated in honour of Professor Fumio Arisaka's 70th birthday. Initially, working in the fields of haemocyanin and actin filament assembly, Fumio went on to publish important work on the elucidation of structural and functional aspects of T4 phage biology. As his career has transitioned levels of complexity from proteins (hemocyanin) to large protein complexes (actin) to even more massive bio-nanomachinery (phage), it is fitting that the subject of this special issue is similarly reflective of his multiscale approach to structural biology. This festschrift contains articles spanning biophysical structure and function from the bio-molecular through to the bio-nanomachine level.

Multiscale permutation entropy analysis of electrocardiogram

NASA Astrophysics Data System (ADS)

Liu, Tiebing; Yao, Wenpo; Wu, Min; Shi, Zhaorong; Wang, Jun; Ning, Xinbao

2017-04-01

To make a comprehensive nonlinear analysis to ECG, multiscale permutation entropy (MPE) was applied to ECG characteristics extraction to make a comprehensive nonlinear analysis of ECG. Three kinds of ECG from PhysioNet database, congestive heart failure (CHF) patients, healthy young and elderly subjects, are applied in this paper. We set embedding dimension to 4 and adjust scale factor from 2 to 100 with a step size of 2, and compare MPE with multiscale entropy (MSE). As increase of scale factor, MPE complexity of the three ECG signals are showing first-decrease and last-increase trends. When scale factor is between 10 and 32, complexities of the three ECG had biggest difference, entropy of the elderly is 0.146 less than the CHF patients and 0.025 larger than the healthy young in average, in line with normal physiological characteristics. Test results showed that MPE can effectively apply in ECG nonlinear analysis, and can effectively distinguish different ECG signals.

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

A physics based multiscale modeling of cavitating flows.

PubMed

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

2017-03-02

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

A physics based multiscale modeling of cavitating flows

PubMed Central

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

2018-01-01

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

CCSI and the role of advanced computing in accelerating the commercial deployment of carbon capture systems

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

Miller, David; Agarwal, Deborah A.; Sun, Xin

2011-09-01

The Carbon Capture Simulation Initiative is developing state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technology. The CCSI Toolset consists of an integrated multi-scale modeling and simulation framework, which includes extensive use of reduced order models (ROMs) and a comprehensive uncertainty quantification (UQ) methodology. This paper focuses on the interrelation among high performance computing, detailed device simulations, ROMs for scale-bridging, UQ and the integration framework.

CCSI and the role of advanced computing in accelerating the commercial deployment of carbon capture systems

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

Miller, D.; Agarwal, D.; Sun, X.

2011-01-01

The Carbon Capture Simulation Initiative is developing state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technology. The CCSI Toolset consists of an integrated multi-scale modeling and simulation framework, which includes extensive use of reduced order models (ROMs) and a comprehensive uncertainty quantification (UQ) methodology. This paper focuses on the interrelation among high performance computing, detailed device simulations, ROMs for scale-bridging, UQ and the integration framework.

Fast Decentralized Averaging via Multi-scale Gossip

NASA Astrophysics Data System (ADS)

Tsianos, Konstantinos I.; Rabbat, Michael G.

We are interested in the problem of computing the average consensus in a distributed fashion on random geometric graphs. We describe a new algorithm called Multi-scale Gossip which employs a hierarchical decomposition of the graph to partition the computation into tractable sub-problems. Using only pairwise messages of fixed size that travel at most O(n^{1/3}) hops, our algorithm is robust and has communication cost of O(n loglogn logɛ - 1) transmissions, which is order-optimal up to the logarithmic factor in n. Simulated experiments verify the good expected performance on graphs of many thousands of nodes.

Simulations and Evaluation of Mesoscale Convective Systems in a Multi-scale Modeling Framework (MMF)

NASA Astrophysics Data System (ADS)

Chern, J. D.; Tao, W. K.

2017-12-01

It is well known that the mesoscale convective systems (MCS) produce more than 50% of rainfall in most tropical regions and play important roles in regional and global water cycles. Simulation of MCSs in global and climate models is a very challenging problem. Typical MCSs have horizontal scale of a few hundred kilometers. Models with a domain of several hundred kilometers and fine enough resolution to properly simulate individual clouds are required to realistically simulate MCSs. The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has shown some capabilities of simulating organized MCS-like storm signals and propagations. However, its embedded CRMs typically have small domain (less than 128 km) and coarse resolution ( 4 km) that cannot realistically simulate MCSs and individual clouds. In this study, a series of simulations were performed using the Goddard MMF. The impacts of the domain size and model grid resolution of the embedded CRMs on simulating MCSs are examined. The changes of cloud structure, occurrence, and properties such as cloud types, updraft and downdraft, latent heating profile, and cold pool strength in the embedded CRMs are examined in details. The simulated MCS characteristics are evaluated against satellite measurements using the Goddard Satellite Data Simulator Unit. The results indicate that embedded CRMs with large domain and fine resolution tend to produce better simulations compared to those simulations with typical MMF configuration (128 km domain size and 4 km model grid spacing).