Sample records for multiscale model simul
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Filters for Improvement of Multiscale Data from Atomistic Simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gardner, David J.; Reynolds, Daniel R.
Multiscale computational models strive to produce accurate and efficient numerical simulations of systems involving interactions across multiple spatial and temporal scales that typically differ by several orders of magnitude. Some such models utilize a hybrid continuum-atomistic approach combining continuum approximations with first-principles-based atomistic models to capture multiscale behavior. By following the heterogeneous multiscale method framework for developing multiscale computational models, unknown continuum scale data can be computed from an atomistic model. Concurrently coupling the two models requires performing numerous atomistic simulations which can dominate the computational cost of the method. Furthermore, when the resulting continuum data is noisy due tomore » sampling error, stochasticity in the model, or randomness in the initial conditions, filtering can result in significant accuracy gains in the computed multiscale data without increasing the size or duration of the atomistic simulations. In this work, we demonstrate the effectiveness of spectral filtering for increasing the accuracy of noisy multiscale data obtained from atomistic simulations. Moreover, we present a robust and automatic method for closely approximating the optimum level of filtering in the case of additive white noise. By improving the accuracy of this filtered simulation data, it leads to a dramatic computational savings by allowing for shorter and smaller atomistic simulations to achieve the same desired multiscale simulation precision.« less
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Filters for Improvement of Multiscale Data from Atomistic Simulations
Gardner, David J.; Reynolds, Daniel R.
2017-01-05
Multiscale computational models strive to produce accurate and efficient numerical simulations of systems involving interactions across multiple spatial and temporal scales that typically differ by several orders of magnitude. Some such models utilize a hybrid continuum-atomistic approach combining continuum approximations with first-principles-based atomistic models to capture multiscale behavior. By following the heterogeneous multiscale method framework for developing multiscale computational models, unknown continuum scale data can be computed from an atomistic model. Concurrently coupling the two models requires performing numerous atomistic simulations which can dominate the computational cost of the method. Furthermore, when the resulting continuum data is noisy due tomore » sampling error, stochasticity in the model, or randomness in the initial conditions, filtering can result in significant accuracy gains in the computed multiscale data without increasing the size or duration of the atomistic simulations. In this work, we demonstrate the effectiveness of spectral filtering for increasing the accuracy of noisy multiscale data obtained from atomistic simulations. Moreover, we present a robust and automatic method for closely approximating the optimum level of filtering in the case of additive white noise. By improving the accuracy of this filtered simulation data, it leads to a dramatic computational savings by allowing for shorter and smaller atomistic simulations to achieve the same desired multiscale simulation precision.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Tawhai, Merryn; Bischoff, Jeff; Einstein, Daniel R.
2009-05-01
Abstract In this article, we describe some current multiscale modeling issues in computational biomechanics from the perspective of the musculoskeletal and respiratory systems and mechanotransduction. First, we outline the necessity of multiscale simulations in these biological systems. Then we summarize challenges inherent to multiscale biomechanics modeling, regardless of the subdiscipline, followed by computational challenges that are system-specific. We discuss some of the current tools that have been utilized to aid research in multiscale mechanics simulations, and the priorities to further the field of multiscale biomechanics computation.
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Performance of distributed multiscale simulations
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
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A Generalized Hybrid Multiscale Modeling Approach for Flow and Reactive Transport in Porous Media
NASA Astrophysics Data System (ADS)
Yang, X.; Meng, X.; Tang, Y. H.; Guo, Z.; Karniadakis, G. E.
2017-12-01
Using emerging understanding of biological and environmental processes at fundamental scales to advance predictions of the larger system behavior requires the development of multiscale approaches, and there is strong interest in coupling models at different scales together in a hybrid multiscale simulation framework. A limited number of hybrid multiscale simulation methods have been developed for subsurface applications, mostly using application-specific approaches for model coupling. The proposed generalized hybrid multiscale approach is designed with minimal intrusiveness to the at-scale simulators (pre-selected) and provides a set of lightweight C++ scripts to manage a complex multiscale workflow utilizing a concurrent coupling approach. The workflow includes at-scale simulators (using the lattice-Boltzmann method, LBM, at the pore and Darcy scale, respectively), scripts for boundary treatment (coupling and kriging), and a multiscale universal interface (MUI) for data exchange. The current study aims to apply the generalized hybrid multiscale modeling approach to couple pore- and Darcy-scale models for flow and mixing-controlled reaction with precipitation/dissolution in heterogeneous porous media. The model domain is packed heterogeneously that the mixing front geometry is more complex and not known a priori. To address those challenges, the generalized hybrid multiscale modeling approach is further developed to 1) adaptively define the locations of pore-scale subdomains, 2) provide a suite of physical boundary coupling schemes and 3) consider the dynamic change of the pore structures due to mineral precipitation/dissolution. The results are validated and evaluated by comparing with single-scale simulations in terms of velocities, reactive concentrations and computing cost.
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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.
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Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen
DOE Office of Scientific and Technical Information (OSTI.GOV)
Plechac, Petr; Vlachos, Dionisios; Katsoulakis, Markos
2013-09-05
The overall objective of this project is to develop multiscale models for understanding and eventually designing complex processes for renewables. To the best of our knowledge, our work is the first attempt at modeling complex reacting systems, whose performance relies on underlying multiscale mathematics. Our specific application lies at the heart of biofuels initiatives of DOE and entails modeling of catalytic systems, to enable economic, environmentally benign, and efficient conversion of biomass into either hydrogen or valuable chemicals. Specific goals include: (i) Development of rigorous spatio-temporal coarse-grained kinetic Monte Carlo (KMC) mathematics and simulation for microscopic processes encountered in biomassmore » transformation. (ii) Development of hybrid multiscale simulation that links stochastic simulation to a deterministic partial differential equation (PDE) model for an entire reactor. (iii) Development of hybrid multiscale simulation that links KMC simulation with quantum density functional theory (DFT) calculations. (iv) Development of parallelization of models of (i)-(iii) to take advantage of Petaflop computing and enable real world applications of complex, multiscale models. In this NCE period, we continued addressing these objectives and completed the proposed work. Main initiatives, key results, and activities are outlined.« less
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Multiscale Modeling and Simulation of Material Processing
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
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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.
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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
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Modeling Framework for Fracture in Multiscale Cement-Based Material Structures
Qian, Zhiwei; Schlangen, Erik; Ye, Guang; van Breugel, Klaas
2017-01-01
Multiscale modeling for cement-based materials, such as concrete, is a relatively young subject, but there are already a number of different approaches to study different aspects of these classical materials. In this paper, the parameter-passing multiscale modeling scheme is established and applied to address the multiscale modeling problem for the integrated system of cement paste, mortar, and concrete. The block-by-block technique is employed to solve the length scale overlap challenge between the mortar level (0.1–10 mm) and the concrete level (1–40 mm). The microstructures of cement paste are simulated by the HYMOSTRUC3D model, and the material structures of mortar and concrete are simulated by the Anm material model. Afterwards the 3D lattice fracture model is used to evaluate their mechanical performance by simulating a uniaxial tensile test. The simulated output properties at a lower scale are passed to the next higher scale to serve as input local properties. A three-level multiscale lattice fracture analysis is demonstrated, including cement paste at the micrometer scale, mortar at the millimeter scale, and concrete at centimeter scale. PMID:28772948
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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.
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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.
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Anatomy and Physiology of Multiscale Modeling and Simulation in Systems Medicine.
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.
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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.
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Multi-scale modeling in cell biology
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
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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.
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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...
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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.
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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 (...
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An approach to multiscale modelling with graph grammars.
Ong, Yongzhi; Streit, Katarína; Henke, Michael; Kurth, Winfried
2014-09-01
Functional-structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.
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An approach to multiscale modelling with graph grammars
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
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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.
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American Society of Composites, 32nd Technical Conference
DOE Office of Scientific and Technical Information (OSTI.GOV)
Aitharaju, Venkat; Wollschlager, Jeffrey; Plakomytis2, Dimitrios
This paper will present a general methodology by which weave draping manufacturing simulation results can be utilized to include the effects of weave draping and scissor angle in a structural multiscale simulation. While the methodology developed is general in nature, this paper will specifically demonstrate the methodology applied to a truncated pyramid, utilizing manufacturing simulation weave draping results from ESI PAM-FORM, and multiscale simulation using Altair Multiscale Designer (MDS) and OptiStruct. From a multiscale simulation perspective, the weave draping manufacturing simulation results will be used to develop a series of woven unit cells which cover the range of weave scissormore » angles existing within the part. For each unit cell, a multiscale material model will be developed, and applied to the corresponding spatial locations within the structural simulation mesh. In addition, the principal material orientation will be mapped from the wave draping manufacturing simulation mesh to the structural simulation mesh using Altair HyperMesh mapping technology. Results of the coupled simulation will be compared and verified against experimental data of the same available via General Motors (GM) Department of Energy (DOE) project.« less
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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.
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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
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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
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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 ...
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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.
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Multi-Scale Characterization of Orthotropic Microstructures
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
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Wadehn, Federico; Schaller, Stephan; Eissing, Thomas; Krauss, Markus; Kupfer, Lars
2016-08-01
A multiscale model for blood glucose regulation in diabetes type I patients is constructed by integrating detailed metabolic network models for fat, liver and muscle cells into a whole body physiologically-based pharmacokinetic/pharmacodynamic (pBPK/PD) model. The blood glucose regulation PBPK/PD model simulates the distribution and metabolization of glucose, insulin and glucagon on an organ and whole body level. The genome-scale metabolic networks in contrast describe intracellular reactions. The developed multiscale model is fitted to insulin, glucagon and glucose measurements of a 48h clinical trial featuring 6 subjects and is subsequently used to simulate (in silico) the influence of geneknockouts and drug-induced enzyme inhibitions on whole body blood glucose levels. Simulations of diabetes associated gene knockouts and impaired cellular glucose metabolism, resulted in elevated whole body blood-glucose levels, but also in a metabolic shift within the cell's reaction network. Such multiscale models have the potential to be employed in the exploration of novel drug-targets or to be integrated into control algorithms for artificial pancreas systems.
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A Hybrid Multiscale Framework for Subsurface Flow and Transport Simulations
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
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Multiscale simulation of molecular processes in cellular environments.
Chiricotto, Mara; Sterpone, Fabio; Derreumaux, Philippe; Melchionna, Simone
2016-11-13
We describe the recent advances in studying biological systems via multiscale simulations. Our scheme is based on a coarse-grained representation of the macromolecules and a mesoscopic description of the solvent. The dual technique handles particles, the aqueous solvent and their mutual exchange of forces resulting in a stable and accurate methodology allowing biosystems of unprecedented size to be simulated.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2016 The Author(s).
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Multi-Scale Simulation of High Energy Density Ionic Liquids
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
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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.
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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.
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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.
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Multiscale Aspects of Modeling Gas-Phase Nanoparticle Synthesis
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
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Computational design and multiscale modeling of a nanoactuator using DNA actuation.
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.
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Evaluation of the Community Multiscale Air Quality model version 5.1
The Community Multiscale Air Quality model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Atmospheric Modeling and Analysis Division (AMAD) of the U.S. Environment...
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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.
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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.
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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.
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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.
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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.
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Multiscale measurement error models for aggregated small area health data.
Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin
2016-08-01
Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates. © The Author(s) 2016.
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Three-Dimensional Visualization of Ozone Process Data.
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
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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
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Computer Laboratory for Multi-scale Simulations of Novel Nanomaterials
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
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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
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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.;
2008-01-01
Numerical cloud resolving models (CRMs), which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that CRMs agree with observations in simulating various types of clouds and cloud systems from different geographic locations. 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 Numerical Weather Prediction (NWP) and regional scale model can be run in grid size similar to cloud resolving model through nesting technique. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a szrper-parameterization or multi-scale modeling -framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign can provide initial conditions as well as validation through utilizing the Earth Satellite simulators. At Goddard, we have developed a multi-scale modeling system with unified physics. The modeling system consists a coupled GCM-CRM (or MMF); a state-of-the-art weather research forecast model (WRF) and a cloud-resolving model (Goddard Cumulus Ensemble model). In these models, the same microphysical schemes (2ICE, several 3ICE), radiation (including explicitly calculated cloud optical properties), and surface models are applied. In addition, a comprehensive unified Earth Satellite simulator has been developed at GSFC, which is designed to fully utilize the multi-scale modeling system. A brief review of the multi-scale modeling system with unified physics/simulator and examples is presented in this article.
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Evaluation of the Community Multiscale Air Quality (CMAQ) Model Version 5.2
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...
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Evaluation of the Community Multi-scale Air Quality Model Version 5.2
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...
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Nonlocal and Mixed-Locality Multiscale Finite Element Methods
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
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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
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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.
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Design of a framework for modeling, integration and simulation of physiological models.
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.
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Evaluation of the Community Multi-scale Air Quality (CMAQ) Model Version 5.1
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...
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Overview and Evaluation of the Community Multiscale Air Quality Model Version 5.2
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...
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Evaluation of the Community Multi-scale Air Quality (CMAQ) Model Version 5.2
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...
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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...
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Trayanova, Natalia A; Tice, Brock M
2009-01-01
Simulation of cardiac electrical function, and specifically, simulation aimed at understanding the mechanisms of cardiac rhythm disorders, represents an example of a successful integrative multiscale modeling approach, uncovering emergent behavior at the successive scales in the hierarchy of structural complexity. The goal of this article is to present a review of the integrative multiscale models of realistic ventricular structure used in the quest to understand and treat ventricular arrhythmias. It concludes with the new advances in image-based modeling of the heart and the promise it holds for the development of individualized models of ventricular function in health and disease. PMID:20628585
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Multiscale modeling of mucosal immune responses
2015-01-01
Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM. Background Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Implementation Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. Conclusion We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut 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
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Multiscale modeling of mucosal immune responses.
Mei, Yongguo; Abedi, Vida; Carbo, Adria; Zhang, Xiaoying; Lu, Pinyi; Philipson, Casandra; Hontecillas, Raquel; Hoops, Stefan; Liles, Nathan; Bassaganya-Riera, Josep
2015-01-01
Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation.Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM.
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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.
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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.
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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
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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
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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.
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Efficient Integration of Coupled Electrical-Chemical Systems in Multiscale Neuronal Simulations
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
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Efficient Integration of Coupled Electrical-Chemical Systems in Multiscale Neuronal Simulations.
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.
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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.
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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.
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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.
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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
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Hybrid multiscale modeling and prediction of cancer cell behavior
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
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Hybrid multiscale modeling and prediction of cancer cell behavior.
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.
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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.
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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.
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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.
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A coupling method for a cardiovascular simulation model which includes the Kalman filter.
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.
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Multiscale modelling in immunology: a review.
Cappuccio, Antonio; Tieri, Paolo; Castiglione, Filippo
2016-05-01
One of the greatest challenges in biomedicine is to get a unified view of observations made from the molecular up to the organism scale. Towards this goal, multiscale models have been highly instrumental in contexts such as the cardiovascular field, angiogenesis, neurosciences and tumour biology. More recently, such models are becoming an increasingly important resource to address immunological questions as well. Systematic mining of the literature in multiscale modelling led us to identify three main fields of immunological applications: host-virus interactions, inflammatory diseases and their treatment and development of multiscale simulation platforms for immunological research and for educational purposes. Here, we review the current developments in these directions, which illustrate that multiscale models can consistently integrate immunological data generated at several scales, and can be used to describe and optimize therapeutic treatments of complex immune diseases. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
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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.
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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
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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.
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A multiscale quantum mechanics/electromagnetics method for device simulations.
Yam, ChiYung; Meng, Lingyi; Zhang, Yu; Chen, GuanHua
2015-04-07
Multiscale modeling has become a popular tool for research applying to different areas including materials science, microelectronics, biology, chemistry, etc. In this tutorial review, we describe a newly developed multiscale computational method, incorporating quantum mechanics into electronic device modeling with the electromagnetic environment included through classical electrodynamics. In the quantum mechanics/electromagnetics (QM/EM) method, the regions of the system where active electron scattering processes take place are treated quantum mechanically, while the surroundings are described by Maxwell's equations and a semiclassical drift-diffusion model. The QM model and the EM model are solved, respectively, in different regions of the system in a self-consistent manner. Potential distributions and current densities at the interface between QM and EM regions are employed as the boundary conditions for the quantum mechanical and electromagnetic simulations, respectively. The method is illustrated in the simulation of several realistic systems. In the case of junctionless field-effect transistors, transfer characteristics are obtained and a good agreement between experiments and simulations is achieved. Optical properties of a tandem photovoltaic cell are studied and the simulations demonstrate that multiple QM regions are coupled through the classical EM model. Finally, the study of a carbon nanotube-based molecular device shows the accuracy and efficiency of the QM/EM method.
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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 (...
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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.
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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.
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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.
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Multiscale modelling and nonlinear simulation of vascular tumour growth
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
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Gyrokinetic predictions of multiscale transport in a DIII-D ITER baseline discharge
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
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Integrating Multiscale Modeling with Drug Effects for Cancer Treatment.
Li, Xiangfang L; Oduola, Wasiu O; Qian, Lijun; Dougherty, Edward R
2015-01-01
In this paper, we review multiscale modeling for cancer treatment with the incorporation of drug effects from an applied system's pharmacology perspective. Both the classical pharmacology and systems biology are inherently quantitative; however, systems biology focuses more on networks and multi factorial controls over biological processes rather than on drugs and targets in isolation, whereas systems pharmacology has a strong focus on studying drugs with regard to the pharmacokinetic (PK) and pharmacodynamic (PD) relations accompanying drug interactions with multiscale physiology as well as the prediction of dosage-exposure responses and economic potentials of drugs. Thus, it requires multiscale methods to address the need for integrating models from the molecular levels to the cellular, tissue, and organism levels. It is a common belief that tumorigenesis and tumor growth can be best understood and tackled by employing and integrating a multifaceted approach that includes in vivo and in vitro experiments, in silico models, multiscale tumor modeling, continuous/discrete modeling, agent-based modeling, and multiscale modeling with PK/PD drug effect inputs. We provide an example application of multiscale modeling employing stochastic hybrid system for a colon cancer cell line HCT-116 with the application of Lapatinib drug. It is observed that the simulation results are similar to those observed from the setup of the wet-lab experiments at the Translational Genomics Research Institute.
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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.
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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.
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Integrated multiscale biomaterials experiment and modelling: a perspective
Buehler, Markus J.; Genin, Guy M.
2016-01-01
Advances in multiscale models and computational power have enabled a broad toolset to predict how molecules, cells, tissues and organs behave and develop. A key theme in biological systems is the emergence of macroscale behaviour from collective behaviours across a range of length and timescales, and a key element of these models is therefore hierarchical simulation. However, this predictive capacity has far outstripped our ability to validate predictions experimentally, particularly when multiple hierarchical levels are involved. The state of the art represents careful integration of multiscale experiment and modelling, and yields not only validation, but also insights into deformation and relaxation mechanisms across scales. We present here a sampling of key results that highlight both challenges and opportunities for integrated multiscale experiment and modelling in biological systems. PMID:28981126
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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<...
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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
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Multiscale Modeling of Multiphase Fluid Flow
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
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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
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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.
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Simulation of atmospheric oxidation capacity in Houston, Texas
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 ...
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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
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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).
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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
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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.
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The Effect of Lateral Boundary Values on Atmospheric Mercury Simulations with the CMAQ Model
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. ...
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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
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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
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Validation of nonlinear gyrokinetic simulations of L- and I-mode plasmas on Alcator C-Mod
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
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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.
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NASA Astrophysics Data System (ADS)
Frantziskonis, George N.; Gur, Sourav
2017-06-01
Thermally induced phase transformation in NiTi shape memory alloys (SMAs) shows strong size and shape, collectively termed length scale effects, at the nano to micrometer scales, and that has important implications for the design and use of devices and structures at such scales. This paper, based on a recently developed multiscale model that utilizes molecular dynamics (MDs) simulations at small scales and MD-verified phase field (PhF) simulations at larger scales, reports results on specific length scale effects, i.e. length scale effects in martensite phase fraction (MPF) evolution, transformation temperatures (martensite and austenite start and finish) and in the thermally cyclic transformation between austenitic and martensitic phase. The multiscale study identifies saturation points for length scale effects and studies, for the first time, the length scale effect on the kinetics (i.e. developed internal strains) in the B19‧ phase during phase transformation. The major part of the work addresses small scale single crystals in specific orientations. However, the multiscale method is used in a unique and novel way to indirectly study length scale and grain size effects on evolution kinetics in polycrystalline NiTi, and to compare the simulation results to experiments. The interplay of the grain size and the length scale effect on the thermally induced MPF evolution is also shown in this present study. Finally, the multiscale coupling results are employed to improve phenomenological material models for NiTi SMA.
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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.
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Computational Chemistry Toolkit for Energetic Materials Design
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
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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
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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.
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Bridging scales through multiscale modeling: a case study on protein kinase A.
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.
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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.
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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...
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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.
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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.
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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.
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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.
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On a sparse pressure-flow rate condensation of rigid circulation models
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
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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.
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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
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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.
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Combining Coarse-Grained Protein Models with Replica-Exchange All-Atom Molecular Dynamics
Wabik, Jacek; Kmiecik, Sebastian; Gront, Dominik; Kouza, Maksim; Koliński, Andrzej
2013-01-01
We describe a combination of all-atom simulations with CABS, a well-established coarse-grained protein modeling tool, into a single multiscale protocol. The simulation method has been tested on the C-terminal beta hairpin of protein G, a model system of protein folding. After reconstructing atomistic details, conformations derived from the CABS simulation were subjected to replica-exchange molecular dynamics simulations with OPLS-AA and AMBER99sb force fields in explicit solvent. Such a combination accelerates system convergence several times in comparison with all-atom simulations starting from the extended chain conformation, demonstrated by the analysis of melting curves, the number of native-like conformations as a function of time and secondary structure propagation. The results strongly suggest that the proposed multiscale method could be an efficient and accurate tool for high-resolution studies of protein folding dynamics in larger systems. PMID:23665897
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Components for Atomistic-to-Continuum Multiscale Modeling of Flow in Micro- and Nanofluidic Systems
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
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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.
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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.
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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
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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Introduction and application of the multiscale coefficient of variation analysis.
Abney, Drew H; Kello, Christopher T; Balasubramaniam, Ramesh
2017-10-01
Quantifying how patterns of behavior relate across multiple levels of measurement typically requires long time series for reliable parameter estimation. We describe a novel analysis that estimates patterns of variability across multiple scales of analysis suitable for time series of short duration. The multiscale coefficient of variation (MSCV) measures the distance between local coefficient of variation estimates within particular time windows and the overall coefficient of variation across all time samples. We first describe the MSCV analysis and provide an example analytical protocol with corresponding MATLAB implementation and code. Next, we present a simulation study testing the new analysis using time series generated by ARFIMA models that span white noise, short-term and long-term correlations. The MSCV analysis was observed to be sensitive to specific parameters of ARFIMA models varying in the type of temporal structure and time series length. We then apply the MSCV analysis to short time series of speech phrases and musical themes to show commonalities in multiscale structure. The simulation and application studies provide evidence that the MSCV analysis can discriminate between time series varying in multiscale structure and length.
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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.
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Diagnostic Analysis of Ozone Concentrations Simulated by Two Regional-Scale Air Quality Models
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...
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Evaluation of the Community Multiscale Air Quality (CMAQ) ...
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
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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.
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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
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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.
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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.
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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.
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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.
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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.
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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
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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
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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
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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
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The role of zonal flows in the saturation of multi-scale gyrokinetic turbulence
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
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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
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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.
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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.
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Interdisciplinary Modeling and Dynamics of Archipelago Straits
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
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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...
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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.
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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...
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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
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Evaluation of the Community Multiscale Air Quality (CMAQ) Model Version 5.1
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...
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Preliminary Evaluation of the Community Multiscale Air Quality (CMAQ) Model Version 5.1
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...
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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.
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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).
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Using CellML with OpenCMISS to Simulate Multi-Scale Physiology
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
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Simulation of Left Atrial Function Using a Multi-Scale Model of the Cardiovascular System
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
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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.
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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
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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.
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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
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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.
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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.
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The Virtual Liver Project: Modeling Tissue Response To Chemicals Through Multiscale Simulation
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...
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SENSITIVITY OF THE CMAQ MERCURY MODEL TO GAS-PHASE OXIDATION CHEMISTRY
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...
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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...
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PROTO-PLASM: parallel language for adaptive and scalable modelling of biosystems.
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.
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Proto-Plasm: parallel language for adaptive and scalable modelling of biosystems
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
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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.
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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.
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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
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Scalability Test of Multiscale Fluid-Platelet Model for Three Top Supercomputers
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
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Stochastic and deterministic multiscale models for systems biology: an auxin-transport case study.
Twycross, Jamie; Band, Leah R; Bennett, Malcolm J; King, John R; Krasnogor, Natalio
2010-03-26
Stochastic and asymptotic methods are powerful tools in developing multiscale systems biology models; however, little has been done in this context to compare the efficacy of these methods. The majority of current systems biology modelling research, including that of auxin transport, uses numerical simulations to study the behaviour of large systems of deterministic ordinary differential equations, with little consideration of alternative modelling frameworks. In this case study, we solve an auxin-transport model using analytical methods, deterministic numerical simulations and stochastic numerical simulations. Although the three approaches in general predict the same behaviour, the approaches provide different information that we use to gain distinct insights into the modelled biological system. We show in particular that the analytical approach readily provides straightforward mathematical expressions for the concentrations and transport speeds, while the stochastic simulations naturally provide information on the variability of the system. Our study provides a constructive comparison which highlights the advantages and disadvantages of each of the considered modelling approaches. This will prove helpful to researchers when weighing up which modelling approach to select. In addition, the paper goes some way to bridging the gap between these approaches, which in the future we hope will lead to integrative hybrid models.
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Hybrid stochastic simplifications for multiscale gene networks.
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.
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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.
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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.
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Sensitivity of air quality simulation to smoke plume rise
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...
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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.
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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
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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.
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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
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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.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Du, Qiang
The rational design of materials, the development of accurate and efficient material simulation algorithms, and the determination of the response of materials to environments and loads occurring in practice all require an understanding of mechanics at disparate spatial and temporal scales. The project addresses mathematical and numerical analyses for material problems for which relevant scales range from those usually treated by molecular dynamics all the way up to those most often treated by classical elasticity. The prevalent approach towards developing a multiscale material model couples two or more well known models, e.g., molecular dynamics and classical elasticity, each of whichmore » is useful at a different scale, creating a multiscale multi-model. However, the challenges behind such a coupling are formidable and largely arise because the atomistic and continuum models employ nonlocal and local models of force, respectively. The project focuses on a multiscale analysis of the peridynamics materials model. Peridynamics can be used as a transition between molecular dynamics and classical elasticity so that the difficulties encountered when directly coupling those two models are mitigated. In addition, in some situations, peridynamics can be used all by itself as a material model that accurately and efficiently captures the behavior of materials over a wide range of spatial and temporal scales. Peridynamics is well suited to these purposes because it employs a nonlocal model of force, analogous to that of molecular dynamics; furthermore, at sufficiently large length scales and assuming smooth deformation, peridynamics can be approximated by classical elasticity. The project will extend the emerging mathematical and numerical analysis of peridynamics. One goal is to develop a peridynamics-enabled multiscale multi-model that potentially provides a new and more extensive mathematical basis for coupling classical elasticity and molecular dynamics, thus enabling next generation atomistic-to-continuum multiscale simulations. In addition, a rigorous studyof nite element discretizations of peridynamics will be considered. Using the fact that peridynamics is spatially derivative free, we will also characterize the space of admissible peridynamic solutions and carry out systematic analyses of the models, in particular rigorously showing how peridynamics encompasses fracture and other failure phenomena. Additional aspects of the project include the mathematical and numerical analysis of peridynamics applied to stochastic peridynamics models. In summary, the project will make feasible mathematically consistent multiscale models for the analysis and design of advanced materials.« less
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Prediction of water loss and viscoelastic deformation of apple tissue using a multiscale model.
Aregawi, Wondwosen A; Abera, Metadel K; Fanta, Solomon W; Verboven, Pieter; Nicolai, Bart
2014-11-19
A two-dimensional multiscale water transport and mechanical model was developed to predict the water loss and deformation of apple tissue (Malus × domestica Borkh. cv. 'Jonagold') during dehydration. At the macroscopic level, a continuum approach was used to construct a coupled water transport and mechanical model. Water transport in the tissue was simulated using a phenomenological approach using Fick's second law of diffusion. Mechanical deformation due to shrinkage was based on a structural mechanics model consisting of two parts: Yeoh strain energy functions to account for non-linearity and Maxwell's rheological model of visco-elasticity. Apparent parameters of the macroscale model were computed from a microscale model. The latter accounted for water exchange between different microscopic structures of the tissue (intercellular space, the cell wall network and cytoplasm) using transport laws with the water potential as the driving force for water exchange between different compartments of tissue. The microscale deformation mechanics were computed using a model where the cells were represented as a closed thin walled structure. The predicted apparent water transport properties of apple cortex tissue from the microscale model showed good agreement with the experimentally measured values. Deviations between calculated and measured mechanical properties of apple tissue were observed at strains larger than 3%, and were attributed to differences in water transport behavior between the experimental compression tests and the simulated dehydration-deformation behavior. Tissue dehydration and deformation in the high relative humidity range ( > 97% RH) could, however, be accurately predicted by the multiscale model. The multiscale model helped to understand the dynamics of the dehydration process and the importance of the different microstructural compartments (intercellular space, cell wall, membrane and cytoplasm) for water transport and mechanical deformation.
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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.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Horstemeyer, Mark R.; Chaudhuri, Santanu
2015-09-30
A multiscale modeling Internal State Variable (ISV) constitutive model was developed that captures the fundamental structure-property relationships. The macroscale ISV model used lower length scale simulations (Butler-Volmer and Electronics Structures results) in order to inform the ISVs at the macroscale. The chemomechanical ISV model was calibrated and validated from experiments with magnesium (Mg) alloys that were investigated under corrosive environments coupled with experimental electrochemical studies. Because the ISV chemomechanical model is physically based, it can be used for other material systems to predict corrosion behavior. As such, others can use the chemomechanical model for analyzing corrosion effects on their designs.
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EMISSION AND SURFACE EXCHANGE PROCESS
This task supports the development, evaluation, and application of emission and dry deposition algorithms in air quality simulation models, such as the Models-3/Community Multiscale Air Quality (CMAQ) modeling system. Emission estimates influence greatly the accuracy of air qual...
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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).
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PAM: Particle automata model in simulation of Fusarium graminearum pathogen expansion.
Wcisło, Rafał; Miller, S Shea; Dzwinel, Witold
2016-01-21
The multi-scale nature and inherent complexity of biological systems are a great challenge for computer modeling and classical modeling paradigms. We present a novel particle automata modeling metaphor in the context of developing a 3D model of Fusarium graminearum infection in wheat. The system consisting of the host plant and Fusarium pathogen cells can be represented by an ensemble of discrete particles defined by a set of attributes. The cells-particles can interact with each other mimicking mechanical resistance of the cell walls and cell coalescence. The particles can move, while some of their attributes can be changed according to prescribed rules. The rules can represent cellular scales of a complex system, while the integrated particle automata model (PAM) simulates its overall multi-scale behavior. We show that due to the ability of mimicking mechanical interactions of Fusarium tip cells with the host tissue, the model is able to simulate realistic penetration properties of the colonization process reproducing both vertical and lateral Fusarium invasion scenarios. The comparison of simulation results with micrographs from laboratory experiments shows encouraging qualitative agreement between the two. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Dynamic evaluation of two decades of WRF-CMAQ ozone simulations over the contiguous United States
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 ...
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Dynamic evaluation of two decades of WRF-CMAQ ozone simulations over the contiguous United States
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...
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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.
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Investigation of Effects of Varying Model Inputs on Mercury Deposition Estimates in the Southwest US
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...
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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...
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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...
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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, ...
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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.
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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.
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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
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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.
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A Hybrid Model for Multiscale Laser Plasma Simulations with Detailed Collisional Physics
2017-06-23
the effects of inelastic collisions on the Multi-Fluid description of plasmas. 15. SUBJECT TERMS Electric propulsion; plasma; collisional...modeling as well as the effects of inelastic collisions on the Multi-Fluid description of plasmas. This work has been recognized in two workshop...encountered during simulation was to define when breakdown occurred during the simulation and correlating the results to the experimentally determined
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Dimethylsulfide Chemistry: Annual, Seasonal, and Spatial Impacts on Sulfate
We incorporated oceanic emissions and atmospheric chemistry of dimethylsulfide (DMS) into the hemispheric Community Multiscale Air Quality model and performed annual model simulations without and with DMS chemistry. The model without DMS chemistry predicts higher concentrations o...
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Advances in multi-scale modeling of solidification and casting processes
NASA Astrophysics Data System (ADS)
Liu, Baicheng; Xu, Qingyan; Jing, Tao; Shen, Houfa; Han, Zhiqiang
2011-04-01
The development of the aviation, energy and automobile industries requires an advanced integrated product/process R&D systems which could optimize the product and the process design as well. Integrated computational materials engineering (ICME) is a promising approach to fulfill this requirement and make the product and process development efficient, economic, and environmentally friendly. Advances in multi-scale modeling of solidification and casting processes, including mathematical models as well as engineering applications are presented in the paper. Dendrite morphology of magnesium and aluminum alloy of solidification process by using phase field and cellular automaton methods, mathematical models of segregation of large steel ingot, and microstructure models of unidirectionally solidified turbine blade casting are studied and discussed. In addition, some engineering case studies, including microstructure simulation of aluminum casting for automobile industry, segregation of large steel ingot for energy industry, and microstructure simulation of unidirectionally solidified turbine blade castings for aviation industry are discussed.
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The CMAQ modeling system has been used to simulate the CONUS using 12-km by 12-km horizontal grid spacing for the entire year of 2006 as part of the Air Quality Model Evaluation International initiative (AQMEII). The operational model performance for O3 and PM2.5<...
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Wen J. Wang; Hong S. He; Martin A. Spetich; Stephen R. Shifley; Frank R. Thompson III; David R. Larsen; Jacob S. Fraser; Jian Yang
2013-01-01
Two challenges confronting forest landscape models (FLMs) are how to simulate fine, standscale processes while making large-scale (i.e., .107 ha) simulation possible, and how to take advantage of extensive forest inventory data such as U.S. Forest Inventory and Analysis (FIA) data to initialize and constrain model parameters. We present the LANDIS PRO model that...
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Special Issue on Uncertainty Quantification in Multiscale System Design and Simulation
Wang, Yan; Swiler, Laura
2017-09-07
The importance of uncertainty has been recognized in various modeling, simulation, and analysis applications, where inherent assumptions and simplifications affect the accuracy of model predictions for physical phenomena. As model predictions are now heavily relied upon for simulation-based system design, which includes new materials, vehicles, mechanical and civil structures, and even new drugs, wrong model predictions could potentially cause catastrophic consequences. Therefore, uncertainty and associated risks due to model errors should be quantified to support robust systems engineering.
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Special Issue on Uncertainty Quantification in Multiscale System Design and Simulation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Yan; Swiler, Laura
The importance of uncertainty has been recognized in various modeling, simulation, and analysis applications, where inherent assumptions and simplifications affect the accuracy of model predictions for physical phenomena. As model predictions are now heavily relied upon for simulation-based system design, which includes new materials, vehicles, mechanical and civil structures, and even new drugs, wrong model predictions could potentially cause catastrophic consequences. Therefore, uncertainty and associated risks due to model errors should be quantified to support robust systems engineering.
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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.
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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.
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NASA Astrophysics Data System (ADS)
Sondak, David; Oberai, Assad
2012-10-01
Novel large eddy simulation (LES) models are developed for incompressible magnetohydrodynamics (MHD). These models include the application of the variational multiscale formulation (VMS) of LES to the equations of incompressible MHD, a new residual-based eddy viscosity model (RBEVM,) and a mixed LES model that combines the strengths of both of these models. The new models result in a consistent numerical method that is relatively simple to implement. A dynamic procedure for determining model coefficients is no longer required. The new LES models are tested on a decaying Taylor-Green vortex generalized to MHD and benchmarked against classical and state-of-the art LES turbulence models as well as direct numerical simulations (DNS). These new models are able to account for the essential MHD physics which is demonstrated via comparisons of energy spectra. We also compare the performance of our models to a DNS simulation by A. Pouquet et al., for which the ratio of DNS modes to LES modes is 262,144. Additionally, we extend these models to a finite element setting in which boundary conditions play a role. A classic problem on which we test these models is turbulent channel flow, which in the case of MHD, is called Hartmann flow.
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Blast and the Consequences on Traumatic Brain Injury-Multiscale Mechanical Modeling of Brain
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
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Lefkimmiatis, Stamatios; Maragos, Petros; Papandreou, George
2009-08-01
We present an improved statistical model for analyzing Poisson processes, with applications to photon-limited imaging. We build on previous work, adopting a multiscale representation of the Poisson process in which the ratios of the underlying Poisson intensities (rates) in adjacent scales are modeled as mixtures of conjugate parametric distributions. Our main contributions include: 1) a rigorous and robust regularized expectation-maximization (EM) algorithm for maximum-likelihood estimation of the rate-ratio density parameters directly from the noisy observed Poisson data (counts); 2) extension of the method to work under a multiscale hidden Markov tree model (HMT) which couples the mixture label assignments in consecutive scales, thus modeling interscale coefficient dependencies in the vicinity of image edges; 3) exploration of a 2-D recursive quad-tree image representation, involving Dirichlet-mixture rate-ratio densities, instead of the conventional separable binary-tree image representation involving beta-mixture rate-ratio densities; and 4) a novel multiscale image representation, which we term Poisson-Haar decomposition, that better models the image edge structure, thus yielding improved performance. Experimental results on standard images with artificially simulated Poisson noise and on real photon-limited images demonstrate the effectiveness of the proposed techniques.
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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.
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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.
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A physics based multiscale modeling of cavitating flows.
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.
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A physics based multiscale modeling of cavitating flows
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
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Goal-oriented robot navigation learning using a multi-scale space representation.
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.
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Hybrid stochastic simplifications for multiscale gene networks
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
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Persistence of initial conditions in continental scale air quality simulations
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...
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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
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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.
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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.
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Dimethylsulfide chemistry: annual, seasonal, and spatial impacts on SO_4^(2-)
We incorporated oceanic emissions and atmospheric chemistry of dimethylsulfide (DMS) into the hemispheric Community Multiscale Air Quality model and performed annual model simulations without and with DMS chemistry. The model without DMS chemistry predicts higher concentrations o...
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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.
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Simulating Cancer Growth with Multiscale Agent-Based Modeling
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
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Beddows, Andrew V; Kitwiroon, Nutthida; Williams, Martin L; Beevers, Sean D
2017-06-06
Gaussian process emulation techniques have been used with the Community Multiscale Air Quality model, simulating the effects of input uncertainties on ozone and NO 2 output, to allow robust global sensitivity analysis (SA). A screening process ranked the effect of perturbations in 223 inputs, isolating the 30 most influential from emissions, boundary conditions (BCs), and reaction rates. Community Multiscale Air Quality (CMAQ) simulations of a July 2006 ozone pollution episode in the UK were made with input values for these variables plus ozone dry deposition velocity chosen according to a 576 point Latin hypercube design. Emulators trained on the output of these runs were used in variance-based SA of the model output to input uncertainties. Performing these analyses for every hour of a 21 day period spanning the episode and several days on either side allowed the results to be presented as a time series of sensitivity coefficients, showing how the influence of different input uncertainties changed during the episode. This is one of the most complex models to which these methods have been applied, and here, they reveal detailed spatiotemporal patterns of model sensitivities, with NO and isoprene emissions, NO 2 photolysis, ozone BCs, and deposition velocity being among the most influential input uncertainties.
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NASA Astrophysics Data System (ADS)
Lyu, Dandan; Li, Shaofan
2017-10-01
Crystal defects have microstructure, and this microstructure should be related to the microstructure of the original crystal. Hence each type of crystals may have similar defects due to the same failure mechanism originated from the same microstructure, if they are under the same loading conditions. In this work, we propose a multiscale crystal defect dynamics (MCDD) model that models defects by considering its intrinsic microstructure derived from the microstructure or material genome of the original perfect crystal. The main novelties of present work are: (1) the discrete exterior calculus and algebraic topology theory are used to construct a scale-up (coarse-grained) dual lattice model for crystal defects, which may represent all possible defect modes inside a crystal; (2) a higher order Cauchy-Born rule (up to the fourth order) is adopted to construct atomistic-informed constitutive relations for various defect process zones, and (3) an hierarchical strain gradient theory based finite element formulation is developed to support an hierarchical multiscale cohesive (process) zone model for various defects in a unified formulation. The efficiency of MCDD computational algorithm allows us to simulate dynamic defect evolution at large scale while taking into account atomistic interaction. The MCDD model has been validated by comparing of the results of MCDD simulations with that of molecular dynamics (MD) in the cases of nanoindentation and uniaxial tension. Numerical simulations have shown that MCDD model can predict dislocation nucleation induced instability and inelastic deformation, and thus it may provide an alternative solution to study crystal plasticity.
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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
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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.
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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.
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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
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MODEL DEVELOPMENT AND TESTING FOR SEMI-VOLATILES (ATRAZINE)
The Community Multi-Scale Air Quality (CMAQ) model, air quality model within EPA's Models-3 system, can be adapted to simulate the fate of semi-volatile compounds that are emitted into the atmosphere. "Semi-volatile" refers to compounds that partition their mass between two ph...
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U.S. EPA MODELS-3/CMAQ - STATUS AND APPLICATIONS
An advanced third-generation air quality modeling system has been developed by the Atmospheric Modeling Division of the U.S. EPA. The air quality simulation model at the heart of the system is known as the Community Multiscale Air Quality (CMAQ) Model. It is comprehensive in ...
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Efficient and Extensible Quasi-Explicit Modular Nonlinear Multiscale Battery Model: GH-MSMD
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kim, Gi-Heon; Smith, Kandler; Lawrence-Simon, Jake
Complex physics and long computation time hinder the adoption of computer aided engineering models in the design of large-format battery cells and systems. A modular, efficient battery simulation model -- the multiscale multidomain (MSMD) model -- was previously introduced to aid the scale-up of Li-ion material and electrode designs to complete cell and pack designs, capturing electrochemical interplay with 3-D electronic current pathways and thermal response. Here, this paper enhances the computational efficiency of the MSMD model using a separation of time-scales principle to decompose model field variables. The decomposition provides a quasi-explicit linkage between the multiple length-scale domains andmore » thus reduces time-consuming nested iteration when solving model equations across multiple domains. In addition to particle-, electrode- and cell-length scales treated in the previous work, the present formulation extends to bus bar- and multi-cell module-length scales. We provide example simulations for several variants of GH electrode-domain models.« less
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Efficient and Extensible Quasi-Explicit Modular Nonlinear Multiscale Battery Model: GH-MSMD
Kim, Gi-Heon; Smith, Kandler; Lawrence-Simon, Jake; ...
2017-03-24
Complex physics and long computation time hinder the adoption of computer aided engineering models in the design of large-format battery cells and systems. A modular, efficient battery simulation model -- the multiscale multidomain (MSMD) model -- was previously introduced to aid the scale-up of Li-ion material and electrode designs to complete cell and pack designs, capturing electrochemical interplay with 3-D electronic current pathways and thermal response. Here, this paper enhances the computational efficiency of the MSMD model using a separation of time-scales principle to decompose model field variables. The decomposition provides a quasi-explicit linkage between the multiple length-scale domains andmore » thus reduces time-consuming nested iteration when solving model equations across multiple domains. In addition to particle-, electrode- and cell-length scales treated in the previous work, the present formulation extends to bus bar- and multi-cell module-length scales. We provide example simulations for several variants of GH electrode-domain models.« less
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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
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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.
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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
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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
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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.
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A framework for WRF to WRF-IBM grid nesting to enable multiscale simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wiersema, David John; Lundquist, Katherine A.; Chow, Fotini Katapodes
With advances in computational power, mesoscale models, such as the Weather Research and Forecasting (WRF) model, are often pushed to higher resolutions. As the model’s horizontal resolution is refined, the maximum resolved terrain slope will increase. Because WRF uses a terrain-following coordinate, this increase in resolved terrain slopes introduces additional grid skewness. At high resolutions and over complex terrain, this grid skewness can introduce large numerical errors that require methods, such as the immersed boundary method, to keep the model accurate and stable. Our implementation of the immersed boundary method in the WRF model, WRF-IBM, has proven effective at microscalemore » simulations over complex terrain. WRF-IBM uses a non-conforming grid that extends beneath the model’s terrain. Boundary conditions at the immersed boundary, the terrain, are enforced by introducing a body force term to the governing equations at points directly beneath the immersed boundary. Nesting between a WRF parent grid and a WRF-IBM child grid requires a new framework for initialization and forcing of the child WRF-IBM grid. This framework will enable concurrent multi-scale simulations within the WRF model, improving the accuracy of high-resolution simulations and enabling simulations across a wide range of scales.« less
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Improved meteorology from an updated WRF/CMAQ modeling system with MODIS vegetation and albedo
Realistic vegetation characteristics and phenology from the Moderate Resolution Imaging Spectroradiometer (MODIS) products improve the simulation for the meteorology and air quality modeling system WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Qual...
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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.
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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.
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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.
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NASA Technical Reports Server (NTRS)
Yamakov, V.; Saether, E.; Phillips, D.; Glaessgen, E. H.
2004-01-01
In this paper, a multiscale modelling strategy is used to study the effect of grain-boundary sliding on stress localization in a polycrystalline microstructure with an uneven distribution of grain size. The development of the molecular dynamics (MD) analysis used to interrogate idealized grain microstructures with various types of grain boundaries and the multiscale modelling strategies for modelling large systems of grains is discussed. Both molecular-dynamics and finite-element (FE) simulations for idealized polycrystalline models of identical geometry are presented with the purpose of demonstrating the effectiveness of the adapted finite-element method using cohesive zone models to reproduce grain-boundary sliding and its effect on the stress distribution in a polycrystalline metal. The yield properties of the grain-boundary interface, used in the FE simulations, are extracted from a MD simulation on a bicrystal. The models allow for the study of the load transfer between adjacent grains of very different size through grain-boundary sliding during deformation. A large-scale FE simulation of 100 grains of a typical microstructure is then presented to reveal that the stress distribution due to grain-boundary sliding during uniform tensile strain can lead to stress localization of two to three times the background stress, thus suggesting a significant effect on the failure properties of the metal.
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A FAST BAYESIAN METHOD FOR UPDATING AND FORECASTING HOURLY OZONE LEVELS
A Bayesian hierarchical space-time model is proposed by combining information from real-time ambient AIRNow air monitoring data, and output from a computer simulation model known as the Community Multi-scale Air Quality (Eta-CMAQ) forecast model. A model validation analysis shows...
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EPA RESEARCH HIGHLIGHTS -- MODELS-3/CMAQ OFFERS COMPREHENSIVE APPROACH TO AIR QUALITY MODELING
Regional and global coordinated efforts are needed to address air quality problems that are growing in complexity and scope. Models-3 CMAQ contains a community multi-scale air quality modeling system for simulating urban to regional scale pollution problems relating to troposphe...
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An Overview of Mesoscale Modeling Software for Energetic Materials Research
2010-03-01
12 2.9 Large-scale Atomic/Molecular Massively Parallel Simulator ( LAMMPS ...13 Table 10. LAMMPS summary...extensive reviews, lectures and workshops are available on multiscale modeling of materials applications (76-78). • Multi-phase mixtures of
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Computational aspects in mechanical modeling of the articular cartilage tissue.
Mohammadi, Hadi; Mequanint, Kibret; Herzog, Walter
2013-04-01
This review focuses on the modeling of articular cartilage (at the tissue level), chondrocyte mechanobiology (at the cell level) and a combination of both in a multiscale computation scheme. The primary objective is to evaluate the advantages and disadvantages of conventional models implemented to study the mechanics of the articular cartilage tissue and chondrocytes. From monophasic material models as the simplest form to more complicated multiscale theories, these approaches have been frequently used to model articular cartilage and have contributed significantly to modeling joint mechanics, addressing and resolving numerous issues regarding cartilage mechanics and function. It should be noted that attentiveness is important when using different modeling approaches, as the choice of the model limits the applications available. In this review, we discuss the conventional models applicable to some of the mechanical aspects of articular cartilage such as lubrication, swelling pressure and chondrocyte mechanics and address some of the issues associated with the current modeling approaches. We then suggest future pathways for a more realistic modeling strategy as applied for the simulation of the mechanics of the cartilage tissue using multiscale and parallelized finite element method.
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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
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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.
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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.
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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.
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In this paper, impact of meteorology derived from the Weather, Research and Forecasting (WRF)– Non–hydrostatic Mesoscale Model (NMM) and WRF–Advanced Research WRF (ARW) meteorological models on the Community Multiscale Air Quality (CMAQ) simulations for ozone and its related prec...
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A framework for multi-scale simulation of crystal growth in the presence of polymers.
Mandal, Taraknath; Huang, Wenjun; Mecca, Jodi M; Getchell, Ashley; Porter, William W; Larson, Ronald G
2017-03-01
We present a multi-scale simulation method for modeling crystal growth in the presence of polymer excipients. The method includes a coarse-grained (CG) model for small molecules of known crystal structure whose force field is obtained using structural properties from atomistic simulations. This CG model is capable of stabilizing the molecular crystal structure and capturing the crystal growth from the melt for a wide range of small organic molecules, as demonstrated by application of our method to the molecules isoniazid, urea, sulfamethoxazole, prilocaine, oxcarbazepine, and phenytoin. This CG model can also be used to study the effect of additives, such as polymers, on the inhibition of crystal growth by polymers, as exemplified by our simulation of suppression of the rate of crystal growth of phenytoin, an active pharmaceutical ingredient (API), by a cellulose excipient, functionalized with acetate (Ac), hydroxy-propyl (Hp) and succinate (Su) groups. We show that the efficacy of the cellulosic polymers in slowing crystal growth of small molecules strongly depends on the functional group substitution on the cellulose backbone, with the acetate substituent group slowing crystal growth more than does the deprotonated succinate group, which we confirm by experimental drug supersaturation studies.
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Adaptive resolution simulation of an atomistic protein in MARTINI water
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zavadlav, Julija; Melo, Manuel Nuno; Marrink, Siewert J., E-mail: s.j.marrink@rug.nl
2014-02-07
We present an adaptive resolution simulation of protein G in multiscale water. We couple atomistic water around the protein with mesoscopic water, where four water molecules are represented with one coarse-grained bead, farther away. We circumvent the difficulties that arise from coupling to the coarse-grained model via a 4-to-1 molecule coarse-grain mapping by using bundled water models, i.e., we restrict the relative movement of water molecules that are mapped to the same coarse-grained bead employing harmonic springs. The water molecules change their resolution from four molecules to one coarse-grained particle and vice versa adaptively on-the-fly. Having performed 15 ns long molecularmore » dynamics simulations, we observe within our error bars no differences between structural (e.g., root-mean-squared deviation and fluctuations of backbone atoms, radius of gyration, the stability of native contacts and secondary structure, and the solvent accessible surface area) and dynamical properties of the protein in the adaptive resolution approach compared to the fully atomistically solvated model. Our multiscale model is compatible with the widely used MARTINI force field and will therefore significantly enhance the scope of biomolecular simulations.« less
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Adaptive resolution simulation of an atomistic protein in MARTINI water.
Zavadlav, Julija; Melo, Manuel Nuno; Marrink, Siewert J; Praprotnik, Matej
2014-02-07
We present an adaptive resolution simulation of protein G in multiscale water. We couple atomistic water around the protein with mesoscopic water, where four water molecules are represented with one coarse-grained bead, farther away. We circumvent the difficulties that arise from coupling to the coarse-grained model via a 4-to-1 molecule coarse-grain mapping by using bundled water models, i.e., we restrict the relative movement of water molecules that are mapped to the same coarse-grained bead employing harmonic springs. The water molecules change their resolution from four molecules to one coarse-grained particle and vice versa adaptively on-the-fly. Having performed 15 ns long molecular dynamics simulations, we observe within our error bars no differences between structural (e.g., root-mean-squared deviation and fluctuations of backbone atoms, radius of gyration, the stability of native contacts and secondary structure, and the solvent accessible surface area) and dynamical properties of the protein in the adaptive resolution approach compared to the fully atomistically solvated model. Our multiscale model is compatible with the widely used MARTINI force field and will therefore significantly enhance the scope of biomolecular simulations.
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Multi-fluid Dynamics for Supersonic Jet-and-Crossflows and Liquid Plug Rupture
NASA Astrophysics Data System (ADS)
Hassan, Ezeldin A.
Multi-fluid dynamics simulations require appropriate numerical treatments based on the main flow characteristics, such as flow speed, turbulence, thermodynamic state, and time and length scales. In this thesis, two distinct problems are investigated: supersonic jet and crossflow interactions; and liquid plug propagation and rupture in an airway. Gaseous non-reactive ethylene jet and air crossflow simulation represents essential physics for fuel injection in SCRAMJET engines. The regime is highly unsteady, involving shocks, turbulent mixing, and large-scale vortical structures. An eddy-viscosity-based multi-scale turbulence model is proposed to resolve turbulent structures consistent with grid resolution and turbulence length scales. Predictions of the time-averaged fuel concentration from the multi-scale model is improved over Reynolds-averaged Navier-Stokes models originally derived from stationary flow. The response to the multi-scale model alone is, however, limited, in cases where the vortical structures are small and scattered thus requiring prohibitively expensive grids in order to resolve the flow field accurately. Statistical information related to turbulent fluctuations is utilized to estimate an effective turbulent Schmidt number, which is shown to be highly varying in space. Accordingly, an adaptive turbulent Schmidt number approach is proposed, by allowing the resolved field to adaptively influence the value of turbulent Schmidt number in the multi-scale turbulence model. The proposed model estimates a time-averaged turbulent Schmidt number adapted to the computed flowfield, instead of the constant value common to the eddy-viscosity-based Navier-Stokes models. This approach is assessed using a grid-refinement study for the normal injection case, and tested with 30 degree injection, showing improved results over the constant turbulent Schmidt model both in mean and variance of fuel concentration predictions. For the incompressible liquid plug propagation and rupture study, numerical simulations are conducted using an Eulerian-Lagrangian approach with a continuous-interface method. A reconstruction scheme is developed to allow topological changes during plug rupture by altering the connectivity information of the interface mesh. Rupture time is shown to be delayed as the initial precursor film thickness increases. During the plug rupture process, a sudden increase of mechanical stresses on the tube wall is recorded, which can cause tissue damage.
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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
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Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes
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
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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
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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.
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SIMULATION OF SULFATE AEROSOL IN EAST ASIA USING MODELS-3/CMAQ WITH RAMS METEOROLOGICAL DATA
The present study attempts to address a few challenges in utilizing the flexibility of the Models-3 Community Multiscale Air Quality (CMAQ) modeling system. We apply the CMAQ system with the meteorological data provided by the Regional Atmospheric Modeling System (RAMS) and to a...
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USING MM5 VERSION 2 WITH CMAQ AND MODELS-3, A USER'S GUIDE AND TUTORIAL
Meteorological data are important in many of the processes simulated in the Community Multi-Scale Air Quality (CMAQ) model and the Models-3 framework. The first meteorology model that has been selected and evaluated with CMAQ is the Fifth-Generation Pennsylvania State University...
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The goal of achieving verisimilitude of air quality simulations to observations is problematic. Chemical transport models such as the Community Multi-Scale Air Quality (CMAQ) modeling system produce volume averages of pollutant concentration fields. When grid sizes are such tha...
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Design of Energetic Ionic Liquids (Preprint)
2008-05-07
mesoscale-level simulations of bulk ionic liquids based upon multiscale coarse graining techniques. 15. SUBJECT TERMS 16. SECURITY...simulations utilizing polarizable force fields, and mesoscale-level simulations of bulk ionic liquids based upon multiscale coarse graining...Simulations of the Energetic Ionic Liquid 1-hydroxyethyl-4-amino-1, 2, 4- triazolium Nitrate (HEATN): Molecular dynamics (MD) simulations have been
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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.
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Adaptive Multiscale Modeling of Geochemical Impacts on Fracture Evolution
NASA Astrophysics Data System (ADS)
Molins, S.; Trebotich, D.; Steefel, C. I.; Deng, H.
2016-12-01
Understanding fracture evolution is essential for many subsurface energy applications, including subsurface storage, shale gas production, fracking, CO2 sequestration, and geothermal energy extraction. Geochemical processes in particular play a significant role in the evolution of fractures through dissolution-driven widening, fines migration, and/or fracture sealing due to precipitation. One obstacle to understanding and exploiting geochemical fracture evolution is that it is a multiscale process. However, current geochemical modeling of fractures cannot capture this multi-scale nature of geochemical and mechanical impacts on fracture evolution, and is limited to either a continuum or pore-scale representation. Conventional continuum-scale models treat fractures as preferential flow paths, with their permeability evolving as a function (often, a cubic law) of the fracture aperture. This approach has the limitation that it oversimplifies flow within the fracture in its omission of pore scale effects while also assuming well-mixed conditions. More recently, pore-scale models along with advanced characterization techniques have allowed for accurate simulations of flow and reactive transport within the pore space (Molins et al., 2014, 2015). However, these models, even with high performance computing, are currently limited in their ability to treat tractable domain sizes (Steefel et al., 2013). Thus, there is a critical need to develop an adaptive modeling capability that can account for separate properties and processes, emergent and otherwise, in the fracture and the rock matrix at different spatial scales. Here we present an adaptive modeling capability that treats geochemical impacts on fracture evolution within a single multiscale framework. Model development makes use of the high performance simulation capability, Chombo-Crunch, leveraged by high resolution characterization and experiments. The modeling framework is based on the adaptive capability in Chombo which not only enables mesh refinement, but also refinement of the model-pore scale or continuum Darcy scale-in a dynamic way such that the appropriate model is used only when and where it is needed. Explicit flux matching provides coupling betwen the scales.
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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...
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Multi-scale modelling of supercapacitors: From molecular simulations to a transmission line model
NASA Astrophysics Data System (ADS)
Pean, C.; Rotenberg, B.; Simon, P.; Salanne, M.
2016-09-01
We perform molecular dynamics simulations of a typical nanoporous-carbon based supercapacitor. The organic electrolyte consists in 1-ethyl-3-methylimidazolium and hexafluorophosphate ions dissolved in acetonitrile. We simulate systems at equilibrium, for various applied voltages. This allows us to determine the relevant thermodynamic (capacitance) and transport (in-pore resistivities) properties. These quantities are then injected in a transmission line model for testing its ability to predict the charging properties of the device. The results from this macroscopic model are in good agreement with non-equilibrium molecular dynamics simulations, which validates its use for interpreting electrochemical impedance experiments.
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Multiscale modelling of palisade formation in gliobastoma multiforme.
Caiazzo, Alfonso; Ramis-Conde, Ignacio
2015-10-21
Palisades are characteristic tissue aberrations that arise in glioblastomas. Observation of palisades is considered as a clinical indicator of the transition from a noninvasive to an invasive tumour. In this paper we propose a computational model to study the influence of the hypoxic switch in palisade formation. For this we produced three-dimensional realistic simulations, based on a multiscale hybrid model, coupling the evolution of tumour cells and the oxygen diffusion in tissue, that depict the shape of palisades during its formation. Our results can be summarized as follows: (1) the presented simulations can provide clinicians and biologists with a better understanding of three-dimensional structure of palisades as well as of glioblastomas growth dynamics; (2) we show that heterogeneity in cell response to hypoxia is a relevant factor in palisade and pseudopalisade formation; (3) we show how selective processes based on the hypoxia switch influence the tumour proliferation. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Module-based multiscale simulation of angiogenesis in skeletal muscle
2011-01-01
Background Mathematical modeling of angiogenesis has been gaining momentum as a means to shed new light on the biological complexity underlying blood vessel growth. A variety of computational models have been developed, each focusing on different aspects of the angiogenesis process and occurring at different biological scales, ranging from the molecular to the tissue levels. Integration of models at different scales is a challenging and currently unsolved problem. Results We present an object-oriented module-based computational integration strategy to build a multiscale model of angiogenesis that links currently available models. As an example case, we use this approach to integrate modules representing microvascular blood flow, oxygen transport, vascular endothelial growth factor transport and endothelial cell behavior (sensing, migration and proliferation). Modeling methodologies in these modules include algebraic equations, partial differential equations and agent-based models with complex logical rules. We apply this integrated model to simulate exercise-induced angiogenesis in skeletal muscle. The simulation results compare capillary growth patterns between different exercise conditions for a single bout of exercise. Results demonstrate how the computational infrastructure can effectively integrate multiple modules by coordinating their connectivity and data exchange. Model parameterization offers simulation flexibility and a platform for performing sensitivity analysis. Conclusions This systems biology strategy can be applied to larger scale integration of computational models of angiogenesis in skeletal muscle, or other complex processes in other tissues under physiological and pathological conditions. PMID:21463529
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Chen, Hai; Liang, Xiaoying; Li, Rui
2013-01-01
Multi-Agent Systems (MAS) offer a conceptual approach to include multi-actor decision making into models of land use change. Through the simulation based on the MAS, this paper tries to show the application of MAS in the micro scale LUCC, and reveal the transformation mechanism of difference scale. This paper starts with a description of the context of MAS research. Then, it adopts the Nested Spatial Choice (NSC) method to construct the multi-scale LUCC decision-making model. And a case study for Mengcha village, Mizhi County, Shaanxi Province is reported. Finally, the potentials and drawbacks of the following approach is discussed and concluded. From our design and implementation of the MAS in multi-scale model, a number of observations and conclusions can be drawn on the implementation and future research directions. (1) The use of the LUCC decision-making and multi-scale transformation framework provides, according to us, a more realistic modeling of multi-scale decision making process. (2) By using continuous function, rather than discrete function, to construct the decision-making of the households is more realistic to reflect the effect. (3) In this paper, attempts have been made to give a quantitative analysis to research the household interaction. And it provides the premise and foundation for researching the communication and learning among the households. (4) The scale transformation architecture constructed in this paper helps to accumulate theory and experience for the interaction research between the micro land use decision-making and the macro land use landscape pattern. Our future research work will focus on: (1) how to rational use risk aversion principle, and put the rule on rotation between household parcels into model. (2) Exploring the methods aiming at researching the household decision-making over a long period, it allows us to find the bridge between the long-term LUCC data and the short-term household decision-making. (3) Researching the quantitative method and model, especially the scenario analysis model which may reflect the interaction among different household types.
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Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform.
Marshall-Colon, Amy; Long, Stephen P; Allen, Douglas K; Allen, Gabrielle; Beard, Daniel A; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A J; Cox, Donna J; Hart, John C; Hirst, Peter M; Kannan, Kavya; Katz, Daniel S; Lynch, Jonathan P; Millar, Andrew J; Panneerselvam, Balaji; Price, Nathan D; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J; Voit, Eberhard O; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang
2017-01-01
Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop.
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Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform
Marshall-Colon, Amy; Long, Stephen P.; Allen, Douglas K.; Allen, Gabrielle; Beard, Daniel A.; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A. J.; Cox, Donna J.; Hart, John C.; Hirst, Peter M.; Kannan, Kavya; Katz, Daniel S.; Lynch, Jonathan P.; Millar, Andrew J.; Panneerselvam, Balaji; Price, Nathan D.; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G.; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J.; Voit, Eberhard O.; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang
2017-01-01
Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop. PMID:28555150
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NASA Astrophysics Data System (ADS)
Barajas-Solano, D. A.; Tartakovsky, A. M.
2017-12-01
We present a multiresolution method for the numerical simulation of flow and reactive transport in porous, heterogeneous media, based on the hybrid Multiscale Finite Volume (h-MsFV) algorithm. The h-MsFV algorithm allows us to couple high-resolution (fine scale) flow and transport models with lower resolution (coarse) models to locally refine both spatial resolution and transport models. The fine scale problem is decomposed into various "local'' problems solved independently in parallel and coordinated via a "global'' problem. This global problem is then coupled with the coarse model to strictly ensure domain-wide coarse-scale mass conservation. The proposed method provides an alternative to adaptive mesh refinement (AMR), due to its capacity to rapidly refine spatial resolution beyond what's possible with state-of-the-art AMR techniques, and the capability to locally swap transport models. We illustrate our method by applying it to groundwater flow and reactive transport of multiple species.
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Biological materials by design.
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.
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NASA Astrophysics Data System (ADS)
Du, Qiang; Li, Yanjun
2015-06-01
In this paper, a multi-scale as-cast grain size prediction model is proposed to predict as-cast grain size of inoculated aluminum alloys melt solidified under non-isothermal condition, i.e., the existence of temperature gradient. Given melt composition, inoculation and heat extraction boundary conditions, the model is able to predict maximum nucleation undercooling, cooling curve, primary phase solidification path and final as-cast grain size of binary alloys. The proposed model has been applied to two Al-Mg alloys, and comparison with laboratory and industrial solidification experimental results have been carried out. The preliminary conclusion is that the proposed model is a promising suitable microscopic model used within the multi-scale casting simulation modelling framework.
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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.
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NASA Technical Reports Server (NTRS)
Shen, Bo-Wen; Tao, Wei-Kuo; Chern, Jiun-Dar
2007-01-01
Improving our understanding of hurricane inter-annual variability and the impact of climate change (e.g., doubling CO2 and/or global warming) on hurricanes brings both scientific and computational challenges to researchers. As hurricane dynamics involves multiscale interactions among synoptic-scale flows, mesoscale vortices, and small-scale cloud motions, an ideal numerical model suitable for hurricane studies should demonstrate its capabilities in simulating these interactions. The newly-developed multiscale modeling framework (MMF, Tao et al., 2007) and the substantial computing power by the NASA Columbia supercomputer show promise in pursuing the related studies, as the MMF inherits the advantages of two NASA state-of-the-art modeling components: the GEOS4/fvGCM and 2D GCEs. This article focuses on the computational issues and proposes a revised methodology to improve the MMF's performance and scalability. It is shown that this prototype implementation enables 12-fold performance improvements with 364 CPUs, thereby making it more feasible to study hurricane climate.
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Wang, Minghuai; Larson, Vincent E.; Ghan, Steven; ...
2015-04-18
In this study, a higher-order turbulence closure scheme, called Cloud Layers Unified by Binormals (CLUBB), is implemented into a Multi-scale Modeling Framework (MMF) model to improve low cloud simulations. The performance of CLUBB in MMF simulations with two different microphysics configurations (one-moment cloud microphysics without aerosol treatment and two-moment cloud microphysics coupled with aerosol treatment) is evaluated against observations and further compared with results from the Community Atmosphere Model, Version 5 (CAM5) with conventional cloud parameterizations. CLUBB is found to improve low cloud simulations in the MMF, and the improvement is particularly evident in the stratocumulus-to-cumulus transition regions. Compared tomore » the single-moment cloud microphysics, CLUBB with two-moment microphysics produces clouds that are closer to the coast, and agrees better with observations. In the stratocumulus-to cumulus transition regions, CLUBB with two-moment cloud microphysics produces shortwave cloud forcing in better agreement with observations, while CLUBB with single moment cloud microphysics overestimates shortwave cloud forcing. CLUBB is further found to produce quantitatively similar improvements in the MMF and CAM5, with slightly better performance in the MMF simulations (e.g., MMF with CLUBB generally produces low clouds that are closer to the coast than CAM5 with CLUBB). As a result, improved low cloud simulations in MMF make it an even more attractive tool for studying aerosol-cloud-precipitation interactions.« less
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THE 2006 CMAQ RELEASE AND PLANS FOR 2007
The 2006 release of the Community Multiscale Air Quality (CMAQ) model (Version 4.6) includes upgrades to several model components as well as new modules for gas-phase chemistry and boundary layer mixing. Capabilities for simulation of hazardous air pollutants have been expanded ...
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INTERDEPENDENCIES OF MULTI-POLLUTANT CONTROL SIMULATIONS IN AN AIR QUALITY MODEL
In this work, we use the Community Multi-Scale Air Quality (CMAQ) modeling system to examine the effect of several control strategies on simultaneous concentrations of ozone, PM2.5, and three important HAPs: formaldehyde, acetaldehyde and benzene.
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Simulating cancer growth with multiscale agent-based modeling.
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.
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Multiscale molecular dynamics simulations of rotary motor proteins.
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.
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Aerosol-cloud interactions in a multi-scale modeling framework
NASA Astrophysics Data System (ADS)
Lin, G.; Ghan, S. J.
2017-12-01
Atmospheric aerosols play an important role in changing the Earth's climate through scattering/absorbing solar and terrestrial radiation and interacting with clouds. However, quantification of the aerosol effects remains one of the most uncertain aspects of current and future climate projection. Much of the uncertainty results from the multi-scale nature of aerosol-cloud interactions, which is very challenging to represent in traditional global climate models (GCMs). In contrast, the multi-scale modeling framework (MMF) provides a viable solution, which explicitly resolves the cloud/precipitation in the cloud resolved model (CRM) embedded in the GCM grid column. In the MMF version of community atmospheric model version 5 (CAM5), aerosol processes are treated with a parameterization, called the Explicit Clouds Parameterized Pollutants (ECPP). It uses the cloud/precipitation statistics derived from the CRM to treat the cloud processing of aerosols on the GCM grid. However, this treatment treats clouds on the CRM grid but aerosols on the GCM grid, which is inconsistent with the reality that cloud-aerosol interactions occur on the cloud scale. To overcome the limitation, here, we propose a new aerosol treatment in the MMF: Explicit Clouds Explicit Aerosols (ECEP), in which we resolve both clouds and aerosols explicitly on the CRM grid. We first applied the MMF with ECPP to the Accelerated Climate Modeling for Energy (ACME) model to have an MMF version of ACME. Further, we also developed an alternative version of ACME-MMF with ECEP. Based on these two models, we have conducted two simulations: one with the ECPP and the other with ECEP. Preliminary results showed that the ECEP simulations tend to predict higher aerosol concentrations than ECPP simulations, because of the more efficient vertical transport from the surface to the higher atmosphere but the less efficient wet removal. We also found that the cloud droplet number concentrations are also different between the two simulations due to the difference in the cloud droplet lifetime. Next, we will explore how the ECEP treatment affects the anthropogenic aerosol forcing, particularly the aerosol indirect forcing, by comparing present-day and pre-industrial simulations.
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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.
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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
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Techniques and resources for storm-scale numerical weather prediction
NASA Technical Reports Server (NTRS)
Droegemeier, Kelvin; Grell, Georg; Doyle, James; Soong, Su-Tzai; Skamarock, William; Bacon, David; Staniforth, Andrew; Crook, Andrew; Wilhelmson, Robert
1993-01-01
The topics discussed include the following: multiscale application of the 5th-generation PSU/NCAR mesoscale model, the coupling of nonhydrostatic atmospheric and hydrostatic ocean models for air-sea interaction studies; a numerical simulation of cloud formation over complex topography; adaptive grid simulations of convection; an unstructured grid, nonhydrostatic meso/cloud scale model; efficient mesoscale modeling for multiple scales using variable resolution; initialization of cloud-scale models with Doppler radar data; and making effective use of future computing architectures, networks, and visualization software.
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Modeling Impact-induced Failure of Polysilicon MEMS: A Multi-scale Approach.
Mariani, Stefano; Ghisi, Aldo; Corigliano, Alberto; Zerbini, Sarah
2009-01-01
Failure of packaged polysilicon micro-electro-mechanical systems (MEMS) subjected to impacts involves phenomena occurring at several length-scales. In this paper we present a multi-scale finite element approach to properly allow for: (i) the propagation of stress waves inside the package; (ii) the dynamics of the whole MEMS; (iii) the spreading of micro-cracking in the failing part(s) of the sensor. Through Monte Carlo simulations, some effects of polysilicon micro-structure on the failure mode are elucidated.
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NASA Technical Reports Server (NTRS)
Yamakov, V.; Saether, E.; Glaessgen, E. H.
2008-01-01
Intergranular fracture is a dominant mode of failure in ultrafine grained materials. In the present study, the atomistic mechanisms of grain-boundary debonding during intergranular fracture in aluminum are modeled using a coupled molecular dynamics finite element simulation. Using a statistical mechanics approach, a cohesive-zone law in the form of a traction-displacement constitutive relationship, characterizing the load transfer across the plane of a growing edge crack, is extracted from atomistic simulations and then recast in a form suitable for inclusion within a continuum finite element model. The cohesive-zone law derived by the presented technique is free of finite size effects and is statistically representative for describing the interfacial debonding of a grain boundary (GB) interface examined at atomic length scales. By incorporating the cohesive-zone law in cohesive-zone finite elements, the debonding of a GB interface can be simulated in a coupled continuum-atomistic model, in which a crack starts in the continuum environment, smoothly penetrates the continuum-atomistic interface, and continues its propagation in the atomistic environment. This study is a step towards relating atomistically derived decohesion laws to macroscopic predictions of fracture and constructing multiscale models for nanocrystalline and ultrafine grained materials.
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NASA Astrophysics Data System (ADS)
Neary, L.; Kaminski, J. W.; Struzewska, J.; Ainslie, B.; McConnell, J. C.
2007-12-01
Tropospheric chemistry and air quality processes were implemented on-line in the Global Environmental Multiscale model. The integrated model, GEM-AQ, has been developed as a platform to investigate chemical weather at scales from global to urban. On the global scale, the model was exercised for five years (2001-2005) to evaluate its ability to simulate seasonal variations and regional distributions of trace gases such as ozone, nitrogen dioxide and carbon monoxide. The model results are compared with observations from satellites, aircraft measurement campaigns and balloon sondes. The same model has also been evaluated on the regional (~15km resolution) and urban scale (~3km resolution). A simulation of the formation and transport of photooxidants during the European heat wave of 2006 was performed and compared with surface observations throughout central and eastern Europe. The complex topographic region of the Lower Fraser Valley in British Columbia was the focus of another model evaluation during the PACIFIC 2001 field campaign. Comparison of model results with observations during this period will be shown.
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Experimental Investigations And Numerical Modelling of 210CR12 Steel in Semi-Solid State
NASA Astrophysics Data System (ADS)
Macioł, Piotr; Zalecki, Władysław; Kuziak, Roman; Jakubowicz, Aleksandra; Weglarczyk, Stanisław
2011-05-01
Experimental investigation, including hot compression and simple closed die filling was performed. Temperature range of tests was between 1225 °C and 1320 °C. Temperature selection was adequate with liquid fraction between 20 and 60%, which is typical for thixoforming processes. In the die filling test, steel dies with ceramic layer was used (highly refractory air-setting mortar JM 3300 manufactured by Thermal Ceramics). Experiments were carried out on the Gleeble 3800 physical simulator with MCU unit. In the paper, methodology of experimental investigation is described. Dependency of forming forces on temperature and forming velocities is analysed. Obtained results are discussed. The second part of the paper concerns numerical modelling of semi-solid forming. Numerical models for both sets of test were developed. Structural and Computational Fluid Dynamics models are compared. Initial works in microstructural modelling of 210CR12 steel behaviour are described. Lattice Boltzman Method model for thixotropic flows is introduced. Microscale and macroscale models were integrated into multiscale simulation of semi-solid forming. Some fundamental issues related to multiscale modelling of thixoforming are discussed.
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Vierheller, Janine; Neubert, Wilhelm; Falcke, Martin; Gilbert, Stephen H.; Chamakuri, Nagaiah
2015-01-01
Mathematical modeling of excitation-contraction coupling (ECC) in ventricular cardiac myocytes is a multiscale problem, and it is therefore difficult to develop spatially detailed simulation tools. ECC involves gradients on the length scale of 100 nm in dyadic spaces and concentration profiles along the 100 μm of the whole cell, as well as the sub-millisecond time scale of local concentration changes and the change of lumenal Ca2+ content within tens of seconds. Our concept for a multiscale mathematical model of Ca2+ -induced Ca2+ release (CICR) and whole cardiomyocyte electrophysiology incorporates stochastic simulation of individual LC- and RyR-channels, spatially detailed concentration dynamics in dyadic clefts, rabbit membrane potential dynamics, and a system of partial differential equations for myoplasmic and lumenal free Ca2+ and Ca2+-binding molecules in the bulk of the cell. We developed a novel computational approach to resolve the concentration gradients from dyadic space to cell level by using a quasistatic approximation within the dyad and finite element methods for integrating the partial differential equations. We show whole cell Ca2+-concentration profiles using three previously published RyR-channel Markov schemes. PMID:26441674
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NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Chern, Jiun-Dar
2017-01-01
The importance of precipitating mesoscale convective systems (MCSs) has been quantified from TRMM precipitation radar and microwave imager retrievals. MCSs generate more than 50% of the rainfall in most tropical regions. MCSs usually have horizontal scales of a few hundred kilometers (km); therefore, a large domain with several hundred km is required for realistic simulations of MCSs in cloud-resolving models (CRMs). Almost all traditional global and climate models do not have adequate parameterizations to represent MCSs. Typical multi-scale modeling frameworks (MMFs) may also lack the resolution (4 km grid spacing) and domain size (128 km) to realistically simulate MCSs. In this study, the impact of MCSs on precipitation is examined by conducting model simulations using the Goddard Cumulus Ensemble (GCE) model and Goddard MMF (GMMF). The results indicate that both models can realistically simulate MCSs with more grid points (i.e., 128 and 256) and higher resolutions (1 or 2 km) compared to those simulations with fewer grid points (i.e., 32 and 64) and low resolution (4 km). The modeling results also show the strengths of the Hadley circulations, mean zonal and regional vertical velocities, surface evaporation, and amount of surface rainfall are weaker or reduced in the GMMF when using more CRM grid points and higher CRM resolution. In addition, the results indicate that large-scale surface evaporation and wind feed back are key processes for determining the surface rainfall amount in the GMMF. A sensitivity test with reduced sea surface temperatures shows both reduced surface rainfall and evaporation.
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NASA Astrophysics Data System (ADS)
Tao, Wei-Kuo; Chern, Jiun-Dar
2017-06-01
The importance of precipitating mesoscale convective systems (MCSs) has been quantified from TRMM precipitation radar and microwave imager retrievals. MCSs generate more than 50% of the rainfall in most tropical regions. MCSs usually have horizontal scales of a few hundred kilometers (km); therefore, a large domain with several hundred km is required for realistic simulations of MCSs in cloud-resolving models (CRMs). Almost all traditional global and climate models do not have adequate parameterizations to represent MCSs. Typical multiscale modeling frameworks (MMFs) may also lack the resolution (4 km grid spacing) and domain size (128 km) to realistically simulate MCSs. The impact of MCSs on precipitation is examined by conducting model simulations using the Goddard Cumulus Ensemble (GCE, a CRM) model and Goddard MMF that uses the GCEs as its embedded CRMs. Both models can realistically simulate MCSs with more grid points (i.e., 128 and 256) and higher resolutions (1 or 2 km) compared to those simulations with fewer grid points (i.e., 32 and 64) and low resolution (4 km). The modeling results also show the strengths of the Hadley circulations, mean zonal and regional vertical velocities, surface evaporation, and amount of surface rainfall are weaker or reduced in the Goddard MMF when using more CRM grid points and higher CRM resolution. In addition, the results indicate that large-scale surface evaporation and wind feedback are key processes for determining the surface rainfall amount in the GMMF. A sensitivity test with reduced sea surface temperatures shows both reduced surface rainfall and evaporation.
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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) ...
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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 ...
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Progress in fast, accurate multi-scale climate simulations
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
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Anatomically realistic multiscale models of normal and abnormal gastrointestinal electrical activity
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
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APPLICATION OF BIAS AND ADJUSTMENT TECHNIQUES TO THE ETA-CMAQ AIR QUALITY FORECAST
The current air quality forecast system, based on linking NOAA's Eta meteorological model with EPA's Community Multiscale Air Quality (CMAQ) model, consistently overpredicts surface ozone concentrations, but simulates its day-to-day variability quite well. The ability of bias cor...
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NASA Astrophysics Data System (ADS)
Huang, Yanhui; Zhao, He; Wang, Yixing; Ratcliff, Tyree; Breneman, Curt; Brinson, L. Catherine; Chen, Wei; Schadler, Linda S.
2017-08-01
It has been found that doping dielectric polymers with a small amount of nanofiller or molecular additive can stabilize the material under a high field and lead to increased breakdown strength and lifetime. Choosing appropriate fillers is critical to optimizing the material performance, but current research largely relies on experimental trial and error. The employment of computer simulations for nanodielectric design is rarely reported. In this work, we propose a multi-scale modeling approach that employs ab initio, Monte Carlo, and continuum scales to predict the breakdown strength and lifetime of polymer nanocomposites based on the charge trapping effect of the nanofillers. The charge transfer, charge energy relaxation, and space charge effects are modeled in respective hierarchical scales by distinctive simulation techniques, and these models are connected together for high fidelity and robustness. The preliminary results show good agreement with the experimental data, suggesting its promise for use in the computer aided material design of high performance dielectrics.
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A tool for multi-scale modelling of the renal nephron
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
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Salavati, Hooman; Soltani, M; Amanpour, Saeid
2018-05-06
The mechanisms involved in tumor growth mainly occur at the microenvironment, where the interactions between the intracellular, intercellular and extracellular scales mediate the dynamics of tumor. In this work, we present a multi-scale model of solid tumor dynamics to simulate the avascular and vascular growth as well as tumor-induced angiogenesis. The extracellular and intercellular scales are modeled using partial differential equations and cellular Potts model, respectively. Also, few biochemical and biophysical rules control the dynamics of intracellular level. On the other hand, the growth of melanoma tumors is modeled in an animal in-vivo study to evaluate the simulation. The simulation shows that the model successfully reproduces a completed image of processes involved in tumor growth such as avascular and vascular growth as well as angiogenesis. The model incorporates the phenotypes of cancerous cells including proliferating, quiescent and necrotic cells, as well as endothelial cells during angiogenesis. The results clearly demonstrate the pivotal effect of angiogenesis on the progression of cancerous cells. Also, the model exhibits important events in tumor-induced angiogenesis like anastomosis. Moreover, the computational trend of tumor growth closely follows the observations in the experimental study. Copyright © 2018 Elsevier Inc. All rights reserved.
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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.
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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.
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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.
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Multiscale Models for the Two-Stream Instability
NASA Astrophysics Data System (ADS)
Joseph, Ilon; Dimits, Andris; Banks, Jeffrey; Berger, Richard; Brunner, Stephan; Chapman, Thomas
2017-10-01
Interpenetrating streams of plasma found in many important scenarios in nature and in the laboratory can develop kinetic two-stream instabilities that exchange momentum and energy between the streams. A quasilinear model for the electrostatic two-stream instability is under development as a component of a multiscale model that couples fluid simulations to kinetic theory. Parameters of the model will be validated with comparison to full kinetic simulations using LOKI and efficient strategies for numerical solution of the quasilinear model and for coupling to the fluid model will be discussed. Extending the kinetic models into the collisional regime requires an efficient treatment of the collision operator. Useful reductions of the collision operator relative to the full multi-species Landau-Fokker-Plank operator are being explored. These are further motivated both by careful consideration of the parameter orderings relevant to two-stream scenarios and by the particular 2D+2V phase space used in the LOKI code. Prepared for US DOE by LLNL under Contract DE-AC52-07NA27344 and LDRD project 17- ERD-081.
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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.
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Multiscale analysis of information dynamics for linear multivariate processes.
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.
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Multiscale systems biology of trauma-induced coagulopathy.
Tsiklidis, Evan; Sims, Carrie; Sinno, Talid; Diamond, Scott L
2018-07-01
Trauma with hypovolemic shock is an extreme pathological state that challenges the body to maintain blood pressure and oxygenation in the face of hemorrhagic blood loss. In conjunction with surgical actions and transfusion therapy, survival requires the patient's blood to maintain hemostasis to stop bleeding. The physics of the problem are multiscale: (a) the systemic circulation sets the global blood pressure in response to blood loss and resuscitation therapy, (b) local tissue perfusion is altered by localized vasoregulatory mechanisms and bleeding, and (c) altered blood and vessel biology resulting from the trauma as well as local hemodynamics control the assembly of clotting components at the site of injury. Building upon ongoing modeling efforts to simulate arterial or venous thrombosis in a diseased vasculature, computer simulation of trauma-induced coagulopathy is an emerging approach to understand patient risk and predict response. Despite uncertainties in quantifying the patient's dynamic injury burden, multiscale systems biology may help link blood biochemistry at the molecular level to multiorgan responses in the bleeding patient. As an important goal of systems modeling, establishing early metrics of a patient's high-dimensional trajectory may help guide transfusion therapy or warn of subsequent later stage bleeding or thrombotic risks. This article is categorized under: Analytical and Computational Methods > Computational Methods Biological Mechanisms > Regulatory Biology Models of Systems Properties and Processes > Mechanistic Models. © 2018 Wiley Periodicals, Inc.
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Computational Modeling Approaches to Multiscale Design of Icephobic Surfaces
NASA Technical Reports Server (NTRS)
Tallman, Aaron; Wang, Yan; Vargas, Mario
2017-01-01
To aid in the design of surfaces that prevent icing, a model and computational simulation of impact ice formation at the single droplet scale was implemented. The nucleation of a single supercooled droplet impacting on a substrate, in rime ice conditions, was simulated. Open source computational fluid dynamics (CFD) software was used for the simulation. To aid in the design of surfaces that prevent icing, a model of impact ice formation at the single droplet scale was proposed•No existing model simulates simultaneous impact and freezing of a single super-cooled water droplet•For the 10-week project, a low-fidelity feasibility study was the goal.
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Multicale modeling of the detonation of aluminized explosives using SPH-MD-QM method
NASA Astrophysics Data System (ADS)
Peng, Qing; Wang, Guangyu; Liu, Gui-Rong; de, Suvranu
Aluminized explosives have been applied in military industry since decades ago. Compared with ideal explosives, aluminized explosives feature both fast detonation and slow metal combustion chemistry, generating a complex multi-phase reactive flow. Here, we introduce a sequential multiscale model of SPH-MD-QM to simulate the detonation behavior of aluminized explosives. At the bottom level, first-principles quantum mechanics (QM) calculations are employed to obtain the training sets for fitting the ReaxFF potentials, which are used in turn in the reactive molecular dynamics (MD) simulations in the middle level to obtain the chemical reaction rates and equations of states. At the up lever, a smooth particle hydrodynamics (SPH) method incorporated ignition and growth model and afterburning model has been used for the simulation of the detonation and combustion of the aluminized explosive. Simulation is compared with experiment and good agreement is observed. The proposed multiscale method of SPH-MD-QM could be used to optimize the performance of aluminized explosives. The authors would like to acknowledge the generous financial support from the Defense Threat Reduction Agency (DTRA) Grant No. HDTRA1-13-1-0025 and the Office of Naval Research Grants ONR Award No. N00014-08-1-0462 and No. N00014-12-1-0527.
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Multiscale Simulations of ALD in Cross Flow Reactors
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
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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.
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Corsini, Chiara; Biglino, Giovanni; Schievano, Silvia; Hsia, Tain-Yen; Migliavacca, Francesco; Pennati, Giancarlo; Taylor, Andrew M
2014-08-01
The size of the modified Blalock-Taussig shunt and the additional presence of aortic coarctation can affect the hemodynamics of the Norwood physiology. Multiscale modeling was used to gather insight into the effects of these variables, in particular on coronary perfusion. A model was reconstructed from cardiac magnetic resonance imaging data of a representative patient, and then simplified with computer-aided design software. Changes were systematically imposed to the semi-idealized three-dimensional model, resulting in a family of nine models (3-, 3.5-, and 4-mm shunt diameter; 0%, 60%, and 90% coarctation severity). Each model was coupled to a lumped parameter network representing the remainder of the circulation to run multiscale simulations. Simulations were repeated including the effect of preserved cerebral perfusion. The concomitant presence of a large shunt and tight coarctation was detrimental in terms of coronary perfusion (13.4% maximal reduction, 1.07 versus 0.927 mL/s) and oxygen delivery (29% maximum reduction, 422 versus 300 mL·min(-1)·m(-2)). A variation in the ratio of pulmonary to systemic blood flow from 0.9 to 1.6 also indicated a "stealing" phenomenon to the detriment of the coronary circulation. A difference could be further appreciated in the computational ventricular pressure-volume loops, with augmented systolic pressures and decreased stroke volumes for tighter coarctation. Accounting for constant cerebral perfusion did not produce substantially different results. Multiscale simulations performed in a parametric fashion revealed a reduction in coronary perfusion in the presence of a large modified Blalock-Taussig shunt and severe coarctation in Norwood patients. Copyright © 2014 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.
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Stochastic simulation of multiscale complex systems with PISKaS: A rule-based approach.
Perez-Acle, Tomas; Fuenzalida, Ignacio; Martin, Alberto J M; Santibañez, Rodrigo; Avaria, Rodrigo; Bernardin, Alejandro; Bustos, Alvaro M; Garrido, Daniel; Dushoff, Jonathan; Liu, James H
2018-03-29
Computational simulation is a widely employed methodology to study the dynamic behavior of complex systems. Although common approaches are based either on ordinary differential equations or stochastic differential equations, these techniques make several assumptions which, when it comes to biological processes, could often lead to unrealistic models. Among others, model approaches based on differential equations entangle kinetics and causality, failing when complexity increases, separating knowledge from models, and assuming that the average behavior of the population encompasses any individual deviation. To overcome these limitations, simulations based on the Stochastic Simulation Algorithm (SSA) appear as a suitable approach to model complex biological systems. In this work, we review three different models executed in PISKaS: a rule-based framework to produce multiscale stochastic simulations of complex systems. These models span multiple time and spatial scales ranging from gene regulation up to Game Theory. In the first example, we describe a model of the core regulatory network of gene expression in Escherichia coli highlighting the continuous model improvement capacities of PISKaS. The second example describes a hypothetical outbreak of the Ebola virus occurring in a compartmentalized environment resembling cities and highways. Finally, in the last example, we illustrate a stochastic model for the prisoner's dilemma; a common approach from social sciences describing complex interactions involving trust within human populations. As whole, these models demonstrate the capabilities of PISKaS providing fertile scenarios where to explore the dynamics of complex systems. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
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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.
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Simulations of Quantum Dot Growth on Semiconductor Surfaces: Morphological Design of Sensor Concepts
2008-12-01
size equalization can be clearly illustrated during the growth process. In this work we develop a fast multiscale 3D kinetic Monte Carlo ( KMC ) QD...model will provide an attractive means for producing predictably ordered nanostructures. MODEL DESCRIPTION The 3D layer-by-layer KMC growth model...Voter, 2001) and KMC simulation experience (Pan et al., 2004; Pan et al., 2006; Meixner et al, 2003) in 2D, we therefore propose the following simple
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2015-12-28
Masoud Anahid, Mahendra K. Samal , and Somnath Ghosh. Dwell fatigue crack nucleation model based on crystal plasticity finite element simulations of...induced crack nucleation in polycrystals. Model. Simul. Mater. Sci. Eng., 17, 064009. 19. Anahid, M., Samal , M. K. & Ghosh, S. (2011). Dwell fatigue...Jour. Plas., 24:428–454, 2008. 4. M. Anahid, M. K. Samal , and S. Ghosh. Dwell fatigue crack nucleation model based on crystal plasticity finite
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Optimization of a hydrodynamic separator using a multiscale computational fluid dynamics approach.
Schmitt, Vivien; Dufresne, Matthieu; Vazquez, Jose; Fischer, Martin; Morin, Antoine
2013-01-01
This article deals with the optimization of a hydrodynamic separator working on the tangential separation mechanism along a screen. The aim of this study is to optimize the shape of the device to avoid clogging. A multiscale approach is used. This methodology combines measurements and computational fluid dynamics (CFD). A local model enables us to observe the different phenomena occurring at the orifice scale, which shows the potential of expanded metal screens. A global model is used to simulate the flow within the device using a conceptual model of the screen (porous wall). After validation against the experimental measurements, the global model was used to investigate the influence of deflectors and disk plates in the structure.
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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
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On Regional Modeling to Support Air Quality Policies
We examine the use of the Community Multiscale Air Quality (CMAQ) model in simulating the changes in the extreme values of air quality that are of interest to the regulatory agencies. Year-to-year changes in ozone air quality are attributable to variations in the prevailing mete...
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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.
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Multiscale modelling of hydraulic conductivity in vuggy porous media
Daly, K. R.; Roose, T.
2014-01-01
Flow in both saturated and non-saturated vuggy porous media, i.e. soil, is inherently multiscale. The complex microporous structure of the soil aggregates and the wider vugs provides a multitude of flow pathways and has received significant attention from the X-ray computed tomography (CT) community with a constant drive to image at higher resolution. Using multiscale homogenization, we derive averaged equations to study the effects of the microscale structure on the macroscopic flow. The averaged model captures the underlying geometry through a series of cell problems and is verified through direct comparison to numerical simulations of the full structure. These methods offer significant reductions in computation time and allow us to perform three-dimensional calculations with complex geometries on a desktop PC. The results show that the surface roughness of the aggregate has a significantly greater effect on the flow than the microstructure within the aggregate. Hence, this is the region in which the resolution of X-ray CT for image-based modelling has the greatest impact. PMID:24511248
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NASA Astrophysics Data System (ADS)
Bultreys, Tom; Van Hoorebeke, Luc; Cnudde, Veerle
2016-09-01
The two-phase flow properties of natural rocks depend strongly on their pore structure and wettability, both of which are often heterogeneous throughout the rock. To better understand and predict these properties, image-based models are being developed. Resulting simulations are however problematic in several important classes of rocks with broad pore-size distributions. We present a new multiscale pore network model to simulate secondary waterflooding in these rocks, which may undergo wettability alteration after primary drainage. This novel approach permits to include the effect of microporosity on the imbibition sequence without the need to describe each individual micropore. Instead, we show that fluid transport through unresolved pores can be taken into account in an upscaled fashion, by the inclusion of symbolic links between macropores, resulting in strongly decreased computational demands. Rules to describe the behavior of these links in the quasistatic invasion sequence are derived from percolation theory. The model is validated by comparison to a fully detailed network representation, which takes each separate micropore into account. Strongly and weakly water-and oil-wet simulations show good results, as do mixed-wettability scenarios with different pore-scale wettability distributions. We also show simulations on a network extracted from a micro-CT scan of Estaillades limestone, which yields good agreement with water-wet and mixed-wet experimental results.
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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
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A 5 year (2002-2006) simulation of CMAQ covering the eastern United States is evaluated using principle component analysis in order to identify and characterize statistically significant patterns of model bias. Such analysis is useful in that in can identify areas of poor model ...
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The impact of climate change on surface-level ozone is examined through a multiscale modeling effort that linked global and regional climate models to drive air quality model simulations. Results are quantified in terms of the relative response factor (RRFE), which estimates the ...
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The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science chemical transport model (CTM) capable of simulating the emission, transport and fate of numerous air pollutants. Similarly, the Weather Research and Forecasting (WRF) model is a state-of-the-science mete...
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Multi-decadal model calculations for the 1990-2010 period are performed with the coupled WRF-CMAQ modeling system over a domain encompassing the northern hemisphere and a nested domain over the continental U.S. Simulated trends in ozone and precursor species concentrations acros...
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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.
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Data Assimilation and Propagation of Uncertainty in Multiscale Cardiovascular Simulation
NASA Astrophysics Data System (ADS)
Schiavazzi, Daniele; Marsden, Alison
2015-11-01
Cardiovascular modeling is the application of computational tools to predict hemodynamics. State-of-the-art techniques couple a 3D incompressible Navier-Stokes solver with a boundary circulation model and can predict local and peripheral hemodynamics, analyze the post-operative performance of surgical designs and complement clinical data collection minimizing invasive and risky measurement practices. The ability of these tools to make useful predictions is directly related to their accuracy in representing measured physiologies. Tuning of model parameters is therefore a topic of paramount importance and should include clinical data uncertainty, revealing how this uncertainty will affect the predictions. We propose a fully Bayesian, multi-level approach to data assimilation of uncertain clinical data in multiscale circulation models. To reduce the computational cost, we use a stable, condensed approximation of the 3D model build by linear sparse regression of the pressure/flow rate relationship at the outlets. Finally, we consider the problem of non-invasively propagating the uncertainty in model parameters to the resulting hemodynamics and compare Monte Carlo simulation with Stochastic Collocation approaches based on Polynomial or Multi-resolution Chaos expansions.
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On the intrinsic flexibility of the opioid receptor through multiscale modeling approaches
NASA Astrophysics Data System (ADS)
Vercauteren, Daniel; FosséPré, Mathieu; Leherte, Laurence; Laaksonen, Aatto
Numerous releases of G protein-coupled receptors crystalline structures created the opportunity for computational methods to widely explore their dynamics. Here, we study the biological implication of the intrinsic flexibility properties of opioid receptor OR. First, one performed classical all-atom (AA) Molecular Dynamics (MD) simulations of OR in its apo-form. We highlighted that the various degrees of bendability of the α-helices present important consequences on the plasticity of the binding site. Hence, this latter adopts a wide diversity of shape and volume, explaining why OR interacts with very diverse ligands. Then, one introduces a new strategy for parameterizing purely mechanical but precise coarse-grained (CG) elastic network models (ENMs). The CG ENMs reproduced in a high accurate way the flexibility properties of OR versus the AA simulations. At last, one uses network modularization to design multi-grained (MG) models. They represent a novel type of low resolution models, different in nature versus CG models as being true multi-resolution models, i . e ., each MG grouping a different number of residues. The three parts constitute hierarchical and multiscale approach for tackling the flexibility of OR.
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Coupling all-atom molecular dynamics simulations of ions in water with Brownian dynamics.
Erban, Radek
2016-02-01
Molecular dynamics (MD) simulations of ions (K + , Na + , Ca 2+ and Cl - ) in aqueous solutions are investigated. Water is described using the SPC/E model. A stochastic coarse-grained description for ion behaviour is presented and parametrized using MD simulations. It is given as a system of coupled stochastic and ordinary differential equations, describing the ion position, velocity and acceleration. The stochastic coarse-grained model provides an intermediate description between all-atom MD simulations and Brownian dynamics (BD) models. It is used to develop a multiscale method which uses all-atom MD simulations in parts of the computational domain and (less detailed) BD simulations in the remainder of the domain.
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A multiscale strength model for tantalum over an extended range of strain rates
NASA Astrophysics Data System (ADS)
Barton, N. R.; Rhee, M.
2013-09-01
A strength model for tantalum is developed and exercised across a range of conditions relevant to various types of experimental observations. The model is based on previous multiscale modeling work combined with experimental observations. As such, the model's parameterization includes a hybrid of quantities that arise directly from predictive sub-scale physics models and quantities that are adjusted to align the model with experimental observations. Given current computing and experimental limitations, the response regions for sub-scale physics simulations and detailed experimental observations have been largely disjoint. In formulating the new model and presenting results here, attention is paid to integrated experimental observations that probe strength response at the elevated strain rates where a previous version of the model has generally been successful in predicting experimental data [Barton et al., J. Appl. Phys. 109(7), 073501 (2011)].
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Micromechanical models of delamination in aluminum-lithium alloys
NASA Astrophysics Data System (ADS)
Messner, Mark Christian
Aluminum lithium (Al-Li) alloys are lighter, stiffer, and tougher than conventional aerospace aluminum alloys. Replacing conventional aluminums with Al-Li could substantially decrease the weight and cost of aerospace structures. However, Al-Li alloys often fracture intergranularly via a mechanism called delamination cracking. While secondary delamination cracks can improve the effective toughness of a component, no current model accurately predicts the initiation and growth of intergranular cracks. Since simulations cannot incorporate delamination into a structural model, designers cannot quantify the effect of delamination cracking on a particular component. This uncertainty limits the application of Al-Li alloys. Previous experiments identify microstructural features linked to delamination. Fractography of failed surfaces indicates plastic void growth triggers intergranular failure. Furthermore, certain types of soft/stiff grain boundaries tend to localize void growth and nucleate delamination cracks. This dissertation develops a mechanism for the initiation of delamination on the microscale that accounts for these experimental observations. Microscale simulations of grain boundaries near a long primary crack explore the delamination mechanism on the mesoscale. In these simulations, a physically-based crystal plasticity (CP) model represents the constitutive response of individual grains. This CP model incorporates plastic voriticity correction terms into a standard objective stress rate integration, to accurately account for the kinematics of lattice deformation. The CP model implements slip system hardening with a modular approach to facilitate quick testing and calibration of different theories of hardening. The microscale models reveal soft/stiff grain boundaries develop elevated mean stress and plastic strain as a consequence of the mechanics of the interface. These elevated stresses and strain drive plastic void growth. The results indicate plastic void growth localizes to the grain boundaries even without the presence of material defects, such as precipitate free zones. Microscale simulations also explain the strong T-stress effect often observed in experimental fracture tests on Al-Li alloys. Finally, this dissertation develops a multiscale model of intergranular damage that incorporates the results of the microscale CP simulations. The multiscale model represents the mechanics of microscale deformation near grain boundaries with a simplified compatibility/equilibrium method. The intergranular stresses and strains from the simplified interface model drive a microscale damage index based on the physics of plastic void growth. Finally, a mesh-size independent scheme homogenizes damage on many grain boundaries into a macroscale damage index and projects the damage index to fail a plane of a macroscale structural model. The multiscale damage model, applied to 2195 Al-Li, successfully predicts delamination crack growth in a variety of standard experimental test configurations. The model correctly represents the microscale physics of delamination initiation and growth; after calibration to experimental data it can reliably predict the growth of delamination cracks in a component with any material configuration and loading. Therefore, the multiscale damage model forms the basis of a simulation method that allows designers to predict the development and net effect of delamination cracking in a structural model -- facilitating the application of lightweight Al-Li alloys in high-performance aerospace structures.
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This paper presents an analysis of the CMAQ v4.5 model performance for particulate matter and its chemical components for the simulated year 2001. This is part two is two part series of papers that examines the model performance of CMAQ v4.5.
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The CMAQ modeling system has been used to simulate the air quality for North America and Europe for the entire year of 2006 as part of the Air Quality Model Evaluation International Initiative (AQMEII) and the operational model performance of O3, fine particulate matte...
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A Physiologically Based, Multi-Scale Model of Skeletal Muscle Structure and Function
Röhrle, O.; Davidson, J. B.; Pullan, A. J.
2012-01-01
Models of skeletal muscle can be classified as phenomenological or biophysical. Phenomenological models predict the muscle’s response to a specified input based on experimental measurements. Prominent phenomenological models are the Hill-type muscle models, which have been incorporated into rigid-body modeling frameworks, and three-dimensional continuum-mechanical models. Biophysically based models attempt to predict the muscle’s response as emerging from the underlying physiology of the system. In this contribution, the conventional biophysically based modeling methodology is extended to include several structural and functional characteristics of skeletal muscle. The result is a physiologically based, multi-scale skeletal muscle finite element model that is capable of representing detailed, geometrical descriptions of skeletal muscle fibers and their grouping. Together with a well-established model of motor-unit recruitment, the electro-physiological behavior of single muscle fibers within motor units is computed and linked to a continuum-mechanical constitutive law. The bridging between the cellular level and the organ level has been achieved via a multi-scale constitutive law and homogenization. The effect of homogenization has been investigated by varying the number of embedded skeletal muscle fibers and/or motor units and computing the resulting exerted muscle forces while applying the same excitatory input. All simulations were conducted using an anatomically realistic finite element model of the tibialis anterior muscle. Given the fact that the underlying electro-physiological cellular muscle model is capable of modeling metabolic fatigue effects such as potassium accumulation in the T-tubular space and inorganic phosphate build-up, the proposed framework provides a novel simulation-based way to investigate muscle behavior ranging from motor-unit recruitment to force generation and fatigue. PMID:22993509
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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.
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Multiscale Cloud System Modeling
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Moncrieff, Mitchell W.
2009-01-01
The central theme of this paper is to describe how cloud system resolving models (CRMs) of grid spacing approximately 1 km have been applied to various important problems in atmospheric science across a wide range of spatial and temporal scales and how these applications relate to other modeling approaches. A long-standing problem concerns the representation of organized precipitating convective cloud systems in weather and climate models. Since CRMs resolve the mesoscale to large scales of motion (i.e., 10 km to global) they explicitly address the cloud system problem. By explicitly representing organized convection, CRMs bypass restrictive assumptions associated with convective parameterization such as the scale gap between cumulus and large-scale motion. Dynamical models provide insight into the physical mechanisms involved with scale interaction and convective organization. Multiscale CRMs simulate convective cloud systems in computational domains up to global and have been applied in place of contemporary convective parameterizations in global models. Multiscale CRMs pose a new challenge for model validation, which is met in an integrated approach involving CRMs, operational prediction systems, observational measurements, and dynamical models in a new international project: the Year of Tropical Convection, which has an emphasis on organized tropical convection and its global effects.
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Jung, Joon -Hee
2016-10-11
Here, the global atmospheric models based on the Multi-scale Modeling Framework (MMF) are able to explicitly resolve subgrid-scale processes by using embedded 2-D Cloud-Resolving Models (CRMs). Up to now, however, those models do not include the orographic effects on the CRM grid scale. This study shows that the effects of CRM grid-scale orography can be simulated reasonably well by the Quasi-3-D MMF (Q3D MMF), which has been developed as a second-generation MMF. In the Q3D framework, the surface topography can be included in the CRM component by using a block representation of the mountains, so that no smoothing of themore » topographic height is necessary. To demonstrate the performance of such a model, the orographic effects over a steep mountain are simulated in an idealized experimental setup with each of the Q3D MMF and the full 3-D CRM. The latter is used as a benchmark. Comparison of the results shows that the Q3D MMF is able to reproduce the horizontal distribution of orographic precipitation and the flow changes around mountains as simulated by the 3-D CRM, even though the embedded CRMs of the Q3D MMF recognize only some aspects of the complex 3-D topography. It is also shown that the use of 3-D CRMs in the Q3D framework, rather than 2-D CRMs, has positive impacts on the simulation of wind fields but does not substantially change the simulated precipitation.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Jung, Joon -Hee
Here, the global atmospheric models based on the Multi-scale Modeling Framework (MMF) are able to explicitly resolve subgrid-scale processes by using embedded 2-D Cloud-Resolving Models (CRMs). Up to now, however, those models do not include the orographic effects on the CRM grid scale. This study shows that the effects of CRM grid-scale orography can be simulated reasonably well by the Quasi-3-D MMF (Q3D MMF), which has been developed as a second-generation MMF. In the Q3D framework, the surface topography can be included in the CRM component by using a block representation of the mountains, so that no smoothing of themore » topographic height is necessary. To demonstrate the performance of such a model, the orographic effects over a steep mountain are simulated in an idealized experimental setup with each of the Q3D MMF and the full 3-D CRM. The latter is used as a benchmark. Comparison of the results shows that the Q3D MMF is able to reproduce the horizontal distribution of orographic precipitation and the flow changes around mountains as simulated by the 3-D CRM, even though the embedded CRMs of the Q3D MMF recognize only some aspects of the complex 3-D topography. It is also shown that the use of 3-D CRMs in the Q3D framework, rather than 2-D CRMs, has positive impacts on the simulation of wind fields but does not substantially change the simulated precipitation.« less
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NASA Astrophysics Data System (ADS)
Jung, Joon-Hee
2016-12-01
The global atmospheric models based on the Multi-scale Modeling Framework (MMF) are able to explicitly resolve subgrid-scale processes by using embedded 2-D Cloud-Resolving Models (CRMs). Up to now, however, those models do not include the orographic effects on the CRM grid scale. This study shows that the effects of CRM grid-scale orography can be simulated reasonably well by the Quasi-3-D MMF (Q3D MMF), which has been developed as a second-generation MMF. In the Q3D framework, the surface topography can be included in the CRM component by using a block representation of the mountains, so that no smoothing of the topographic height is necessary. To demonstrate the performance of such a model, the orographic effects over a steep mountain are simulated in an idealized experimental setup with each of the Q3D MMF and the full 3-D CRM. The latter is used as a benchmark. Comparison of the results shows that the Q3D MMF is able to reproduce the horizontal distribution of orographic precipitation and the flow changes around mountains as simulated by the 3-D CRM, even though the embedded CRMs of the Q3D MMF recognize only some aspects of the complex 3-D topography. It is also shown that the use of 3-D CRMs in the Q3D framework, rather than 2-D CRMs, has positive impacts on the simulation of wind fields but does not substantially change the simulated precipitation.
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On Efficient Multigrid Methods for Materials Processing Flows with Small Particles
NASA Technical Reports Server (NTRS)
Thomas, James (Technical Monitor); Diskin, Boris; Harik, VasylMichael
2004-01-01
Multiscale modeling of materials requires simulations of multiple levels of structural hierarchy. The computational efficiency of numerical methods becomes a critical factor for simulating large physical systems with highly desperate length scales. Multigrid methods are known for their superior efficiency in representing/resolving different levels of physical details. The efficiency is achieved by employing interactively different discretizations on different scales (grids). To assist optimization of manufacturing conditions for materials processing with numerous particles (e.g., dispersion of particles, controlling flow viscosity and clusters), a new multigrid algorithm has been developed for a case of multiscale modeling of flows with small particles that have various length scales. The optimal efficiency of the algorithm is crucial for accurate predictions of the effect of processing conditions (e.g., pressure and velocity gradients) on the local flow fields that control the formation of various microstructures or clusters.
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Multi-scale computation methods: Their applications in lithium-ion battery research and development
NASA Astrophysics Data System (ADS)
Siqi, Shi; Jian, Gao; Yue, Liu; Yan, Zhao; Qu, Wu; Wangwei, Ju; Chuying, Ouyang; Ruijuan, Xiao
2016-01-01
Based upon advances in theoretical algorithms, modeling and simulations, and computer technologies, the rational design of materials, cells, devices, and packs in the field of lithium-ion batteries is being realized incrementally and will at some point trigger a paradigm revolution by combining calculations and experiments linked by a big shared database, enabling accelerated development of the whole industrial chain. Theory and multi-scale modeling and simulation, as supplements to experimental efforts, can help greatly to close some of the current experimental and technological gaps, as well as predict path-independent properties and help to fundamentally understand path-independent performance in multiple spatial and temporal scales. Project supported by the National Natural Science Foundation of China (Grant Nos. 51372228 and 11234013), the National High Technology Research and Development Program of China (Grant No. 2015AA034201), and Shanghai Pujiang Program, China (Grant No. 14PJ1403900).
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Equation-free multiscale computation: algorithms and applications.
Kevrekidis, Ioannis G; Samaey, Giovanni
2009-01-01
In traditional physicochemical modeling, one derives evolution equations at the (macroscopic, coarse) scale of interest; these are used to perform a variety of tasks (simulation, bifurcation analysis, optimization) using an arsenal of analytical and numerical techniques. For many complex systems, however, although one observes evolution at a macroscopic scale of interest, accurate models are only given at a more detailed (fine-scale, microscopic) level of description (e.g., lattice Boltzmann, kinetic Monte Carlo, molecular dynamics). Here, we review a framework for computer-aided multiscale analysis, which enables macroscopic computational tasks (over extended spatiotemporal scales) using only appropriately initialized microscopic simulation on short time and length scales. The methodology bypasses the derivation of macroscopic evolution equations when these equations conceptually exist but are not available in closed form-hence the term equation-free. We selectively discuss basic algorithms and underlying principles and illustrate the approach through representative applications. We also discuss potential difficulties and outline areas for future research.
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Sibole, Scott C.; Erdemir, Ahmet
2012-01-01
Cells of the musculoskeletal system are known to respond to mechanical loading and chondrocytes within the cartilage are not an exception. However, understanding how joint level loads relate to cell level deformations, e.g. in the cartilage, is not a straightforward task. In this study, a multi-scale analysis pipeline was implemented to post-process the results of a macro-scale finite element (FE) tibiofemoral joint model to provide joint mechanics based displacement boundary conditions to micro-scale cellular FE models of the cartilage, for the purpose of characterizing chondrocyte deformations in relation to tibiofemoral joint loading. It was possible to identify the load distribution within the knee among its tissue structures and ultimately within the cartilage among its extracellular matrix, pericellular environment and resident chondrocytes. Various cellular deformation metrics (aspect ratio change, volumetric strain, cellular effective strain and maximum shear strain) were calculated. To illustrate further utility of this multi-scale modeling pipeline, two micro-scale cartilage constructs were considered: an idealized single cell at the centroid of a 100×100×100 μm block commonly used in past research studies, and an anatomically based (11 cell model of the same volume) representation of the middle zone of tibiofemoral cartilage. In both cases, chondrocytes experienced amplified deformations compared to those at the macro-scale, predicted by simulating one body weight compressive loading on the tibiofemoral joint. In the 11 cell case, all cells experienced less deformation than the single cell case, and also exhibited a larger variance in deformation compared to other cells residing in the same block. The coupling method proved to be highly scalable due to micro-scale model independence that allowed for exploitation of distributed memory computing architecture. The method’s generalized nature also allows for substitution of any macro-scale and/or micro-scale model providing application for other multi-scale continuum mechanics problems. PMID:22649535
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NASA Astrophysics Data System (ADS)
Hosenfeld, Fabian; Horst, Fabian; Iñíguez, Benjamín; Lime, François; Kloes, Alexander
2017-11-01
Source-to-drain (SD) tunneling decreases the device performance in MOSFETs falling below the 10 nm channel length. Modeling quantum mechanical effects including SD tunneling has gained more importance specially for compact model developers. The non-equilibrium Green's function (NEGF) has become a state-of-the-art method for nano-scaled device simulation in the past years. In the sense of a multi-scale simulation approach it is necessary to bridge the gap between compact models with their fast and efficient calculation of the device current, and numerical device models which consider quantum effects of nano-scaled devices. In this work, an NEGF based analytical model for nano-scaled double-gate (DG) MOSFETs is introduced. The model consists of a closed-form potential solution of a classical compact model and a 1D NEGF formalism for calculating the device current, taking into account quantum mechanical effects. The potential calculation omits the iterative coupling and allows the straightforward current calculation. The model is based on a ballistic NEGF approach whereby backscattering effects are considered as second order effect in a closed-form. The accuracy and scalability of the non-iterative DG MOSFET model is inspected in comparison with numerical NanoMOS TCAD data for various channel lengths. With the help of this model investigations on short-channel and temperature effects are performed.
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An updated and expanded Carbon Bond mechanism (CB05) has been incorporated into the Community Multiscale Air Quality modeling system to more accurately simulate wintertime, pristine, and high altitude situations. The CB05 mechanism has nearly twice the number of reactions compare...
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Presentation slides provide background on model evaluation techniques. Also included in the presentation is an operational evaluation of 2001 Community Multiscale Air Quality (CMAQ) annual simulation, and an evaluation of PM2.5 for the CMAQ air quality forecast (AQF) ...
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CONCENTRATIONS OF TOXIC AIR POLLUTANTS IN THE U.S. SIMULATED BY AN AIR QUALITY MODEL
As part of the US National Air Toxics Assessment, we have applied the Community Multiscale Air Quality Model, CMAQ, to study the concentrations of twenty gas-phase, toxic, hazardous air pollutants (HAPs) in the atmosphere over the continental United States. We modified the Carbo...
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Validation of Operational Multiscale Environment Model With Grid Adaptivity (OMEGA).
1995-12-01
Center for the period of the Chernobyl Nuclear Accident. The physics of the model is tested using National Weather Service Medium Range Forecast data by...Climatology Center for the first three days following the release at the Chernobyl Nuclear Plant. A user-defined source term was developed to simulate
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An air-quality forecasting (AQF) system based on the National Weather Service (NWS) National Centers for Environmental Prediction's (NCEP's) Eta model and the U.S. EPA's Community Multiscale Air Quality (CMAQ) Modeling System is used to simulate the distributions of tropospheric ...
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Atmospheric deposition of nitrogen contributes to eutrophication of estuarine waters and acidification of lakes and streams. Ammonia also contributes to fine particle formation in the atmosphere and associated health effects. Model projections suggest that NH3 depositi...
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Modeling crop residue burning experiments and assessing the fire impacts on air quality
Prescribed burning is a common land management practice that results in ambient emissions of a variety of primary and secondary pollutants with negative health impacts. The community Multiscale Air Quality (CMAQ) model is used to conduct 2 km grid resolution simulations of prescr...
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On Regional Modeling to Support Air Quality Policies (book chapter)
We examine the use of the Community Multiscale Air Quality (CMAQ) model in simulating the changes in the extreme values of air quality that are of interest to the regulatory agencies. Year-to-year changes in ozone air quality are attributable to variations in the prevailing meteo...
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Multiscale Modeling of Primary Cilium Deformations Under Local Forces and Shear Flows
NASA Astrophysics Data System (ADS)
Peng, Zhangli; Feng, Zhe; Resnick, Andrew; Young, Yuan-Nan
2017-11-01
We study the detailed deformations of a primary cilium under local forces and shear flows by developing a multiscale model based on the state-of-the-art understanding of its molecular structure. Most eukaryotic cells are ciliated with primary cilia. Primary cilia play important roles in chemosensation, thermosensation, and mechanosensation, but the detailed mechanism for mechanosensation is not well understood. We apply the dissipative particle dynamics (DPD) to model an entire well with a primary cilium and consider its different components, including the basal body, microtubule doublets, actin cortex, and lipid bilayer. We calibrate the mechanical properties of individual components and their interactions from experimental measurements and molecular dynamics simulations. We validate the simulations by comparing the deformation profile of the cilium and the rotation of the basal body with optical trapping experiments. After validations, we investigate the deformation of the primary cilium under shear flows. Furthermore, we calculate the membrane tensions and cytoskeleton stresses, and use them to predict the activation of mechanosensitive channels.
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Inferring multi-scale neural mechanisms with brain network modelling
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
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MULTISCALE ADAPTIVE SMOOTHING MODELS FOR THE HEMODYNAMIC RESPONSE FUNCTION IN FMRI*
Wang, Jiaping; Zhu, Hongtu; Fan, Jianqing; Giovanello, Kelly; Lin, Weili
2012-01-01
In the event-related functional magnetic resonance imaging (fMRI) data analysis, there is an extensive interest in accurately and robustly estimating the hemodynamic response function (HRF) and its associated statistics (e.g., the magnitude and duration of the activation). Most methods to date are developed in the time domain and they have utilized almost exclusively the temporal information of fMRI data without accounting for the spatial information. The aim of this paper is to develop a multiscale adaptive smoothing model (MASM) in the frequency domain by integrating the spatial and temporal information to adaptively and accurately estimate HRFs pertaining to each stimulus sequence across all voxels in a three-dimensional (3D) volume. We use two sets of simulation studies and a real data set to examine the finite sample performance of MASM in estimating HRFs. Our real and simulated data analyses confirm that MASM outperforms several other state-of-art methods, such as the smooth finite impulse response (sFIR) model. PMID:24533041
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Fast Proton Titration Scheme for Multiscale Modeling of Protein Solutions.
Teixeira, Andre Azevedo Reis; Lund, Mikael; da Silva, Fernando Luís Barroso
2010-10-12
Proton exchange between titratable amino acid residues and the surrounding solution gives rise to exciting electric processes in proteins. We present a proton titration scheme for studying acid-base equilibria in Metropolis Monte Carlo simulations where salt is treated at the Debye-Hückel level. The method, rooted in the Kirkwood model of impenetrable spheres, is applied on the three milk proteins α-lactalbumin, β-lactoglobulin, and lactoferrin, for which we investigate the net-charge, molecular dipole moment, and charge capacitance. Over a wide range of pH and salt conditions, excellent agreement is found with more elaborate simulations where salt is explicitly included. The implicit salt scheme is orders of magnitude faster than the explicit analog and allows for transparent interpretation of physical mechanisms. It is shown how the method can be expanded to multiscale modeling of aqueous salt solutions of many biomolecules with nonstatic charge distributions. Important examples are protein-protein aggregation, protein-polyelectrolyte complexation, and protein-membrane association.
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NASA Technical Reports Server (NTRS)
Bednarcyk, Brett A.; Arnold, Steven M.
2006-01-01
A framework is presented that enables coupled multiscale analysis of composite structures. The recently developed, free, Finite Element Analysis - Micromechanics Analysis Code (FEAMAC) software couples the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) with ABAQUS to perform micromechanics based FEA such that the nonlinear composite material response at each integration point is modeled at each increment by MAC/GMC. As a result, the stochastic nature of fiber breakage in composites can be simulated through incorporation of an appropriate damage and failure model that operates within MAC/GMC on the level of the fiber. Results are presented for the progressive failure analysis of a titanium matrix composite tensile specimen that illustrate the power and utility of the framework and address the techniques needed to model the statistical nature of the problem properly. In particular, it is shown that incorporating fiber strength randomness on multiple scales improves the quality of the simulation by enabling failure at locations other than those associated with structural level stress risers.
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Multiscale Modeling of UHTC: Thermal Conductivity
NASA Technical Reports Server (NTRS)
Lawson, John W.; Murry, Daw; Squire, Thomas; Bauschlicher, Charles W.
2012-01-01
We are developing a multiscale framework in computational modeling for the ultra high temperature ceramics (UHTC) ZrB2 and HfB2. These materials are characterized by high melting point, good strength, and reasonable oxidation resistance. They are candidate materials for a number of applications in extreme environments including sharp leading edges of hypersonic aircraft. In particular, we used a combination of ab initio methods, atomistic simulations and continuum computations to obtain insights into fundamental properties of these materials. Ab initio methods were used to compute basic structural, mechanical and thermal properties. From these results, a database was constructed to fit a Tersoff style interatomic potential suitable for atomistic simulations. These potentials were used to evaluate the lattice thermal conductivity of single crystals and the thermal resistance of simple grain boundaries. Finite element method (FEM) computations using atomistic results as inputs were performed with meshes constructed on SEM images thereby modeling the realistic microstructure. These continuum computations showed the reduction in thermal conductivity due to the grain boundary network.
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NASA Technical Reports Server (NTRS)
Bednarcyk, Brett A.; Arnold, Steven M.
2007-01-01
A framework is presented that enables coupled multiscale analysis of composite structures. The recently developed, free, Finite Element Analysis-Micromechanics Analysis Code (FEAMAC) software couples the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) with ABAQUS to perform micromechanics based FEA such that the nonlinear composite material response at each integration point is modeled at each increment by MAC/GMC. As a result, the stochastic nature of fiber breakage in composites can be simulated through incorporation of an appropriate damage and failure model that operates within MAC/GMC on the level of the fiber. Results are presented for the progressive failure analysis of a titanium matrix composite tensile specimen that illustrate the power and utility of the framework and address the techniques needed to model the statistical nature of the problem properly. In particular, it is shown that incorporating fiber strength randomness on multiple scales improves the quality of the simulation by enabling failure at locations other than those associated with structural level stress risers.
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Evaluation of the Community Multi-scale Air Quality (CMAQ) ...
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
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Three-dimensional multi-scale model of deformable platelets adhesion to vessel wall in blood flow
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
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Na; Zhang, Peng; Kang, Wei
Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters aremore » systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately.« less
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2015-01-01
Background Multiscale approaches for integrating submodels of various levels of biological organization into a single model became the major tool of systems biology. In this paper, we have constructed and simulated a set of multiscale models of spatially distributed microbial communities and study an influence of unevenly distributed environmental factors on the genetic diversity and evolution of the community members. Results Haploid Evolutionary Constructor software http://evol-constructor.bionet.nsc.ru/ was expanded by adding the tool for the spatial modeling of a microbial community (1D, 2D and 3D versions). A set of the models of spatially distributed communities was built to demonstrate that the spatial distribution of cells affects both intensity of selection and evolution rate. Conclusion In spatially heterogeneous communities, the change in the direction of the environmental flow might be reflected in local irregular population dynamics, while the genetic structure of populations (frequencies of the alleles) remains stable. Furthermore, in spatially heterogeneous communities, the chemotaxis might dramatically affect the evolution of community members. PMID:25708911
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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.
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Multiscale Issues and Simulation-Based Science and Engineering for Materials-by-Design
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
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Computational Materials: Modeling and Simulation of Nanostructured Materials and Systems
NASA Technical Reports Server (NTRS)
Gates, Thomas S.; Hinkley, Jeffrey A.
2003-01-01
The paper provides details on the structure and implementation of the Computational Materials program at the NASA Langley Research Center. Examples are given that illustrate the suggested approaches to predicting the behavior and influencing the design of nanostructured materials such as high-performance polymers, composites, and nanotube-reinforced polymers. Primary simulation and measurement methods applicable to multi-scale modeling are outlined. Key challenges including verification and validation of models are highlighted and discussed within the context of NASA's broad mission objectives.
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NASA Astrophysics Data System (ADS)
Horstemeyer, M. F.
This review of multiscale modeling covers a brief history of various multiscale methodologies related to solid materials and the associated experimental influences, the various influence of multiscale modeling on different disciplines, and some examples of multiscale modeling in the design of structural components. Although computational multiscale modeling methodologies have been developed in the late twentieth century, the fundamental notions of multiscale modeling have been around since da Vinci studied different sizes of ropes. The recent rapid growth in multiscale modeling is the result of the confluence of parallel computing power, experimental capabilities to characterize structure-property relations down to the atomic level, and theories that admit multiple length scales. The ubiquitous research that focus on multiscale modeling has broached different disciplines (solid mechanics, fluid mechanics, materials science, physics, mathematics, biological, and chemistry), different regions of the world (most continents), and different length scales (from atoms to autos).
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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;
2002-01-01
A multidisciplinary, collaborative simulation has been performed on a Grid of geographically distributed PC clusters. The multiscale simulation approach seamlessly combines i) atomistic simulation backed on the molecular dynamics (MD) method and ii) quantum mechanical (QM) calculation based on the density functional theory (DFT), so that accurate but less scalable computations are performed only where they are needed. The multiscale MD/QM simulation code has been Grid-enabled using i) a modular, additive hybridization scheme, ii) multiple QM clustering, and iii) computation/communication overlapping. The Gridified MD/QM simulation code has been used to study environmental effects of water molecules on fracture in silicon. A preliminary run of the code has achieved a parallel efficiency of 94% on 25 PCs distributed over 3 PC clusters in the US and Japan, and a larger test involving 154 processors on 5 distributed PC clusters is in progress.
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2013-01-01
Background The end-systolic pressure-volume relationship is often considered as a load-independent property of the heart and, for this reason, is widely used as an index of ventricular contractility. However, many criticisms have been expressed against this index and the underlying time-varying elastance theory: first, it does not consider the phenomena underlying contraction and second, the end-systolic pressure volume relationship has been experimentally shown to be load-dependent. Methods In place of the time-varying elastance theory, a microscopic model of sarcomere contraction is used to infer the pressure generated by the contraction of the left ventricle, considered as a spherical assembling of sarcomere units. The left ventricle model is inserted into a closed-loop model of the cardiovascular system. Finally, parameters of the modified cardiovascular system model are identified to reproduce the hemodynamics of a normal dog. Results Experiments that have proven the limitations of the time-varying elastance theory are reproduced with our model: (1) preload reductions, (2) afterload increases, (3) the same experiments with increased ventricular contractility, (4) isovolumic contractions and (5) flow-clamps. All experiments simulated with the model generate different end-systolic pressure-volume relationships, showing that this relationship is actually load-dependent. Furthermore, we show that the results of our simulations are in good agreement with experiments. Conclusions We implemented a multi-scale model of the cardiovascular system, in which ventricular contraction is described by a detailed sarcomere model. Using this model, we successfully reproduced a number of experiments that have shown the failing points of the time-varying elastance theory. In particular, the developed multi-scale model of the cardiovascular system can capture the load-dependence of the end-systolic pressure-volume relationship. PMID:23363818
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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
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2016-01-01
An important challenge in the simulation of biomolecular systems is a quantitative description of the protonation and deprotonation process of amino acid residues. Despite the seeming simplicity of adding or removing a positively charged hydrogen nucleus, simulating the actual protonation/deprotonation process is inherently difficult. It requires both the explicit treatment of the excess proton, including its charge defect delocalization and Grotthuss shuttling through inhomogeneous moieties (water and amino residues), and extensive sampling of coupled condensed phase motions. In a recent paper (J. Chem. Theory Comput.2014, 10, 2729−273725061442), a multiscale approach was developed to map high-level quantum mechanics/molecular mechanics (QM/MM) data into a multiscale reactive molecular dynamics (MS-RMD) model in order to describe amino acid deprotonation in bulk water. In this article, we extend the fitting approach (called FitRMD) to create MS-RMD models for ionizable amino acids within proteins. The resulting models are shown to faithfully reproduce the free energy profiles of the reference QM/MM Hamiltonian for PT inside an example protein, the ClC-ec1 H+/Cl– antiporter. Moreover, we show that the resulting MS-RMD models are computationally efficient enough to then characterize more complex 2-dimensional free energy surfaces due to slow degrees of freedom such as water hydration of internal protein cavities that can be inherently coupled to the excess proton charge translocation. The FitRMD method is thus shown to be an effective way to map ab initio level accuracy into a much more computationally efficient reactive MD method in order to explicitly simulate and quantitatively describe amino acid protonation/deprotonation in proteins. PMID:26734942
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Lee, Sangyun; Liang, Ruibin; Voth, Gregory A; Swanson, Jessica M J
2016-02-09
An important challenge in the simulation of biomolecular systems is a quantitative description of the protonation and deprotonation process of amino acid residues. Despite the seeming simplicity of adding or removing a positively charged hydrogen nucleus, simulating the actual protonation/deprotonation process is inherently difficult. It requires both the explicit treatment of the excess proton, including its charge defect delocalization and Grotthuss shuttling through inhomogeneous moieties (water and amino residues), and extensive sampling of coupled condensed phase motions. In a recent paper (J. Chem. Theory Comput. 2014, 10, 2729-2737), a multiscale approach was developed to map high-level quantum mechanics/molecular mechanics (QM/MM) data into a multiscale reactive molecular dynamics (MS-RMD) model in order to describe amino acid deprotonation in bulk water. In this article, we extend the fitting approach (called FitRMD) to create MS-RMD models for ionizable amino acids within proteins. The resulting models are shown to faithfully reproduce the free energy profiles of the reference QM/MM Hamiltonian for PT inside an example protein, the ClC-ec1 H(+)/Cl(-) antiporter. Moreover, we show that the resulting MS-RMD models are computationally efficient enough to then characterize more complex 2-dimensional free energy surfaces due to slow degrees of freedom such as water hydration of internal protein cavities that can be inherently coupled to the excess proton charge translocation. The FitRMD method is thus shown to be an effective way to map ab initio level accuracy into a much more computationally efficient reactive MD method in order to explicitly simulate and quantitatively describe amino acid protonation/deprotonation in proteins.
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NASA Astrophysics Data System (ADS)
Latypov, Marat I.; Kalidindi, Surya R.
2017-10-01
There is a critical need for the development and verification of practically useful multiscale modeling strategies for simulating the mechanical response of multiphase metallic materials with heterogeneous microstructures. In this contribution, we present data-driven reduced order models for effective yield strength and strain partitioning in such microstructures. These models are built employing the recently developed framework of Materials Knowledge Systems that employ 2-point spatial correlations (or 2-point statistics) for the quantification of the heterostructures and principal component analyses for their low-dimensional representation. The models are calibrated to a large collection of finite element (FE) results obtained for a diverse range of microstructures with various sizes, shapes, and volume fractions of the phases. The performance of the models is evaluated by comparing the predictions of yield strength and strain partitioning in two-phase materials with the corresponding predictions from a classical self-consistent model as well as results of full-field FE simulations. The reduced-order models developed in this work show an excellent combination of accuracy and computational efficiency, and therefore present an important advance towards computationally efficient microstructure-sensitive multiscale modeling frameworks.
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NASA Astrophysics Data System (ADS)
Huang, M.; Bowman, K. W.; Carmichael, G. R.; Lee, M.; Park, R.; Henze, D. K.; Chai, T.; Flemming, J.; Lin, M.; Weinheimer, A. J.; Wisthaler, A.; Jaffe, D. A.
2014-12-01
Near-surface ozone in the western US can be sensitive to transported background pollutants from the free troposphere over the eastern Pacific, as well as various local emissions sources. Accurately estimating ozone source contributions in this region has strong policy-relevant significance as the air quality standards tend to go down. Here we improve modeled contributions from local and non-local sources to western US ozone base on the HTAP2 (Task Force on Hemispheric Transport of Air Pollution) multi-model experiment, along with multi-scale chemical data assimilation. We simulate western US air quality using the STEM regional model on a 12 km horizontal resolution grid, during the NASA ARCTAS field campaign period in June 2008. STEM simulations use time-varying boundary conditions downscaled from global GEOS-Chem model simulations. Standard GEOS-Chem simulation overall underpredicted ozone at 1-5 km in the eastern Pacific, resulting in underestimated contributions from the transported background pollutants to surface ozone inland. These negative biases can be reduced by using the output from several global models that support the HTAP2 experiment, which all ran with the HTAP2 harmonized emission inventory and also calculated the contributions from east Asian anthropogenic emissions. We demonstrate that the biases in GEOS-Chem boundary conditions can be more efficiently reduced via assimilating satellite ozone profiles from the Tropospheric Emission Spectrometer (TES) instrument using the three dimensional variational (3D-Var) approach. Base upon these TES-constrained GEOS-Chem boundary conditions, we then update regional nitrogen dioxide and isoprene emissions in STEM through the four dimensional variational (4D-Var) assimilation of the Ozone Monitoring Instrument (OMI) nitrogen dioxide columns and the NASA DC-8 aircraft isoprene measurements. The 4D-Var assimilation spatially redistributed the emissions of nitrogen oxides and isoprene from various US sources, and in the meantime updated the modeled ozone and its US source contributions. Compared with available independent measurements (e.g., ozone observed on the DC-8 aircraft, and at EPA and Mt. Bachelor monitoring stations) during this period, modeled ozone fields after the multi-scale assimilation show overall improvement.
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NASA Astrophysics Data System (ADS)
Liu, C.; Yang, X.; Bailey, V. L.; Bond-Lamberty, B. P.; Hinkle, C.
2013-12-01
Mathematical representations of hydrological and biogeochemical processes in soil, plant, aquatic, and atmospheric systems vary with scale. Process-rich models are typically used to describe hydrological and biogeochemical processes at the pore and small scales, while empirical, correlation approaches are often used at the watershed and regional scales. A major challenge for multi-scale modeling is that water flow, biogeochemical processes, and reactive transport are described using different physical laws and/or expressions at the different scales. For example, the flow is governed by the Navier-Stokes equations at the pore-scale in soils, by the Darcy law in soil columns and aquifer, and by the Navier-Stokes equations again in open water bodies (ponds, lake, river) and atmosphere surface layer. This research explores whether the physical laws at the different scales and in different physical domains can be unified to form a unified multi-scale model (UMSM) to systematically investigate the cross-scale, cross-domain behavior of fundamental processes at different scales. This presentation will discuss our research on the concept, mathematical equations, and numerical execution of the UMSM. Three-dimensional, multi-scale hydrological processes at the Disney Wilderness Preservation (DWP) site, Florida will be used as an example for demonstrating the application of the UMSM. In this research, the UMSM was used to simulate hydrological processes in rooting zones at the pore and small scales including water migration in soils under saturated and unsaturated conditions, root-induced hydrological redistribution, and role of rooting zone biogeochemical properties (e.g., root exudates and microbial mucilage) on water storage and wetting/draining. The small scale simulation results were used to estimate effective water retention properties in soil columns that were superimposed on the bulk soil water retention properties at the DWP site. The UMSM parameterized from smaller scale simulations were then used to simulate coupled flow and moisture migration in soils in saturated and unsaturated zones, surface and groundwater exchange, and surface water flow in streams and lakes at the DWP site under dynamic precipitation conditions. Laboratory measurements of soil hydrological and biogeochemical properties are used to parameterize the UMSM at the small scales, and field measurements are used to evaluate the UMSM.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Seethala, C.; Pandithurai, G.; Fast, Jerome D.
We utilized WRF-Chem multi-scale model to simulate the regional distribution of aerosols, optical properties and its effect on radiation over India for a winter month. The model is evaluated using measurements obtained from upper-air soundings, AERONET sun photometers, various satellite instruments, and pyranometers operated by the Indian Meteorological Department. The simulated downward shortwave flux was overestimated when the effect of aerosols on radiation and clouds was neglected. Downward shortwave radiation from a simulation that included aerosol-radiation interaction processes was 5 to 25 Wm{sup -2} closer to the observations, while a simulation that included aerosol-cloud interaction processes were another 1 tomore » 20 Wm{sup -2} closer to the observations. For the few observations available, the model usually underestimated particulate concentration. This is likely due to turbulent mixing, transport errors and the lack of secondary organic aerosol treatment in the model. The model efficiently captured the broad regional hotspots such as high aerosol optical depth over Indo-Gangetic basin as well as the northwestern and southern part of India. The regional distribution of aerosol optical depth compares well with AVHRR aerosol optical depth and the TOMS aerosol index. The magnitude and wavelength-dependence of simulated aerosol optical depth was also similar to the AERONET observations across India. Differences in surface shortwave radiation between simulations that included and neglected aerosol-radiation interactions were as high as -25 Wm{sup -2}, while differences in surface shortwave radiation between simulations that included and neglect aerosol-radiation-cloud interactions were as high as -30 Wm{sup -2}. The spatial variations of these differences were also compared with AVHRR observation. This study suggests that the model is able to qualitatively simulate the impact of aerosols on radiation over India; however, additional measurements of particulate mass and composition are needed to fully evaluate whether the aerosol precursor emissions are adequate when simulating radiative forcing in the region.« less
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Understanding Prairie Fen Hydrology - a Hierarchical Multi-Scale Groundwater Modeling Approach
NASA Astrophysics Data System (ADS)
Sampath, P.; Liao, H.; Abbas, H.; Ma, L.; Li, S.
2012-12-01
Prairie fens provide critical habitat to more than 50 rare species and significantly contribute to the biodiversity of the upper Great Lakes region. The sustainability of these globally unique ecosystems, however, requires that they be fed by a steady supply of pristine, calcareous groundwater. Understanding the hydrology that supports the existence of such fens is essential in preserving these valuable habitats. This research uses process-based multi-scale groundwater modeling for this purpose. Two fen-sites, MacCready Fen and Ives Road Fen, in Southern Michigan were systematically studied. A hierarchy of nested steady-state models was built for each fen-site to capture the system's dynamics at spatial scales ranging from the regional groundwater-shed to the local fens. The models utilize high-resolution Digital Elevation Models (DEM), National Hydrologic Datasets (NHD), a recently-assembled water-well database, and results from a state-wide groundwater mapping project to represent the complex hydro-geological and stress framework. The modeling system simulates both shallow glacial and deep bedrock aquifers as well as the interaction between surface water and groundwater. Aquifer heterogeneities were explicitly simulated with multi-scale transition probability geo-statistics. A two-way hydraulic head feedback mechanism was set up between the nested models, such that the parent models provided boundary conditions to the child models, and in turn the child models provided local information to the parent models. A hierarchical mass budget analysis was performed to estimate the seepage fluxes at the surface water/groundwater interfaces and to assess the relative importance of the processes at multiple scales that contribute water to the fens. The models were calibrated using observed base-flows at stream gauging stations and/or static water levels at wells. Three-dimensional particle tracking was used to predict the sources of water to the fens. We observed from the multi-scale simulations that the water system that supports the fens is a much larger, more connected, and more complex one than expected. The water in the fen can be traced back to a network of sources, including lakes and wetlands at different elevations, which are connected to a regional mound through a "cascade delivery mechanism". This "master recharge area" is the ultimate source of water not only to the fens in its vicinity, but also for many major rivers and aquifers. The implication of this finding is that prairie fens must be managed as part of a much larger, multi-scale groundwater system and we must consider protection of the shorter and long-term water sources. This will require a fundamental reassessment of our current approach to fen conservation, which is primarily based on protection of individual fens and their immediate surroundings. Clearly, in the future we must plan for conservation of the broad recharge areas and the multiple fen complexes they support.
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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.
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On multiscale moving contact line theory.
Li, Shaofan; Fan, Houfu
2015-07-08
In this paper, a multiscale moving contact line (MMCL) theory is presented and employed to simulate liquid droplet spreading and capillary motion. The proposed MMCL theory combines a coarse-grained adhesive contact model with a fluid interface membrane theory, so that it can couple molecular scale adhesive interaction and surface tension with hydrodynamics of microscale flow. By doing so, the intermolecular force, the van der Waals or double layer force, separates and levitates the liquid droplet from the supporting solid substrate, which avoids the shear stress singularity caused by the no-slip condition in conventional hydrodynamics theory of moving contact line. Thus, the MMCL allows the difference of the surface energies and surface stresses to drive droplet spreading naturally. To validate the proposed MMCL theory, we have employed it to simulate droplet spreading over various elastic substrates. The numerical simulation results obtained by using MMCL are in good agreement with the molecular dynamics results reported in the literature.
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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.
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Hierarchical coarse-graining strategy for protein-membrane systems to access mesoscopic scales
Ayton, Gary S.; Lyman, Edward
2014-01-01
An overall multiscale simulation strategy for large scale coarse-grain simulations of membrane protein systems is presented. The protein is modeled as a heterogeneous elastic network, while the lipids are modeled using the hybrid analytic-systematic (HAS) methodology, where in both cases atomistic level information obtained from molecular dynamics simulation is used to parameterize the model. A feature of this approach is that from the outset liposome length scales are employed in the simulation (i.e., on the order of ½ a million lipids plus protein). A route to develop highly coarse-grained models from molecular-scale information is proposed and results for N-BAR domain protein remodeling of a liposome are presented. PMID:20158037
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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.
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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.
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NASA Astrophysics Data System (ADS)
Abedi, S.; Mashhadian, M.; Noshadravan, A.
2015-12-01
Increasing the efficiency and sustainability in operation of hydrocarbon recovery from organic-rich shales requires a fundamental understanding of chemomechanical properties of organic-rich shales. This understanding is manifested in form of physics-bases predictive models capable of capturing highly heterogeneous and multi-scale structure of organic-rich shale materials. In this work we present a framework of experimental characterization, micromechanical modeling, and uncertainty quantification that spans from nanoscale to macroscale. Application of experiments such as coupled grid nano-indentation and energy dispersive x-ray spectroscopy and micromechanical modeling attributing the role of organic maturity to the texture of the material, allow us to identify unique clay mechanical properties among different samples that are independent of maturity of shale formations and total organic content. The results can then be used to inform the physically-based multiscale model for organic rich shales consisting of three levels that spans from the scale of elementary building blocks (e.g. clay minerals in clay-dominated formations) of organic rich shales to the scale of the macroscopic inorganic/organic hard/soft inclusion composite. Although this approach is powerful in capturing the effective properties of organic-rich shale in an average sense, it does not account for the uncertainty in compositional and mechanical model parameters. Thus, we take this model one step forward by systematically incorporating the main sources of uncertainty in modeling multiscale behavior of organic-rich shales. In particular we account for the uncertainty in main model parameters at different scales such as porosity, elastic properties and mineralogy mass percent. To that end, we use Maximum Entropy Principle and random matrix theory to construct probabilistic descriptions of model inputs based on available information. The Monte Carlo simulation is then carried out to propagate the uncertainty and consequently construct probabilistic descriptions of properties at multiple length-scales. The combination of experimental characterization and stochastic multi-scale modeling presented in this work improves the robustness in the prediction of essential subsurface parameters in engineering scale.
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Emissions of elemental mercury (Hg0) from natural processes are believed to be as large as anthropogenic mercury emissions and are a critical source required to model the transport and fate of mercury. Recent ecosystem scale measurements indicate that a fraction of rec...
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The impact of climate change on surface level ozone is examined through a multi-scale modeling effort that linked global and regional climate models to drive air quality model simulations. Results are quantified in terms of the Relative Response Factor (RRFE), which es...
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Halloran, J. P.; Sibole, S.; van Donkelaar, C. C.; van Turnhout, M. C.; Oomens, C. W. J.; Weiss, J. A.; Guilak, F.; Erdemir, A.
2012-01-01
Articular cartilage experiences significant mechanical loads during daily activities. Healthy cartilage provides the capacity for load bearing and regulates the mechanobiological processes for tissue development, maintenance, and repair. Experimental studies at multiple scales have provided a fundamental understanding of macroscopic mechanical function, evaluation of the micromechanical environment of chondrocytes, and the foundations for mechanobiological response. In addition, computational models of cartilage have offered a concise description of experimental data at many spatial levels under healthy and diseased conditions, and have served to generate hypotheses for the mechanical and biological function. Further, modeling and simulation provides a platform for predictive risk assessment, management of dysfunction, as well as a means to relate multiple spatial scales. Simulation-based investigation of cartilage comes with many challenges including both the computational burden and often insufficient availability of data for model development and validation. This review outlines recent modeling and simulation approaches to understand cartilage function from a mechanical systems perspective, and illustrates pathways to associate mechanics with biological function. Computational representations at single scales are provided from the body down to the microstructure, along with attempts to explore multiscale mechanisms of load sharing that dictate the mechanical environment of the cartilage and chondrocytes. PMID:22648577
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The role of continuity in residual-based variational multiscale modeling of turbulence
NASA Astrophysics Data System (ADS)
Akkerman, I.; Bazilevs, Y.; Calo, V. M.; Hughes, T. J. R.; Hulshoff, S.
2008-02-01
This paper examines the role of continuity of the basis in the computation of turbulent flows. We compare standard finite elements and non-uniform rational B-splines (NURBS) discretizations that are employed in Isogeometric Analysis (Hughes et al. in Comput Methods Appl Mech Eng, 194:4135 4195, 2005). We make use of quadratic discretizations that are C 0-continuous across element boundaries in standard finite elements, and C 1-continuous in the case of NURBS. The variational multiscale residual-based method (Bazilevs in Isogeometric analysis of turbulence and fluid-structure interaction, PhD thesis, ICES, UT Austin, 2006; Bazilevs et al. in Comput Methods Appl Mech Eng, submitted, 2007; Calo in Residual-based multiscale turbulence modeling: finite volume simulation of bypass transition. PhD thesis, Department of Civil and Environmental Engineering, Stanford University, 2004; Hughes et al. in proceedings of the XXI international congress of theoretical and applied mechanics (IUTAM), Kluwer, 2004; Scovazzi in Multiscale methods in science and engineering, PhD thesis, Department of Mechanical Engineering, Stanford Universty, 2004) is employed as a turbulence modeling technique. We find that C 1-continuous discretizations outperform their C 0-continuous counterparts on a per-degree-of-freedom basis. We also find that the effect of continuity is greater for higher Reynolds number flows.
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Multiscale Analysis of Delamination of Carbon Fiber-Epoxy Laminates with Carbon Nanotubes
NASA Technical Reports Server (NTRS)
Riddick, Jaret C.; Frankland, SJV; Gates, TS
2006-01-01
A multi-scale analysis is presented to parametrically describe the Mode I delamination of a carbon fiber/epoxy laminate. In the midplane of the laminate, carbon nanotubes are included for the purposes of selectively enhancing the fracture toughness of the laminate. To analyze carbon fiber epoxy carbon nanotube laminate, the multi-scale methodology presented here links a series of parameterizations taken at various length scales ranging from the atomistic through the micromechanical to the structural level. At the atomistic scale molecular dynamics simulations are performed in conjunction with an equivalent continuum approach to develop constitutive properties for representative volume elements of the molecular structure of components of the laminate. The molecular-level constitutive results are then used in the Mori-Tanaka micromechanics to develop bulk properties for the epoxy-carbon nanotube matrix system. In order to demonstrate a possible application of this multi-scale methodology, a double cantilever beam specimen is modeled. An existing analysis is employed which uses discrete springs to model the fiber bridging affect during delamination propagation. In the absence of empirical data or a damage mechanics model describing the effect of CNTs on fracture toughness, several tractions laws are postulated, linking CNT volume fraction to fiber bridging in a DCB specimen. Results from this demonstration are presented in terms of DCB specimen load-displacement responses.
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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.
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Multiscale modeling and simulation of microtubule-motor-protein assemblies.
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.
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Multiscale modeling and simulation of microtubule–motor-protein assemblies
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
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Patentability aspects of computational cancer models
NASA Astrophysics Data System (ADS)
Lishchuk, Iryna
2017-07-01
Multiscale cancer models, implemented in silico, simulate tumor progression at various spatial and temporal scales. Having the innovative substance and possessing the potential of being applied as decision support tools in clinical practice, patenting and obtaining patent rights in cancer models seems prima facie possible. What legal hurdles the cancer models need to overcome for being patented we inquire from this paper.
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NASA Technical Reports Server (NTRS)
Cheng, Anning; Xu, Kuan-Man
2015-01-01
Five-year simulation experiments with a multi-scale modeling Framework (MMF) with a advanced intermediately prognostic higher-order turbulence closure (IPHOC) in its cloud resolving model (CRM) component, also known as SPCAM-IPHOC (super parameterized Community Atmospheric Model), are performed to understand the fast tropical (30S-30N) cloud response to an instantaneous doubling of CO2 concentration with SST held fixed at present-day values. SPCAM-IPHOC has substantially improved the low-level representation compared with SPCAM. It is expected that the cloud responses to greenhouse warming in SPCAM-IPHOC is more realistic. The change of rising motion, surface precipitation, cloud cover, and shortwave and longwave cloud radiative forcing in SPCAM-IPHOC from the greenhouse warming will be presented in the presentation.
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Mesoscopic modelling and simulation of soft matter.
Schiller, Ulf D; Krüger, Timm; Henrich, Oliver
2017-12-20
The deformability of soft condensed matter often requires modelling of hydrodynamical aspects to gain quantitative understanding. This, however, requires specialised methods that can resolve the multiscale nature of soft matter systems. We review a number of the most popular simulation methods that have emerged, such as Langevin dynamics, dissipative particle dynamics, multi-particle collision dynamics, sometimes also referred to as stochastic rotation dynamics, and the lattice-Boltzmann method. We conclude this review with a short glance at current compute architectures for high-performance computing and community codes for soft matter simulation.
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Modeling Solar Wind Flow with the Multi-Scale Fluid-Kinetic Simulation Suite
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
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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.
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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
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Shock waves simulated using the dual domain material point method combined with molecular dynamics
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
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Multi-scale Finite Element Modeling of Eustachian Tube Function: Influence of Mucosal Adhesion
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
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Integrated Multiscale Modeling of Molecular Computing Devices. Final Report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tim Schulze
2012-11-01
The general theme of this research has been to expand the capabilities of a simulation technique, Kinetic Monte Carlo (KMC) and apply it to study self-assembled nano-structures on epitaxial thin films. KMC simulates thin film growth and evolution by replacing the detailed dynamics of the system's evolution, which might otherwise be studied using molecular dynamics, with an appropriate stochastic process.
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Hierarchical Multiscale Modeling of Macromolecules and their Assemblies
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
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Multiscale Data Assimilation for Large-Eddy Simulations
NASA Astrophysics Data System (ADS)
Li, Z.; Cheng, X.; Gustafson, W. I., Jr.; Xiao, H.; Vogelmann, A. M.; Endo, S.; Toto, T.
2017-12-01
Large-eddy simulation (LES) is a powerful tool for understanding atmospheric turbulence, boundary layer physics and cloud development, and there is a great need for developing data assimilation methodologies that can constrain LES models. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility has been developing the capability to routinely generate ensembles of LES. The LES ARM Symbiotic Simulation and Observation (LASSO) project (https://www.arm.gov/capabilities/modeling/lasso) is generating simulations for shallow convection days at the ARM Southern Great Plains site in Oklahoma. One of major objectives of LASSO is to develop the capability to observationally constrain LES using a hierarchy of ARM observations. We have implemented a multiscale data assimilation (MSDA) scheme, which allows data assimilation to be implemented separately for distinct spatial scales, so that the localized observations can be effectively assimilated to constrain the mesoscale fields in the LES area of about 15 km in width. The MSDA analysis is used to produce forcing data that drive LES. With such LES workflow we have examined 13 days with shallow convection selected from the period May-August 2016. We will describe the implementation of MSDA, present LES results, and address challenges and opportunities for applying data assimilation to LES studies.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Jamshidian, M., E-mail: jamshidian@cc.iut.ac.ir; Institute of Structural Mechanics, Bauhaus-University Weimar, Marienstrasse 15, 99423 Weimar; Thamburaja, P., E-mail: prakash.thamburaja@gmail.com
A previously-developed finite-deformation- and crystal-elasticity-based constitutive theory for stressed grain growth in cubic polycrystalline bodies has been augmented to include a description of excess surface energy and grain-growth stagnation mechanisms through the use of surface effect state variables in a thermodynamically-consistent manner. The constitutive theory was also implemented into a multiscale coupled finite-element and phase-field computational framework. With the material parameters in the constitutive theory suitably calibrated, our three-dimensional numerical simulations show that the constitutive model is able to accurately predict the experimentally-determined evolution of crystallographic texture and grain size statistics in polycrystalline copper thin films deposited on polyimide substratemore » and annealed at high-homologous temperatures. In particular, our numerical analyses show that the broad texture transition observed in the annealing experiments of polycrystalline thin films is caused by grain growth stagnation mechanisms. - Graphical abstract: - Highlights: • Developing a theory for stressed grain growth in polycrystalline thin films. • Implementation into a multiscale coupled finite-element and phase-field framework. • Quantitative reproduction of the experimental grain growth data by simulations. • Revealing the cause of texture transition to be due to the stagnation mechanisms.« less
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Multiscale modeling of a rectifying bipolar nanopore: Comparing Poisson-Nernst-Planck to Monte Carlo
NASA Astrophysics Data System (ADS)
Matejczyk, Bartłomiej; Valiskó, Mónika; Wolfram, Marie-Therese; Pietschmann, Jan-Frederik; Boda, Dezső
2017-03-01
In the framework of a multiscale modeling approach, we present a systematic study of a bipolar rectifying nanopore using a continuum and a particle simulation method. The common ground in the two methods is the application of the Nernst-Planck (NP) equation to compute ion transport in the framework of the implicit-water electrolyte model. The difference is that the Poisson-Boltzmann theory is used in the Poisson-Nernst-Planck (PNP) approach, while the Local Equilibrium Monte Carlo (LEMC) method is used in the particle simulation approach (NP+LEMC) to relate the concentration profile to the electrochemical potential profile. Since we consider a bipolar pore which is short and narrow, we perform simulations using two-dimensional PNP. In addition, results of a non-linear version of PNP that takes crowding of ions into account are shown. We observe that the mean field approximation applied in PNP is appropriate to reproduce the basic behavior of the bipolar nanopore (e.g., rectification) for varying parameters of the system (voltage, surface charge, electrolyte concentration, and pore radius). We present current data that characterize the nanopore's behavior as a device, as well as concentration, electrical potential, and electrochemical potential profiles.
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Ngandjong, Alain C; Rucci, Alexis; Maiza, Mariem; Shukla, Garima; Vazquez-Arenas, Jorge; Franco, Alejandro A
2017-12-07
A novel multiscale modeling platform is proposed to demonstrate the importance of particle assembly during battery electrode fabrication by showing its effect on battery performance. For the first time, a discretized three-dimensional (3D) electrode resulting from the simulation of its fabrication has been incorporated within a 3D continuum performance model. The study used LiNi 0.5 Co 0.2 Mn 0.3 O 2 as active material, and the effect of changes of electrode formulation is explored for three cases, namely 85:15, 90:10, and 95:5 ratios between active material and carbon-binder domains. Coarse-grained molecular dynamics is used to simulate the electrode fabrication. The resulting electrode mesostructure is characterized in terms of active material surface coverage by the carbon-binder domains and porosity. The trends observed are nonintuitive, indicating a high degree of complexity of the system. These structures are subsequently implemented into a 3D continuum model which displays distinct discharge behaviors for the three cases. The study offers a method for developing a coherent theoretical understanding of electrode fabrication that can help optimize battery performance.
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Nonholonomic Hamiltonian Method for Meso-macroscale Simulations of Reacting Shocks
NASA Astrophysics Data System (ADS)
Fahrenthold, Eric; Lee, Sangyup
2015-06-01
The seamless integration of macroscale, mesoscale, and molecular scale models of reacting shock physics has been hindered by dramatic differences in the model formulation techniques normally used at different scales. In recent research the authors have developed the first unified discrete Hamiltonian approach to multiscale simulation of reacting shock physics. Unlike previous work, the formulation employs reacting themomechanical Hamiltonian formulations at all scales, including the continuum. Unlike previous work, the formulation employs a nonholonomic modeling approach to systematically couple the models developed at all scales. Example applications of the method show meso-macroscale shock to detonation simulations in nitromethane and RDX. Research supported by the Defense Threat Reduction Agency.
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Multiscale Modeling of Damage Processes in Aluminum Alloys: Grain-Scale Mechanisms
NASA Technical Reports Server (NTRS)
Hochhalter, J. D.; Veilleux, M. G.; Bozek, J. E.; Glaessgen, E. H.; Ingraffea, A. R.
2008-01-01
This paper has two goals related to the development of a physically-grounded methodology for modeling the initial stages of fatigue crack growth in an aluminum alloy. The aluminum alloy, AA 7075-T651, is susceptible to fatigue cracking that nucleates from cracked second phase iron-bearing particles. Thus, the first goal of the paper is to validate an existing framework for the prediction of the conditions under which the particles crack. The observed statistics of particle cracking (defined as incubation for this alloy) must be accurately predicted to simulate the stochastic nature of microstructurally small fatigue crack (MSFC) formation. Also, only by simulating incubation of damage in a statistically accurate manner can subsequent stages of crack growth be accurately predicted. To maintain fidelity and computational efficiency, a filtering procedure was developed to eliminate particles that were unlikely to crack. The particle filter considers the distributions of particle sizes and shapes, grain texture, and the configuration of the surrounding grains. This filter helps substantially reduce the number of particles that need to be included in the microstructural models and forms the basis of the future work on the subsequent stages of MSFC, crack nucleation and microstructurally small crack propagation. A physics-based approach to simulating fracture should ultimately begin at nanometer length scale, in which atomistic simulation is used to predict the fundamental damage mechanisms of MSFC. These mechanisms include dislocation formation and interaction, interstitial void formation, and atomic diffusion. However, atomistic simulations quickly become computationally intractable as the system size increases, especially when directly linking to the already large microstructural models. Therefore, the second goal of this paper is to propose a method that will incorporate atomistic simulation and small-scale experimental characterization into the existing multiscale framework. At the microscale, the nanoscale mechanics are represented within cohesive zones where appropriate, i.e. where the mechanics observed at the nanoscale can be represented as occurring on a plane such as at grain boundaries or slip planes at a crack front. Important advancements that are yet to be made include: 1. an increased fidelity in cohesive zone modeling; 2. a means to understand how atomistic simulation scales with time; 3. a new experimental methodology for generating empirical models for CZMs and emerging materials; and 4. a validation of simulations of the damage processes at the nano-micro scale. With ever-increasing computer power, the long-term ability to employ atomistic simulation for the prognosis of structural components will not be limited by computation power, but by our lack of knowledge in incorporating atomistic models into simulations of MSFC into a multiscale framework.
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Multiscale methods for computational RNA enzymology
Panteva, Maria T.; Dissanayake, Thakshila; Chen, Haoyuan; Radak, Brian K.; Kuechler, Erich R.; Giambaşu, George M.; Lee, Tai-Sung; York, Darrin M.
2016-01-01
RNA catalysis is of fundamental importance to biology and yet remains ill-understood due to its complex nature. The multi-dimensional “problem space” of RNA catalysis includes both local and global conformational rearrangements, changes in the ion atmosphere around nucleic acids and metal ion binding, dependence on potentially correlated protonation states of key residues and bond breaking/forming in the chemical steps of the reaction. The goal of this article is to summarize and apply multiscale modeling methods in an effort to target the different parts of the RNA catalysis problem space while also addressing the limitations and pitfalls of these methods. Classical molecular dynamics (MD) simulations, reference interaction site model (RISM) calculations, constant pH molecular dynamics (CpHMD) simulations, Hamiltonian replica exchange molecular dynamics (HREMD) and quantum mechanical/molecular mechanical (QM/MM) simulations will be discussed in the context of the study of RNA backbone cleavage transesterification. This reaction is catalyzed by both RNA and protein enzymes, and here we examine the different mechanistic strategies taken by the hepatitis delta virus ribozyme (HDVr) and RNase A. PMID:25726472
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A COMPARISON OF CMAQ-BASED AEROSOL PROPERTIES WITH IMPROVE, MODIS, AND AERONET DATA
We compare select aerosol Properties derived from the Community Multiscale Air Quality (CMAQ) model-simulated aerosol mass concentrations with routine data from the National Aeronautics and Space Administration (NASA) satellite-borne Moderate Resolution Imaging Spectro-radiometer...
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“Skin-Core-Skin” Structure of Polymer Crystallization Investigated by Multiscale Simulation
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
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2014-06-12
interferometry and polarimetry . In the paper, the model was used to simulate SAR data for Mangrove (tropical) and Nezer (temperate) forests for P-band and...Scattering Model Applied to Radiometry, Interferometry, and Polarimetry at P- and L-Band. IEEE Transactions on Geoscience and Remote Sensing 44(4): 849
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A comprehensive three-dimensional Eulerian photochemical model (URM-1ATM) was developed that simulates urban and regional gas and size-resolved aerosol concentrations of pollutants in the atmosphere and both wet and dry deposition. In this study, RAMS and EMS-95 are used to ge...
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The difficulty in assessing errors in numerical models of air quality is a major obstacle to improving their ability to predict and retrospectively map air quality. In this paper, using simulation outputs from the Community Multi-scale Air Quality Model (CMAQ), the statistic...
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Examining the Impact of Nitrous Acid Chemistry on Ozone and PM over the Pearl River Delta Region
The impact of nitrous acid (HONO) chemistry on regional ozone and particulate matter in Pearl River Delta region was investigated using the community multiscale air quality (CMAQ) modeling system and the CB05 mechanism. Model simulations were conducted for a ten-day period in Oct...
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Chimaera simulation of complex states of flowing matter
2016-01-01
We discuss a unified mesoscale framework (chimaera) for the simulation of complex states of flowing matter across scales of motion. The chimaera framework can deal with each of the three macro–meso–micro levels through suitable ‘mutations’ of the basic mesoscale formulation. The idea is illustrated through selected simulations of complex micro- and nanoscale flows. This article is part of the themed issue ‘Multiscale modelling at the physics–chemistry–biology interface’. PMID:27698031
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NASA Astrophysics Data System (ADS)
Evans, John; Coley, Christopher; Aronson, Ryan; Nelson, Corey
2017-11-01
In this talk, a large eddy simulation methodology for turbulent incompressible flow will be presented which combines the best features of divergence-conforming discretizations and the residual-based variational multiscale approach to large eddy simulation. In this method, the resolved motion is represented using a divergence-conforming discretization, that is, a discretization that preserves the incompressibility constraint in a pointwise manner, and the unresolved fluid motion is explicitly modeled by subgrid vortices that lie within individual grid cells. The evolution of the subgrid vortices is governed by dynamical model equations driven by the residual of the resolved motion. Consequently, the subgrid vortices appropriately vanish for laminar flow and fully resolved turbulent flow. As the resolved velocity field and subgrid vortices are both divergence-free, the methodology conserves mass in a pointwise sense and admits discrete balance laws for energy, enstrophy, and helicity. Numerical results demonstrate the methodology yields improved results versus state-of-the-art eddy viscosity models in the context of transitional, wall-bounded, and rotational flow when a divergence-conforming B-spline discretization is utilized to represent the resolved motion.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Lian, Xiaojuan, E-mail: xjlian2005@gmail.com; Cartoixà, Xavier; Miranda, Enrique
2014-06-28
We depart from first-principle simulations of electron transport along paths of oxygen vacancies in HfO{sub 2} to reformulate the Quantum Point Contact (QPC) model in terms of a bundle of such vacancy paths. By doing this, the number of model parameters is reduced and a much clearer link between the microscopic structure of the conductive filament (CF) and its electrical properties can be provided. The new multi-scale QPC model is applied to two different HfO{sub 2}-based devices operated in the unipolar and bipolar resistive switching (RS) modes. Extraction of the QPC model parameters from a statistically significant number of CFsmore » allows revealing significant structural differences in the CF of these two types of devices and RS modes.« less
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NASA Astrophysics Data System (ADS)
Zheng, J.; Zhu, J.; Wang, Z.; Fang, F.; Pain, C. C.; Xiang, J.
2015-06-01
A new anisotropic hr-adaptive mesh technique has been applied to modelling of multiscale transport phenomena, 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 setup for two-dimensional (2-D) transport phenomena. Comparisons have been made between the results obtained using uniform resolution meshes and anisotropic adaptive resolution meshes.
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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.
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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
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A Review of Computational Methods in Materials Science: Examples from Shock-Wave and Polymer Physics
Steinhauser, Martin O.; Hiermaier, Stefan
2009-01-01
This review discusses several computational methods used on different length and time scales for the simulation of material behavior. First, the importance of physical modeling and its relation to computer simulation on multiscales is discussed. Then, computational methods used on different scales are shortly reviewed, before we focus on the molecular dynamics (MD) method. Here we survey in a tutorial-like fashion some key issues including several MD optimization techniques. Thereafter, computational examples for the capabilities of numerical simulations in materials research are discussed. We focus on recent results of shock wave simulations of a solid which are based on two different modeling approaches and we discuss their respective assets and drawbacks with a view to their application on multiscales. Then, the prospects of computer simulations on the molecular length scale using coarse-grained MD methods are covered by means of examples pertaining to complex topological polymer structures including star-polymers, biomacromolecules such as polyelectrolytes and polymers with intrinsic stiffness. This review ends by highlighting new emerging interdisciplinary applications of computational methods in the field of medical engineering where the application of concepts of polymer physics and of shock waves to biological systems holds a lot of promise for improving medical applications such as extracorporeal shock wave lithotripsy or tumor treatment. PMID:20054467
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Fogarty, Aoife C., E-mail: fogarty@mpip-mainz.mpg.de; Potestio, Raffaello, E-mail: potestio@mpip-mainz.mpg.de; Kremer, Kurt, E-mail: kremer@mpip-mainz.mpg.de
A fully atomistic modelling of many biophysical and biochemical processes at biologically relevant length- and time scales is beyond our reach with current computational resources, and one approach to overcome this difficulty is the use of multiscale simulation techniques. In such simulations, when system properties necessitate a boundary between resolutions that falls within the solvent region, one can use an approach such as the Adaptive Resolution Scheme (AdResS), in which solvent particles change their resolution on the fly during the simulation. Here, we apply the existing AdResS methodology to biomolecular systems, simulating a fully atomistic protein with an atomistic hydrationmore » shell, solvated in a coarse-grained particle reservoir and heat bath. Using as a test case an aqueous solution of the regulatory protein ubiquitin, we first confirm the validity of the AdResS approach for such systems, via an examination of protein and solvent structural and dynamical properties. We then demonstrate how, in addition to providing a computational speedup, such a multiscale AdResS approach can yield otherwise inaccessible physical insights into biomolecular function. We use our methodology to show that protein structure and dynamics can still be correctly modelled using only a few shells of atomistic water molecules. We also discuss aspects of the AdResS methodology peculiar to biomolecular simulations.« less
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NASA Astrophysics Data System (ADS)
Bultreys, Tom; Stappen, Jeroen Van; Kock, Tim De; Boever, Wesley De; Boone, Marijn A.; Hoorebeke, Luc Van; Cnudde, Veerle
2016-11-01
The relative permeability behavior of rocks with wide ranges of pore sizes is in many cases still poorly understood and is difficult to model at the pore scale. In this work, we investigate the capillary pressure and relative permeability behavior of three outcrop carbonates and two tight reservoir sandstones with wide, multimodal pore size distributions. To examine how the drainage and imbibition properties of these complex rock types are influenced by the connectivity of macropores to each other and to zones with unresolved small-scale porosity, we apply a previously presented microcomputed-tomography-based multiscale pore network model to these samples. The sensitivity to the properties of the small-scale porosity is studied by performing simulations with different artificial sphere-packing-based networks as a proxy for these pores. Finally, the mixed-wet water-flooding behavior of the samples is investigated, assuming different wettability distributions for the microporosity and macroporosity. While this work is not an attempt to perform predictive modeling, it seeks to qualitatively explain the behavior of the investigated samples and illustrates some of the most recent developments in multiscale pore network modeling.
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Ható, Zoltán; Valiskó, Mónika; Kristóf, Tamás; Gillespie, Dirk; Boda, Dezsö
2017-07-21
In a multiscale modeling approach, we present computer simulation results for a rectifying bipolar nanopore at two modeling levels. In an all-atom model, we use explicit water to simulate ion transport directly with the molecular dynamics technique. In a reduced model, we use implicit water and apply the Local Equilibrium Monte Carlo method together with the Nernst-Planck transport equation. This hybrid method makes the fast calculation of ion transport possible at the price of lost details. We show that the implicit-water model is an appropriate representation of the explicit-water model when we look at the system at the device (i.e., input vs. output) level. The two models produce qualitatively similar behavior of the electrical current for different voltages and model parameters. Looking at the details of concentration and potential profiles, we find profound differences between the two models. These differences, however, do not influence the basic behavior of the model as a device because they do not influence the z-dependence of the concentration profiles which are the main determinants of current. These results then address an old paradox: how do reduced models, whose assumptions should break down in a nanoscale device, predict experimental data? Our simulations show that reduced models can still capture the overall device physics correctly, even though they get some important aspects of the molecular-scale physics quite wrong; reduced models work because they include the physics that is necessary from the point of view of device function. Therefore, reduced models can suffice for general device understanding and device design, but more detailed models might be needed for molecular level understanding.
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Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility
NASA Astrophysics Data System (ADS)
Kou, Jisheng; Sun, Shuyu
2016-08-01
In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from the microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young-Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young-Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young-Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally, numerical tests are carried out to verify the effectiveness of the proposed multi-scale method.
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Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kou, Jisheng; Sun, Shuyu, E-mail: shuyu.sun@kaust.edu.sa; School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049
2016-08-01
In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng–Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from themore » microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young–Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young–Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young–Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally, numerical tests are carried out to verify the effectiveness of the proposed multi-scale method.« less
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3D multiscale crack propagation using the XFEM applied to a gas turbine blade
NASA Astrophysics Data System (ADS)
Holl, Matthias; Rogge, Timo; Loehnert, Stefan; Wriggers, Peter; Rolfes, Raimund
2014-01-01
This work presents a new multiscale technique to investigate advancing cracks in three dimensional space. This fully adaptive multiscale technique is designed to take into account cracks of different length scales efficiently, by enabling fine scale domains locally in regions of interest, i.e. where stress concentrations and high stress gradients occur. Due to crack propagation, these regions change during the simulation process. Cracks are modeled using the extended finite element method, such that an accurate and powerful numerical tool is achieved. Restricting ourselves to linear elastic fracture mechanics, the -integral yields an accurate solution of the stress intensity factors, and with the criterion of maximum hoop stress, a precise direction of growth. If necessary, the on the finest scale computed crack surface is finally transferred to the corresponding scale. In a final step, the model is applied to a quadrature point of a gas turbine blade, to compute crack growth on the microscale of a real structure.
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Borge, Rafael; Santiago, Jose Luis; de la Paz, David; Martín, Fernando; Domingo, Jessica; Valdés, Cristina; Sánchez, Beatriz; Rivas, Esther; Rozas, Mª Teresa; Lázaro, Sonia; Pérez, Javier; Fernández, Álvaro
2018-05-05
Air pollution continues to be one of the main issues in urban areas. In addition to air quality plans and emission abatement policies, additional measures for high pollution episodes are needed to avoid exceedances of hourly limit values under unfavourable meteorological conditions such as the Madrid's short-term action NO 2 protocol. In December 2016 there was a strong atmospheric stability episode that turned out in generalized high NO 2 levels, causing the stage 3 of the NO 2 protocol to be triggered for the first time in Madrid (29th December). In addition to other traffic-related measures, this involves access restrictions to the city centre (50% to private cars). We simulated the episode with and without measures under a multi-scale modelling approach. A 1 km 2 resolution modelling system based on WRF-SMOKE-CMAQ was applied to assess city-wide effects while the Star-CCM+ (RANS CFD model) was used to investigate the effect at street level in a microscale domain in the city centre, focusing on Gran Vía Avenue. Changes in road traffic were simulated with the mesoscale VISUM model, incorporating real flux measurements during those days. The corresponding simulations suggest that the application of the protocol during this particular episode may have prevented concentrations to increase by 24 μg·m -3 (14% respect to the hypothetical no action scenario) downtown although it may have cause NO 2 to slightly increase in the city outskirts due to traffic redistribution. Speed limitation and parking restrictions alone (stages 1 and 2 respectively) have a very limited effect. The microscale simulation provides consistent results but shows an important variability at street level, with reduction above 100 μg·m -3 in some spots inside Gran Vía. Although further research is needed, these results point out the need to implement short-term action plans and to apply a consistent multi-scale modelling assessment to optimize urban air quality abatement strategies. Copyright © 2018 Elsevier B.V. All rights reserved.
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The CMAQ (Community Multiscale Air Quality) us model in combination with observations for INTEX-NA/ICARTT (Intercontinental Chemical Transport Experiment–North America/International Consortium for Atmospheric Research on Transport and Transformation) 2004 are used to evalua...
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Multiscale modeling and simulation of embryogenesis for in silico predictive toxicology (WC9)
Translating big data from alternative and HTS platforms into hazard identification and risk assessment is an important need for predictive toxicology and for elucidating adverse outcome pathways (AOPs) in developmental toxicity. Understanding how chemical disruption of molecular ...
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Parameterizing the Morse Potential for Coarse-Grained Modeling of Blood Plasma
Zhang, Na; Zhang, Peng; Kang, Wei; Bluestein, Danny; Deng, Yuefan
2014-01-01
Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters are systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately. PMID:24910470
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SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.
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.
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Development of mpi_EPIC model for global agroecosystem modeling
Kang, Shujiang; Wang, Dali; Jeff A. Nichols; ...
2014-12-31
Models that address policy-maker concerns about multi-scale effects of food and bioenergy production systems are computationally demanding. We integrated the message passing interface algorithm into the process-based EPIC model to accelerate computation of ecosystem effects. Simulation performance was further enhanced by applying the Vampir framework. When this enhanced mpi_EPIC model was tested, total execution time for a global 30-year simulation of a switchgrass cropping system was shortened to less than 0.5 hours on a supercomputer. The results illustrate that mpi_EPIC using parallel design can balance simulation workloads and facilitate large-scale, high-resolution analysis of agricultural production systems, management alternatives and environmentalmore » effects.« less
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Computational Modeling System for Deformation and Failure in Polycrystalline Metals
2009-03-29
FIB/EHSD 3.3 The Voronoi Cell FEM for Micromechanical Modeling 3.4 VCFEM for Microstructural Damage Modeling 3.5 Adaptive Multiscale Simulations...accurate and efficient image-based micromechanical finite element model, for crystal plasticity and damage , incorporating real morphological and...topology with evolving strain localization and damage . (v) Development of multi-scaling algorithms in the time domain for compression and localization in
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Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stander, Nielen; Basudhar, Anirban; Basu, Ushnish
2015-09-14
Ever-tightening regulations on fuel economy, and the likely future regulation of carbon emissions, demand persistent innovation in vehicle design to reduce vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials, by adding material diversity and composite materials, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing plate thickness while retaining sufficient strength and ductility required for durability and safety. A project tomore » develop computational material models for advanced high strength steel is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the US Department of Energy. Under this program, new Third Generation Advanced High Strength Steel (i.e., 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. The objectives of the project are to integrate atomistic, microstructural, forming and performance models to create an integrated computational materials engineering (ICME) toolkit for 3GAHSS. The mechanical properties of Advanced High Strength Steels (AHSS) are controlled by many factors, including phase composition and distribution in the overall microstructure, volume fraction, size and morphology of phase constituents as well as stability of the metastable retained austenite phase. The complex phase transformation and deformation mechanisms in these steels make the well-established traditional techniques obsolete, and a multi-scale microstructure-based modeling approach following the ICME [0]strategy was therefore chosen in this project. Multi-scale modeling as a major area of research and development is an outgrowth of the Comprehensive Test Ban Treaty of 1996 which banned surface testing of nuclear devices [1]. This had the effect that experimental work was reduced from large scale tests to multiscale experiments to provide material models with validation at different length scales. In the subsequent years industry realized that multi-scale modeling and simulation-based design were transferable to the design optimization of any structural system. Horstemeyer [1] lists a number of advantages of the use of multiscale modeling. Among these are: the reduction of product development time by alleviating costly trial-and-error iterations as well as the reduction of product costs through innovations in material, product and process designs. Multi-scale modeling can reduce the number of costly large scale experiments and can increase product quality by providing more accurate predictions. Research tends to be focussed on each particular length scale, which enhances accuracy in the long term. This paper serves as an introduction to the LS-OPT and LS-DYNA methodology for multi-scale modeling. It mainly focuses on an approach to integrate material identification using material models of different length scales. As an example, a multi-scale material identification strategy, consisting of a Crystal Plasticity (CP) material model and a homogenized State Variable (SV) model, is discussed and the parameter identification of the individual material models of different length scales is demonstrated. The paper concludes with thoughts on integrating the multi-scale methodology into the overall vehicle design.« less
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PyRhO: A Multiscale Optogenetics Simulation Platform
Evans, Benjamin D.; Jarvis, Sarah; Schultz, Simon R.; Nikolic, Konstantin
2016-01-01
Optogenetics has become a key tool for understanding the function of neural circuits and controlling their behavior. An array of directly light driven opsins have been genetically isolated from several families of organisms, with a wide range of temporal and spectral properties. In order to characterize, understand and apply these opsins, we present an integrated suite of open-source, multi-scale computational tools called PyRhO. The purpose of developing PyRhO is three-fold: (i) to characterize new (and existing) opsins by automatically fitting a minimal set of experimental data to three-, four-, or six-state kinetic models, (ii) to simulate these models at the channel, neuron and network levels, and (iii) provide functional insights through model selection and virtual experiments in silico. The module is written in Python with an additional IPython/Jupyter notebook based GUI, allowing models to be fit, simulations to be run and results to be shared through simply interacting with a webpage. The seamless integration of model fitting algorithms with simulation environments (including NEURON and Brian2) for these virtual opsins will enable neuroscientists to gain a comprehensive understanding of their behavior and rapidly identify the most suitable variant for application in a particular biological system. This process may thereby guide not only experimental design and opsin choice but also alterations of the opsin genetic code in a neuro-engineering feed-back loop. In this way, we expect PyRhO will help to significantly advance optogenetics as a tool for transforming biological sciences. PMID:27148037
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PyRhO: A Multiscale Optogenetics Simulation Platform.
Evans, Benjamin D; Jarvis, Sarah; Schultz, Simon R; Nikolic, Konstantin
2016-01-01
Optogenetics has become a key tool for understanding the function of neural circuits and controlling their behavior. An array of directly light driven opsins have been genetically isolated from several families of organisms, with a wide range of temporal and spectral properties. In order to characterize, understand and apply these opsins, we present an integrated suite of open-source, multi-scale computational tools called PyRhO. The purpose of developing PyRhO is three-fold: (i) to characterize new (and existing) opsins by automatically fitting a minimal set of experimental data to three-, four-, or six-state kinetic models, (ii) to simulate these models at the channel, neuron and network levels, and (iii) provide functional insights through model selection and virtual experiments in silico. The module is written in Python with an additional IPython/Jupyter notebook based GUI, allowing models to be fit, simulations to be run and results to be shared through simply interacting with a webpage. The seamless integration of model fitting algorithms with simulation environments (including NEURON and Brian2) for these virtual opsins will enable neuroscientists to gain a comprehensive understanding of their behavior and rapidly identify the most suitable variant for application in a particular biological system. This process may thereby guide not only experimental design and opsin choice but also alterations of the opsin genetic code in a neuro-engineering feed-back loop. In this way, we expect PyRhO will help to significantly advance optogenetics as a tool for transforming biological sciences.
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Parallel multiscale simulations of a brain aneurysm
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
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Munoz-Esparza, Domingo; Lundquist, Julie K.; Sauer, Jeremy A.
Multiscale modeling of a diurnal cycle of real-world conditions is presented for the first time, validated using data from the CWEX-13 field experiment. Dynamical downscaling from synoptic-scale down to resolved three-dimensional eddies in the atmospheric boundary layer (ABL) was performed, spanning 4 orders of magnitude in horizontal grid resolution: from 111 km down to 8.2 m (30 m) in stable (convective) conditions. Computationally efficient mesoscale-to-microscale transition was made possible by the generalized cell perturbation method with time-varying parameters derived from mesoscale forcing conditions, which substantially reduced the fetch to achieve fully developed turbulence. In addition, careful design of the simulationsmore » was made to inhibit the presence of under-resolved convection at convection-resolving mesoscale resolution and to ensure proper turbulence representation in stably-stratified conditions. Comparison to in situ wind-profiling lidar and near-surface sonic anemometer measurements demonstrated the ability to reproduce the ABL structure throughout the entire diurnal cycle with a high degree of fidelity. The multiscale simulations exhibit realistic atmospheric features such as convective rolls and global intermittency. Also, the diurnal evolution of turbulence was accurately simulated, with probability density functions of resolved turbulent velocity fluctuations nearly identical to the lidar measurements. Explicit representation of turbulence in the stably-stratified ABL was found to provide the right balance with larger scales, resulting in the development of intra-hour variability as observed by the wind lidar; this variability was not captured by the mesoscale model. Furthermore, multiscale simulations improved mean ABL characteristics such as horizontal velocity, vertical wind shear, and turbulence.« less
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Munoz-Esparza, Domingo; Lundquist, Julie K.; Sauer, Jeremy A.; ...
2017-04-25
Multiscale modeling of a diurnal cycle of real-world conditions is presented for the first time, validated using data from the CWEX-13 field experiment. Dynamical downscaling from synoptic-scale down to resolved three-dimensional eddies in the atmospheric boundary layer (ABL) was performed, spanning 4 orders of magnitude in horizontal grid resolution: from 111 km down to 8.2 m (30 m) in stable (convective) conditions. Computationally efficient mesoscale-to-microscale transition was made possible by the generalized cell perturbation method with time-varying parameters derived from mesoscale forcing conditions, which substantially reduced the fetch to achieve fully developed turbulence. In addition, careful design of the simulationsmore » was made to inhibit the presence of under-resolved convection at convection-resolving mesoscale resolution and to ensure proper turbulence representation in stably-stratified conditions. Comparison to in situ wind-profiling lidar and near-surface sonic anemometer measurements demonstrated the ability to reproduce the ABL structure throughout the entire diurnal cycle with a high degree of fidelity. The multiscale simulations exhibit realistic atmospheric features such as convective rolls and global intermittency. Also, the diurnal evolution of turbulence was accurately simulated, with probability density functions of resolved turbulent velocity fluctuations nearly identical to the lidar measurements. Explicit representation of turbulence in the stably-stratified ABL was found to provide the right balance with larger scales, resulting in the development of intra-hour variability as observed by the wind lidar; this variability was not captured by the mesoscale model. Furthermore, multiscale simulations improved mean ABL characteristics such as horizontal velocity, vertical wind shear, and turbulence.« less
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Parallel multiscale simulations of a brain aneurysm.
Grinberg, Leopold; Fedosov, Dmitry A; Karniadakis, George Em
2013-07-01
Cardiovascular pathologies, such as a brain aneurysm, are affected by the global blood circulation as well as by the local microrheology. Hence, developing computational models for such cases requires the coupling of disparate spatial and temporal scales often governed by diverse mathematical descriptions, e.g., by partial differential equations (continuum) and ordinary differential equations for discrete particles (atomistic). However, interfacing atomistic-based with continuum-based domain discretizations is a challenging problem that requires both mathematical and computational advances. We present here a hybrid methodology that enabled us to perform the first multi-scale simulations of platelet depositions on the wall of a brain aneurysm. The large scale flow features in the intracranial network are accurately resolved by using the high-order spectral element Navier-Stokes solver 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.
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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
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Peridynamic Multiscale Finite Element Methods
DOE Office of Scientific and Technical Information (OSTI.GOV)
Costa, Timothy; Bond, Stephen D.; Littlewood, David John
The problem of computing quantum-accurate design-scale solutions to mechanics problems is rich with applications and serves as the background to modern multiscale science research. The prob- lem can be broken into component problems comprised of communicating across adjacent scales, which when strung together create a pipeline for information to travel from quantum scales to design scales. Traditionally, this involves connections between a) quantum electronic structure calculations and molecular dynamics and between b) molecular dynamics and local partial differ- ential equation models at the design scale. The second step, b), is particularly challenging since the appropriate scales of molecular dynamic andmore » local partial differential equation models do not overlap. The peridynamic model for continuum mechanics provides an advantage in this endeavor, as the basic equations of peridynamics are valid at a wide range of scales limiting from the classical partial differential equation models valid at the design scale to the scale of molecular dynamics. In this work we focus on the development of multiscale finite element methods for the peridynamic model, in an effort to create a mathematically consistent channel for microscale information to travel from the upper limits of the molecular dynamics scale to the design scale. In particular, we first develop a Nonlocal Multiscale Finite Element Method which solves the peridynamic model at multiple scales to include microscale information at the coarse-scale. We then consider a method that solves a fine-scale peridynamic model to build element-support basis functions for a coarse- scale local partial differential equation model, called the Mixed Locality Multiscale Finite Element Method. Given decades of research and development into finite element codes for the local partial differential equation models of continuum mechanics there is a strong desire to couple local and nonlocal models to leverage the speed and state of the art of local models with the flexibility and accuracy of the nonlocal peridynamic model. In the mixed locality method this coupling occurs across scales, so that the nonlocal model can be used to communicate material heterogeneity at scales inappropriate to local partial differential equation models. Additionally, the computational burden of the weak form of the peridynamic model is reduced dramatically by only requiring that the model be solved on local patches of the simulation domain which may be computed in parallel, taking advantage of the heterogeneous nature of next generation computing platforms. Addition- ally, we present a novel Galerkin framework, the 'Ambulant Galerkin Method', which represents a first step towards a unified mathematical analysis of local and nonlocal multiscale finite element methods, and whose future extension will allow the analysis of multiscale finite element methods that mix models across scales under certain assumptions of the consistency of those models.« less
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NASA Astrophysics Data System (ADS)
Macioł, Piotr; Regulski, Krzysztof
2016-08-01
We present a process of semantic meta-model development for data management in an adaptable multiscale modeling framework. The main problems in ontology design are discussed, and a solution achieved as a result of the research is presented. The main concepts concerning the application and data management background for multiscale modeling were derived from the AM3 approach—object-oriented Agile multiscale modeling methodology. The ontological description of multiscale models enables validation of semantic correctness of data interchange between submodels. We also present a possibility of using the ontological model as a supervisor in conjunction with a multiscale model controller and a knowledge base system. Multiscale modeling formal ontology (MMFO), designed for describing multiscale models' data and structures, is presented. A need for applying meta-ontology in the MMFO development process is discussed. Examples of MMFO application in describing thermo-mechanical treatment of metal alloys are discussed. Present and future applications of MMFO are described.
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NASA Technical Reports Server (NTRS)
Pineda, Evan J.; Fassin, Marek; Bednarcyk, Brett A.; Reese, Stefanie; Simon, Jaan-Willem
2017-01-01
Three different multiscale models, based on the method of cells (generalized and high fidelity) micromechanics models were developed and used to predict the elastic properties of C/C-SiC composites. In particular, the following multiscale modeling strategies were employed: Concurrent multiscale modeling of all phases using the generalized method of cells, synergistic (two-way coupling in space) multiscale modeling with the generalized method of cells, and hierarchical (one-way coupling in space) multiscale modeling with the high fidelity generalized method of cells. The three models are validated against data from a hierarchical multiscale finite element model in the literature for a repeating unit cell of C/C-SiC. Furthermore, the multiscale models are used in conjunction with classical lamination theory to predict the stiffness of C/C-SiC plates manufactured via a wet filament winding and liquid silicon infiltration process recently developed by the German Aerospace Institute.
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Land-Atmosphere Coupling in the Multi-Scale Modelling Framework
NASA Astrophysics Data System (ADS)
Kraus, P. M.; Denning, S.
2015-12-01
The Multi-Scale Modeling Framework (MMF), in which cloud-resolving models (CRMs) are embedded within general circulation model (GCM) gridcells to serve as the model's cloud parameterization, has offered a number of benefits to GCM simulations. The coupling of these cloud-resolving models directly to land surface model instances, rather than passing averaged atmospheric variables to a single instance of a land surface model, the logical next step in model development, has recently been accomplished. This new configuration offers conspicuous improvements to estimates of precipitation and canopy through-fall, but overall the model exhibits warm surface temperature biases and low productivity.This work presents modifications to a land-surface model that take advantage of the new multi-scale modeling framework, and accommodate the change in spatial scale from a typical GCM range of ~200 km to the CRM grid-scale of 4 km.A parameterization is introduced to apportion modeled surface radiation into direct-beam and diffuse components. The diffuse component is then distributed among the land-surface model instances within each GCM cell domain. This substantially reduces the number excessively low light values provided to the land-surface model when cloudy conditions are modeled in the CRM, associated with its 1-D radiation scheme. The small spatial scale of the CRM, ~4 km, as compared with the typical ~200 km GCM scale, provides much more realistic estimates of precipitation intensity, this permits the elimination of a model parameterization of canopy through-fall. However, runoff at such scales can no longer be considered as an immediate flow to the ocean. Allowing sub-surface water flow between land-surface instances within the GCM domain affords better realism and also reduces temperature and productivity biases.The MMF affords a number of opportunities to land-surface modelers, providing both the advantages of direct simulation at the 4 km scale and a much reduced conceptual gap between model resolution and parameterized processes.
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Chimaera simulation of complex states of flowing matter.
Succi, S
2016-11-13
We discuss a unified mesoscale framework (chimaera) for the simulation of complex states of flowing matter across scales of motion. The chimaera framework can deal with each of the three macro-meso-micro levels through suitable 'mutations' of the basic mesoscale formulation. The idea is illustrated through selected simulations of complex micro- and nanoscale flows.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2016 The Author(s).
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NASA Astrophysics Data System (ADS)
Fogarty, Aoife C.; Potestio, Raffaello; Kremer, Kurt
2015-05-01
A fully atomistic modelling of many biophysical and biochemical processes at biologically relevant length- and time scales is beyond our reach with current computational resources, and one approach to overcome this difficulty is the use of multiscale simulation techniques. In such simulations, when system properties necessitate a boundary between resolutions that falls within the solvent region, one can use an approach such as the Adaptive Resolution Scheme (AdResS), in which solvent particles change their resolution on the fly during the simulation. Here, we apply the existing AdResS methodology to biomolecular systems, simulating a fully atomistic protein with an atomistic hydration shell, solvated in a coarse-grained particle reservoir and heat bath. Using as a test case an aqueous solution of the regulatory protein ubiquitin, we first confirm the validity of the AdResS approach for such systems, via an examination of protein and solvent structural and dynamical properties. We then demonstrate how, in addition to providing a computational speedup, such a multiscale AdResS approach can yield otherwise inaccessible physical insights into biomolecular function. We use our methodology to show that protein structure and dynamics can still be correctly modelled using only a few shells of atomistic water molecules. We also discuss aspects of the AdResS methodology peculiar to biomolecular simulations.
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Multi-Scale Modeling of the Gamma Radiolysis of Nitrate Solutions.
Horne, Gregory P; Donoclift, Thomas A; Sims, Howard E; Orr, Robin M; Pimblott, Simon M
2016-11-17
A multiscale modeling approach has been developed for the extended time scale long-term radiolysis of aqueous systems. The approach uses a combination of stochastic track structure and track chemistry as well as deterministic homogeneous chemistry techniques and involves four key stages: radiation track structure simulation, the subsequent physicochemical processes, nonhomogeneous diffusion-reaction kinetic evolution, and homogeneous bulk chemistry modeling. The first three components model the physical and chemical evolution of an isolated radiation chemical track and provide radiolysis yields, within the extremely low dose isolated track paradigm, as the input parameters for a bulk deterministic chemistry model. This approach to radiation chemical modeling has been tested by comparison with the experimentally observed yield of nitrite from the gamma radiolysis of sodium nitrate solutions. This is a complex radiation chemical system which is strongly dependent on secondary reaction processes. The concentration of nitrite is not just dependent upon the evolution of radiation track chemistry and the scavenging of the hydrated electron and its precursors but also on the subsequent reactions of the products of these scavenging reactions with other water radiolysis products. Without the inclusion of intratrack chemistry, the deterministic component of the multiscale model is unable to correctly predict experimental data, highlighting the importance of intratrack radiation chemistry in the chemical evolution of the irradiated system.
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Kerckhoffs, Roy C. P.; Neal, Maxwell L.; Gu, Quan; Bassingthwaighte, James B.; Omens, Jeff H.; McCulloch, Andrew D.
2010-01-01
In this study we present a novel, robust method to couple finite element (FE) models of cardiac mechanics to systems models of the circulation (CIRC), independent of cardiac phase. For each time step through a cardiac cycle, left and right ventricular pressures were calculated using ventricular compliances from the FE and CIRC models. These pressures served as boundary conditions in the FE and CIRC models. In succeeding steps, pressures were updated to minimize cavity volume error (FE minus CIRC volume) using Newton iterations. Coupling was achieved when a predefined criterion for the volume error was satisfied. Initial conditions for the multi-scale model were obtained by replacing the FE model with a varying elastance model, which takes into account direct ventricular interactions. Applying the coupling, a novel multi-scale model of the canine cardiovascular system was developed. Global hemodynamics and regional mechanics were calculated for multiple beats in two separate simulations with a left ventricular ischemic region and pulmonary artery constriction, respectively. After the interventions, global hemodynamics changed due to direct and indirect ventricular interactions, in agreement with previously published experimental results. The coupling method allows for simulations of multiple cardiac cycles for normal and pathophysiology, encompassing levels from cell to system. PMID:17111210
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de la Cruz, Roberto; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás
2017-12-01
The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth.
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NASA Astrophysics Data System (ADS)
de la Cruz, Roberto; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás
2017-12-01
The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth.
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NASA Astrophysics Data System (ADS)
Kim, Youngseob; Wu, You; Seigneur, Christian; Roustan, Yelva
2018-02-01
A new multi-scale model of urban air pollution is presented. This model combines a chemistry-transport model (CTM) that includes a comprehensive treatment of atmospheric chemistry and transport on spatial scales down to 1 km and a street-network model that describes the atmospheric concentrations of pollutants in an urban street network. The street-network model is the Model of Urban Network of Intersecting Canyons and Highways (MUNICH), which consists of two main components: a street-canyon component and a street-intersection component. MUNICH is coupled to the Polair3D CTM of the Polyphemus air quality modeling platform to constitute the Street-in-Grid (SinG) model. MUNICH is used to simulate the concentrations of the chemical species in the urban canopy, which is located in the lowest layer of Polair3D, and the simulation of pollutant concentrations above rooftops is performed with Polair3D. Interactions between MUNICH and Polair3D occur at roof level and depend on a vertical mass transfer coefficient that is a function of atmospheric turbulence. SinG is used to simulate the concentrations of nitrogen oxides (NOx) and ozone (O3) in a Paris suburb. Simulated concentrations are compared to NOx concentrations measured at two monitoring stations within a street canyon. SinG shows better performance than MUNICH for nitrogen dioxide (NO2) concentrations. However, both SinG and MUNICH underestimate NOx. For the case study considered, the model performance for NOx concentrations is not sensitive to using a complex chemistry model in MUNICH and the Leighton NO-NO2-O3 set of reactions is sufficient.
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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.
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NASA Astrophysics Data System (ADS)
Slaughter, A. E.; Permann, C.; Peterson, J. W.; Gaston, D.; Andrs, D.; Miller, J.
2014-12-01
The Idaho National Laboratory (INL)-developed Multiphysics Object Oriented Simulation Environment (MOOSE; www.mooseframework.org), is an open-source, parallel computational framework for enabling the solution of complex, fully implicit multiphysics systems. MOOSE provides a set of computational tools that scientists and engineers can use to create sophisticated multiphysics simulations. Applications built using MOOSE have computed solutions for chemical reaction and transport equations, computational fluid dynamics, solid mechanics, heat conduction, mesoscale materials modeling, geomechanics, and others. To facilitate the coupling of diverse and highly-coupled physical systems, MOOSE employs the Jacobian-free Newton-Krylov (JFNK) method when solving the coupled nonlinear systems of equations arising in multiphysics applications. The MOOSE framework is written in C++, and leverages other high-quality, open-source scientific software packages such as LibMesh, Hypre, and PETSc. MOOSE uses a "hybrid parallel" model which combines both shared memory (thread-based) and distributed memory (MPI-based) parallelism to ensure efficient resource utilization on a wide range of computational hardware. MOOSE-based applications are inherently modular, which allows for simulation expansion (via coupling of additional physics modules) and the creation of multi-scale simulations. Any application developed with MOOSE supports running (in parallel) any other MOOSE-based application. Each application can be developed independently, yet easily communicate with other applications (e.g., conductivity in a slope-scale model could be a constant input, or a complete phase-field micro-structure simulation) without additional code being written. This method of development has proven effective at INL and expedites the development of sophisticated, sustainable, and collaborative simulation tools.
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Evaluation of the Community Multiscale Air Quality (CMAQ) ...
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
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Adaptive two-regime method: Application to front propagation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Robinson, Martin, E-mail: martin.robinson@maths.ox.ac.uk; Erban, Radek, E-mail: erban@maths.ox.ac.uk; Flegg, Mark, E-mail: mark.flegg@monash.edu
2014-03-28
The Adaptive Two-Regime Method (ATRM) is developed for hybrid (multiscale) stochastic simulation of reaction-diffusion problems. It efficiently couples detailed Brownian dynamics simulations with coarser lattice-based models. The ATRM is a generalization of the previously developed Two-Regime Method [Flegg et al., J. R. Soc., Interface 9, 859 (2012)] to multiscale problems which require a dynamic selection of regions where detailed Brownian dynamics simulation is used. Typical applications include a front propagation or spatio-temporal oscillations. In this paper, the ATRM is used for an in-depth study of front propagation in a stochastic reaction-diffusion system which has its mean-field model given in termsmore » of the Fisher equation [R. Fisher, Ann. Eugen. 7, 355 (1937)]. It exhibits a travelling reaction front which is sensitive to stochastic fluctuations at the leading edge of the wavefront. Previous studies into stochastic effects on the Fisher wave propagation speed have focused on lattice-based models, but there has been limited progress using off-lattice (Brownian dynamics) models, which suffer due to their high computational cost, particularly at the high molecular numbers that are necessary to approach the Fisher mean-field model. By modelling only the wavefront itself with the off-lattice model, it is shown that the ATRM leads to the same Fisher wave results as purely off-lattice models, but at a fraction of the computational cost. The error analysis of the ATRM is also presented for a morphogen gradient model.« less
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“Impact of CB6 and CB05TU chemical mechanisms on air quality”
“Impacts of CB6 and CB05TU chemical mechanisms on air quality”In this study, we incorporate the newly developed Carbon Bond chemical mechanism (CB6) into the Community Multiscale Air Quality modeling system (CMAQv5.0.1) and perform air quality model simulations with the CB6 and t...
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NASA Astrophysics Data System (ADS)
Chern, J. D.; Tao, W. K.; Lang, S. E.; Matsui, T.; Mohr, K. I.
2014-12-01
Four six-month (March-August 2014) experiments with the Goddard Multi-scale Modeling Framework (MMF) were performed to study the impacts of different Goddard one-moment bulk microphysical schemes and large-scale forcings on the performance of the MMF. Recently a new Goddard one-moment bulk microphysics with four-ice classes (cloud ice, snow, graupel, and frozen drops/hail) has been developed based on cloud-resolving model simulations with large-scale forcings from field campaign observations. The new scheme has been successfully implemented to the MMF and two MMF experiments were carried out with this new scheme and the old three-ice classes (cloud ice, snow graupel) scheme. The MMF has global coverage and can rigorously evaluate microphysics performance for different cloud regimes. The results show MMF with the new scheme outperformed the old one. The MMF simulations are also strongly affected by the interaction between large-scale and cloud-scale processes. Two MMF sensitivity experiments with and without nudging large-scale forcings to those of ERA-Interim reanalysis were carried out to study the impacts of large-scale forcings. The model simulated mean and variability of surface precipitation, cloud types, cloud properties such as cloud amount, hydrometeors vertical profiles, and cloud water contents, etc. in different geographic locations and climate regimes are evaluated against GPM, TRMM, CloudSat/CALIPSO satellite observations. The Goddard MMF has also been coupled with the Goddard Satellite Data Simulation Unit (G-SDSU), a system with multi-satellite, multi-sensor, and multi-spectrum satellite simulators. The statistics of MMF simulated radiances and backscattering can be directly compared with satellite observations to assess the strengths and/or deficiencies of MMF simulations and provide guidance on how to improve the MMF and microphysics.
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Understanding sources of organic aerosol during CalNex-2010 using the CMAQ-VBS
Community Multiscale Air Quality (CMAQ) model simulations utilizing the traditional organic aerosol (OA) treatment (CMAQ-AE6) and a volatility basis set (VBS) treatment for OA (CMAQ-VBS) were evaluated against measurements collected at routine monitoring networks (Chemical Specia...
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A DYNAMIC SIMULATOR OF ENVIRONMENTAL CHEMICAL PARTITIONING
A version of the Community Multiscale Air Quality (CMAQ) model has been developed by the U.S. EPA that is capable of addressing the atmospheric fate, transport and deposition of some common trace toxics. An initial, 36-km rectangular grid-cell application for atrazine has been...
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Multi-scale Fatigue Damage Life Assessment of Railroad Wheels
DOT National Transportation Integrated Search
2018-01-01
This study focused on the presence of a crack in the railway wheels subsurface and how it affects the wheels fatigue life. A 3-D FE-model was constructed to simulate the stress/strain fields that take place under the rolling contact of railway ...
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Multiscale Modeling of Plasmon-Enhanced Power Conversion Efficiency in Nanostructured Solar Cells.
Meng, Lingyi; Yam, ChiYung; Zhang, Yu; Wang, Rulin; Chen, GuanHua
2015-11-05
The unique optical properties of nanometallic structures can be exploited to confine light at subwavelength scales. This excellent light trapping is critical to improve light absorption efficiency in nanoscale photovoltaic devices. Here, we apply a multiscale quantum mechanics/electromagnetics (QM/EM) method to model the current-voltage characteristics and optical properties of plasmonic nanowire-based solar cells. The QM/EM method features a combination of first-principles quantum mechanical treatment of the photoactive component and classical description of electromagnetic environment. The coupled optical-electrical QM/EM simulations demonstrate a dramatic enhancement for power conversion efficiency of nanowire solar cells due to the surface plasmon effect of nanometallic structures. The improvement is attributed to the enhanced scattering of light into the photoactive layer. We further investigate the optimal configuration of the nanostructured solar cell. Our QM/EM simulation result demonstrates that a further increase of internal quantum efficiency can be achieved by scattering light into the n-doped region of the device.
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Ftmp-Based Simulation of Twin Nucleation and Substructure Evolution Under Hypervelocity Impact
NASA Astrophysics Data System (ADS)
Okuda, Tatsuya; Imiya, Kazuhiro; Hasebe, Tadashi
2013-01-01
The deformation twinning model based on Field Theory of Multiscale Plasticity (FTMP) represents the twin degrees of freedom with the incompatibility tensor, which is incorporated into the hardening law of the FTMP-based crystalline plasticity framework. The model is further implemented into a finite element code. In the present study, the model is adapted to a single slip-oriented FCC single crystal sample, and preliminary simulations are conducted under static conditions to confirm the model's basic capabilities. The simulation results exhibit nucleation and growth of twinned regions, accompanied by serrated stress response and overall softening. Simulations under hypervelocity impact conditions are also conducted to investigate the model's descriptive capabilities of induced complex substructures composing of both twins and dislocations. The simulated nucleation of twins is examined in detail by using duality diagrams in terms of the flow-evolutionary hypothesis.
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Hayenga, Heather N; Thorne, Bryan C; Peirce, Shayn M; Humphrey, Jay D
2011-11-01
There is a need to develop multiscale models of vascular adaptations to understand tissue-level manifestations of cellular level mechanisms. Continuum-based biomechanical models are well suited for relating blood pressures and flows to stress-mediated changes in geometry and properties, but less so for describing underlying mechanobiological processes. Discrete stochastic agent-based models are well suited for representing biological processes at a cellular level, but not for describing tissue-level mechanical changes. We present here a conceptually new approach to facilitate the coupling of continuum and agent-based models. Because of ubiquitous limitations in both the tissue- and cell-level data from which one derives constitutive relations for continuum models and rule-sets for agent-based models, we suggest that model verification should enforce congruency across scales. That is, multiscale model parameters initially determined from data sets representing different scales should be refined, when possible, to ensure that common outputs are consistent. Potential advantages of this approach are illustrated by comparing simulated aortic responses to a sustained increase in blood pressure predicted by continuum and agent-based models both before and after instituting a genetic algorithm to refine 16 objectively bounded model parameters. We show that congruency-based parameter refinement not only yielded increased consistency across scales, it also yielded predictions that are closer to in vivo observations.
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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.
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Milenin, Andrzej; Kopernik, Magdalena
2011-01-01
The prosthesis - pulsatory ventricular assist device (VAD) - is made of polyurethane (PU) and biocompatible TiN deposited by pulsed laser deposition (PLD) method. The paper discusses the numerical modelling and computer-aided design of such an artificial organ. Two types of VADs: POLVAD and POLVAD_EXT are investigated. The main tasks and assumptions of the computer program developed are presented. The multiscale model of VAD based on finite element method (FEM) is introduced and the analysis of the stress-strain state in macroscale for the blood chamber in both versions of VAD is shown, as well as the verification of the results calculated by applying ABAQUS, a commercial FEM code. The FEM code developed is based on a new approach to the simulation of multilayer materials obtained by using PLD method. The model in microscale includes two components, i.e., model of initial stresses (residual stress) caused by the deposition process and simulation of active loadings observed in the blood chamber of POLVAD and POLVAD_EXT. The computed distributions of stresses and strains in macro- and microscales are helpful in defining precisely the regions of blood chamber, which can be defined as the failure-source areas.
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NASA Astrophysics Data System (ADS)
Comer, Joanne; Indiana Olbert, Agnieszka; Nash, Stephen; Hartnett, Michael
2017-02-01
Urban developments in coastal zones are often exposed to natural hazards such as flooding. In this research, a state-of-the-art, multi-scale nested flood (MSN_Flood) model is applied to simulate complex coastal-fluvial urban flooding due to combined effects of tides, surges and river discharges. Cork city on Ireland's southwest coast is a study case. The flood modelling system comprises a cascade of four dynamically linked models that resolve the hydrodynamics of Cork Harbour and/or its sub-region at four scales: 90, 30, 6 and 2 m. Results demonstrate that the internalization of the nested boundary through the use of ghost cells combined with a tailored adaptive interpolation technique creates a highly dynamic moving boundary that permits flooding and drying of the nested boundary. This novel feature of MSN_Flood provides a high degree of choice regarding the location of the boundaries to the nested domain and therefore flexibility in model application. The nested MSN_Flood model through dynamic downscaling facilitates significant improvements in accuracy of model output without incurring the computational expense of high spatial resolution over the entire model domain. The urban flood model provides full characteristics of water levels and flow regimes necessary for flood hazard identification and flood risk assessment.
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SOMAR-LES: A framework for multi-scale modeling of turbulent stratified oceanic flows
NASA Astrophysics Data System (ADS)
Chalamalla, Vamsi K.; Santilli, Edward; Scotti, Alberto; Jalali, Masoud; Sarkar, Sutanu
2017-12-01
A new multi-scale modeling technique, SOMAR-LES, is presented in this paper. Localized grid refinement gives SOMAR (the Stratified Ocean Model with Adaptive Resolution) access to small scales of the flow which are normally inaccessible to general circulation models (GCMs). SOMAR-LES drives a LES (Large Eddy Simulation) on SOMAR's finest grids, forced with large scale forcing from the coarser grids. Three-dimensional simulations of internal tide generation, propagation and scattering are performed to demonstrate this multi-scale modeling technique. In the case of internal tide generation at a two-dimensional bathymetry, SOMAR-LES is able to balance the baroclinic energy budget and accurately model turbulence losses at only 10% of the computational cost required by a non-adaptive solver running at SOMAR-LES's fine grid resolution. This relative cost is significantly reduced in situations with intermittent turbulence or where the location of the turbulence is not known a priori because SOMAR-LES does not require persistent, global, high resolution. To illustrate this point, we consider a three-dimensional bathymetry with grids adaptively refined along the tidally generated internal waves to capture remote mixing in regions of wave focusing. The computational cost in this case is found to be nearly 25 times smaller than that of a non-adaptive solver at comparable resolution. In the final test case, we consider the scattering of a mode-1 internal wave at an isolated two-dimensional and three-dimensional topography, and we compare the results with Legg (2014) numerical experiments. We find good agreement with theoretical estimates. SOMAR-LES is less dissipative than the closure scheme employed by Legg (2014) near the bathymetry. Depending on the flow configuration and resolution employed, a reduction of more than an order of magnitude in computational costs is expected, relative to traditional existing solvers.
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NASA Technical Reports Server (NTRS)
Lawson, John W.; Daw, Murray S.; Squire, Thomas H.; Bauschlicher, Charles W.
2012-01-01
We are developing a multiscale framework in computational modeling for the ultra high temperature ceramics (UHTC) ZrB2 and HfB2. These materials are characterized by high melting point, good strength, and reasonable oxidation resistance. They are candidate materials for a number of applications in extreme environments including sharp leading edges of hypersonic aircraft. In particular, we used a combination of ab initio methods, atomistic simulations and continuum computations to obtain insights into fundamental properties of these materials. Ab initio methods were used to compute basic structural, mechanical and thermal properties. From these results, a database was constructed to fit a Tersoff style interatomic potential suitable for atomistic simulations. These potentials were used to evaluate the lattice thermal conductivity of single crystals and the thermal resistance of simple grain boundaries. Finite element method (FEM) computations using atomistic results as inputs were performed with meshes constructed on SEM images thereby modeling the realistic microstructure. These continuum computations showed the reduction in thermal conductivity due to the grain boundary network.
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Multiscale contact mechanics model for RF-MEMS switches with quantified uncertainties
NASA Astrophysics Data System (ADS)
Kim, Hojin; Huda Shaik, Nurul; Xu, Xin; Raman, Arvind; Strachan, Alejandro
2013-12-01
We introduce a multiscale model for contact mechanics between rough surfaces and apply it to characterize the force-displacement relationship for a metal-dielectric contact relevant for radio frequency micro-electromechanicl system (MEMS) switches. We propose a mesoscale model to describe the history-dependent force-displacement relationships in terms of the surface roughness, the long-range attractive interaction between the two surfaces, and the repulsive interaction between contacting asperities (including elastic and plastic deformation). The inputs to this model are the experimentally determined surface topography and the Hamaker constant as well as the mechanical response of individual asperities obtained from density functional theory calculations and large-scale molecular dynamics simulations. The model captures non-trivial processes including the hysteresis during loading and unloading due to plastic deformation, yet it is computationally efficient enough to enable extensive uncertainty quantification and sensitivity analysis. We quantify how uncertainties and variability in the input parameters, both experimental and theoretical, affect the force-displacement curves during approach and retraction. In addition, a sensitivity analysis quantifies the relative importance of the various input quantities for the prediction of force-displacement during contact closing and opening. The resulting force-displacement curves with quantified uncertainties can be directly used in device-level simulations of micro-switches and enable the incorporation of atomic and mesoscale phenomena in predictive device-scale simulations.
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Probabilistic Methods for Structural Reliability and Risk
NASA Technical Reports Server (NTRS)
Chamis, Christos C.
2010-01-01
A probabilistic method is used to evaluate the structural reliability and risk of select metallic and composite structures. The method is a multiscale, multifunctional and it is based on the most elemental level. A multifactor interaction model is used to describe the material properties which are subsequently evaluated probabilistically. The metallic structure is a two rotor aircraft engine, while the composite structures consist of laminated plies (multiscale) and the properties of each ply are the multifunctional representation. The structural component is modeled by finite element. The solution method for structural responses is obtained by an updated simulation scheme. The results show that the risk for the two rotor engine is about 0.0001 and the composite built-up structure is also 0.0001.
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Probabilistic Methods for Structural Reliability and Risk
NASA Technical Reports Server (NTRS)
Chamis, Christos C.
2008-01-01
A probabilistic method is used to evaluate the structural reliability and risk of select metallic and composite structures. The method is a multiscale, multifunctional and it is based on the most elemental level. A multi-factor interaction model is used to describe the material properties which are subsequently evaluated probabilistically. The metallic structure is a two rotor aircraft engine, while the composite structures consist of laminated plies (multiscale) and the properties of each ply are the multifunctional representation. The structural component is modeled by finite element. The solution method for structural responses is obtained by an updated simulation scheme. The results show that the risk for the two rotor engine is about 0.0001 and the composite built-up structure is also 0.0001.
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Formalizing Knowledge in Multi-Scale Agent-Based Simulations
Somogyi, Endre; Sluka, James P.; Glazier, James A.
2017-01-01
Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused. PMID:29338063
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Formalizing Knowledge in Multi-Scale Agent-Based Simulations.
Somogyi, Endre; Sluka, James P; Glazier, James A
2016-10-01
Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused.
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From Single-Cell Dynamics to Scaling Laws in Oncology
NASA Astrophysics Data System (ADS)
Chignola, Roberto; Sega, Michela; Stella, Sabrina; Vyshemirsky, Vladislav; Milotti, Edoardo
We are developing a biophysical model of tumor biology. We follow a strictly quantitative approach where each step of model development is validated by comparing simulation outputs with experimental data. While this strategy may slow down our advancements, at the same time it provides an invaluable reward: we can trust simulation outputs and use the model to explore territories of cancer biology where current experimental techniques fail. Here, we review our multi-scale biophysical modeling approach and show how a description of cancer at the cellular level has led us to general laws obeyed by both in vitro and in vivo tumors.
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Multi-scale finite element modeling of Eustachian tube function: influence of mucosal adhesion.
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.
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NASA Astrophysics Data System (ADS)
Yoon, H.; Mook, W. M.; Dewers, T. A.
2017-12-01
Multiscale characteristics of textural and compositional (e.g., clay, cement, organics, etc.) heterogeneity profoundly influence the mechanical properties of shale. In particular, strongly anisotropic (i.e., laminated) heterogeneities are often observed to have a significant influence on hydrological and mechanical properties. In this work, we investigate a sample of the Cretaceous Mancos Shale to explore the importance of lamination, cements, organic content, and the spatial distribution of these characteristics. For compositional and structural characterization, the mineralogical distribution of thin core sample polished by ion-milling is analyzed using QEMSCAN® with MAPS MineralogyTM (developed by FEI Corporoation). Based on mineralogy and organic matter distribution, multi-scale nanoindentation testing was performed to directly link compositional heterogeneity to mechanical properties. With FIB-SEM (3D) and high-magnitude SEM (2D) images, key nanoindentation patterns are analyzed to evaluate elastic and plastic responses. Combined with MAPs Mineralogy data and fine-resolution BSE images, nanoindentation results are explained as a function of compositional and structural heterogeneity. Finite element modeling is used to quantitatively evaluate the link between the heterogeneity and mechanical behavior during nanoindentation. In addition, the spatial distribution of compositional heterogeneity, anisotropic bedding patterns, and mechanical anisotropy are employed as inputs for multiscale brittle fracture simulations using a phase field model. Comparison of experimental and numerical simulations reveal that proper incorporation of additional material information, such as bedding layer thickness and other geometrical attributes of the microstructures, may yield improvements on the numerical predictions of the mesoscale fracture patterns and hence the macroscopic effective toughness. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.
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A BAYESIAN STATISTICAL APPROACH FOR THE EVALUATION OF CMAQ
Bayesian statistical methods are used to evaluate Community Multiscale Air Quality (CMAQ) model simulations of sulfate aerosol over a section of the eastern US for 4-week periods in summer and winter 2001. The observed data come from two U.S. Environmental Protection Agency data ...