Biological materials by design.

PubMed

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

2014-02-19

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

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2014-03-01

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

EMISSIONS PROCESSING FOR THE ETA/ CMAQ AIR QUALITY FORECAST SYSTEM

EPA Science Inventory

NOAA and EPA have created an Air Quality Forecast (AQF) system. This AQF system links an adaptation of the EPA's Community Multiscale Air Quality Model with the 12 kilometer ETA model running operationally at NOAA's National Center for Environmental Predication (NCEP). One of the...

Multi-Scale Computational Modeling of Two-Phased Metal Using GMC Method

NASA Technical Reports Server (NTRS)

Moghaddam, Masoud Ghorbani; Achuthan, A.; Bednacyk, B. A.; Arnold, S. M.; Pineda, E. J.

2014-01-01

A multi-scale computational model for determining plastic behavior in two-phased CMSX-4 Ni-based superalloys is developed on a finite element analysis (FEA) framework employing crystal plasticity constitutive model that can capture the microstructural scale stress field. The generalized method of cells (GMC) micromechanics model is used for homogenizing the local field quantities. At first, GMC as stand-alone is validated by analyzing a repeating unit cell (RUC) as a two-phased sample with 72.9% volume fraction of gamma'-precipitate in the gamma-matrix phase and comparing the results with those predicted by finite element analysis (FEA) models incorporating the same crystal plasticity constitutive model. The global stress-strain behavior and the local field quantity distributions predicted by GMC demonstrated good agreement with FEA. High computational saving, at the expense of some accuracy in the components of local tensor field quantities, was obtained with GMC. Finally, the capability of the developed multi-scale model linking FEA and GMC to solve real life sized structures is demonstrated by analyzing an engine disc component and determining the microstructural scale details of the field quantities.

Evaluating the effects of climate change on summertime ozone using a relative reduction factor approach for policymakers

EPA Science Inventory

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 ...

Modeling and Simulation of High Dimensional Stochastic Multiscale PDE Systems at the Exascale

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

Kevrekidis, Ioannis

2017-03-22

The thrust of the proposal was to exploit modern data-mining tools in a way that will create a systematic, computer-assisted approach to the representation of random media -- and also to the representation of the solutions of an array of important physicochemical processes that take place in/on such media. A parsimonious representation/parametrization of the random media links directly (via uncertainty quantification tools) to good sampling of the distribution of random media realizations. It also links directly to modern multiscale computational algorithms (like the equation-free approach that has been developed in our group) and plays a crucial role in accelerating themore » scientific computation of solutions of nonlinear PDE models (deterministic or stochastic) in such media – both solutions in particular realizations of the random media, and estimation of the statistics of the solutions over multiple realizations (e.g. expectations).« less

DTN routing in body sensor networks with dynamic postural partitioning.

PubMed

Quwaider, Muhannad; Biswas, Subir

2010-11-01

This paper presents novel store-and-forward packet routing algorithms for Wireless Body Area Networks ( WBAN ) with frequent postural partitioning. A prototype WBAN has been constructed for experimentally characterizing on-body topology disconnections in the presence of ultra short range radio links, unpredictable RF attenuation, and human postural mobility. On-body DTN routing protocols are then developed using a stochastic link cost formulation, capturing multi-scale topological localities in human postural movements. Performance of the proposed protocols are evaluated experimentally and via simulation, and are compared with a number of existing single-copy DTN routing protocols and an on-body packet flooding mechanism that serves as a performance benchmark with delay lower-bound. It is shown that via multi-scale modeling of the spatio-temporal locality of on-body link disconnection patterns, the proposed algorithms can provide better routing performance compared to a number of existing probabilistic, opportunistic, and utility-based DTN routing protocols in the literature.

THE EMISSION PROCESSING SYSTEM FOR THE ETA/CMAQ AIR QUALITY FORECAST SYSTEM

EPA Science Inventory

NOAA and EPA have created an Air Quality Forecast (AQF) system. This AQF system links an adaptation of the EPA's Community Multiscale Air Quality Model with the 12 kilometer ETA model running operationally at NOAA's National Center for Environmental Predication (NCEP). One of th...

Inferring multi-scale neural mechanisms with brain network modelling

PubMed Central

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

2018-01-01

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

Delineating parameter unidentifiabilities in complex models

NASA Astrophysics Data System (ADS)

Raman, Dhruva V.; Anderson, James; Papachristodoulou, Antonis

2017-03-01

Scientists use mathematical modeling as a tool for understanding and predicting the properties of complex physical systems. In highly parametrized models there often exist relationships between parameters over which model predictions are identical, or nearly identical. These are known as structural or practical unidentifiabilities, respectively. They are hard to diagnose and make reliable parameter estimation from data impossible. They furthermore imply the existence of an underlying model simplification. We describe a scalable method for detecting unidentifiabilities, as well as the functional relations defining them, for generic models. This allows for model simplification, and appreciation of which parameters (or functions thereof) cannot be estimated from data. Our algorithm can identify features such as redundant mechanisms and fast time-scale subsystems, as well as the regimes in parameter space over which such approximations are valid. We base our algorithm on a quantification of regional parametric sensitivity that we call `multiscale sloppiness'. Traditionally, the link between parametric sensitivity and the conditioning of the parameter estimation problem is made locally, through the Fisher information matrix. This is valid in the regime of infinitesimal measurement uncertainty. We demonstrate the duality between multiscale sloppiness and the geometry of confidence regions surrounding parameter estimates made where measurement uncertainty is non-negligible. Further theoretical relationships are provided linking multiscale sloppiness to the likelihood-ratio test. From this, we show that a local sensitivity analysis (as typically done) is insufficient for determining the reliability of parameter estimation, even with simple (non)linear systems. Our algorithm can provide a tractable alternative. We finally apply our methods to a large-scale, benchmark systems biology model of necrosis factor (NF)-κ B , uncovering unidentifiabilities.

A multi-scale framework to link remotely sensed metrics with socioeconomic data

NASA Astrophysics Data System (ADS)

Watmough, Gary; Svenning, Jens-Christian; Palm, Cheryl; Sullivan, Clare; Danylo, Olha; McCallum, Ian

2017-04-01

There is increasing interest in the use of remotely sensed satellite data for estimating human poverty as it can bridge data gaps that prevent fine scale monitoring of development goals across large areas. The ways in which metrics derived from satellite imagery are linked with socioeconomic data are crucial for accurate estimation of poverty. Yet, to date, approaches in the literature linking satellite metrics with socioeconomic data are poorly characterized. Typically, approaches use a GIS approach such as circular buffer zones around a village or household or an administrative boundary such as a district or census enumeration area. These polygons are then used to extract environmental data from satellite imagery and related to the socioeconomic data in statistical analyses. The use of a single polygon to link environment and socioeconomic data is inappropriate in coupled human-natural systems as processes operate over multiple scales. Human interactions with the environment occur at multiple levels from individual (household) access to agricultural plots adjacent to homes, to communal access to common pool resources (CPR) such as forests at the village level. Here, we present a multi-scale framework that explicitly considers how people use the landscape. The framework is presented along with a case study example in Kenya. The multi-scale approach could enhance the modelling of human-environment interactions which will have important consequences for monitoring the sustainable development goals for human livelihoods and biodiversity conservation.

Modeling responses of large-river fish populations to global climate change through downscaling and incorporation of predictive uncertainty

USGS Publications Warehouse

Wildhaber, Mark L.; Wikle, Christopher K.; Anderson, Christopher J.; Franz, Kristie J.; Moran, Edward H.; Dey, Rima; Mader, Helmut; Kraml, Julia

2012-01-01

Climate change operates over a broad range of spatial and temporal scales. Understanding its effects on ecosystems requires multi-scale models. For understanding effects on fish populations of riverine ecosystems, climate predicted by coarse-resolution Global Climate Models must be downscaled to Regional Climate Models to watersheds to river hydrology to population response. An additional challenge is quantifying sources of uncertainty given the highly nonlinear nature of interactions between climate variables and community level processes. We present a modeling approach for understanding and accomodating uncertainty by applying multi-scale climate models and a hierarchical Bayesian modeling framework to Midwest fish population dynamics and by linking models for system components together by formal rules of probability. The proposed hierarchical modeling approach will account for sources of uncertainty in forecasts of community or population response. The goal is to evaluate the potential distributional changes in an ecological system, given distributional changes implied by a series of linked climate and system models under various emissions/use scenarios. This understanding will aid evaluation of management options for coping with global climate change. In our initial analyses, we found that predicted pallid sturgeon population responses were dependent on the climate scenario considered.

Evaluating the Effects of Climate Change on Summertime Ozone using a Relative Response Factor approach for Policy Makers

EPA Science Inventory

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 (RRF_E), which es...

Real-Time Bias-Adjusted O3 and PM2.5 Air Quality Index Forecasts and their Performance Evaluations over the Continental United States

EPA Science Inventory

The National Air Quality Forecast Capacity (NAQFC) system, which links NOAA's North American Mesoscale (NAM) meteorological model with EPA's Community Multiscale Air Quality (CMAQ) model, provided operational ozone (O₃) and experimental fine particular matter (PM_2...

Multiscale model within-host and between-host for viral infectious diseases.

PubMed

Almocera, Alexis Erich S; Nguyen, Van Kinh; Hernandez-Vargas, Esteban A

2018-05-08

Multiscale models possess the potential to uncover new insights into infectious diseases. Here, a rigorous stability analysis of a multiscale model within-host and between-host is presented. The within-host model describes viral replication and the respective immune response while disease transmission is represented by a susceptible-infected model. The bridging of scales from within- to between-host considered transmission as a function of the viral load. Consequently, stability and bifurcation analyses were developed coupling the two basic reproduction numbers [Formula: see text] and [Formula: see text] for the within- and the between-host subsystems, respectively. Local stability results for each subsystem, including a unique stable equilibrium point, recapitulate classical approaches to infection and epidemic control. Using a Lyapunov function, global stability of the between-host system was obtained. Our main result was the derivation of the [Formula: see text] as an increasing function of [Formula: see text]. Numerical analyses reveal that a Michaelis-Menten form based on the virus is more likely to recapitulate the behavior between the scales than a form directly proportional to the virus. Our work contributes basic understandings of the two models and casts light on the potential effects of the coupling function on linking the two scales.

Multi-scale quantum point contact model for filamentary conduction in resistive random access memories devices

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

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

PubMed Central

2013-01-01

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

Degradation of metallic materials studied by correlative tomography

NASA Astrophysics Data System (ADS)

Burnett, T. L.; Holroyd, N. J. H.; Lewandowski, J. J.; Ogurreck, M.; Rau, C.; Kelley, R.; Pickering, E. J.; Daly, M.; Sherry, A. H.; Pawar, S.; Slater, T. J. A.; Withers, P. J.

2017-07-01

There are a huge array of characterization techniques available today and increasingly powerful computing resources allowing for the effective analysis and modelling of large datasets. However, each experimental and modelling tool only spans limited time and length scales. Correlative tomography can be thought of as the extension of correlative microscopy into three dimensions connecting different techniques, each providing different types of information, or covering different time or length scales. Here the focus is on the linking of time lapse X-ray computed tomography (CT) and serial section electron tomography using the focussed ion beam (FIB)-scanning electron microscope to study the degradation of metals. Correlative tomography can provide new levels of detail by delivering a multiscale 3D picture of key regions of interest. Specifically, the Xe+ Plasma FIB is used as an enabling tool for large-volume high-resolution serial sectioning of materials, and also as a tool for preparation of microscale test samples and samples for nanoscale X-ray CT imaging. The exemplars presented illustrate general aspects relating to correlative workflows, as well as to the time-lapse characterisation of metal microstructures during various failure mechanisms, including ductile fracture of steel and the corrosion of aluminium and magnesium alloys. Correlative tomography is already providing significant insights into materials behaviour, linking together information from different instruments across different scales. Multiscale and multifaceted work flows will become increasingly routine, providing a feed into multiscale materials models as well as illuminating other areas, particularly where hierarchical structures are of interest.

On Multiscale Modeling: Preserving Energy Dissipation Across the Scales with Consistent Handshaking Methods

NASA Technical Reports Server (NTRS)

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

2013-01-01

A mesh objective crack band model was implemented within the generalized method of cells micromechanics theory. This model was linked to a macroscale finite element model to predict post-peak strain softening in composite materials. Although a mesh objective theory was implemented at the microscale, it does not preclude pathological mesh dependence at the macroscale. To ensure mesh objectivity at both scales, the energy density and the energy release rate must be preserved identically across the two scales. This requires a consistent characteristic length or localization limiter. The effects of scaling (or not scaling) the dimensions of the microscale repeating unit cell (RUC), according to the macroscale element size, in a multiscale analysis was investigated using two examples. Additionally, the ramifications of the macroscale element shape, compared to the RUC, was studied.

PERFORMANCE AND DIAGNOSTIC EVALUATION OF OZONE PREDICTIONS BY THE ETA-COMMUNITY MULTISCALE AIR QUALITY FORECAST SYSTEM DURING THE 2002 NEW ENGLAND AIR QUALITY STUDY

EPA Science Inventory

A real-time air quality forecasting system (Eta-CMAQ model suite) has been developed by linking the NCEP Eta model to the U.S. EPA CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting O₃ over the northeastern U.S d...

Equation-free and variable free modeling for complex/multiscale systems. Coarse-grained computation in science and engineering using fine-grained models

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

Kevrekidis, Ioannis G.

The work explored the linking of modern developing machine learning techniques (manifold learning and in particular diffusion maps) with traditional PDE modeling/discretization/scientific computation techniques via the equation-free methodology developed by the PI. The result (in addition to several PhD degrees, two of them by CSGF Fellows) was a sequence of strong developments - in part on the algorithmic side, linking data mining with scientific computing, and in part on applications, ranging from PDE discretizations to molecular dynamics and complex network dynamics.

Multiscale characteristics of mechanical and mineralogical heterogeneity using nanoindentation and Maps Mineralogy in Mancos Shale

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.

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

PubMed Central

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

2011-01-01

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

A multiscale modeling approach to inflammation: A case study in human endotoxemia

NASA Astrophysics Data System (ADS)

Scheff, Jeremy D.; Mavroudis, Panteleimon D.; Foteinou, Panagiota T.; An, Gary; Calvano, Steve E.; Doyle, John; Dick, Thomas E.; Lowry, Stephen F.; Vodovotz, Yoram; Androulakis, Ioannis P.

2013-07-01

Inflammation is a critical component in the body's response to injury. A dysregulated inflammatory response, in which either the injury is not repaired or the inflammatory response does not appropriately self-regulate and end, is associated with a wide range of inflammatory diseases such as sepsis. Clinical management of sepsis is a significant problem, but progress in this area has been slow. This may be due to the inherent nonlinearities and complexities in the interacting multiscale pathways that are activated in response to systemic inflammation, motivating the application of systems biology techniques to better understand the inflammatory response. Here, we review our past work on a multiscale modeling approach applied to human endotoxemia, a model of systemic inflammation, consisting of a system of compartmentalized differential equations operating at different time scales and through a discrete model linking inflammatory mediators with changing patterns in the beating of the heart, which has been correlated with outcome and severity of inflammatory disease despite unclear mechanistic underpinnings. Working towards unraveling the relationship between inflammation and heart rate variability (HRV) may enable greater understanding of clinical observations as well as novel therapeutic targets.

Ensuring congruency in multiscale modeling: towards linking agent based and continuum biomechanical models of arterial adaptation.

PubMed

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.

Computational Modeling of Airway and Pulmonary Vascular Structure and Function: Development of a “Lung Physiome”

PubMed Central

Tawhai, M. H.; Clark, A. R.; Donovan, G. M.; Burrowes, K. S.

2011-01-01

Computational models of lung structure and function necessarily span multiple spatial and temporal scales, i.e., dynamic molecular interactions give rise to whole organ function, and the link between these scales cannot be fully understood if only molecular or organ-level function is considered. Here, we review progress in constructing multiscale finite element models of lung structure and function that are aimed at providing a computational framework for bridging the spatial scales from molecular to whole organ. These include structural models of the intact lung, embedded models of the pulmonary airways that couple to model lung tissue, and models of the pulmonary vasculature that account for distinct structural differences at the extra- and intra-acinar levels. Biophysically based functional models for tissue deformation, pulmonary blood flow, and airway bronchoconstriction are also described. The development of these advanced multiscale models has led to a better understanding of complex physiological mechanisms that govern regional lung perfusion and emergent heterogeneity during bronchoconstriction. PMID:22011236

Integrative Systems Models of Cardiac Excitation Contraction Coupling

PubMed Central

Greenstein, Joseph L.; Winslow, Raimond L.

2010-01-01

Excitation-contraction coupling in the cardiac myocyte is mediated by a number of highly integrated mechanisms of intracellular Ca2+ transport. The complexity and integrative nature of heart cell electrophysiology and Ca2+-cycling has led to an evolution of computational models that have played a crucial role in shaping our understanding of heart function. An important emerging theme in systems biology is that the detailed nature of local signaling events, such as those that occur in the cardiac dyad, have important consequences at higher biological scales. Multi-scale modeling techniques have revealed many mechanistic links between micro-scale events, such as Ca2+ binding to a channel protein, and macro-scale phenomena, such as excitation-contraction coupling gain. Here we review experimentally based multi-scale computational models of excitation-contraction coupling and the insights that have been gained through their application. PMID:21212390

Multiscale Modeling: A Review

NASA Astrophysics Data System (ADS)

Horstemeyer, M. F.

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

Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation.

PubMed

An, Gary

2008-05-27

One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM) can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure. ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems. A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior in the intensive care setting. The ABMs all utilize cell-level agents that encapsulate specific mechanistic knowledge extracted from in vitro experiments. The execution of the ABMs results in a dynamic representation of the multi-scale conceptual models derived from those experiments. These models represent a qualitative means of integrating basic scientific information on acute inflammation in a multi-scale, modular architecture as a means of conceptual model verification that can potentially be used to concatenate, communicate and advance community-wide knowledge.

A multiscale framework based on the physiome markup languages for exploring the initiation of osteoarthritis at the bone-cartilage interface.

PubMed

Shim, Vickie B; Hunter, Peter J; Pivonka, Peter; Fernandez, Justin W

2011-12-01

The initiation of osteoarthritis (OA) has been linked to the onset and progression of pathologic mechanisms at the cartilage-bone interface. Most importantly, this degenerative disease involves cross-talk between the cartilage and subchondral bone environments, so an informative model should contain the complete complex. In order to evaluate this process, we have developed a multiscale model using the open-source ontologies developed for the Physiome Project with cartilage and bone descriptions at the cellular, micro, and macro levels. In this way, we can effectively model the influence of whole body loadings at the macro level and the influence of bone organization and architecture at the micro level, and have cell level processes that determine bone and cartilage remodeling. Cell information is then passed up the spatial scales to modify micro architecture and provide a macro spatial characterization of cartilage inflammation. We evaluate the framework by linking a common knee injury (anterior cruciate ligament deficiency) to proinflammatory mediators as a possible pathway to initiate OA. This framework provides a "virtual bone-cartilage" tool for evaluating hypotheses, treatment effects, and disease onset to inform and strengthen clinical studies.

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

PubMed

Lu, Zhao; Sun, Jing; Butts, Kenneth

2016-02-03

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

A Hybrid Multiscale Framework for Subsurface Flow and Transport Simulations

DOE PAGES

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

2015-06-01

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

Information Management Workflow and Tools Enabling Multiscale Modeling Within ICME Paradigm

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Bednarcyk, Brett A.; Austin, Nic; Terentjev, Igor; Cebon, Dave; Marsden, Will

2016-01-01

With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Fortunately, material information management systems and physics-based multiscale modeling methods have kept pace with the growing user demands. Herein, recent efforts to establish workflow for and demonstrate a unique set of web application tools for linking NASA GRC's Integrated Computational Materials Engineering (ICME) Granta MI database schema and NASA GRC's Integrated multiscale Micromechanics Analysis Code (ImMAC) software toolset are presented. The goal is to enable seamless coupling between both test data and simulation data, which is captured and tracked automatically within Granta MI®, with full model pedigree information. These tools, and this type of linkage, are foundational to realizing the full potential of ICME, in which materials processing, microstructure, properties, and performance are coupled to enable application-driven design and optimization of materials and structures.

The Potential Link Between High Angle Grain Boundary Morphology and Grain Boundary Deformation in a Nickel-Based Superalloy (Postprint)

DTIC Science & Technology

2015-06-01

Ghosh, M.K. Samal , Multiscale Crystal Plasticity Modeling of Microtwinning Induced Deformation in Gamma–Gamma Prime Nickel Based Superalloys, Shanghai...University, Shanghai, Peoples Republic of China, 2011, pp. 487–488. [3] H. Deuchman, P.J. Phillips, N. Zhou, M. Samal , S. Ghosh, Y. Wang, M.J. Mills

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

NASA Astrophysics Data System (ADS)

Macioł, Piotr; Regulski, Krzysztof

2016-08-01

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

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

NASA Technical Reports Server (NTRS)

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

2017-01-01

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

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

Antonelli, Perry Edward

A low-level model-to-model interface is presented that will enable independent models to be linked into an integrated system of models. The interface is based on a standard set of functions that contain appropriate export and import schemas that enable models to be linked with no changes to the models themselves. These ideas are presented in the context of a specific multiscale material problem that couples atomistic-based molecular dynamics calculations to continuum calculations of fluid ow. These simulations will be used to examine the influence of interactions of the fluid with an adjacent solid on the fluid ow. The interface willmore » also be examined by adding it to an already existing modeling code, Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and comparing it with our own molecular dynamics code.« less

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

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.

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

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

Andrade, José E; Rudnicki, John W

2012-12-14

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

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).

Multiscale systems biology of trauma-induced coagulopathy.

PubMed

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.

Simulating secondary waterflooding in heterogeneous rocks with variable wettability using an image-based, multiscale pore network model

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.

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

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

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

2009-05-01

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

A complete categorization of multiscale models of infectious disease systems.

PubMed

Garira, Winston

2017-12-01

Modelling of infectious disease systems has entered a new era in which disease modellers are increasingly turning to multiscale modelling to extend traditional modelling frameworks into new application areas and to achieve higher levels of detail and accuracy in characterizing infectious disease systems. In this paper we present a categorization framework for categorizing multiscale models of infectious disease systems. The categorization framework consists of five integration frameworks and five criteria. We use the categorization framework to give a complete categorization of host-level immuno-epidemiological models (HL-IEMs). This categorization framework is also shown to be applicable in categorizing other types of multiscale models of infectious diseases beyond HL-IEMs through modifying the initial categorization framework presented in this study. Categorization of multiscale models of infectious disease systems in this way is useful in bringing some order to the discussion on the structure of these multiscale models.

Role of weakest links and system-size scaling in multiscale modeling of stochastic plasticity

NASA Astrophysics Data System (ADS)

Ispánovity, Péter Dusán; Tüzes, Dániel; Szabó, Péter; Zaiser, Michael; Groma, István

2017-02-01

Plastic deformation of crystalline and amorphous matter often involves intermittent local strain burst events. To understand the physical background of the phenomenon a minimal stochastic mesoscopic model was introduced, where details of the microstructure evolution are statistically represented in terms of a fluctuating local yield threshold. In the present paper we propose a method for determining the corresponding yield stress distribution for the case of crystal plasticity from lower scale discrete dislocation dynamics simulations which we combine with weakest link arguments. The success of scale linking is demonstrated by comparing stress-strain curves obtained from the resulting mesoscopic and the underlying discrete dislocation models in the microplastic regime. As shown by various scaling relations they are statistically equivalent and behave identically in the thermodynamic limit. The proposed technique is expected to be applicable to different microstructures and also to amorphous materials.

A Multiscale Computational Model Combining a Single Crystal Plasticity Constitutive Model with the Generalized Method of Cells (GMC) for Metallic Polycrystals.

PubMed

Ghorbani Moghaddam, Masoud; Achuthan, Ajit; Bednarcyk, Brett A; Arnold, Steven M; Pineda, Evan J

2016-05-04

A multiscale computational model is developed for determining the elasto-plastic behavior of polycrystal metals by employing a single crystal plasticity constitutive model that can capture the microstructural scale stress field on a finite element analysis (FEA) framework. The generalized method of cells (GMC) micromechanics model is used for homogenizing the local field quantities. At first, the stand-alone GMC is applied for studying simple material microstructures such as a repeating unit cell (RUC) containing single grain or two grains under uniaxial loading conditions. For verification, the results obtained by the stand-alone GMC are compared to those from an analogous FEA model incorporating the same single crystal plasticity constitutive model. This verification is then extended to samples containing tens to hundreds of grains. The results demonstrate that the GMC homogenization combined with the crystal plasticity constitutive framework is a promising approach for failure analysis of structures as it allows for properly predicting the von Mises stress in the entire RUC, in an average sense, as well as in the local microstructural level, i.e. , each individual grain. Two-three orders of saving in computational cost, at the expense of some accuracy in prediction, especially in the prediction of the components of local tensor field quantities and the quantities near the grain boundaries, was obtained with GMC. Finally, the capability of the developed multiscale model linking FEA and GMC to solve real-life-sized structures is demonstrated by successfully analyzing an engine disc component and determining the microstructural scale details of the field quantities.

A Multiscale Computational Model Combining a Single Crystal Plasticity Constitutive Model with the Generalized Method of Cells (GMC) for Metallic Polycrystals

PubMed Central

Ghorbani Moghaddam, Masoud; Achuthan, Ajit; Bednarcyk, Brett A.; Arnold, Steven M.; Pineda, Evan J.

2016-01-01

A multiscale computational model is developed for determining the elasto-plastic behavior of polycrystal metals by employing a single crystal plasticity constitutive model that can capture the microstructural scale stress field on a finite element analysis (FEA) framework. The generalized method of cells (GMC) micromechanics model is used for homogenizing the local field quantities. At first, the stand-alone GMC is applied for studying simple material microstructures such as a repeating unit cell (RUC) containing single grain or two grains under uniaxial loading conditions. For verification, the results obtained by the stand-alone GMC are compared to those from an analogous FEA model incorporating the same single crystal plasticity constitutive model. This verification is then extended to samples containing tens to hundreds of grains. The results demonstrate that the GMC homogenization combined with the crystal plasticity constitutive framework is a promising approach for failure analysis of structures as it allows for properly predicting the von Mises stress in the entire RUC, in an average sense, as well as in the local microstructural level, i.e., each individual grain. Two–three orders of saving in computational cost, at the expense of some accuracy in prediction, especially in the prediction of the components of local tensor field quantities and the quantities near the grain boundaries, was obtained with GMC. Finally, the capability of the developed multiscale model linking FEA and GMC to solve real-life-sized structures is demonstrated by successfully analyzing an engine disc component and determining the microstructural scale details of the field quantities. PMID:28773458

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

PubMed Central

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

2012-01-01

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

Microphysics in Multi-scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2012-01-01

Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.

Community Multiscale Air Quality Model

EPA Science Inventory

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

Novel Multiscale Modeling Tool Applied to Pseudomonas aeruginosa Biofilm Formation

PubMed Central

Biggs, Matthew B.; Papin, Jason A.

2013-01-01

Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool. PMID:24147108

Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.

PubMed

Biggs, Matthew B; Papin, Jason A

2013-01-01

Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool.

An approach to multiscale modelling with graph grammars.

PubMed

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

2014-09-01

Functional-structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.

An approach to multiscale modelling with graph grammars

PubMed Central

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

2014-01-01

Background and Aims Functional–structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. Methods A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Key Results Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. Conclusions The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models. PMID:25134929

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

PubMed Central

Ruan, Chunlei

2018-01-01

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

Multilayer Brain Networks

NASA Astrophysics Data System (ADS)

Vaiana, Michael; Muldoon, Sarah Feldt

2018-01-01

The field of neuroscience is facing an unprecedented expanse in the volume and diversity of available data. Traditionally, network models have provided key insights into the structure and function of the brain. With the advent of big data in neuroscience, both more sophisticated models capable of characterizing the increasing complexity of the data and novel methods of quantitative analysis are needed. Recently, multilayer networks, a mathematical extension of traditional networks, have gained increasing popularity in neuroscience due to their ability to capture the full information of multi-model, multi-scale, spatiotemporal data sets. Here, we review multilayer networks and their applications in neuroscience, showing how incorporating the multilayer framework into network neuroscience analysis has uncovered previously hidden features of brain networks. We specifically highlight the use of multilayer networks to model disease, structure-function relationships, network evolution, and link multi-scale data. Finally, we close with a discussion of promising new directions of multilayer network neuroscience research and propose a modified definition of multilayer networks designed to unite and clarify the use of the multilayer formalism in describing real-world systems.

An aquatic multiscale assessment and planning framework approach—forest plan revision case study

Treesearch

Kerry Overton; Ann D. Carlson; Cynthia Tait

2010-01-01

The Aquatic Multiscale Assessment and Planning Framework is a Web-based decision-support tool developed to assist aquatic practitioners in managing fisheries and watershed information. This tool, or framework, was designed to assist resource assessments and planning efforts from the broad scale to the fine scale, to document procedures, and to link directly to relevant...

Towards a Multiscale Approach to Cybersecurity Modeling

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

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

2013-11-12

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

Filters for Improvement of Multiscale Data from Atomistic Simulations

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

Gardner, David J.; Reynolds, Daniel R.

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

Filters for Improvement of Multiscale Data from Atomistic Simulations

DOE PAGES

Gardner, David J.; Reynolds, Daniel R.

2017-01-05

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

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.

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

PubMed Central

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

2017-01-01

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

Large-scale inverse and forward modeling of adaptive resonance in the tinnitus decompensation.

PubMed

Low, Yin Fen; Trenado, Carlos; Delb, Wolfgang; D'Amelio, Roberto; Falkai, Peter; Strauss, Daniel J

2006-01-01

Neural correlates of psychophysiological tinnitus models in humans may be used for their neurophysiological validation as well as for their refinement and improvement to better understand the pathogenesis of the tinnitus decompensation and to develop new therapeutic approaches. In this paper we make use of neural correlates of top-down projections, particularly, a recently introduced synchronization stability measure, together with a multiscale evoked response potential (ERP) model in order to study and evaluate the tinnitus decompensation by using a hybrid inverse-forward mathematical methodology. The neural synchronization stability, which according to the underlying model is linked to the focus of attention on the tinnitus signal, follows the experimental and inverse way and allows to discriminate between a group of compensated and decompensated tinnitus patients. The multiscale ERP model, which works in the forward direction, is used to consolidate hypotheses which are derived from the experiments for a known neural source dynamics related to attention. It is concluded that both methodologies agree and support each other in the description of the discriminatory character of the neural correlate proposed, but also help to fill the gap between the top-down adaptive resonance theory and the Jastreboff model of tinnitus.

Accessible, almost ab initio multi-scale modeling of entangled polymers via slip-links

NASA Astrophysics Data System (ADS)

Andreev, Marat

It is widely accepted that dynamics of entangled polymers can be described by the tube model. Here we advocate for an alternative approach to entanglement modeling known as slip-links. Recently, slip-links were shown to possess important advantages over tube models, namely they have strong connections to atomistic, multichain levels of description, agree with non-equilibrium thermodynamics, are applicable to any chain architecture and can be used in linear or non-linear rheology. We present a hierarchy of slip-link models that are connected to each other through successive coarse graining. Models in the hierarchy are consistent in their overlapping domains of applicability in order to allow a straightforward mapping of parameters. In particular, the most--detailed level of description has four parameters, three of which can be determined directly from atomistic simulations. On the other hand, the least--detailed member of the hierarchy is numerically accessible, and allows for non-equilibrium flow predictions of complex chain architectures. Using GPU implementation these predictions can be obtained in minutes of computational time on a single desktop equipped with a mainstream gaming GPU. The GPU code is available online for free download.

Linking Air Quality and Human Health Effects Models: An Application to the Los Angeles Air Basin

PubMed Central

Stewart, Devoun R; Saunders, Emily; Perea, Roberto A; Fitzgerald, Rosa; Campbell, David E; Stockwell, William R

2017-01-01

Proposed emission control strategies for reducing ozone and particulate matter are evaluated better when air quality and health effects models are used together. The Community Multiscale Air Quality (CMAQ) model is the US Environmental Protection Agency’s model for determining public policy and forecasting air quality. CMAQ was used to forecast air quality changes due to several emission control strategies that could be implemented between 2008 and 2030 for the South Coast Air Basin that includes Los Angeles. The Environmental Benefits Mapping and Analysis Program—Community Edition (BenMAP-CE) was used to estimate health and economic impacts of the different emission control strategies based on CMAQ simulations. BenMAP-CE is a computer program based on epidemiologic studies that link human health and air quality. This modeling approach is better for determining optimum public policy than approaches that only examine concentration changes. PMID:29162976

Linking Air Quality and Human Health Effects Models: An Application to the Los Angeles Air Basin.

PubMed

Stewart, Devoun R; Saunders, Emily; Perea, Roberto A; Fitzgerald, Rosa; Campbell, David E; Stockwell, William R

2017-01-01

Proposed emission control strategies for reducing ozone and particulate matter are evaluated better when air quality and health effects models are used together. The Community Multiscale Air Quality (CMAQ) model is the US Environmental Protection Agency's model for determining public policy and forecasting air quality. CMAQ was used to forecast air quality changes due to several emission control strategies that could be implemented between 2008 and 2030 for the South Coast Air Basin that includes Los Angeles. The Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) was used to estimate health and economic impacts of the different emission control strategies based on CMAQ simulations. BenMAP-CE is a computer program based on epidemiologic studies that link human health and air quality. This modeling approach is better for determining optimum public policy than approaches that only examine concentration changes.

Integrating Multiscale Modeling with Drug Effects for Cancer Treatment.

PubMed

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

2015-01-01

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

Engineering Digestion: Multiscale Processes of Food Digestion.

PubMed

Bornhorst, Gail M; Gouseti, Ourania; Wickham, Martin S J; Bakalis, Serafim

2016-03-01

Food digestion is a complex, multiscale process that has recently become of interest to the food industry due to the developing links between food and health or disease. Food digestion can be studied by using either in vitro or in vivo models, each having certain advantages or disadvantages. The recent interest in food digestion has resulted in a large number of studies in this area, yet few have provided an in-depth, quantitative description of digestion processes. To provide a framework to develop these quantitative comparisons, a summary is given here between digestion processes and parallel unit operations in the food and chemical industry. Characterization parameters and phenomena are suggested for each step of digestion. In addition to the quantitative characterization of digestion processes, the multiscale aspect of digestion must also be considered. In both food systems and the gastrointestinal tract, multiple length scales are involved in food breakdown, mixing, absorption. These different length scales influence digestion processes independently as well as through interrelated mechanisms. To facilitate optimized development of functional food products, a multiscale, engineering approach may be taken to describe food digestion processes. A framework for this approach is described in this review, as well as examples that demonstrate the importance of process characterization as well as the multiple, interrelated length scales in the digestion process. © 2016 Institute of Food Technologists®

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.

Coarse-Grained Models for Protein-Cell Membrane Interactions

PubMed Central

Bradley, Ryan; Radhakrishnan, Ravi

2015-01-01

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

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

PubMed

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

2011-01-01

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

Development of high-resolution multi-scale modelling system for simulation of coastal-fluvial urban flooding

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.

Intercomparison of Multiscale Modeling Approaches in Simulating Subsurface Flow and Transport

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Multiscale Materials Modeling Workshop Summary

DOT National Transportation Integrated Search

2013-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

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

PubMed

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

2017-07-01

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

Modelling future impacts of air pollution using the multi-scale UK Integrated Assessment Model (UKIAM).

PubMed

Oxley, Tim; Dore, Anthony J; ApSimon, Helen; Hall, Jane; Kryza, Maciej

2013-11-01

Integrated assessment modelling has evolved to support policy development in relation to air pollutants and greenhouse gases by providing integrated simulation tools able to produce quick and realistic representations of emission scenarios and their environmental impacts without the need to re-run complex atmospheric dispersion models. The UK Integrated Assessment Model (UKIAM) has been developed to investigate strategies for reducing UK emissions by bringing together information on projected UK emissions of SO2, NOx, NH3, PM10 and PM2.5, atmospheric dispersion, criteria for protection of ecosystems, urban air quality and human health, and data on potential abatement measures to reduce emissions, which may subsequently be linked to associated analyses of costs and benefits. We describe the multi-scale model structure ranging from continental to roadside, UK emission sources, atmospheric dispersion of emissions, implementation of abatement measures, integration with European-scale modelling, and environmental impacts. The model generates outputs from a national perspective which are used to evaluate alternative strategies in relation to emissions, deposition patterns, air quality metrics and ecosystem critical load exceedance. We present a selection of scenarios in relation to the 2020 Business-As-Usual projections and identify potential further reductions beyond those currently being planned. © 2013.

A multiscale modeling study of particle size effects on the tissue penetration efficacy of drug-delivery nanoparticles.

PubMed

Islam, Mohammad Aminul; Barua, Sutapa; Barua, Dipak

2017-11-25

Particle size is a key parameter for drug-delivery nanoparticle design. It is believed that the size of a nanoparticle may have important effects on its ability to overcome the transport barriers in biological tissues. Nonetheless, such effects remain poorly understood. Using a multiscale model, this work investigates particle size effects on the tissue distribution and penetration efficacy of drug-delivery nanoparticles. We have developed a multiscale spatiotemporal model of nanoparticle transport in biological tissues. The model implements a time-adaptive Brownian Dynamics algorithm that links microscale particle-cell interactions and adhesion dynamics to tissue-scale particle dispersion and penetration. The model accounts for the advection, diffusion, and cellular uptakes of particles. Using the model, we have analyzed how particle size affects the intra-tissue dispersion and penetration of drug delivery nanoparticles. We focused on two published experimental works that investigated particle size effects in in vitro and in vivo tissue conditions. By analyzing experimental data reported in these two studies, we show that particle size effects may appear pronounced in an in vitro cell-free tissue system, such as collagen matrix. In an in vivo tissue system, the effects of particle size could be relatively modest. We provide a detailed analysis on how particle-cell interactions may determine distribution and penetration of nanoparticles in a biological tissue. Our work suggests that the size of a nanoparticle may play a less significant role in its ability to overcome the intra-tissue transport barriers. We show that experiments involving cell-free tissue systems may yield misleading observations of particle size effects due to the absence of advective transport and particle-cell interactions.

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.

EEG functional connectivity, axon delays and white matter disease.

PubMed

Nunez, Paul L; Srinivasan, Ramesh; Fields, R Douglas

2015-01-01

Both structural and functional brain connectivities are closely linked to white matter disease. We discuss several such links of potential interest to neurologists, neurosurgeons, radiologists, and non-clinical neuroscientists. Treatment of brains as genuine complex systems suggests major emphasis on the multi-scale nature of brain connectivity and dynamic behavior. Cross-scale interactions of local, regional, and global networks are apparently responsible for much of EEG's oscillatory behaviors. Finite axon propagation speed, often assumed to be infinite in local network models, is central to our conceptual framework. Myelin controls axon speed, and the synchrony of impulse traffic between distant cortical regions appears to be critical for optimal mental performance and learning. Several experiments suggest that axon conduction speed is plastic, thereby altering the regional and global white matter connections that facilitate binding of remote local networks. Combined EEG and high resolution EEG can provide distinct multi-scale estimates of functional connectivity in both healthy and diseased brains with measures like frequency and phase spectra, covariance, and coherence. White matter disease may profoundly disrupt normal EEG coherence patterns, but currently these kinds of studies are rare in scientific labs and essentially missing from clinical environments. Copyright © 2014 International Federation of Clinical Neurophysiology. All rights reserved.

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

PubMed

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

2015-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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

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

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

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

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

DOE PAGES

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

2018-02-04

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

On the sub-model errors of a generalized one-way coupling scheme for linking models at different scales

NASA Astrophysics Data System (ADS)

Zeng, Jicai; Zha, Yuanyuan; Zhang, Yonggen; Shi, Liangsheng; Zhu, Yan; Yang, Jinzhong

2017-11-01

Multi-scale modeling of the localized groundwater flow problems in a large-scale aquifer has been extensively investigated under the context of cost-benefit controversy. An alternative is to couple the parent and child models with different spatial and temporal scales, which may result in non-trivial sub-model errors in the local areas of interest. Basically, such errors in the child models originate from the deficiency in the coupling methods, as well as from the inadequacy in the spatial and temporal discretizations of the parent and child models. In this study, we investigate the sub-model errors within a generalized one-way coupling scheme given its numerical stability and efficiency, which enables more flexibility in choosing sub-models. To couple the models at different scales, the head solution at parent scale is delivered downward onto the child boundary nodes by means of the spatial and temporal head interpolation approaches. The efficiency of the coupling model is improved either by refining the grid or time step size in the parent and child models, or by carefully locating the sub-model boundary nodes. The temporal truncation errors in the sub-models can be significantly reduced by the adaptive local time-stepping scheme. The generalized one-way coupling scheme is promising to handle the multi-scale groundwater flow problems with complex stresses and heterogeneity.

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

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

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

2015-01-01

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

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.

Multiscale hidden Markov models for photon-limited imaging

NASA Astrophysics Data System (ADS)

Nowak, Robert D.

1999-06-01

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

CellML metadata standards, associated tools and repositories

PubMed Central

Beard, Daniel A.; Britten, Randall; Cooling, Mike T.; Garny, Alan; Halstead, Matt D.B.; Hunter, Peter J.; Lawson, James; Lloyd, Catherine M.; Marsh, Justin; Miller, Andrew; Nickerson, David P.; Nielsen, Poul M.F.; Nomura, Taishin; Subramanium, Shankar; Wimalaratne, Sarala M.; Yu, Tommy

2009-01-01

The development of standards for encoding mathematical models is an important component of model building and model sharing among scientists interested in understanding multi-scale physiological processes. CellML provides such a standard, particularly for models based on biophysical mechanisms, and a substantial number of models are now available in the CellML Model Repository. However, there is an urgent need to extend the current CellML metadata standard to provide biological and biophysical annotation of the models in order to facilitate model sharing, automated model reduction and connection to biological databases. This paper gives a broad overview of a number of new developments on CellML metadata and provides links to further methodological details available from the CellML website. PMID:19380315

Multiscale modelling in immunology: a review.

PubMed

Cappuccio, Antonio; Tieri, Paolo; Castiglione, Filippo

2016-05-01

One of the greatest challenges in biomedicine is to get a unified view of observations made from the molecular up to the organism scale. Towards this goal, multiscale models have been highly instrumental in contexts such as the cardiovascular field, angiogenesis, neurosciences and tumour biology. More recently, such models are becoming an increasingly important resource to address immunological questions as well. Systematic mining of the literature in multiscale modelling led us to identify three main fields of immunological applications: host-virus interactions, inflammatory diseases and their treatment and development of multiscale simulation platforms for immunological research and for educational purposes. Here, we review the current developments in these directions, which illustrate that multiscale models can consistently integrate immunological data generated at several scales, and can be used to describe and optimize therapeutic treatments of complex immune diseases. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Wavefield complexity and stealth structures: Resolution constraints by wave physics

NASA Astrophysics Data System (ADS)

Nissen-Meyer, T.; Leng, K.

2017-12-01

Imaging the Earth's interior relies on understanding how waveforms encode information from heterogeneous multi-scale structure. This relation is given by elastodynamics, but forward modeling in the context of tomography primarily serves to deliver synthetic waveforms and gradients for the inversion procedure. While this is entirely appropriate, it depreciates a wealth of complementary inference that can be obtained from the complexity of the wavefield. Here, we are concerned with the imprint of realistic multi-scale Earth structure on the wavefield, and the question on the inherent physical resolution limit of structures encoded in seismograms. We identify parameter and scattering regimes where structures remain invisible as a function of seismic wavelength, structural multi-scale geometry, scattering strength, and propagation path. Ultimately, this will aid in interpreting tomographic images by acknowledging the scope of "forgotten" structures, and shall offer guidance for optimising the selection of seismic data for tomography. To do so, we use our novel 3D modeling method AxiSEM3D which tackles global wave propagation in visco-elastic, anisotropic 3D structures with undulating boundaries at unprecedented resolution and efficiency by exploiting the inherent azimuthal smoothness of wavefields via a coupled Fourier expansion-spectral-element approach. The method links computational cost to wavefield complexity and thereby lends itself well to exploring the relation between waveforms and structures. We will show various examples of multi-scale heterogeneities which appear or disappear in the waveform, and argue that the nature of the structural power spectrum plays a central role in this. We introduce the concept of wavefield learning to examine the true wavefield complexity for a complexity-dependent modeling framework and discriminate which scattering structures can be retrieved by surface measurements. This leads to the question of physical invisibility and the tomographic resolution limit, and offers insight as to why tomographic images still show stark differences for smaller-scale heterogeneities despite progress in modeling and data resolution. Finally, we give an outlook on how we expand this modeling framework towards an inversion procedure guided by wavefield complexity.

Performance of distributed multiscale simulations

PubMed Central

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

2014-01-01

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

Module-based multiscale simulation of angiogenesis in skeletal muscle

PubMed Central

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

Crystallization of isotactic polypropylene in different shear regimes

NASA Astrophysics Data System (ADS)

Spina, Roberto; Spekowius, Marcel; Hopmann, Christian

2017-10-01

The investigation of the shear-induced crystallization of isotactic polypropylene in isothermal conditions in different shear regimes is the aim of the present research. A multiscale framework is developed and implemented to compute the nucleation and growth of spherulites, based on material parameters needed to connect crystallization kinetics to the molecular material properties. The framework consists of a macro-model based on a Finite Element Method linked to a micro-model based on Cellular Automata. The main results are the evolution of the crystallization degree and spherulite space filling as a function of imposed temperature ash shear rate.

Multiscale Modeling in the Clinic: Drug Design and Development

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

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

A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multi-scale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multi-scale approaches present in silico opportunities to advance laboratory research to bedside clinical applications in pharmaceuticals research. This is achievable through the capability of modeling to reveal phenomena occurring across multiple spatial and temporal scales, which are not otherwise readily accessible to experimentation. The resultant models, when validated, are capable of making testable predictions tomore » guide drug design and delivery. In this review we describe the goals, methods, and opportunities of multi-scale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical techniques employed for multi-scale modeling approaches used in pharmacology and present several examples illustrating the current state-of-the-art regarding drug development for: Excitable Systems (Heart); Cancer (Metastasis and Differentiation); Cancer (Angiogenesis and Drug Targeting); Metabolic Disorders; and Inflammation and Sepsis. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multi-scale models.« less

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

PubMed

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

2017-11-01

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

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

PubMed

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

2017-12-07

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

Characterization of Cyclohexanone Inclusions in Class 1 RDX

DTIC Science & Technology

2014-06-01

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

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

PubMed

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

2016-09-01

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

Multiscale Models in the Biomechanics of Plant Growth

PubMed Central

Fozard, John A.

2015-01-01

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

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

PubMed

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

2015-02-01

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

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

PubMed

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

2016-09-01

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

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

PubMed Central

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

2016-01-01

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

Modeling Framework for Fracture in Multiscale Cement-Based Material Structures

PubMed Central

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

2017-01-01

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

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.

Fluorescence Across Space and Time (2017 FAST Campaign): Investigating the multiscale links between fluorescence and photosynthesis

NASA Astrophysics Data System (ADS)

Porcar-Castell, A.; Atherton, J.; Rajewicz, P. A.; Riikonen, A.; Gebre, S.; Liu, W.; Aalto, J.; Bendoula, R.; Burkart, A.; Chen, H.; Erkkilä, K. M.; Feret, J. B.; Fernández-Marín, B.; García-Plazaola, J. I.; Hakala, T.; Hartikainen, S.; Honkavaara, E.; Ihalainen, J.; Julitta, T.; Kolari, P.; Kooijmans, L.; Levula, J.; Loponen, M.; Mac Arthur, A.; Magney, T.; Maseyk, K. S.; Mottus, M.; Neimane, S.; Oksa, E.; Osterman, G. B.; Robinson, I.; Robson, M. T.; Sabater, N.; Solanki, T.; Tikkanen, M.; Mäkipää, R.; Aro, E. M.; Rascher, U.; Frankenberg, C.; Kulmala, M. T.; Vesala, T.; Back, J. K.

2017-12-01

The use of solar-induced chlorophyll fluorescence (ChlF) as a tracer of photosynthesis is rapidly expanding with increasing numbers of measurements from towers, drones, aircrafts, or satellites. But how to integrate all the informative potential of these multiscale datasets? The connection between ChlF and photosynthesis takes place via multiple mechansisms that depend on the scale. At the leaf level, diurnal variations in ChlF may indicate changes in photochemical or non-photochemical quenching processes, whereas seasonal variations may indicate changes in the protein structure or pigment composition of the photosynthetic apparatus. At the canopy level, variations in ChlF may also reflect changes in total leaf area, canopy structure, species composition, changes in illumination or sun-target-sensor geometry, background properties, etc. At the pixel level, the dynamics of the atmosphere are also important. It is therefore essential to characterize the impact of factors that control ChlF and photosynthesis at each scale. A combination of multiscale and continuous experimentation and modelling is probably the best option to close the remaining knowledge gaps. The goal of the FAST campaign was to characterize the processes that control the ChlF signal dynamics at each scale, establishing a comprehensive dataset for multiscale hypothesis and model validation. The campaign took place in Hyytiälä (Southern Finland) and lasted for 6 months. Measurements expanded from the molecular to the satellite pixel level and from the picosecond to the seasonal scale, including multiple species, and providing a unique optical and phenomenological record of the multiscale spring recovery of photosynthesis in a boreal forest. Amongst others we measured and registered: leaf ChlF spectra, OJIP kinetics, PSI and PSII activity, photosynthetic gas exchange, carbonyl sulphide (COS), volatile organic compounds (VOCs), total leaf absorption, pigment concentrations, photosynthetic proteins, fluorescence lifetime, canopy SIF, CO2, water, COS, and VOC fluxes, as well as vertical profiles of forest SIF using a drone and target OCO-2 observations at 1x2km pixel resolution. We here present preliminary results from the FAST campaign which emphasize the variability and role of different controls across scales.

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

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

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

It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale mediummore » property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.« less

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

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

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

It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale mediummore » property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.« less

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

DOE PAGES

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

2015-04-14

It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale mediummore » property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.« less

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

Treesearch

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

2016-01-01

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

Microphysics in the Multi-Scale Modeling Systems with Unified Physics

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

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

EPA Pesticide Factsheets

We describe a multi-scale framework for modeling acetaminophen-induced liver toxicity. Acetaminophen is a widely used analgesic. Overdose of acetaminophen can result in liver injury via its biotransformation into toxic product, which further induce massive necrosis. Our study focuses on developing a multi-scale computational model to characterize both phase I and phase II metabolism of acetaminophen, by bridging Physiologically Based Pharmacokinetic (PBPK) modeling at the whole body level, cell movement and blood flow at the tissue level and cell signaling and drug metabolism at the sub-cellular level. To validate the model, we estimated our model parameters by fi?tting serum concentrations of acetaminophen and its glucuronide and sulfate metabolites to experiments, and carried out sensitivity analysis on 35 parameters selected from three modules. Our study focuses on developing a multi-scale computational model to characterize both phase I and phase II metabolism of acetaminophen, by bridging Physiologically Based Pharmacokinetic (PBPK) modeling at the whole body level, cell movement and blood flow at the tissue level and cell signaling and drug metabolism at the sub-cellular level. This multiscale model bridges the CompuCell3D tool used by the Virtual Tissue project with the httk tool developed by the Rapid Exposure and Dosimetry project.

A bidirectional coupling procedure applied to multiscale respiratory modeling

NASA Astrophysics Data System (ADS)

Kuprat, A. P.; Kabilan, S.; Carson, J. P.; Corley, R. A.; Einstein, D. R.

2013-07-01

In this study, we present a novel multiscale computational framework for efficiently linking multiple lower-dimensional models describing the distal lung mechanics to imaging-based 3D computational fluid dynamics (CFDs) models of the upper pulmonary airways in order to incorporate physiologically appropriate outlet boundary conditions. The framework is an extension of the modified Newton's method with nonlinear Krylov accelerator developed by Carlson and Miller [1], Miller [2] and Scott and Fenves [3]. Our extensions include the retention of subspace information over multiple timesteps, and a special correction at the end of a timestep that allows for corrections to be accepted with verified low residual with as little as a single residual evaluation per timestep on average. In the case of a single residual evaluation per timestep, the method has zero additional computational cost compared to uncoupled or unidirectionally coupled simulations. We expect these enhancements to be generally applicable to other multiscale coupling applications where timestepping occurs. In addition we have developed a "pressure-drop" residual which allows for stable coupling of flows between a 3D incompressible CFD application and another (lower-dimensional) fluid system. We expect this residual to also be useful for coupling non-respiratory incompressible fluid applications, such as multiscale simulations involving blood flow. The lower-dimensional models that are considered in this study are sets of simple ordinary differential equations (ODEs) representing the compliant mechanics of symmetric human pulmonary airway trees. To validate the method, we compare the predictions of hybrid CFD-ODE models against an ODE-only model of pulmonary airflow in an idealized geometry. Subsequently, we couple multiple sets of ODEs describing the distal lung to an imaging-based human lung geometry. Boundary conditions in these models consist of atmospheric pressure at the mouth and intrapleural pressure applied to the multiple sets of ODEs. In both the simplified geometry and in the imaging-based geometry, the performance of the method was comparable to that of monolithic schemes, in most cases requiring only a single CFD evaluation per time step. Thus, this new accelerator allows us to begin combining pulmonary CFD models with lower-dimensional models of pulmonary mechanics with little computational overhead. Moreover, because the CFD and lower-dimensional models are totally separate, this framework affords great flexibility in terms of the type and breadth of the adopted lower-dimensional model, allowing the biomedical researcher to appropriately focus on model design. Research funded by the National Heart and Blood Institute Award 1RO1HL073598.

Progress in modelling agricultural impacts of and adaptations to climate change.

PubMed

Rötter, R P; Hoffmann, M P; Koch, M; Müller, C

2018-06-01

Modelling is a key tool to explore agricultural impacts of and adaptations to climate change. Here we report recent progress made especially referring to the large project initiatives MACSUR and AgMIP; in particular, in modelling potential crop impacts from field to global using multi-model ensembles. We identify two main fields where further progress is necessary: a more mechanistic understanding of climate impacts and management options for adaptation and mitigation; and focusing on cropping systems and integrative multi-scale assessments instead of single season and crops, especially in complex tropical and neglected but important cropping systems. Stronger linking of experimentation with statistical and eco-physiological crop modelling could facilitate the necessary methodological advances. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multiscale Modeling of PEEK Using Reactive Molecular Dynamics Modeling and Micromechanics

NASA Technical Reports Server (NTRS)

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

2018-01-01

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

Integrated multiscale biomaterials experiment and modelling: a perspective

PubMed Central

Buehler, Markus J.; Genin, Guy M.

2016-01-01

Advances in multiscale models and computational power have enabled a broad toolset to predict how molecules, cells, tissues and organs behave and develop. A key theme in biological systems is the emergence of macroscale behaviour from collective behaviours across a range of length and timescales, and a key element of these models is therefore hierarchical simulation. However, this predictive capacity has far outstripped our ability to validate predictions experimentally, particularly when multiple hierarchical levels are involved. The state of the art represents careful integration of multiscale experiment and modelling, and yields not only validation, but also insights into deformation and relaxation mechanisms across scales. We present here a sampling of key results that highlight both challenges and opportunities for integrated multiscale experiment and modelling in biological systems. PMID:28981126

A Bidirectional Coupling Procedure Applied to Multiscale Respiratory Modeling☆

PubMed Central

Kuprat, A.P.; Kabilan, S.; Carson, J.P.; Corley, R.A.; Einstein, D.R.

2012-01-01

In this study, we present a novel multiscale computational framework for efficiently linking multiple lower-dimensional models describing the distal lung mechanics to imaging-based 3D computational fluid dynamics (CFD) models of the upper pulmonary airways in order to incorporate physiologically appropriate outlet boundary conditions. The framework is an extension of the Modified Newton’s Method with nonlinear Krylov accelerator developed by Carlson and Miller [1, 2, 3]. Our extensions include the retention of subspace information over multiple timesteps, and a special correction at the end of a timestep that allows for corrections to be accepted with verified low residual with as little as a single residual evaluation per timestep on average. In the case of a single residual evaluation per timestep, the method has zero additional computational cost compared to uncoupled or unidirectionally coupled simulations. We expect these enhancements to be generally applicable to other multiscale coupling applications where timestepping occurs. In addition we have developed a “pressure-drop” residual which allows for stable coupling of flows between a 3D incompressible CFD application and another (lower-dimensional) fluid system. We expect this residual to also be useful for coupling non-respiratory incompressible fluid applications, such as multiscale simulations involving blood flow. The lower-dimensional models that are considered in this study are sets of simple ordinary differential equations (ODEs) representing the compliant mechanics of symmetric human pulmonary airway trees. To validate the method, we compare the predictions of hybrid CFD-ODE models against an ODE-only model of pulmonary airflow in an idealized geometry. Subsequently, we couple multiple sets of ODEs describing the distal lung to an imaging-based human lung geometry. Boundary conditions in these models consist of atmospheric pressure at the mouth and intrapleural pressure applied to the multiple sets of ODEs. In both the simplified geometry and in the imaging-based geometry, the performance of the method was comparable to that of monolithic schemes, in most cases requiring only a single CFD evaluation per time step. Thus, this new accelerator allows us to begin combining pulmonary CFD models with lower-dimensional models of pulmonary mechanics with little computational overhead. Moreover, because the CFD and lower-dimensional models are totally separate, this framework affords great flexibility in terms of the type and breadth of the adopted lower-dimensional model, allowing the biomedical researcher to appropriately focus on model design. Research funded by the National Heart and Blood Institute Award 1RO1HL073598. PMID:24347680

Nonlocal and Mixed-Locality Multiscale Finite Element Methods

DOE PAGES

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

2018-03-27

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

Nonlocal and Mixed-Locality Multiscale Finite Element Methods

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

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

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

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

NASA Astrophysics Data System (ADS)

Dehghan Banadaki, Arash

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

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

PubMed

Zanin, Massimiliano; Chorbev, Ivan; Stres, Blaz; Stalidzans, Egils; Vera, Julio; Tieri, Paolo; Castiglione, Filippo; Groen, Derek; Zheng, Huiru; Baumbach, Jan; Schmid, Johannes A; Basilio, José; Klimek, Peter; Debeljak, Nataša; Rozman, Damjana; Schmidt, Harald H H W

2017-12-05

Systems medicine holds many promises, but has so far provided only a limited number of proofs of principle. To address this road block, possible barriers and challenges of translating systems medicine into clinical practice need to be identified and addressed. The members of the European Cooperation in Science and Technology (COST) Action CA15120 Open Multiscale Systems Medicine (OpenMultiMed) wish to engage the scientific community of systems medicine and multiscale modelling, data science and computing, to provide their feedback in a structured manner. This will result in follow-up white papers and open access resources to accelerate the clinical translation of systems medicine. © The Author 2017. Published by Oxford University Press.

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

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

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

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

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

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

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

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

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

PubMed

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

2011-10-01

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

Multi-scale signed envelope inversion

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Application of finite elements heterogeneous multi-scale method to eddy currents non destructive testing of carbon composites material

NASA Astrophysics Data System (ADS)

Khebbab, Mohamed; Feliachi, Mouloud; El Hadi Latreche, Mohamed

2018-03-01

In this present paper, a simulation of eddy current non-destructive testing (EC NDT) on unidirectional carbon fiber reinforced polymer is performed; for this magneto-dynamic formulation in term of magnetic vector potential is solved using finite element heterogeneous multi-scale method (FE HMM). FE HMM has as goal to compute the homogenized solution without calculating the homogenized tensor explicitly, the solution is based only on the physical characteristic known in micro domain. This feature is well adapted to EC NDT to evaluate defect in carbon composite material in microscopic scale, where the defect detection is performed by coil impedance measurement; the measurement value is intimately linked to material characteristic in microscopic level. Based on this, our model can handle different defects such as: cracks, inclusion, internal electrical conductivity changes, heterogeneities, etc. The simulation results were compared with the solution obtained with homogenized material using mixture law, a good agreement was found.

Parallel multiscale simulations of a brain aneurysm

PubMed Central

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

2012-01-01

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

Parallel multiscale simulations of a brain aneurysm.

PubMed

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

2013-07-01

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

Parallel multiscale simulations of a brain aneurysm

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

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

2013-07-01

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

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

NASA Astrophysics Data System (ADS)

Yan, Jihong; Guo, Chaozhong; Wang, Xing

2011-05-01

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

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

Treesearch

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

2016-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2008-01-01

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

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

PubMed

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

2016-11-13

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

Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen

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

Plechac, Petr

2016-03-01

The overall objective of this project was to develop multiscale models for understanding and eventually designing complex processes for renewables. To the best of our knowledge, our work is the first attempt at modeling complex reacting systems, whose performance relies on underlying multiscale mathematics and developing rigorous mathematical techniques and computational algorithms to study such models. Our specific application lies at the heart of biofuels initiatives of DOE and entails modeling of catalytic systems, to enable economic, environmentally benign, and efficient conversion of biomass into either hydrogen or valuable chemicals.

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

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

Zabaras, Nicolas J.

2016-11-08

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

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

NASA Technical Reports Server (NTRS)

Koch, Steven E. (Editor)

1993-01-01

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

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

NASA Astrophysics Data System (ADS)

Field, Martin J.; Wymore, Troy W.

2014-10-01

The 2013 Nobel Prize in Chemistry was awarded for the development of multiscale models for complex chemical systems, whereas the 2013 Peace Prize was given to the Organisation for the Prohibition of Chemical Weapons for their efforts to eliminate chemical warfare agents. This review relates the two by introducing the field of multiscale modeling and highlighting its application to the study of the biological mechanisms by which selected chemical weapon agents exert their effects at an atomic level.

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

PubMed Central

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

2007-01-01

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

Multiscale analysis of neural spike trains.

PubMed

Ramezan, Reza; Marriott, Paul; Chenouri, Shojaeddin

2014-01-30

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

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

NASA Technical Reports Server (NTRS)

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

1997-01-01

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

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

NASA Astrophysics Data System (ADS)

Tao, W. K.

2017-12-01

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

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

In recent years, exponentially increasing computer power extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale models can be run in grid size similar to cloud resolving models through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model). (2) a regional scale model (a NASA unified weather research and forecast, W8F). (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling systems to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use the multi-satellite simulator to improve precipitation processes will be discussed.

Using Multi-Scale Modeling Systems to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2010-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Predictive modeling of solidification during laser additive manufacturing of nickel superalloys: recent developments, future directions

NASA Astrophysics Data System (ADS)

Ghosh, Supriyo

2018-01-01

Additive manufacturing (AM) processes produce parts with improved physical, chemical, and mechanical properties compared to conventional manufacturing processes. In AM processes, intricate part geometries are produced from multicomponent alloy powder, in a layer-by-layer fashion with multipass laser melting, solidification, and solid-state phase transformations, in a shorter manufacturing time, with minimal surface finishing, and at a reasonable cost. However, there is an increasing need for post-processing of the manufactured parts via, for example, stress relieving heat treatment and hot isostatic pressing to achieve homogeneous microstructure and properties at all times. Solidification in an AM process controls the size, shape, and distribution of the grains, the growth morphology, the elemental segregation and precipitation, the subsequent solid-state phase changes, and ultimately the material properties. The critical issues in this process are linked with multiphysics (such as fluid flow and diffusion of heat and mass) and multiscale (lengths, times and temperature ranges) challenges that arise due to localized rapid heating and cooling during AM processing. The alloy chemistry-process-microstructure-property-performance correlation in this process will be increasingly better understood through multiscale modeling and simulation.

Beyond Darcy's law: The role of phase topology and ganglion dynamics for two-fluid flow

DOE PAGES

Armstrong, Ryan T.; McClure, James E.; Berrill, Mark A.; ...

2016-10-27

Relative permeability quantifies the ease at which immiscible phases flow through porous rock and is one of the most well known constitutive relationships for petroleum engineers. It however exhibits troubling dependencies on experimental conditions and is not a unique function of phase saturation as commonly accepted in industry practices. The problem lies in the multi-scale nature of the problem where underlying disequilibrium processes create anomalous macroscopic behavior. Here we show that relative permeability rate dependencies are explained by ganglion dynamic flow. We utilize fast X-ray micro-tomography and pore-scale simulations to identify unique flow regimes during the fractional flow of immisciblemore » phases and quantify the contribution of ganglion flux to the overall flux of non-wetting phase. We anticipate our approach to be the starting point for the development of sophisticated multi-scale flow models that directly link pore-scale parameters to macro-scale behavior. Such models will have a major impact on how we recover hydrocarbons from the subsurface, store sequestered CO 2 in geological formations, and remove non-aqueous environmental hazards from the vadose zone.« less

An Overview of Prognosis Health Management Research at Glenn Research Center for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Goldberg, Robert K.; Lerch, Bradley A.; Saleeb, Atef F.

2009-01-01

Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include (1) diagnostic/detection methodology, (2) prognosis/lifing methodology, (3) diagnostic/prognosis linkage, (4) experimental validation, and (5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multimechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.

An Overview of Prognosis Health Management Research at GRC for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Goldberg, Robert K.; Lerch, Bradley A.; Saleeb, Atef F.

2009-01-01

Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include 1) diagnostic/detection methodology, 2) prognosis/lifing methodology, 3) diagnostic/prognosis linkage, 4) experimental validation and 5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multi-mechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.

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

EPA Science Inventory

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

Evaluation of the Community Multiscale Air Quality model version 5.1

EPA Science Inventory

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

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

PubMed Central

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

2015-01-01

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

COMMUNITY MULTISCALE AIR QUALITY MODELING SYSTEM (ONE ATMOSPHERE)

EPA Science Inventory

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

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

EPA Science Inventory

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

Multiscale modeling methods in biomechanics.

PubMed

Bhattacharya, Pinaki; Viceconti, Marco

2017-05-01

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

Multiscale Modeling and Simulation of Material Processing

DTIC Science & Technology

2006-07-01

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

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

PubMed Central

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

2010-01-01

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

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

PubMed Central

Puglisi, G.

2016-01-01

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

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

ERIC Educational Resources Information Center

Schwalbe, Michelle Kristin

2010-01-01

This dissertation has two primary concerns: (i) evaluating the uncertainty and prediction capabilities of a nanodiamond drug delivery model using Bayesian calibration and bias correction, and (ii) determining conceptual difficulties of multi-scale analysis from an engineering education perspective. A Bayesian uncertainty quantification scheme…

Multiscale polar theory of microtubule and motor-protein assemblies

DOE PAGES

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

2015-01-27

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

Computational Medicine: Translating Models to Clinical Care

PubMed Central

Winslow, Raimond L.; Trayanova, Natalia; Geman, Donald; Miller, Michael I.

2013-01-01

Because of the inherent complexity of coupled nonlinear biological systems, the development of computational models is necessary for achieving a quantitative understanding of their structure and function in health and disease. Statistical learning is applied to high-dimensional biomolecular data to create models that describe relationships between molecules and networks. Multiscale modeling links networks to cells, organs, and organ systems. Computational approaches are used to characterize anatomic shape and its variations in health and disease. In each case, the purposes of modeling are to capture all that we know about disease and to develop improved therapies tailored to the needs of individuals. We discuss advances in computational medicine, with specific examples in the fields of cancer, diabetes, cardiology, and neurology. Advances in translating these computational methods to the clinic are described, as well as challenges in applying models for improving patient health. PMID:23115356

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

EPA Science Inventory

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

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

EPA Science Inventory

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

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

EPA Science Inventory

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

Multiscale Simulation Framework for Coupled Fluid Flow and Mechanical Deformation

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

Hou, Thomas; Efendiev, Yalchin; Tchelepi, Hamdi

2016-05-24

Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scalemore » basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics.« less

Multiscale analysis and computation for flows in heterogeneous media

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

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

Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scalemore » basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics. Below, we present a brief overview of each of these contributions.« less

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

EPA Science Inventory

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

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

EPA Science Inventory

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

Multi-Scale Computational Models for Electrical Brain Stimulation

PubMed Central

Seo, Hyeon; Jun, Sung C.

2017-01-01

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

Transition between inverse and direct energy cascades in multiscale optical turbulence

DOE PAGES

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

2018-03-06

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

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

PubMed

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

2015-01-01

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

Morphogenesis of early stage melanoma

NASA Astrophysics Data System (ADS)

Chatelain, Clément; Amar, Martine Ben

2015-08-01

Melanoma early detection is possible by simple skin examination and can insure a high survival probability when successful. However it requires efficient methods for identifying malignant lesions from common moles. This paper provides an overview first of the biological and physical mechanisms controlling melanoma early evolution, and then of the clinical tools available today for detecting melanoma in vivo at an early stage. It highlights the lack of diagnosis methods rationally linking macroscopic observables to the microscopic properties of the tissue, which define the malignancy of the tumor. The possible inputs of multiscale models for improving these methods are shortly discussed.

A perspective on modeling the multiscale response of energetic materials

NASA Astrophysics Data System (ADS)

Rice, Betsy M.

2017-01-01

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

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

EPA Science Inventory

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

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

EPA Science Inventory

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

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

EPA Science Inventory

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

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

EPA Science Inventory

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

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

EPA Science Inventory

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

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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

PubMed

Lu, Zhao; Sun, Jing; Butts, Kenneth

2014-05-01

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

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

PubMed

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

2016-08-01

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

A Liver-centric Multiscale Modeling Framework for Xenobiotics

EPA Science Inventory

We describe a multi-scale framework for modeling acetaminophen-induced liver toxicity. Acetaminophen is a widely used analgesic. Overdose of acetaminophen can result in liver injury via its biotransformation into toxic product, which further induce massive necrosis. Our study foc...

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

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

Mehrez, Loujaine; Ghanem, Roger; McAuliffe, Colin

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

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

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

Stander, Nielen; Basudhar, Anirban; Basu, Ushnish

2015-09-14

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

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

EPA Science Inventory

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

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

EPA Science Inventory

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

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

EPA Science Inventory

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

Tracing Multi-Scale Climate Change at Low Latitude from Glacier Shrinkage

NASA Astrophysics Data System (ADS)

Moelg, T.; Cullen, N. J.; Hardy, D. R.; Kaser, G.

2009-12-01

Significant shrinkage of glaciers on top of Africa's highest mountain (Kilimanjaro, 5895 m a.s.l.) has been observed between the late 19th century and the present. Multi-year data from our automatic weather station on the largest remaining slope glacier at 5873 m allow us to force and verify a process-based distributed glacier mass balance model. This generates insights into energy and mass fluxes at the glacier-atmosphere interface, their feedbacks, and how they are linked to atmospheric conditions. By means of numerical atmospheric modeling and global climate model simulations, we explore the linkages of the local climate in Kilimanjaro's summit zone to larger-scale climate dynamics - which suggests a causal connection between Indian Ocean dynamics, mesoscale mountain circulation, and glacier mass balance. Based on this knowledge, the verified mass balance model is used for backward modeling of the steady-state glacier extent observed in the 19th century, which yields the characteristics of local climate change between that time and the present (30-45% less precipitation, 0.1-0.3 hPa less water vapor pressure, 2-4 percentage units less cloud cover at present). Our multi-scale approach provides an important contribution, from a cryospheric viewpoint, to the understanding of how large-scale climate change propagates to the tropical free troposphere. Ongoing work in this context targets the millennium-scale relation between large-scale climate and glacier behavior (by downscaling precipitation), and the possible effects of regional anthropogenic activities (land use change) on glacier mass balance.

Quantitative Systems Pharmacology Modeling of Acid Sphingomyelinase Deficiency and the Enzyme Replacement Therapy Olipudase Alfa Is an Innovative Tool for Linking Pathophysiology and Pharmacology.

PubMed

Kaddi, Chanchala D; Niesner, Bradley; Baek, Rena; Jasper, Paul; Pappas, John; Tolsma, John; Li, Jing; van Rijn, Zachary; Tao, Mengdi; Ortemann-Renon, Catherine; Easton, Rachael; Tan, Sharon; Puga, Ana Cristina; Schuchman, Edward H; Barrett, Jeffrey S; Azer, Karim

2018-06-19

Acid sphingomyelinase deficiency (ASMD) is a rare lysosomal storage disorder with heterogeneous clinical manifestations, including hepatosplenomegaly and infiltrative pulmonary disease, and is associated with significant morbidity and mortality. Olipudase alfa (recombinant human acid sphingomyelinase) is an enzyme replacement therapy under development for the non-neurological manifestations of ASMD. We present a quantitative systems pharmacology (QSP) model supporting the clinical development of olipudase alfa. The model is multiscale and mechanistic, linking the enzymatic deficiency driving the disease to molecular-level, cellular-level, and organ-level effects. Model development was informed by natural history, and preclinical and clinical studies. By considering patient-specific pharmacokinetic (PK) profiles and indicators of disease severity, the model describes pharmacodynamic (PD) and clinical end points for individual patients. The ASMD QSP model provides a platform for quantitatively assessing systemic pharmacological effects in adult and pediatric patients, and explaining variability within and across these patient populations, thereby supporting the extrapolation of treatment response from adults to pediatrics. © 2018 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Multiscale System for Environmentally-Driven Infectious Disease with Threshold Control Strategy

NASA Astrophysics Data System (ADS)

Sun, Xiaodan; Xiao, Yanni

A multiscale system for environmentally-driven infectious disease is proposed, in which control measures at three different scales are implemented when the number of infected hosts exceeds a certain threshold. Our coupled model successfully describes the feedback mechanisms of between-host dynamics on within-host dynamics by employing one-scale variable guided enhancement of interventions on other scales. The modeling approach provides a novel idea of how to link the large-scale dynamics to small-scale dynamics. The dynamic behaviors of the multiscale system on two time-scales, i.e. fast system and slow system, are investigated. The slow system is further simplified to a two-dimensional Filippov system. For the Filippov system, we study the dynamics of its two subsystems (i.e. free-system and control-system), the sliding mode dynamics, the boundary equilibrium bifurcations, as well as the global behaviors. We prove that both subsystems may undergo backward bifurcations and the sliding domain exists. Meanwhile, it is possible that the pseudo-equilibrium exists and is globally stable, or the pseudo-equilibrium, the disease-free equilibrium and the real equilibrium are tri-stable, or the pseudo-equilibrium and the real equilibrium are bi-stable, or the pseudo-equilibrium and disease-free equilibrium are bi-stable, which depends on the threshold value and other parameter values. The global stability of the pseudo-equilibrium reveals that we may maintain the number of infected hosts at a previously given value. Moreover, the bi-stability and tri-stability indicate that whether the number of infected individuals tends to zero or a previously given value or other positive values depends on the parameter values and the initial states of the system. These results highlight the challenges in the control of environmentally-driven infectious disease.

Fourth-power law structure of the shock wave fronts in metals and ceramics

NASA Astrophysics Data System (ADS)

Bayandin, Yuriy; Naimark, Oleg; Saveleva, Natalia

2017-06-01

The plate impact experiments were performed for solids during last fifty years. It was established that the dependence between the strain rate and the shock wave amplitude for metals and ceramics expressed by a fourth-power law. Present study is focused on the theoretical investigation and numerical simulation of plane shock wave propagation in metals and ceramics. Statistically based constitutive model of solid with defects (microcracks and microshears) was developed to provide the relation between damage induced mechanisms of structural relaxation, thermally activated plastic flow and material reactions for extreme loading conditions. Original approach based on the wide range constitutive equations was proposed for the numerical simulation of multiscale damage-failure transition mechanisms and plane shock wave propagation in solids with defects in the range of strain rate 103 -108s-1 . It was shown that mechanisms of plastic relaxation and damage-failure transitions are linked to the multiscale kinetics of defects leading to the self-similar nature of shock wave fronts in metals and ceramics. The work was supported by the Russian Science Foundation (Project No. 14-19-01173).

Multiscale Failure Analysis of Laminated Composite Panels Subjected to Blast Loading Using FEAMAC/Explicit

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Waas, Anthony M.; Berdnarcyk, Brett A.; Arnold, Steven M.; Collier, Craig S.

2009-01-01

This preliminary report demonstrates the capabilities of the recently developed software implementation that links the Generalized Method of Cells to explicit finite element analysis by extending a previous development which tied the generalized method of cells to implicit finite elements. The multiscale framework, which uses explicit finite elements at the global-scale and the generalized method of cells at the microscale is detailed. This implementation is suitable for both dynamic mechanics problems and static problems exhibiting drastic and sudden changes in material properties, which often encounter convergence issues with commercial implicit solvers. Progressive failure analysis of stiffened and un-stiffened fiber-reinforced laminates subjected to normal blast pressure loads was performed and is used to demonstrate the capabilities of this framework. The focus of this report is to document the development of the software implementation; thus, no comparison between the results of the models and experimental data is drawn. However, the validity of the results are assessed qualitatively through the observation of failure paths, stress contours, and the distribution of system energies.

Multiscale geometric modeling of macromolecules II: Lagrangian representation

PubMed Central

Feng, Xin; Xia, Kelin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei

2013-01-01

Geometric modeling of biomolecules plays an essential role in the conceptualization of biolmolecular structure, function, dynamics and transport. Qualitatively, geometric modeling offers a basis for molecular visualization, which is crucial for the understanding of molecular structure and interactions. Quantitatively, geometric modeling bridges the gap between molecular information, such as that from X-ray, NMR and cryo-EM, and theoretical/mathematical models, such as molecular dynamics, the Poisson-Boltzmann equation and the Nernst-Planck equation. In this work, we present a family of variational multiscale geometric models for macromolecular systems. Our models are able to combine multiresolution geometric modeling with multiscale electrostatic modeling in a unified variational framework. We discuss a suite of techniques for molecular surface generation, molecular surface meshing, molecular volumetric meshing, and the estimation of Hadwiger’s functionals. Emphasis is given to the multiresolution representations of biomolecules and the associated multiscale electrostatic analyses as well as multiresolution curvature characterizations. The resulting fine resolution representations of a biomolecular system enable the detailed analysis of solvent-solute interaction, and ion channel dynamics, while our coarse resolution representations highlight the compatibility of protein-ligand bindings and possibility of protein-protein interactions. PMID:23813599

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

EPA Science Inventory

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

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

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

EPA Science Inventory

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

The Grand Challenge of Scale in Scientific Hydrology: Some Personal Reflections

NASA Astrophysics Data System (ADS)

Gupta, V. K.

2009-12-01

Scale issues in hydrology have shaped my entire scientific career. I first recognized the challenge of scale during the 1970s in linking multi-scale hydrologic processes through collaborative work on solute transport in saturated porous media. Linking geometry, dynamics and statistics, and the role of diagnostics in testing theoretical predictions against experimental observations, played a foundational role. This foundation has guided the rest of my multi-scale research on larger space-time scales of river basins, regional, and global. After the blue book was published in 1991, NSF needed a futuristic implementation plan for the blue book, but did not communicate it to Pete. I came to know of it in 1998 after six years of pursuing an ‘open-ended agenda’ in which Doug played a key role. The upper management of the Geosciences Directorate first mentioned to me in 1998 that the blue book needed a broad and futuristic implementation plan. It led to the Water, Earth, and Biota (WEB) report in 2000 following an NSF-funded workshop in 1999. The multi-scale nature of hydrology served as the central organizing theme for the WEB report. The history from 1984 to 2001 is summarized on the CUAHSI web page under “history”, so I will only share a few personal reflections from this period. Where do we go from here? My perspective is that an urgent need exists to modernize hydrology curriculum that should include the progress that has been made in addressing multi-scale challenges. I will share some personal reflections, both intellectual and administrative, from my experiences in implementing a graduate hydrology science program at the University of Colorado after joining it in 1989.

A Multi-Scale Energy Food Systems Modeling Framework For Climate Adaptation

NASA Astrophysics Data System (ADS)

Siddiqui, S.; Bakker, C.; Zaitchik, B. F.; Hobbs, B. F.; Broaddus, E.; Neff, R.; Haskett, J.; Parker, C.

2016-12-01

Our goal is to understand coupled system dynamics across scales in a manner that allows us to quantify the sensitivity of critical human outcomes (nutritional satisfaction, household economic well-being) to development strategies and to climate or market induced shocks in sub-Saharan Africa. We adopt both bottom-up and top-down multi-scale modeling approaches focusing our efforts on food, energy, water (FEW) dynamics to define, parameterize, and evaluate modeled processes nationally as well as across climate zones and communities. Our framework comprises three complementary modeling techniques spanning local, sub-national and national scales to capture interdependencies between sectors, across time scales, and on multiple levels of geographic aggregation. At the center is a multi-player micro-economic (MME) partial equilibrium model for the production, consumption, storage, and transportation of food, energy, and fuels, which is the focus of this presentation. We show why such models can be very useful for linking and integrating across time and spatial scales, as well as a wide variety of models including an agent-based model applied to rural villages and larger population centers, an optimization-based electricity infrastructure model at a regional scale, and a computable general equilibrium model, which is applied to understand FEW resources and economic patterns at national scale. The MME is based on aggregating individual optimization problems for relevant players in an energy, electricity, or food market and captures important food supply chain components of trade and food distribution accounting for infrastructure and geography. Second, our model considers food access and utilization by modeling food waste and disaggregating consumption by income and age. Third, the model is set up to evaluate the effects of seasonality and system shocks on supply, demand, infrastructure, and transportation in both energy and food.

Assessing the multi-scale predictive ability of ecosystem functional attributes for species distribution modelling.

PubMed

Arenas-Castro, Salvador; Gonçalves, João; Alves, Paulo; Alcaraz-Segura, Domingo; Honrado, João P

2018-01-01

Global environmental changes are rapidly affecting species' distributions and habitat suitability worldwide, requiring a continuous update of biodiversity status to support effective decisions on conservation policy and management. In this regard, satellite-derived Ecosystem Functional Attributes (EFAs) offer a more integrative and quicker evaluation of ecosystem responses to environmental drivers and changes than climate and structural or compositional landscape attributes. Thus, EFAs may hold advantages as predictors in Species Distribution Models (SDMs) and for implementing multi-scale species monitoring programs. Here we describe a modelling framework to assess the predictive ability of EFAs as Essential Biodiversity Variables (EBVs) against traditional datasets (climate, land-cover) at several scales. We test the framework with a multi-scale assessment of habitat suitability for two plant species of conservation concern, both protected under the EU Habitats Directive, differing in terms of life history, range and distribution pattern (Iris boissieri and Taxus baccata). We fitted four sets of SDMs for the two test species, calibrated with: interpolated climate variables; landscape variables; EFAs; and a combination of climate and landscape variables. EFA-based models performed very well at the several scales (AUCmedian from 0.881±0.072 to 0.983±0.125), and similarly to traditional climate-based models, individually or in combination with land-cover predictors (AUCmedian from 0.882±0.059 to 0.995±0.083). Moreover, EFA-based models identified additional suitable areas and provided valuable information on functional features of habitat suitability for both test species (narrowly vs. widely distributed), for both coarse and fine scales. Our results suggest a relatively small scale-dependence of the predictive ability of satellite-derived EFAs, supporting their use as meaningful EBVs in SDMs from regional and broader scales to more local and finer scales. Since the evaluation of species' conservation status and habitat quality should as far as possible be performed based on scalable indicators linking to meaningful processes, our framework may guide conservation managers in decision-making related to biodiversity monitoring and reporting schemes.

Multiscale modeling of mucosal immune responses

PubMed Central

2015-01-01

Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM. Background Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Implementation Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. Conclusion We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation. PMID:26329787

Multiscale modeling of mucosal immune responses.

PubMed

Mei, Yongguo; Abedi, Vida; Carbo, Adria; Zhang, Xiaoying; Lu, Pinyi; Philipson, Casandra; Hontecillas, Raquel; Hoops, Stefan; Liles, Nathan; Bassaganya-Riera, Josep

2015-01-01

Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation.Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM.

A conceptual review on systems biology in health and diseases: from biological networks to modern therapeutics.

PubMed

Somvanshi, Pramod Rajaram; Venkatesh, K V

2014-03-01

Human physiology is an ensemble of various biological processes spanning from intracellular molecular interactions to the whole body phenotypic response. Systems biology endures to decipher these multi-scale biological networks and bridge the link between genotype to phenotype. The structure and dynamic properties of these networks are responsible for controlling and deciding the phenotypic state of a cell. Several cells and various tissues coordinate together to generate an organ level response which further regulates the ultimate physiological state. The overall network embeds a hierarchical regulatory structure, which when unusually perturbed can lead to undesirable physiological state termed as disease. Here, we treat a disease diagnosis problem analogous to a fault diagnosis problem in engineering systems. Accordingly we review the application of engineering methodologies to address human diseases from systems biological perspective. The review highlights potential networks and modeling approaches used for analyzing human diseases. The application of such analysis is illustrated in the case of cancer and diabetes. We put forth a concept of cell-to-human framework comprising of five modules (data mining, networking, modeling, experimental and validation) for addressing human physiology and diseases based on a paradigm of system level analysis. The review overtly emphasizes on the importance of multi-scale biological networks and subsequent modeling and analysis for drug target identification and designing efficient therapies.

A scale-entropy diffusion equation to describe the multi-scale features of turbulent flames near a wall

NASA Astrophysics Data System (ADS)

Queiros-Conde, D.; Foucher, F.; Mounaïm-Rousselle, C.; Kassem, H.; Feidt, M.

2008-12-01

Multi-scale features of turbulent flames near a wall display two kinds of scale-dependent fractal features. In scale-space, an unique fractal dimension cannot be defined and the fractal dimension of the front is scale-dependent. Moreover, when the front approaches the wall, this dependency changes: fractal dimension also depends on the wall-distance. Our aim here is to propose a general geometrical framework that provides the possibility to integrate these two cases, in order to describe the multi-scale structure of turbulent flames interacting with a wall. Based on the scale-entropy quantity, which is simply linked to the roughness of the front, we thus introduce a general scale-entropy diffusion equation. We define the notion of “scale-evolutivity” which characterises the deviation of a multi-scale system from the pure fractal behaviour. The specific case of a constant “scale-evolutivity” over the scale-range is studied. In this case, called “parabolic scaling”, the fractal dimension is a linear function of the logarithm of scale. The case of a constant scale-evolutivity in the wall-distance space implies that the fractal dimension depends linearly on the logarithm of the wall-distance. We then verified experimentally, that parabolic scaling represents a good approximation of the real multi-scale features of turbulent flames near a wall.

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

EPA Science Inventory

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

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

EPA Science Inventory

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

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

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

The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process takingmore » place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.« less

A geospatial database model for the management of remote sensing datasets at multiple spectral, spatial, and temporal scales

NASA Astrophysics Data System (ADS)

Ifimov, Gabriela; Pigeau, Grace; Arroyo-Mora, J. Pablo; Soffer, Raymond; Leblanc, George

2017-10-01

In this study the development and implementation of a geospatial database model for the management of multiscale datasets encompassing airborne imagery and associated metadata is presented. To develop the multi-source geospatial database we have used a Relational Database Management System (RDBMS) on a Structure Query Language (SQL) server which was then integrated into ArcGIS and implemented as a geodatabase. The acquired datasets were compiled, standardized, and integrated into the RDBMS, where logical associations between different types of information were linked (e.g. location, date, and instrument). Airborne data, at different processing levels (digital numbers through geocorrected reflectance), were implemented in the geospatial database where the datasets are linked spatially and temporally. An example dataset consisting of airborne hyperspectral imagery, collected for inter and intra-annual vegetation characterization and detection of potential hydrocarbon seepage events over pipeline areas, is presented. Our work provides a model for the management of airborne imagery, which is a challenging aspect of data management in remote sensing, especially when large volumes of data are collected.

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

USGS Publications Warehouse

Dorazio, Robert; Erickson, Richard A.

2017-01-01

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

Multiscale Modeling and Uncertainty Quantification for Nuclear Fuel Performance

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

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

2017-03-23

In this project, we will address the challenges associated with constructing high fidelity multiscale models of nuclear fuel performance. We (*) propose a novel approach for coupling mesoscale and macroscale models, (*) devise efficient numerical methods for simulating the coupled system, and (*) devise and analyze effective numerical approaches for error and uncertainty quantification for the coupled multiscale system. As an integral part of the project, we will carry out analysis of the effects of upscaling and downscaling, investigate efficient methods for stochastic sensitivity analysis of the individual macroscale and mesoscale models, and carry out a posteriori error analysis formore » computed results. We will pursue development and implementation of solutions in software used at Idaho National Laboratories on models of interest to the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program.« less

Lower Length Scale Model Development for Embrittlement of Reactor Presure Vessel Steel

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

Zhang, Yongfeng; Schwen, Daniel; Chakraborty, Pritam

2016-09-01

This report summarizes the lower-length-scale effort during FY 2016 in developing mesoscale capabilities for microstructure evolution, plasticity and fracture in reactor pressure vessel steels. During operation, reactor pressure vessels are subject to hardening and embrittlement caused by irradiation induced defect accumulation and irradiation enhanced solute precipitation. Both defect production and solute precipitation start from the atomic scale, and manifest their eventual effects as degradation in engineering scale properties. To predict the property degradation, multiscale modeling and simulation are needed to deal with the microstructure evolution, and to link the microstructure feature to material properties. In this report, the development ofmore » mesoscale capabilities for defect accumulation and solute precipitation are summarized. A crystal plasticity model to capture defect-dislocation interaction and a damage model for cleavage micro-crack propagation is also provided.« less

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

PubMed

Xia, Kelin

2017-12-20

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

The Structure of Borders in a Small World

PubMed Central

Thiemann, Christian; Theis, Fabian; Grady, Daniel; Brune, Rafael; Brockmann, Dirk

2010-01-01

Territorial subdivisions and geographic borders are essential for understanding phenomena in sociology, political science, history, and economics. They influence the interregional flow of information and cross-border trade and affect the diffusion of innovation and technology. However, it is unclear if existing administrative subdivisions that typically evolved decades ago still reflect the most plausible organizational structure of today. The complexity of modern human communication, the ease of long-distance movement, and increased interaction across political borders complicate the operational definition and assessment of geographic borders that optimally reflect the multi-scale nature of today's human connectivity patterns. What border structures emerge directly from the interplay of scales in human interactions is an open question. Based on a massive proxy dataset, we analyze a multi-scale human mobility network and compute effective geographic borders inherent to human mobility patterns in the United States. We propose two computational techniques for extracting these borders and for quantifying their strength. We find that effective borders only partially overlap with existing administrative borders, and show that some of the strongest mobility borders exist in unexpected regions. We show that the observed structures cannot be generated by gravity models for human traffic. Finally, we introduce the concept of link significance that clarifies the observed structure of effective borders. Our approach represents a novel type of quantitative, comparative analysis framework for spatially embedded multi-scale interaction networks in general and may yield important insight into a multitude of spatiotemporal phenomena generated by human activity. PMID:21124970

The structure of borders in a small world.

PubMed

Thiemann, Christian; Theis, Fabian; Grady, Daniel; Brune, Rafael; Brockmann, Dirk

2010-11-18

Territorial subdivisions and geographic borders are essential for understanding phenomena in sociology, political science, history, and economics. They influence the interregional flow of information and cross-border trade and affect the diffusion of innovation and technology. However, it is unclear if existing administrative subdivisions that typically evolved decades ago still reflect the most plausible organizational structure of today. The complexity of modern human communication, the ease of long-distance movement, and increased interaction across political borders complicate the operational definition and assessment of geographic borders that optimally reflect the multi-scale nature of today's human connectivity patterns. What border structures emerge directly from the interplay of scales in human interactions is an open question. Based on a massive proxy dataset, we analyze a multi-scale human mobility network and compute effective geographic borders inherent to human mobility patterns in the United States. We propose two computational techniques for extracting these borders and for quantifying their strength. We find that effective borders only partially overlap with existing administrative borders, and show that some of the strongest mobility borders exist in unexpected regions. We show that the observed structures cannot be generated by gravity models for human traffic. Finally, we introduce the concept of link significance that clarifies the observed structure of effective borders. Our approach represents a novel type of quantitative, comparative analysis framework for spatially embedded multi-scale interaction networks in general and may yield important insight into a multitude of spatiotemporal phenomena generated by human activity.

Multiscale Modeling of Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

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

2015-01-01

Results of multiscale modeling simulations of the nonlinear response of SiC/SiC ceramic matrix composites are reported, wherein the microstructure of the ceramic matrix is captured. This micro scale architecture, which contains free Si material as well as the SiC ceramic, is responsible for residual stresses that play an important role in the subsequent thermo-mechanical behavior of the SiC/SiC composite. Using the novel Multiscale Generalized Method of Cells recursive micromechanics theory, the microstructure of the matrix, as well as the microstructure of the composite (fiber and matrix) can be captured.

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

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

EPA Science Inventory

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

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

EPA Science Inventory

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

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

EPA Science Inventory

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

Multi-scale habitat selection modeling: A review and outlook

Treesearch

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

2016-01-01

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

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

EPA Science Inventory

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

Mesoscale modeling of solute precipitation and radiation damage

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

Zhang, Yongfeng; Schwen, Daniel; Ke, Huibin

2015-09-01

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

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

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

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

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

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

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

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

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

2017-02-01

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

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

PubMed Central

Ong, Frank; Lustig, Michael

2016-01-01

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

Using the Community Multiscale Air Quality (CMAQ) model to estimate public health impacts of PM2.5 from individual power plants.

PubMed

Buonocore, Jonathan J; Dong, Xinyi; Spengler, John D; Fu, Joshua S; Levy, Jonathan I

2014-07-01

We estimated PM2.5-related public health impacts/ton emitted of primary PM2.5, SO2, and NOx for a set of power plants in the Mid-Atlantic and Lower Great Lakes regions of the United States, selected to include varying emission profiles and broad geographic representation. We then developed a regression model explaining variability in impacts per ton emitted using the population distributions around each plant. We linked outputs from the Community Multiscale Air Quality (CMAQ) model v 4.7.1 with census data and concentration-response functions for PM2.5-related mortality, and monetized health estimates using the value-of-statistical-life. The median impacts for the final set of plants were $130,000/ton for primary PM2.5 (range: $22,000-230,000), $28,000/ton for SO2 (range: $19,000-33,000), and $16,000/ton for NOx (range: $7100-26,000). Impacts of NOx were a median of 34% (range: 20%-75%) from ammonium nitrate and 66% (range: 25%-79%) from ammonium sulfate. The latter pathway is likely from NOx enhancing atmospheric oxidative capacity and amplifying sulfate formation, and is often excluded. Our regression models explained most of the variation in impact/ton estimates using basic population covariates, and can aid in estimating impacts averted from interventions such as pollution controls, alternative energy installations, or demand-side management. Copyright © 2014 Elsevier Ltd. All rights reserved.

Epidermal Homeostasis and Radiation Responses in a Multiscale Tissue Modeling Framework

NASA Technical Reports Server (NTRS)

Hu, Shaowen; Cucinotta, Francis A.

2013-01-01

The surface of skin is lined with several thin layers of epithelial cells that are maintained throughout life time by a small population of stem cells. High dose radiation exposures could injure and deplete the underlying proliferative cells and induce cutaneous radiation syndrome. In this work we propose a multiscale computational model for skin epidermal dynamics that links phenomena occurring at the subcellular, cellular, and tissue levels of organization, to simulate the experimental data of the radiation response of swine epidermis, which is closely similar to human epidermis. Incorporating experimentally measured histological and cell kinetic parameters, we obtain results of population kinetics and proliferation indexes comparable to observations in unirradiated and acutely irradiated swine experiments. At the sub-cellular level, several recently published Wnt signaling controlled cell-cycle models are applied and the roles of key components and parameters are analyzed. Based on our simulation results, we demonstrate that a moderate increase of proliferation rate for the survival proliferative cells is sufficient to fully repopulate the area denuded by high dose radiation, as long as the integrity of underlying basement membrane is maintained. Our work highlights the importance of considering proliferation kinetics as well as the spatial organization of tissues when conducting in vivo investigations of radiation responses. This integrated model allow us to test the validity of several basic biological rules at the cellular level and sub-cellular mechanisms by qualitatively comparing simulation results with published research, and enhance our understanding of the pathophysiological effects of ionizing radiation on skin.

Multiscale Investigation from Subcellular to Tissue Scale of Onion Epidermal Plant Cell Wall Mechanical Properties

NASA Astrophysics Data System (ADS)

Zamil, Mohammad Shafayet

The physical and mechanical properties of cell walls, their shape, how they are arranged and interact with each other determine the architecture of plant organs and how they mechanically respond to different environmental and loading conditions. Due to the distinctive hierarchy from subcellular to tissue scale, plant materials can exhibit remarkably different mechanical properties. To date, how the subcellular scale arrangement and the mechanical properties of plant cell wall structural constituents give rise to macro or tissue scale mechanical responses is not yet well understood. Although the tissue scale plant cell wall samples are easy to prepare and put to different types of mechanical tests, the hierarchical features that emerge when moving towards a higher scale make it complicated to link the macro scale results to micro or subcellular scale structural components. On the other hand, the microscale size of cell brings formidable challenges to prepare and grip samples and carry mechanical tests under tensile loading at subcellular scale. This study attempted to develop a set of test protocols based on microelectromechanical system (MEMS) tensile testing devices for characterizing plant cell wall materials at different length scales. For the ease of sample preparation and well established database of the composition and conformation of its structural constituents, onion epidermal cell wall profile was chosen as the study material. Based on the results and findings of multiscale mechanical characterization, a framework of architecture-based finite element method (FEM) computational model was developed. The computational model laid the foundation of bridging the subcellular or microscale to the tissue or macroscale mechanical properties. This study suggests that there are important insights of cell wall mechanics and structural features that can only be investigated by carrying tensile characterization of samples not confounded by extracellular parameters. To the best of our knowledge, the plant cell wall at subcellular scale was never characterized under tensile loading. By coupling the structure based multiscale modeling and mechanical characterizations at different length scales, an attempt was made to provide novel insights towards understanding the mechanics and architecture of cell wall. This study also suggests that a multiscale investigation is essential for garnering fundamental insights into the hierarchical deformation of biological systems.

Low-wave number analysis of observations and ensemble forecasts to develop metrics for the selection of most realistic members to study multi-scale interactions between the environment and the convective organization of hurricanes: Focus on Rapid Intensification

NASA Astrophysics Data System (ADS)

Hristova-Veleva, S. M.; Chen, H.; Gopalakrishnan, S.; Haddad, Z. S.

2017-12-01

Tropical cyclones (TCs) are the product of complex multi-scale processes and interactions. The role of the environment has long been recognized. However, recent research has shown that convective-scale processes in the hurricane core might also play a crucial role in determining TCs intensity and size. Several studies have linked Rapid Intensification to the characteristics of the convective clouds (shallow versus deep), their organization (isolated versus wide-spread) and their location with respect to dynamical controls (the vertical shear, the radius of maximum wind). Yet a third set of controls signifies the interaction between the storm-scale and large-scale processes. Our goal is to use observations and models to advance the still-lacking understanding of these processes. Recently, hurricane models have improved significantly. However, deterministic forecasts have limitations due to the uncertainty in the representation of the physical processes and initial conditions. A crucial step forward is the use of high-resolution ensembles. We adopt the following approach: i) generate a high resolution ensemble forecast using HWRF; ii) produce synthetic data (e.g. brightness temperature) from the model fields for direct comparison to satellite observations; iii) develop metrics to allow us to sub-select the realistic members of the ensemble, based on objective measures of the similarity between observed and forecasted structures; iv) for these most-realistic members, determine the skill in forecasting TCs to provide"guidance on guidance"; v) use the members with the best predictive skill to untangle the complex multi-scale interactions. We will report on the first three goals of our research, using forecasts and observations of hurricane Edouard (2014), focusing on RI. We will focus on describing the metrics for the selection of the most appropriate ensemble members, based on applying low-wave number analysis (WNA - Hristova-Veleva et al., 2016) to the observed and forecasted 2D fields to develop objective criteria for consistency. We investigate the WNA cartoons of environmental moisture, precipitation structure and surface convergence. We will present the preliminary selection of most skillful members and will outline our future goals - analyzing the multi-scale interactions using these members

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

PubMed

Malkin, V M; Fisch, N J

2018-03-01

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

Transition between inverse and direct energy cascades in multiscale optical turbulence

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Hybrid multiscale modeling and prediction of cancer cell behavior

PubMed Central

Habibi, Jafar

2017-01-01

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

Hybrid multiscale modeling and prediction of cancer cell behavior.

PubMed

Zangooei, Mohammad Hossein; Habibi, Jafar

2017-01-01

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

SHORT RANGE ENSEMBLE Products

Science.gov Websites

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

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

EPA Science Inventory

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

Science framework for conservation and restoration of the sagebrush biome: Linking the Department of the Interior’s Integrated Rangeland Fire Management Strategy to long-term strategic conservation actions

Treesearch

J.C. Chambers; J.L. Beck; J.B. Bradford; J. Bybee; S. Campbell; J. Carlson; T.J. Christiansen; K.J. Clause; G. Collins; M.R. Crist; J.B. Dinkins; K.E. Doherty; F. Edwards; S. Espinosa; K.A. Griffin; P. Griffin; J.R. Haas; S.E. Hanser; D.W. Havlina; K.F. Henke; J.D. Hennig; L.A. Joyce; F.M. Kilkenny; S.M. Kulpa; L.L. Kurth; J.D. Maestas; M. Manning; K.E. Mayer; B.A. Mealor; C. McCarthy; M. Pellant; M.A. Perea; K.L. Prentice; D.A. Pyke; L.A. Wiechman; A. Wuenschel

2017-01-01

The Science Framework is intended to link the Department of the Interior’s Integrated Rangeland Fire Management Strategy with long-term strategic conservation actions in the sagebrush biome. The Science Framework provides a multiscale approach for prioritizing areas for management and determining effective management strategies within the sagebrush biome. The emphasis...

Oxygen Modulates the Effectiveness of Granuloma Mediated Host Response to Mycobacterium tuberculosis: A Multiscale Computational Biology Approach

PubMed Central

Sershen, Cheryl L.; Plimpton, Steven J.; May, Elebeoba E.

2016-01-01

Mycobacterium tuberculosis associated granuloma formation can be viewed as a structural immune response that can contain and halt the spread of the pathogen. In several mammalian hosts, including non-human primates, Mtb granulomas are often hypoxic, although this has not been observed in wild type murine infection models. While a presumed consequence, the structural contribution of the granuloma to oxygen limitation and the concomitant impact on Mtb metabolic viability and persistence remains to be fully explored. We develop a multiscale computational model to test to what extent in vivo Mtb granulomas become hypoxic, and investigate the effects of hypoxia on host immune response efficacy and mycobacterial persistence. Our study integrates a physiological model of oxygen dynamics in the extracellular space of alveolar tissue, an agent-based model of cellular immune response, and a systems biology-based model of Mtb metabolic dynamics. Our theoretical studies suggest that the dynamics of granuloma organization mediates oxygen availability and illustrates the immunological contribution of this structural host response to infection outcome. Furthermore, our integrated model demonstrates the link between structural immune response and mechanistic drivers influencing Mtbs adaptation to its changing microenvironment and the qualitative infection outcome scenarios of clearance, containment, dissemination, and a newly observed theoretical outcome of transient containment. We observed hypoxic regions in the containment granuloma similar in size to granulomas found in mammalian in vivo models of Mtb infection. In the case of the containment outcome, our model uniquely demonstrates that immune response mediated hypoxic conditions help foster the shift down of bacteria through two stages of adaptation similar to thein vitro non-replicating persistence (NRP) observed in the Wayne model of Mtb dormancy. The adaptation in part contributes to the ability of Mtb to remain dormant for years after initial infection. PMID:26913242

Oxygen Modulates the Effectiveness of Granuloma Mediated Host Response to Mycobacterium tuberculosis: A Multiscale Computational Biology Approach.

PubMed

Sershen, Cheryl L; Plimpton, Steven J; May, Elebeoba E

2016-01-01

Mycobacterium tuberculosis associated granuloma formation can be viewed as a structural immune response that can contain and halt the spread of the pathogen. In several mammalian hosts, including non-human primates, Mtb granulomas are often hypoxic, although this has not been observed in wild type murine infection models. While a presumed consequence, the structural contribution of the granuloma to oxygen limitation and the concomitant impact on Mtb metabolic viability and persistence remains to be fully explored. We develop a multiscale computational model to test to what extent in vivo Mtb granulomas become hypoxic, and investigate the effects of hypoxia on host immune response efficacy and mycobacterial persistence. Our study integrates a physiological model of oxygen dynamics in the extracellular space of alveolar tissue, an agent-based model of cellular immune response, and a systems biology-based model of Mtb metabolic dynamics. Our theoretical studies suggest that the dynamics of granuloma organization mediates oxygen availability and illustrates the immunological contribution of this structural host response to infection outcome. Furthermore, our integrated model demonstrates the link between structural immune response and mechanistic drivers influencing Mtbs adaptation to its changing microenvironment and the qualitative infection outcome scenarios of clearance, containment, dissemination, and a newly observed theoretical outcome of transient containment. We observed hypoxic regions in the containment granuloma similar in size to granulomas found in mammalian in vivo models of Mtb infection. In the case of the containment outcome, our model uniquely demonstrates that immune response mediated hypoxic conditions help foster the shift down of bacteria through two stages of adaptation similar to the in vitro non-replicating persistence (NRP) observed in the Wayne model of Mtb dormancy. The adaptation in part contributes to the ability of Mtb to remain dormant for years after initial infection.

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.;

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Versatile Micromechanics Model for Multiscale Analysis of Composite Structures

NASA Astrophysics Data System (ADS)

Kwon, Y. W.; Park, M. S.

2013-08-01

A general-purpose micromechanics model was developed so that the model could be applied to various composite materials such as reinforced by particles, long fibers and short fibers as well as those containing micro voids. Additionally, the model can be used with hierarchical composite materials. The micromechanics model can be used to compute effective material properties like elastic moduli, shear moduli, Poisson's ratios, and coefficients of thermal expansion for the various composite materials. The model can also calculate the strains and stresses at the constituent material level such as fibers, particles, and whiskers from the composite level stresses and strains. The model was implemented into ABAQUS using the UMAT option for multiscale analysis. An extensive set of examples are presented to demonstrate the reliability and accuracy of the developed micromechanics model for different kinds of composite materials. Another set of examples is provided to study the multiscale analysis of composite structures.

Multiscale Modeling of Multiphase Fluid Flow

DTIC Science & Technology

2016-08-01

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

Multi-Scale Characterization of Orthotropic Microstructures

DTIC Science & Technology

2008-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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

PubMed

Lefkimmiatis, Stamatios; Maragos, Petros; Papandreou, George

2009-08-01

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

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

DTIC Science & Technology

2011-04-09

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

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

DTIC Science & Technology

2016-07-15

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

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

DTIC Science & Technology

2016-07-15

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

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

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.

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

PubMed

Chaddad, Ahmad; Daniel, Paul; Niazi, Tamim

2018-01-01

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

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

PubMed Central

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

2012-01-01

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

On-lattice agent-based simulation of populations of cells within the open-source Chaste framework.

PubMed

Figueredo, Grazziela P; Joshi, Tanvi V; Osborne, James M; Byrne, Helen M; Owen, Markus R

2013-04-06

Over the years, agent-based models have been developed that combine cell division and reinforced random walks of cells on a regular lattice, reaction-diffusion equations for nutrients and growth factors; and ordinary differential equations for the subcellular networks regulating the cell cycle. When linked to a vascular layer, this multiple scale model framework has been applied to tumour growth and therapy. Here, we report on the creation of an agent-based multi-scale environment amalgamating the characteristics of these models within a Virtual Physiological Human (VPH) Exemplar Project. This project enables reuse, integration, expansion and sharing of the model and relevant data. The agent-based and reaction-diffusion parts of the multi-scale model have been implemented and are available for download as part of the latest public release of Chaste (Cancer, Heart and Soft Tissue Environment; http://www.cs.ox.ac.uk/chaste/), part of the VPH Toolkit (http://toolkit.vph-noe.eu/). The environment functionalities are verified against the original models, in addition to extra validation of all aspects of the code. In this work, we present the details of the implementation of the agent-based environment, including the system description, the conceptual model, the development of the simulation model and the processes of verification and validation of the simulation results. We explore the potential use of the environment by presenting exemplar applications of the 'what if' scenarios that can easily be studied in the environment. These examples relate to tumour growth, cellular competition for resources and tumour responses to hypoxia (low oxygen levels). We conclude our work by summarizing the future steps for the expansion of the current system.

Multiscale Modeling of Virus Entry via Receptor-Mediated Endocytosis

NASA Astrophysics Data System (ADS)

Liu, Jin

2012-11-01

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

Modeling crack propagation in polycrystalline microstructure using variational multiscale method

DOE PAGES

Sun, Shang; Sundararaghavan, Veera

2016-01-01

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

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

EPA Science Inventory

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

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

EPA Science Inventory

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

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

USDA-ARS?s Scientific Manuscript database

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

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

EPA Science Inventory

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

Numerical Simulations of a Multiscale Model of Stratified Langmuir Circulation

NASA Astrophysics Data System (ADS)

Malecha, Ziemowit; Chini, Gregory; Julien, Keith

2012-11-01

Langmuir circulation (LC), a prominent form of wind and surface-wave driven shear turbulence in the ocean surface boundary layer (BL), is commonly modeled using the Craik-Leibovich (CL) equations, a phase-averaged variant of the Navier-Stokes (NS) equations. Although surface-wave filtering renders the CL equations more amenable to simulation than are the instantaneous NS equations, simulations in wide domains, hundreds of times the BL depth, currently earn the ``grand challenge'' designation. To facilitate simulations of LC in such spatially-extended domains, we have derived multiscale CL equations by exploiting the scale separation between submesoscale and BL flows in the upper ocean. The numerical algorithm for simulating this multiscale model resembles super-parameterization schemes used in meteorology, but retains a firm mathematical basis. We have validated our algorithm and here use it to perform multiscale simulations of the interaction between LC and upper ocean density stratification. ZMM, GPC, KJ gratefully acknowledge funding from NSF CMG Award 0934827.

Data Services and Transnational Access for European Geosciences Multi-Scale Laboratories

NASA Astrophysics Data System (ADS)

Funiciello, Francesca; Rosenau, Matthias; Sagnotti, Leonardo; Scarlato, Piergiorgio; Tesei, Telemaco; Trippanera, Daniele; Spires, Chris; Drury, Martyn; Kan-Parker, Mirjam; Lange, Otto; Willingshofer, Ernst

2016-04-01

The EC policy for research in the new millennium supports the development of european-scale research infrastructures. In this perspective, the existing research infrastructures are going to be integrated with the objective to increase their accessibility and to enhance the usability of their multidisciplinary data. Building up integrating Earth Sciences infrastructures in Europe is the mission of the Implementation Phase (IP) of the European Plate Observing System (EPOS) project (2015-2019). The integration of european multiscale laboratories - analytical, experimental petrology and volcanology, magnetic and analogue laboratories - plays a key role in this context and represents a specific task of EPOS IP. In the frame of the WP16 of EPOS IP working package 16, European geosciences multiscale laboratories aims to be linked, merging local infrastructures into a coherent and collaborative network. In particular, the EPOS IP WP16-task 4 "Data services" aims at standardize data and data products, already existing and newly produced by the participating laboratories, and made them available through a new digital platform. The following data and repositories have been selected for the purpose: 1) analytical and properties data a) on volcanic ash from explosive eruptions, of interest to the aviation industry, meteorological and government institutes, b) on magmas in the context of eruption and lava flow hazard evaluation, and c) on rock systems of key importance in mineral exploration and mining operations; 2) experimental data describing: a) rock and fault properties of importance for modelling and forecasting natural and induced subsidence, seismicity and associated hazards, b) rock and fault properties relevant for modelling the containment capacity of rock systems for CO2, energy sources and wastes, c) crustal and upper mantle rheology as needed for modelling sedimentary basin formation and crustal stress distributions, d) the composition, porosity, permeability, and frackability of reservoir rocks of interest in relation to unconventional resources and geothermal energy; 3) repository of analogue models on tectonic processes, from the plate to the reservoir scale, relevant to the understanding of Earth dynamics, geo-hazards and geo-energy; 4) paleomagnetic data, that are crucial a) for understanding the evolution of sedimentary basins and associated resources, and b) for charting geo-hazard frequency. EPOS IP WP16 - task 5 aims to create mechanisms and procedures for easy trans-national access to multiscale laboratory facilities. Moreover, the same task will coordinate all the activities in a pilot phase to test, validate and consolidate the over mentioned services and to provide a proof of concept for what will be offered beyond the completion of the EPOS IP.

Multi-scale structural community organisation of the human genome.

PubMed

Boulos, Rasha E; Tremblay, Nicolas; Arneodo, Alain; Borgnat, Pierre; Audit, Benjamin

2017-04-11

Structural interaction frequency matrices between all genome loci are now experimentally achievable thanks to high-throughput chromosome conformation capture technologies. This ensues a new methodological challenge for computational biology which consists in objectively extracting from these data the structural motifs characteristic of genome organisation. We deployed the fast multi-scale community mining algorithm based on spectral graph wavelets to characterise the networks of intra-chromosomal interactions in human cell lines. We observed that there exist structural domains of all sizes up to chromosome length and demonstrated that the set of structural communities forms a hierarchy of chromosome segments. Hence, at all scales, chromosome folding predominantly involves interactions between neighbouring sites rather than the formation of links between distant loci. Multi-scale structural decomposition of human chromosomes provides an original framework to question structural organisation and its relationship to functional regulation across the scales. By construction the proposed methodology is independent of the precise assembly of the reference genome and is thus directly applicable to genomes whose assembly is not fully determined.

Computational Chemistry Toolkit for Energetic Materials Design

DTIC Science & Technology

2006-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed Central

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

2014-01-01

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

Multiscale turbulence models based on convected fluid microstructure

NASA Astrophysics Data System (ADS)

Holm, Darryl D.; Tronci, Cesare

2012-11-01

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

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

PubMed

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

2016-01-01

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

Multiscale approach to link red blood cell dynamics, shear viscosity, and ATP release.

PubMed

Forsyth, Alison M; Wan, Jiandi; Owrutsky, Philip D; Abkarian, Manouk; Stone, Howard A

2011-07-05

RBCs are known to release ATP, which acts as a signaling molecule to cause dilation of blood vessels. A reduction in the release of ATP from RBCs has been linked to diseases such as type II diabetes and cystic fibrosis. Furthermore, reduced deformation of RBCs has been correlated with myocardial infarction and coronary heart disease. Because ATP release has been linked to cell deformation, we undertook a multiscale approach to understand the links between single RBC dynamics, ATP release, and macroscopic viscosity all at physiological shear rates. Our experimental approach included microfluidics, ATP measurements using a bioluminescent reaction, and rheology. Using microfluidics technology with high-speed imaging, we visualize the deformation and dynamics of single cells, which are known to undergo motions such as tumbling, swinging, tanktreading, and deformation. We report that shear thinning is not due to cellular deformation as previously believed, but rather it is due to the tumbling-to-tanktreading transition. In addition, our results indicate that ATP release is constant at shear stresses below a threshold (3 Pa), whereas above the threshold ATP release is increased and accompanied by large cellular deformations. Finally, performing experiments with well-known inhibitors, we show that the Pannexin 1 hemichannel is the main avenue for ATP release both above and below the threshold, whereas, the cystic fibrosis transmembrane conductance regulator only contributes to deformation-dependent ATP release above the stress threshold.

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

NASA Technical Reports Server (NTRS)

Noor, Ahmed K. (Compiler)

2002-01-01

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

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

PubMed Central

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Upscaling the Coupled Water and Heat Transport in the Shallow Subsurface

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

PubMed

Zhang, Xueqing; Bieberle-Hütter, Anja

2016-06-08

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

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

PubMed Central

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

2012-01-01

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

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

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

Goldhaber, Steve; Holland, Marika

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

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

DOE PAGES

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

2015-04-29

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

Multiscale model reduction for shale gas transport in poroelastic fractured media

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

Jiang, P.; Yu, Z.

2011-12-01

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

Multiscale Granger causality

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Multiscale information modelling for heart morphogenesis

NASA Astrophysics Data System (ADS)

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

2010-07-01

Science is made feasible by the adoption of common systems of units. As research has become more data intensive, especially in the biomedical domain, it requires the adoption of a common system of information models, to make explicit the relationship between one set of data and another, regardless of format. This is being realised through the OBO Foundry to develop a suite of reference ontologies, and NCBO Bioportal to provide services to integrate biomedical resources and functionality to visualise and create mappings between ontology terms. Biomedical experts tend to be focused at one level of spatial scale, be it biochemistry, cell biology, or anatomy. Likewise, the ontologies they use tend to be focused at a particular level of scale. There is increasing interest in a multiscale systems approach, which attempts to integrate between different levels of scale to gain understanding of emergent effects. This is a return to physiological medicine with a computational emphasis, exemplified by the worldwide Physiome initiative, and the European Union funded Network of Excellence in the Virtual Physiological Human. However, little work has been done on how information modelling itself may be tailored to a multiscale systems approach. We demonstrate how this can be done for the complex process of heart morphogenesis, which requires multiscale understanding in both time and spatial domains. Such an effort enables the integration of multiscale metrology.

Relative Navigation Strategies for the Magnetopheric Multiscale Mission

NASA Technical Reports Server (NTRS)

Gramling, Cheryl; Carpenter, Russell; Lee, Taesul; Long, Anne

2004-01-01

This paper evaluates several navigation approaches for the Magnetospheric Multiscale (MMS) mission, which consists of a tetrahedral formation of satellites flying in highly eccentric Earth orbits. For this investigation, inter-satellite separations of approximately 10 kilometers near apogee are used for the first two phases of the MMS mission. Navigation approaches were studied using ground station two-way Doppler measurements, Global Positioning System (GPS) pseudorange measurements, and cross-link range measurements between the members of the formation. An absolute position accuracy of 15 kilometers or better can be achieved with most of the approaches studied, and a relative position accuracy of 100 meters or better can be achieved at apogee in several cases.

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

Du, Qiang

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

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.

Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites

DTIC Science & Technology

2016-03-09

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

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

EPA Science Inventory

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

Modeling process-structure-property relationships for additive manufacturing

NASA Astrophysics Data System (ADS)

Yan, Wentao; Lin, Stephen; Kafka, Orion L.; Yu, Cheng; Liu, Zeliang; Lian, Yanping; Wolff, Sarah; Cao, Jian; Wagner, Gregory J.; Liu, Wing Kam

2018-02-01

This paper presents our latest work on comprehensive modeling of process-structure-property relationships for additive manufacturing (AM) materials, including using data-mining techniques to close the cycle of design-predict-optimize. To illustrate the processstructure relationship, the multi-scale multi-physics process modeling starts from the micro-scale to establish a mechanistic heat source model, to the meso-scale models of individual powder particle evolution, and finally to the macro-scale model to simulate the fabrication process of a complex product. To link structure and properties, a highefficiency mechanistic model, self-consistent clustering analyses, is developed to capture a variety of material response. The model incorporates factors such as voids, phase composition, inclusions, and grain structures, which are the differentiating features of AM metals. Furthermore, we propose data-mining as an effective solution for novel rapid design and optimization, which is motivated by the numerous influencing factors in the AM process. We believe this paper will provide a roadmap to advance AM fundamental understanding and guide the monitoring and advanced diagnostics of AM processing.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Biocultural approaches to well-being and sustainability indicators across scales

Treesearch

Eleanor J. Sterling; Christopher Filardi; Anne Toomey; Amanda Sigouin; Erin Betley; Nadav Gazit; Jennifer Newell; Simon Albert; Diana Alvira; Nadia Bergamini; Mary Blair; David Boseto; Kate Burrows; Nora Bynum; Sophie Caillon; Jennifer E. Caselle; Joachim Claudet; Georgina Cullman; Rachel Dacks; Pablo B. Eyzaguirre; Steven Gray; James Herrera; Peter Kenilorea; Kealohanuiopuna Kinney; Natalie Kurashima; Suzanne Macey; Cynthia Malone; Senoveva Mauli; Joe McCarter; Heather McMillen; Pua’ala Pascua; Patrick Pikacha; Ana L. Porzecanski; Pascale de Robert; Matthieu Salpeteur; Myknee Sirikolo; Mark H. Stege; Kristina Stege; Tamara Ticktin; Ron Vave; Alaka Wali; Paige West; Kawika B. Winter; Stacy D. Jupiter

2017-01-01

Monitoring and evaluation are central to ensuring that innovative, multi-scale, and interdisciplinary approaches to sustainability are effective. The development of relevant indicators for local sustainable management outcomes, and the ability to link these to broader national and international policy targets, are key challenges for resource managers, policymakers, and...

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

DTIC Science & Technology

2017-09-01

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

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

DTIC Science & Technology

2011-09-26

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

PubMed Central

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

2013-01-01

During a full cardiac cycle, the left atrium successively behaves as a reservoir, a conduit and a pump. This complex behavior makes it unrealistic to apply the time-varying elastance theory to characterize the left atrium, first, because this theory has known limitations, and second, because it is still uncertain whether the load independence hypothesis holds. In this study, we aim to bypass this uncertainty by relying on another kind of mathematical model of the cardiac chambers. In the present work, we describe both the left atrium and the left ventricle with a multi-scale model. The multi-scale property of this model comes from the fact that pressure inside a cardiac chamber is derived from a model of the sarcomere behavior. Macroscopic model parameters are identified from reference dog hemodynamic data. The multi-scale model of the cardiovascular system including the left atrium is then simulated to show that the physiological roles of the left atrium are correctly reproduced. This include a biphasic pressure wave and an eight-shaped pressure-volume loop. We also test the validity of our model in non basal conditions by reproducing a preload reduction experiment by inferior vena cava occlusion with the model. We compute the variation of eight indices before and after this experiment and obtain the same variation as experimentally observed for seven out of the eight indices. In summary, the multi-scale mathematical model presented in this work is able to correctly account for the three roles of the left atrium and also exhibits a realistic left atrial pressure-volume loop. Furthermore, the model has been previously presented and validated for the left ventricle. This makes it a proper alternative to the time-varying elastance theory if the focus is set on precisely representing the left atrial and left ventricular behaviors. PMID:23755183

Functional connectivity in replicated urban landscapes in the land snail (Cornu aspersum).

PubMed

Balbi, Manon; Ernoult, Aude; Poli, Pedro; Madec, Luc; Guiller, Annie; Martin, Marie-Claire; Nabucet, Jean; Beaujouan, Véronique; Petit, Eric J

2018-03-01

Urban areas are highly fragmented and thereby exert strong constraints on individual dispersal. Despite this, some species manage to persist in urban areas, such as the garden snail, Cornu aspersum, which is common in cityscapes despite its low mobility. Using landscape genetic approaches, we combined study area replication and multiscale analysis to determine how landscape composition, configuration and connectivity influence snail dispersal across urban areas. At the overall landscape scale, areas with a high percentage of roads decreased genetic differentiation between populations. At the population scale, genetic differentiation was positively linked with building surface, the proportion of borders where wooded patches and roads appeared side by side and the proportion of borders combining wooded patches and other impervious areas. Analyses based on pairwise genetic distances validated the isolation-by-distance and isolation-by-resistance models for this land snail, with an equal fit to least-cost paths and circuit-theory-based models. Each of the 12 landscapes analysed separately yielded specific relations to environmental features, whereas analyses integrating all replicates highlighted general common effects. Our results suggest that urban transport infrastructures facilitate passive snail dispersal. At a local scale, corresponding to active dispersal, unfavourable habitats (wooded and impervious areas) isolate populations. This work upholds the use of replicated landscapes to increase the generalizability of landscape genetics results and shows how multiscale analyses provide insight into scale-dependent processes. © 2018 John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

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

2012-03-01

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

Multiscale modelling and nonlinear simulation of vascular tumour growth

PubMed Central

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

2011-01-01

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

Multi-scale finite element model of growth plate damage during the development of slipped capital femoral epiphysis.

PubMed

Farzaneh, S; Paseta, O; Gómez-Benito, M J

2015-04-01

Slipped capital femoral epiphysis (SCFE) is one of the most common disorders of adolescent hips. A number of works have related the development of SCFE to mechanical factors. Due to the difficulty of diagnosing SCFE in its early stages, the disorder often progresses over time, resulting in serious side effects. Therefore, the development of a tool to predict the initiation of damage in the growth plate is needed. Because the growth plate is a heterogeneous structure, to develop a precise and reliable model, it is necessary to consider this structure from both macro- and microscale perspectives. Thus, the main objective of this work is to develop a numerical multi-scale model that links damage occurring at the microscale to damage occurring at the macroscale. The use of this model enables us to predict which regions of the growth plate are at high risk of damage. First, we have independently analyzed the microscale to simulate the microstructure under shear and tensile tests to calibrate the damage model. Second, we have employed the model to simulate damage occurring in standardized healthy and affected femurs during the heel-strike stage of stair climbing. Our results indicate that on the macroscale, damage is concentrated in the medial region of the growth plate in both healthy and affected femurs. Furthermore, damage to the affected femur is greater than damage to the healthy femur from both the micro- and macrostandpoints. Maximal damage is observed in territorial matrices. Furthermore, simulations illustrate that little damage occurs in the reserve zone. These findings are consistent with previous findings reported in well-known experimental works.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

An optimized algorithm for multiscale wideband deconvolution of radio astronomical images

NASA Astrophysics Data System (ADS)

Offringa, A. R.; Smirnov, O.

2017-10-01

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

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

PubMed

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Multiscale modeling of particle in suspension with smoothed dissipative particle dynamics

NASA Astrophysics Data System (ADS)

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

2012-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

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

Treesearch

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

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

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

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

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

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

DOE PAGES

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

2018-04-04

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

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

PubMed

Hamdi, Mustapha

2009-12-02

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

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

DOE PAGES

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

2018-03-15

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

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

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

Chen, Zhangxing; Huang, Tianyu; Shao, Yimin

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

PDF-based heterogeneous multiscale filtration model.

PubMed

Gong, Jian; Rutland, Christopher J

2015-04-21

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

Computational aspects in mechanical modeling of the articular cartilage tissue.

PubMed

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.

Solar Activity Across the Scales: From Small-Scale Quiet-Sun Dynamics to Magnetic Activity Cycles

NASA Technical Reports Server (NTRS)

Kitiashvili, Irina N.; Collins, Nancy N.; Kosovichev, Alexander G.; Mansour, Nagi N.; Wray, Alan A.

2017-01-01

Observations as well as numerical and theoretical models show that solar dynamics is characterized by complicated interactions and energy exchanges among different temporal and spatial scales. It reveals magnetic self-organization processes from the smallest scale magnetized vortex tubes to the global activity variation known as the solar cycle. To understand these multiscale processes and their relationships, we use a two-fold approach: 1) realistic 3D radiative MHD simulations of local dynamics together with high resolution observations by IRIS, Hinode, and SDO; and 2) modeling of solar activity cycles by using simplified MHD dynamo models and mathematical data assimilation techniques. We present recent results of this approach, including the interpretation of observational results from NASA heliophysics missions and predictive capabilities. In particular, we discuss the links between small-scale dynamo processes in the convection zone and atmospheric dynamics, as well as an early prediction of Solar Cycle 25.

Solar activity across the scales: from small-scale quiet-Sun dynamics to magnetic activity cycles

NASA Astrophysics Data System (ADS)

Kitiashvili, I.; Collins, N.; Kosovichev, A. G.; Mansour, N. N.; Wray, A. A.

2017-12-01

Observations as well as numerical and theoretical models show that solar dynamics is characterized by complicated interactions and energy exchanges among different temporal and spatial scales. It reveals magnetic self-organization processes from the smallest scale magnetized vortex tubes to the global activity variation known as the solar cycle. To understand these multiscale processes and their relationships, we use a two-fold approach: 1) realistic 3D radiative MHD simulations of local dynamics together with high-resolution observations by IRIS, Hinode, and SDO; and 2) modeling of solar activity cycles by using simplified MHD dynamo models and mathematical data assimilation techniques. We present recent results of this approach, including the interpretation of observational results from NASA heliophysics missions and predictive capabilities. In particular, we discuss the links between small-scale dynamo processes in the convection zone and atmospheric dynamics, as well as an early prediction of Solar Cycle 25.

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

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2012-01-01

A framework for the multiscale design and analysis of composite materials and structures is presented. The ImMAC software suite, developed at NASA Glenn Research Center, embeds efficient, nonlinear micromechanics capabilities within higher scale structural analysis methods such as finite element analysis. The result is an integrated, multiscale tool that relates global loading to the constituent scale, captures nonlinearities at this scale, and homogenizes local nonlinearities to predict their effects at the structural scale. Example applications of the multiscale framework are presented for the stochastic progressive failure of a SiC/Ti composite tensile specimen and the effects of microstructural variations on the nonlinear response of woven polymer matrix composites.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2011-01-01

A framework for the multiscale design and analysis of composite materials and structures is presented. The ImMAC software suite, developed at NASA Glenn Research Center, embeds efficient, nonlinear micromechanics capabilities within higher scale structural analysis methods such as finite element analysis. The result is an integrated, multiscale tool that relates global loading to the constituent scale, captures nonlinearities at this scale, and homogenizes local nonlinearities to predict their effects at the structural scale. Example applications of the multiscale framework are presented for the stochastic progressive failure of a SiC/Ti composite tensile specimen and the effects of microstructural variations on the nonlinear response of woven polymer matrix composites.

Multiscale Modeling of Mesoscale and Interfacial Phenomena

NASA Astrophysics Data System (ADS)

Petsev, Nikolai Dimitrov

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

Nonlinear dynamics and damage induced properties of soft matter with application in oncology

NASA Astrophysics Data System (ADS)

Naimark, O.

2017-09-01

Molecular-morphological signs of oncogenesis could be linked to multiscale collective effects in molecular, cell and tissue related to defects (damage) dynamics. It was shown that nonlinear behavior of biological systems can be linked to the existence of characteristic collective open state modes providing the coherent expression dynamics. New type of criticality in nonequilibrium systems with defects—structural-scaling transition allows the definition of the `driving force' for a biological soft matter related to consolidated open states. The set of collective open states (breathers, autosolitons and blow-up modes) in the molecular ensembles provides the collective expression dynamics to attract the entire system (cell, tissue) toward a few preferred global states. The co-existence of three types of collective modes determines the multifractal scenario of biological soft matter dynamics. The appearance of `globally convergent' dynamics corresponding to the coherent behavior of multiscale blow-up open states (blow-up gene expression) leads to anomalous localized softening (blow-up localized damage) and the subjection of the cells (or tissue) to monofractal dynamics. This dynamics can be associated with cancer progression.

Multiscale Analysis of Independent Alzheimer's Cohorts Finds Disruption of Molecular, Genetic, and Clinical Networks by Human Herpesvirus.

PubMed

Readhead, Ben; Haure-Mirande, Jean-Vianney; Funk, Cory C; Richards, Matthew A; Shannon, Paul; Haroutunian, Vahram; Sano, Mary; Liang, Winnie S; Beckmann, Noam D; Price, Nathan D; Reiman, Eric M; Schadt, Eric E; Ehrlich, Michelle E; Gandy, Sam; Dudley, Joel T

2018-06-21

Investigators have long suspected that pathogenic microbes might contribute to the onset and progression of Alzheimer's disease (AD) although definitive evidence has not been presented. Whether such findings represent a causal contribution, or reflect opportunistic passengers of neurodegeneration, is also difficult to resolve. We constructed multiscale networks of the late-onset AD-associated virome, integrating genomic, transcriptomic, proteomic, and histopathological data across four brain regions from human post-mortem tissue. We observed increased human herpesvirus 6A (HHV-6A) and human herpesvirus 7 (HHV-7) from subjects with AD compared with controls. These results were replicated in two additional, independent and geographically dispersed cohorts. We observed regulatory relationships linking viral abundance and modulators of APP metabolism, including induction of APBB2, APPBP2, BIN1, BACE1, CLU, PICALM, and PSEN1 by HHV-6A. This study elucidates networks linking molecular, clinical, and neuropathological features with viral activity and is consistent with viral activity constituting a general feature of AD. Copyright © 2018 Elsevier Inc. All rights reserved.

Physics-based multiscale coupling for full core nuclear reactor simulation

DOE PAGES

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

2015-10-01

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

A Multiscale Agent-Based in silico Model of Liver Fibrosis Progression

PubMed Central

Dutta-Moscato, Joyeeta; Solovyev, Alexey; Mi, Qi; Nishikawa, Taichiro; Soto-Gutierrez, Alejandro; Fox, Ira J.; Vodovotz, Yoram

2014-01-01

Chronic hepatic inflammation involves a complex interplay of inflammatory and mechanical influences, ultimately manifesting in a characteristic histopathology of liver fibrosis. We created an agent-based model (ABM) of liver tissue in order to computationally examine the consequence of liver inflammation. Our liver fibrosis ABM (LFABM) is comprised of literature-derived rules describing molecular and histopathological aspects of inflammation and fibrosis in a section of chemically injured liver. Hepatocytes are modeled as agents within hexagonal lobules. Injury triggers an inflammatory reaction, which leads to activation of local Kupffer cells and recruitment of monocytes from circulation. Portal fibroblasts and hepatic stellate cells are activated locally by the products of inflammation. The various agents in the simulation are regulated by above-threshold concentrations of pro- and anti-inflammatory cytokines and damage-associated molecular pattern molecules. The simulation progresses from chronic inflammation to collagen deposition, exhibiting periportal fibrosis followed by bridging fibrosis, and culminating in disruption of the regular lobular structure. The ABM exhibited key histopathological features observed in liver sections from rats treated with carbon tetrachloride (CCl4). An in silico “tension test” for the hepatic lobules predicted an overall increase in tissue stiffness, in line with clinical elastography literature and published studies in CCl4-treated rats. Therapy simulations suggested differential anti-fibrotic effects of neutralizing tumor necrosis factor alpha vs. enhancing M2 Kupffer cells. We conclude that a computational model of liver inflammation on a structural skeleton of physical forces can recapitulate key histopathological and macroscopic properties of CCl4-injured liver. This multiscale approach linking molecular and chemomechanical stimuli enables a model that could be used to gain translationally relevant insights into liver fibrosis. PMID:25152891

Multiscale simulation of molecular processes in cellular environments.

PubMed

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

2016-11-13

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

A physics based multiscale modeling of cavitating flows.

PubMed

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

2017-03-02

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

A grain boundary damage model for delamination

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

A physics based multiscale modeling of cavitating flows

PubMed Central

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

2018-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

Three-Dimensional Visualization of Ozone Process Data.

DTIC Science & Technology

1997-06-18

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

Multiscale Simulation of Blood Flow in Brain Arteries with an Aneurysm

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

Leopold Grinberg; Vitali Morozov; Dmitry A. Fedosov

2013-04-24

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

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

PubMed

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

2015-12-01

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

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

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

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

EPA Pesticide Factsheets

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

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

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

DTIC Science & Technology

2013-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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.

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

PubMed

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

2008-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

A study of microindentation hardness tests by mechanism-based strain gradient plasticity

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

Huang, Y.; Xue, Z.; Gao, H.

2000-08-01

We recently proposed a theory of mechanism-based strain gradient (MSG) plasticity to account for the size dependence of plastic deformation at micron- and submicron-length scales. The MSG plasticity theory connects micron-scale plasticity to dislocation theories via a multiscale, hierarchical framework linking Taylor's dislocation hardening model to strain gradient plasticity. Here we show that the theory of MSG plasticity, when used to study micro-indentation, indeed reproduces the linear dependence observed in experiments, thus providing an important self-consistent check of the theory. The effects of pileup, sink-in, and the radius of indenter tip have been taken into account in the indentation model.more » In accomplishing this objective, we have generalized the MSG plasticity theory to include the elastic deformation in the hierarchical framework. (c) 2000 Materials Research Society.« less

Characterization of heterogeneity in the Heletz sandstone from core to pore scale and quantification of its impact on multi-phase flow

DOE PAGES

Hingerl, Ferdinand F.; Yang, Feifei; Pini, Ronny; ...

2016-02-02

In this paper we present the results of an extensive multiscale characterization of the flow properties and structural and capillary heterogeneities of the Heletz sandstone. We performed petrographic, porosity and capillary pressure measurements on several subsamples. We quantified mm-scale heterogeneity in saturation distributions in a rock core during multi-phase flow using conventional X-ray CT scanning. Core-flooding experiments were conducted under reservoirs conditions (9 MPa, 50 °C) to obtain primary drainage and secondary imbibition relative permeabilities and residual trapping was analyzed and quantified. We provide parameters for relative permeability, capillary pressure and trapping models for further modeling studies. A synchrotron-based microtomographymore » study complements our cm- to mm-scale investigation by providing links between the micromorphology and mm-scale saturation heterogeneities.« less

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

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

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

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

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

EPA Pesticide Factsheets

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

Multiscale Aspects of Modeling Gas-Phase Nanoparticle Synthesis

PubMed Central

Buesser, B.; Gröhn, A.J.

2013-01-01

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

Multiscale Modeling of Cardiac Cellular Energetics

PubMed Central

BASSINGTHWAIGHTE, JAMES B.; CHIZECK, HOWARD J.; ATLAS, LES E.; QIAN, HONG

2010-01-01

Multiscale modeling is essential to integrating knowledge of human physiology starting from genomics, molecular biology, and the environment through the levels of cells, tissues, and organs all the way to integrated systems behavior. The lowest levels concern biophysical and biochemical events. The higher levels of organization in tissues, organs, and organism are complex, representing the dynamically varying behavior of billions of cells interacting together. Models integrating cellular events into tissue and organ behavior are forced to resort to simplifications to minimize computational complexity, thus reducing the model’s ability to respond correctly to dynamic changes in external conditions. Adjustments at protein and gene regulatory levels shortchange the simplified higher-level representations. Our cell primitive is composed of a set of subcellular modules, each defining an intracellular function (action potential, tricarboxylic acid cycle, oxidative phosphorylation, glycolysis, calcium cycling, contraction, etc.), composing what we call the “eternal cell,” which assumes that there is neither proteolysis nor protein synthesis. Within the modules are elements describing each particular component (i.e., enzymatic reactions of assorted types, transporters, ionic channels, binding sites, etc.). Cell subregions are stirred tanks, linked by diffusional or transporter-mediated exchange. The modeling uses ordinary differential equations rather than stochastic or partial differential equations. This basic model is regarded as a primitive upon which to build models encompassing gene regulation, signaling, and long-term adaptations in structure and function. During simulation, simpler forms of the model are used, when possible, to reduce computation. However, when this results in error, the more complex and detailed modules and elements need to be employed to improve model realism. The processes of error recognition and of mapping between different levels of model form complexity are challenging but are essential for successful modeling of large-scale systems in reasonable time. Currently there is to this end no established methodology from computational sciences. PMID:16093514

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

PubMed Central

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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

PubMed

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

2014-01-01

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

Multi-Scale Simulation of High Energy Density Ionic Liquids

DTIC Science & Technology

2007-06-19

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

Multiscale agent-based cancer modeling.

PubMed

Zhang, Le; Wang, Zhihui; Sagotsky, Jonathan A; Deisboeck, Thomas S

2009-04-01

Agent-based modeling (ABM) is an in silico technique that is being used in a variety of research areas such as in social sciences, economics and increasingly in biomedicine as an interdisciplinary tool to study the dynamics of complex systems. Here, we describe its applicability to integrative tumor biology research by introducing a multi-scale tumor modeling platform that understands brain cancer as a complex dynamic biosystem. We summarize significant findings of this work, and discuss both challenges and future directions for ABM in the field of cancer research.

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

NASA Astrophysics Data System (ADS)

Gao, David Yang

2016-10-01

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

Multiscale modeling of the human arterial tree on the TeraGrid.

NASA Astrophysics Data System (ADS)

Karniadakis, Gerorge

2009-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Multiscale characterization and prediction of monsoon rainfall in India using Hilbert-Huang transform and time-dependent intrinsic correlation analysis

NASA Astrophysics Data System (ADS)

Adarsh, S.; Reddy, M. Janga

2017-07-01

In this paper, the Hilbert-Huang transform (HHT) approach is used for the multiscale characterization of All India Summer Monsoon Rainfall (AISMR) time series and monsoon rainfall time series from five homogeneous regions in India. The study employs the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) for multiscale decomposition of monsoon rainfall in India and uses the Normalized Hilbert Transform and Direct Quadrature (NHT-DQ) scheme for the time-frequency characterization. The cross-correlation analysis between orthogonal modes of All India monthly monsoon rainfall time series and that of five climate indices such as Quasi Biennial Oscillation (QBO), El Niño Southern Oscillation (ENSO), Sunspot Number (SN), Atlantic Multi Decadal Oscillation (AMO), and Equatorial Indian Ocean Oscillation (EQUINOO) in the time domain showed that the links of different climate indices with monsoon rainfall are expressed well only for few low-frequency modes and for the trend component. Furthermore, this paper investigated the hydro-climatic teleconnection of ISMR in multiple time scales using the HHT-based running correlation analysis technique called time-dependent intrinsic correlation (TDIC). The results showed that both the strength and nature of association between different climate indices and ISMR vary with time scale. Stemming from this finding, a methodology employing Multivariate extension of EMD and Stepwise Linear Regression (MEMD-SLR) is proposed for prediction of monsoon rainfall in India. The proposed MEMD-SLR method clearly exhibited superior performance over the IMD operational forecast, M5 Model Tree (MT), and multiple linear regression methods in ISMR predictions and displayed excellent predictive skill during 1989-2012 including the four extreme events that have occurred during this period.

Multiscale decoding for reliable brain-machine interface performance over time.

PubMed

Han-Lin Hsieh; Wong, Yan T; Pesaran, Bijan; Shanechi, Maryam M

2017-07-01

Recordings from invasive implants can degrade over time, resulting in a loss of spiking activity for some electrodes. For brain-machine interfaces (BMI), such a signal degradation lowers control performance. Achieving reliable performance over time is critical for BMI clinical viability. One approach to improve BMI longevity is to simultaneously use spikes and other recording modalities such as local field potentials (LFP), which are more robust to signal degradation over time. We have developed a multiscale decoder that can simultaneously model the different statistical profiles of multi-scale spike/LFP activity (discrete spikes vs. continuous LFP). This decoder can also run at multiple time-scales (millisecond for spikes vs. tens of milliseconds for LFP). Here, we validate the multiscale decoder for estimating the movement of 7 major upper-arm joint angles in a non-human primate (NHP) during a 3D reach-to-grasp task. The multiscale decoder uses motor cortical spike/LFP recordings as its input. We show that the multiscale decoder can improve decoding accuracy by adding information from LFP to spikes, while running at the fast millisecond time-scale of the spiking activity. Moreover, this improvement is achieved using relatively few LFP channels, demonstrating the robustness of the approach. These results suggest that using multiscale decoders has the potential to improve the reliability and longevity of BMIs.

Particle Interactions Mediated by Dynamical Networks: Assessment of Macroscopic Descriptions

NASA Astrophysics Data System (ADS)

Barré, J.; Carrillo, J. A.; Degond, P.; Peurichard, D.; Zatorska, E.

2018-02-01

We provide a numerical study of the macroscopic model of Barré et al. (Multiscale Model Simul, 2017, to appear) derived from an agent-based model for a system of particles interacting through a dynamical network of links. Assuming that the network remodeling process is very fast, the macroscopic model takes the form of a single aggregation-diffusion equation for the density of particles. The theoretical study of the macroscopic model gives precise criteria for the phase transitions of the steady states, and in the one-dimensional case, we show numerically that the stationary solutions of the microscopic model undergo the same phase transitions and bifurcation types as the macroscopic model. In the two-dimensional case, we show that the numerical simulations of the macroscopic model are in excellent agreement with the predicted theoretical values. This study provides a partial validation of the formal derivation of the macroscopic model from a microscopic formulation and shows that the former is a consistent approximation of an underlying particle dynamics, making it a powerful tool for the modeling of dynamical networks at a large scale.

Particle Interactions Mediated by Dynamical Networks: Assessment of Macroscopic Descriptions.

PubMed

Barré, J; Carrillo, J A; Degond, P; Peurichard, D; Zatorska, E

2018-01-01

We provide a numerical study of the macroscopic model of Barré et al. (Multiscale Model Simul, 2017, to appear) derived from an agent-based model for a system of particles interacting through a dynamical network of links. Assuming that the network remodeling process is very fast, the macroscopic model takes the form of a single aggregation-diffusion equation for the density of particles. The theoretical study of the macroscopic model gives precise criteria for the phase transitions of the steady states, and in the one-dimensional case, we show numerically that the stationary solutions of the microscopic model undergo the same phase transitions and bifurcation types as the macroscopic model. In the two-dimensional case, we show that the numerical simulations of the macroscopic model are in excellent agreement with the predicted theoretical values. This study provides a partial validation of the formal derivation of the macroscopic model from a microscopic formulation and shows that the former is a consistent approximation of an underlying particle dynamics, making it a powerful tool for the modeling of dynamical networks at a large scale.

Reaction-diffusion basis of retroviral infectivity

NASA Astrophysics Data System (ADS)

Sadiq, S. Kashif

2016-11-01

Retrovirus particle (virion) infectivity requires diffusion and clustering of multiple transmembrane envelope proteins (Env3) on the virion exterior, yet is triggered by protease-dependent degradation of a partially occluding, membrane-bound Gag polyprotein lattice on the virion interior. The physical mechanism underlying such coupling is unclear and only indirectly accessible via experiment. Modelling stands to provide insight but the required spatio-temporal range far exceeds current accessibility by all-atom or even coarse-grained molecular dynamics simulations. Nor do such approaches account for chemical reactions, while conversely, reaction kinetics approaches handle neither diffusion nor clustering. Here, a recently developed multiscale approach is considered that applies an ultra-coarse-graining scheme to treat entire proteins at near-single particle resolution, but which also couples chemical reactions with diffusion and interactions. A model is developed of Env3 molecules embedded in a truncated Gag lattice composed of membrane-bound matrix proteins linked to capsid subunits, with freely diffusing protease molecules. Simulations suggest that in the presence of Gag but in the absence of lateral lattice-forming interactions, Env3 diffuses comparably to Gag-absent Env3. Initial immobility of Env3 is conferred through lateral caging by matrix trimers vertically coupled to the underlying hexameric capsid layer. Gag cleavage by protease vertically decouples the matrix and capsid layers, induces both matrix and Env3 diffusion, and permits Env3 clustering. Spreading across the entire membrane surface reduces crowding, in turn, enhancing the effect and promoting infectivity. This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'.

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

NASA Astrophysics Data System (ADS)

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

2012-01-01

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

Length scale effects and multiscale modeling of thermally induced phase transformation kinetics in NiTi SMA

NASA Astrophysics Data System (ADS)

Frantziskonis, George N.; Gur, Sourav

2017-06-01

Thermally induced phase transformation in NiTi shape memory alloys (SMAs) shows strong size and shape, collectively termed length scale effects, at the nano to micrometer scales, and that has important implications for the design and use of devices and structures at such scales. This paper, based on a recently developed multiscale model that utilizes molecular dynamics (MDs) simulations at small scales and MD-verified phase field (PhF) simulations at larger scales, reports results on specific length scale effects, i.e. length scale effects in martensite phase fraction (MPF) evolution, transformation temperatures (martensite and austenite start and finish) and in the thermally cyclic transformation between austenitic and martensitic phase. The multiscale study identifies saturation points for length scale effects and studies, for the first time, the length scale effect on the kinetics (i.e. developed internal strains) in the B19‧ phase during phase transformation. The major part of the work addresses small scale single crystals in specific orientations. However, the multiscale method is used in a unique and novel way to indirectly study length scale and grain size effects on evolution kinetics in polycrystalline NiTi, and to compare the simulation results to experiments. The interplay of the grain size and the length scale effect on the thermally induced MPF evolution is also shown in this present study. Finally, the multiscale coupling results are employed to improve phenomenological material models for NiTi SMA.

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

DOE PAGES

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

2018-02-13

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

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

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

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

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

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

PubMed

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

Multi-scale damage modelling in a ceramic matrix composite using a finite-element microstructure meshfree methodology

PubMed Central

2016-01-01

The problem of multi-scale modelling of damage development in a SiC ceramic fibre-reinforced SiC matrix ceramic composite tube is addressed, with the objective of demonstrating the ability of the finite-element microstructure meshfree (FEMME) model to introduce important aspects of the microstructure into a larger scale model of the component. These are particularly the location, orientation and geometry of significant porosity and the load-carrying capability and quasi-brittle failure behaviour of the fibre tows. The FEMME model uses finite-element and cellular automata layers, connected by a meshfree layer, to efficiently couple the damage in the microstructure with the strain field at the component level. Comparison is made with experimental observations of damage development in an axially loaded composite tube, studied by X-ray computed tomography and digital volume correlation. Recommendations are made for further development of the model to achieve greater fidelity to the microstructure. This article is part of the themed issue ‘Multiscale modelling of the structural integrity of composite materials’. PMID:27242308

Multiscale modelling approaches for assessing cosmetic ingredients safety.

PubMed

Bois, Frédéric Y; Ochoa, Juan G Diaz; Gajewska, Monika; Kovarich, Simona; Mauch, Klaus; Paini, Alicia; Péry, Alexandre; Benito, Jose Vicente Sala; Teng, Sophie; Worth, Andrew

2017-12-01

The European Union's ban on animal testing for cosmetic ingredients and products has generated a strong momentum for the development of in silico and in vitro alternative methods. One of the focus of the COSMOS project was ab initio prediction of kinetics and toxic effects through multiscale pharmacokinetic modeling and in vitro data integration. In our experience, mathematical or computer modeling and in vitro experiments are complementary. We present here a summary of the main models and results obtained within the framework of the project on these topics. A first section presents our work at the organelle and cellular level. We then go toward modeling cell levels effects (monitored continuously), multiscale physiologically based pharmacokinetic and effect models, and route to route extrapolation. We follow with a short presentation of the automated KNIME workflows developed for dissemination and easy use of the models. We end with a discussion of two challenges to the field: our limited ability to deal with massive data and complex computations. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

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

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

None

2011-01-01

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

A multiscale restriction-smoothed basis method for high contrast porous media represented on unstructured grids

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

Møyner, Olav, E-mail: olav.moyner@sintef.no; Lie, Knut-Andreas, E-mail: knut-andreas.lie@sintef.no

2016-01-01

A wide variety of multiscale methods have been proposed in the literature to reduce runtime and provide better scaling for the solution of Poisson-type equations modeling flow in porous media. We present a new multiscale restricted-smoothed basis (MsRSB) method that is designed to be applicable to both rectilinear grids and unstructured grids. Like many other multiscale methods, MsRSB relies on a coarse partition of the underlying fine grid and a set of local prolongation operators (multiscale basis functions) that map unknowns associated with the fine grid cells to unknowns associated with blocks in the coarse partition. These mappings are constructedmore » by restricted smoothing: Starting from a constant, a localized iterative scheme is applied directly to the fine-scale discretization to compute prolongation operators that are consistent with the local properties of the differential operators. The resulting method has three main advantages: First of all, both the coarse and the fine grid can have general polyhedral geometry and unstructured topology. This means that partitions and good prolongation operators can easily be constructed for complex models involving high media contrasts and unstructured cell connections introduced by faults, pinch-outs, erosion, local grid refinement, etc. In particular, the coarse partition can be adapted to geological or flow-field properties represented on cells or faces to improve accuracy. Secondly, the method is accurate and robust when compared to existing multiscale methods and does not need expensive recomputation of local basis functions to account for transient behavior: Dynamic mobility changes are incorporated by continuing to iterate a few extra steps on existing basis functions. This way, the cost of updating the prolongation operators becomes proportional to the amount of change in fluid mobility and one reduces the need for expensive, tolerance-based updates. Finally, since the MsRSB method is formulated on top of a cell-centered, conservative, finite-volume method, it is applicable to any flow model in which one can isolate a pressure equation. Herein, we only discuss single and two-phase incompressible models. Compressible flow, e.g., as modeled by the black-oil equations, is discussed in a separate paper.« less

Multi-scale Modeling of Plasticity in Tantalum.

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

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

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

Oxygen Modulates the Effectiveness of Granuloma Mediated Host Response to Mycobacterium tuberculosis: A Multiscale Computational Biology Approach

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

Sershen, Cheryl L.; Plimpton, Steven J.; May, Elebeoba E.

Mycobacterium tuberculosis associated granuloma formation can be viewed as a structural immune response that can contain and halt the spread of the pathogen. In several mammalian hosts, including non-human primates, Mtb granulomas are often hypoxic, although this has not been observed in wild type murine infection models. While a presumed consequence, the structural contribution of the granuloma to oxygen limitation and the concomitant impact on Mtb metabolic viability and persistence remains to be fully explored. We develop a multiscale computational model to test to what extent in vivo Mtb granulomas become hypoxic, and investigate the effects of hypoxia on hostmore » immune response efficacy and mycobacterial persistence. Our study integrates a physiological model of oxygen dynamics in the extracellular space of alveolar tissue, an agent-based model of cellular immune response, and a systems biology-based model of Mtb metabolic dynamics. Our theoretical studies suggest that the dynamics of granuloma organization mediates oxygen availability and illustrates the immunological contribution of this structural host response to infection outcome. Furthermore, our integrated model demonstrates the link between structural immune response and mechanistic drivers influencing Mtbs adaptation to its changing microenvironment and the qualitative infection outcome scenarios of clearance, containment, dissemination, and a newly observed theoretical outcome of transient containment. We observed hypoxic regions in the containment granuloma similar in size to granulomas found in mammalian in vivo models of Mtb infection. In the case of the containment outcome, our model uniquely demonstrates that immune response mediated hypoxic conditions help foster the shift down of bacteria through two stages of adaptation similar to thein vitro non-replicating persistence (NRP) observed in the Wayne model of Mtb dormancy. Lastly, the adaptation in part contributes to the ability of Mtb to remain dormant for years after initial infection.« less

Multiscale mathematical modeling of the hypothalamo-pituitary-gonadal axis.

PubMed

Clément, Frédérique

2016-07-01

Although the fields of systems and integrative biology are in full expansion, few teams are involved worldwide into the study of reproductive function from the mathematical modeling viewpoint. This may be due to the fact that the reproductive function is not compulsory for individual organism survival, even if it is for species survival. Alternatively, the complexity of reproductive physiology may be discouraging. Indeed, the hypothalamo-pituitary-gonadal (HPG) axis involves not only several organs and tissues but also intricate time (from the neuronal millisecond timescale to circannual rhythmicity) and space (from molecules to organs) scales. Yet, mathematical modeling, and especially multiscale modeling, can renew our approaches of the molecular, cellular, and physiological processes underlying the control of reproductive functions. In turn, the remarkable dynamic features exhibited by the HPG axis raise intriguing and challenging questions to modelers and applied mathematicians. In this article, we draw a panoramic review of some mathematical models designed in the framework of the female HPG, with a special focus on the gonadal and central control of follicular development. On the gonadal side, the modeling of follicular development calls to the generic formalism of structured cell populations, that allows one to make mechanistic links between the control of cell fate (proliferation, differentiation, or apoptosis) and that of the follicle fate (ovulation or degeneration) or to investigate how the functional interactions between the oocyte and its surrounding cells shape the follicle morphogenesis. On the central, mainly hypothalamic side, models based on dynamical systems with multiple timescales allow one to represent within a single framework both the pulsatile and surge patterns of the neurohormone GnRH. Beyond their interest in basic research investigations, mathematical models can also be at the source of useful tools to study the encoding and decoding of the (neuro-) hormonal signals at play within the HPG axis and detect complex, possibly hidden rhythms, in experimental time series. Copyright © 2016 Elsevier Inc. All rights reserved.

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

DOE PAGES

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

2014-11-06

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

Oxygen Modulates the Effectiveness of Granuloma Mediated Host Response to Mycobacterium tuberculosis: A Multiscale Computational Biology Approach

DOE PAGES

Sershen, Cheryl L.; Plimpton, Steven J.; May, Elebeoba E.

2016-02-15

Mycobacterium tuberculosis associated granuloma formation can be viewed as a structural immune response that can contain and halt the spread of the pathogen. In several mammalian hosts, including non-human primates, Mtb granulomas are often hypoxic, although this has not been observed in wild type murine infection models. While a presumed consequence, the structural contribution of the granuloma to oxygen limitation and the concomitant impact on Mtb metabolic viability and persistence remains to be fully explored. We develop a multiscale computational model to test to what extent in vivo Mtb granulomas become hypoxic, and investigate the effects of hypoxia on hostmore » immune response efficacy and mycobacterial persistence. Our study integrates a physiological model of oxygen dynamics in the extracellular space of alveolar tissue, an agent-based model of cellular immune response, and a systems biology-based model of Mtb metabolic dynamics. Our theoretical studies suggest that the dynamics of granuloma organization mediates oxygen availability and illustrates the immunological contribution of this structural host response to infection outcome. Furthermore, our integrated model demonstrates the link between structural immune response and mechanistic drivers influencing Mtbs adaptation to its changing microenvironment and the qualitative infection outcome scenarios of clearance, containment, dissemination, and a newly observed theoretical outcome of transient containment. We observed hypoxic regions in the containment granuloma similar in size to granulomas found in mammalian in vivo models of Mtb infection. In the case of the containment outcome, our model uniquely demonstrates that immune response mediated hypoxic conditions help foster the shift down of bacteria through two stages of adaptation similar to thein vitro non-replicating persistence (NRP) observed in the Wayne model of Mtb dormancy. Lastly, the adaptation in part contributes to the ability of Mtb to remain dormant for years after initial infection.« less

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

SCIENCE FOR INTEGRATED WATERSHED MANAGEMENT: A MULTI-SCALE EXPERIMENTAL CASE STUDY LINKING LAND USE MANAGEMENT PRACTICES AND WATER QUALITY IN SOUTHERN OHIO

EPA Science Inventory

Although it is routine for watershed management programs to coincide the monitoring of land use impacts and water quality at different spatial scales, rarely are the data collected in a manner to elucidate the linkages among ecological systems across a drainage network. There rem...

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

PubMed

Erson, E Zeynep; Cavuşoğlu, M Cenk

2012-09-01

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

Classification of JERS-1 Image Mosaic of Central Africa Using A Supervised Multiscale Classifier of Texture Features

NASA Technical Reports Server (NTRS)

Saatchi, Sassan; DeGrandi, Franco; Simard, Marc; Podest, Erika

1999-01-01

In this paper, a multiscale approach is introduced to classify the Japanese Research Satellite-1 (JERS-1) mosaic image over the Central African rainforest. A series of texture maps are generated from the 100 m mosaic image at various scales. Using a quadtree model and relating classes at each scale by a Markovian relationship, the multiscale images are classified from course to finer scale. The results are verified at various scales and the evolution of classification is monitored by calculating the error at each stage.

Multiscale characterization and mechanical modeling of an Al-Zn-Mg electron beam weld

NASA Astrophysics Data System (ADS)

Puydt, Quentin; Flouriot, Sylvain; Ringeval, Sylvain; Parry, Guillaume; De Geuser, Frédéric; Deschamps, Alexis

Welding of precipitation hardening alloys results in multi-scale microstructural heterogeneities, from the hardening nano-scale precipitates to the micron-scale solidification structures and to the component geometry. This heterogeneity results in a complex mechanical response, with gradients in strength, stress triaxiality and damage initiation sites.

A systematic multiscale modeling and experimental approach to protect grain boundaries in magnesium alloys from corrosion

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

Horstemeyer, Mark R.; Chaudhuri, Santanu

2015-09-30

A multiscale modeling Internal State Variable (ISV) constitutive model was developed that captures the fundamental structure-property relationships. The macroscale ISV model used lower length scale simulations (Butler-Volmer and Electronics Structures results) in order to inform the ISVs at the macroscale. The chemomechanical ISV model was calibrated and validated from experiments with magnesium (Mg) alloys that were investigated under corrosive environments coupled with experimental electrochemical studies. Because the ISV chemomechanical model is physically based, it can be used for other material systems to predict corrosion behavior. As such, others can use the chemomechanical model for analyzing corrosion effects on their designs.

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

NASA Astrophysics Data System (ADS)

Du, Wenbo

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

A Multi-scale Computational Platform to Mechanistically Assess the Effect of Genetic Variation on Drug Responses in Human Erythrocyte Metabolism

PubMed Central

Bordbar, Aarash; Palsson, Bernhard O.

2016-01-01

Progress in systems medicine brings promise to addressing patient heterogeneity and individualized therapies. Recently, genome-scale models of metabolism have been shown to provide insight into the mechanistic link between drug therapies and systems-level off-target effects while being expanded to explicitly include the three-dimensional structure of proteins. The integration of these molecular-level details, such as the physical, structural, and dynamical properties of proteins, notably expands the computational description of biochemical network-level properties and the possibility of understanding and predicting whole cell phenotypes. In this study, we present a multi-scale modeling framework that describes biological processes which range in scale from atomistic details to an entire metabolic network. Using this approach, we can understand how genetic variation, which impacts the structure and reactivity of a protein, influences both native and drug-induced metabolic states. As a proof-of-concept, we study three enzymes (catechol-O-methyltransferase, glucose-6-phosphate dehydrogenase, and glyceraldehyde-3-phosphate dehydrogenase) and their respective genetic variants which have clinically relevant associations. Using all-atom molecular dynamic simulations enables the sampling of long timescale conformational dynamics of the proteins (and their mutant variants) in complex with their respective native metabolites or drug molecules. We find that changes in a protein’s structure due to a mutation influences protein binding affinity to metabolites and/or drug molecules, and inflicts large-scale changes in metabolism. PMID:27467583

A Multi-scale Computational Platform to Mechanistically Assess the Effect of Genetic Variation on Drug Responses in Human Erythrocyte Metabolism.

PubMed

Mih, Nathan; Brunk, Elizabeth; Bordbar, Aarash; Palsson, Bernhard O

2016-07-01

Progress in systems medicine brings promise to addressing patient heterogeneity and individualized therapies. Recently, genome-scale models of metabolism have been shown to provide insight into the mechanistic link between drug therapies and systems-level off-target effects while being expanded to explicitly include the three-dimensional structure of proteins. The integration of these molecular-level details, such as the physical, structural, and dynamical properties of proteins, notably expands the computational description of biochemical network-level properties and the possibility of understanding and predicting whole cell phenotypes. In this study, we present a multi-scale modeling framework that describes biological processes which range in scale from atomistic details to an entire metabolic network. Using this approach, we can understand how genetic variation, which impacts the structure and reactivity of a protein, influences both native and drug-induced metabolic states. As a proof-of-concept, we study three enzymes (catechol-O-methyltransferase, glucose-6-phosphate dehydrogenase, and glyceraldehyde-3-phosphate dehydrogenase) and their respective genetic variants which have clinically relevant associations. Using all-atom molecular dynamic simulations enables the sampling of long timescale conformational dynamics of the proteins (and their mutant variants) in complex with their respective native metabolites or drug molecules. We find that changes in a protein's structure due to a mutation influences protein binding affinity to metabolites and/or drug molecules, and inflicts large-scale changes in metabolism.

Analysis of Hepatitis C Virus Decline during Treatment with the Protease Inhibitor Danoprevir Using a Multiscale Model

DOE PAGES

Rong, Libin; Guedj, Jeremie; Dahari, Harel; ...

2013-03-14

The current paradigm for studying hepatitis C virus (HCV) dynamics in patients utilizes a standard viral dynamic model that keeps track of uninfected (target) cells, infected cells, and virus. The model does not account for the dynamics of intracellular viral replication, which is the major target of direct-acting antiviral agents (DAAs). In this paper, we describe and study a recently developed multiscale age-structured model that explicitly considers the potential effects of DAAs on intracellular viral RNA production, degradation, and secretion as virus into the circulation. We show that when therapy significantly blocks both intracellular viral RNA production and virus secretion,more » the serum viral load decline has three phases, with slopes reflecting the rate of serum viral clearance, the rate of loss of intracellular viral RNA, and the rate of loss of intracellular replication templates and infected cells, respectively. We also derive analytical approximations of the multiscale model and use one of them to analyze data from patients treated for 14 days with the HCV protease inhibitor danoprevir. Analysis suggests that danoprevir significantly blocks intracellular viral production (with mean effectiveness 99.2%), enhances intracellular viral RNA degradation about 5-fold, and moderately inhibits viral secretion (with mean effectiveness 56%). Finally, the multiscale model can be used to study viral dynamics in patients treated with other DAAs and explore their mechanisms of action in treatment of hepatitis C.« less

Multispacecraft Observations and Modeling of the 22/23 June 2015 Geomagnetic Storm

NASA Technical Reports Server (NTRS)

Reiff, P. H.; Daou, A. G.; Sazykin, S. Y.; Nakamura, R.; Hairston, M. R.; Coffey, V.; Chandler, M. O.; Anderson, B. J.; Russell, C. T.; Welling, D.;

Modeling On-Body DTN Packet Routing Delay in the Presence of Postural Disconnections.

PubMed

Quwaider, Muhannad; Taghizadeh, Mahmoud; Biswas, Subir

2011-01-01

This paper presents a stochastic modeling framework for store-and-forward packet routing in Wireless Body Area Networks ( WBAN ) with postural partitioning. A prototype WBANs has been constructed for experimentally characterizing and capturing on-body topology disconnections in the presence of ultrashort range radio links, unpredictable RF attenuation, and human postural mobility. Delay modeling techniques for evaluating single-copy on-body DTN routing protocols are then developed. End-to-end routing delay for a series of protocols including opportunistic, randomized, and two other mechanisms that capture multiscale topological localities in human postural movements have been evaluated. Performance of the analyzed protocols are then evaluated experimentally and via simulation to compare with the results obtained from the developed model. Finally, a mechanism for evaluating the topological importance of individual on-body sensor nodes is developed. It is shown that such information can be used for selectively reducing the on-body sensor-count without substantially sacrificing the packet delivery delay.

Modeling On-Body DTN Packet Routing Delay in the Presence of Postural Disconnections

PubMed Central

Quwaider, Muhannad; Taghizadeh, Mahmoud; Biswas, Subir

2014-01-01

This paper presents a stochastic modeling framework for store-and-forward packet routing in Wireless Body Area Networks (WBAN) with postural partitioning. A prototype WBANs has been constructed for experimentally characterizing and capturing on-body topology disconnections in the presence of ultrashort range radio links, unpredictable RF attenuation, and human postural mobility. Delay modeling techniques for evaluating single-copy on-body DTN routing protocols are then developed. End-to-end routing delay for a series of protocols including opportunistic, randomized, and two other mechanisms that capture multiscale topological localities in human postural movements have been evaluated. Performance of the analyzed protocols are then evaluated experimentally and via simulation to compare with the results obtained from the developed model. Finally, a mechanism for evaluating the topological importance of individual on-body sensor nodes is developed. It is shown that such information can be used for selectively reducing the on-body sensor-count without substantially sacrificing the packet delivery delay. PMID:25530749

Prediction of water loss and viscoelastic deformation of apple tissue using a multiscale model.

PubMed

Aregawi, Wondwosen A; Abera, Metadel K; Fanta, Solomon W; Verboven, Pieter; Nicolai, Bart

2014-11-19

A two-dimensional multiscale water transport and mechanical model was developed to predict the water loss and deformation of apple tissue (Malus × domestica Borkh. cv. 'Jonagold') during dehydration. At the macroscopic level, a continuum approach was used to construct a coupled water transport and mechanical model. Water transport in the tissue was simulated using a phenomenological approach using Fick's second law of diffusion. Mechanical deformation due to shrinkage was based on a structural mechanics model consisting of two parts: Yeoh strain energy functions to account for non-linearity and Maxwell's rheological model of visco-elasticity. Apparent parameters of the macroscale model were computed from a microscale model. The latter accounted for water exchange between different microscopic structures of the tissue (intercellular space, the cell wall network and cytoplasm) using transport laws with the water potential as the driving force for water exchange between different compartments of tissue. The microscale deformation mechanics were computed using a model where the cells were represented as a closed thin walled structure. The predicted apparent water transport properties of apple cortex tissue from the microscale model showed good agreement with the experimentally measured values. Deviations between calculated and measured mechanical properties of apple tissue were observed at strains larger than 3%, and were attributed to differences in water transport behavior between the experimental compression tests and the simulated dehydration-deformation behavior. Tissue dehydration and deformation in the high relative humidity range ( > 97% RH) could, however, be accurately predicted by the multiscale model. The multiscale model helped to understand the dynamics of the dehydration process and the importance of the different microstructural compartments (intercellular space, cell wall, membrane and cytoplasm) for water transport and mechanical deformation.

Multiscale Space-Time Computational Methods for Fluid-Structure Interactions

DTIC Science & Technology

2015-09-13

prescribed fully or partially, is from an actual locust, extracted from high-speed, multi-camera video recordings of the locust in a wind tunnel . We use...With creative methods for coupling the fluid and structure, we can increase the scope and efficiency of the FSI modeling . Multiscale methods, which now...play an important role in computational mathematics, can also increase the accuracy and efficiency of the computer modeling techniques. The main

Non-invasive biomarkers of fetal brain development reflecting prenatal stress: An integrative multi-scale multi-species perspective on data collection and analysis.

PubMed

Frasch, Martin G; Lobmaier, Silvia M; Stampalija, Tamara; Desplats, Paula; Pallarés, María Eugenia; Pastor, Verónica; Brocco, Marcela A; Wu, Hau-Tieng; Schulkin, Jay; Herry, Christophe L; Seely, Andrew J E; Metz, Gerlinde A S; Louzoun, Yoram; Antonelli, Marta C

2018-05-30

Prenatal stress (PS) impacts early postnatal behavioural and cognitive development. This process of 'fetal programming' is mediated by the effects of the prenatal experience on the developing hypothalamic-pituitary-adrenal (HPA) axis and autonomic nervous system (ANS). We derive a multi-scale multi-species approach to devising preclinical and clinical studies to identify early non-invasively available pre- and postnatal biomarkers of PS. The multiple scales include brain epigenome, metabolome, microbiome and the ANS activity gauged via an array of advanced non-invasively obtainable properties of fetal heart rate fluctuations. The proposed framework has the potential to reveal mechanistic links between maternal stress during pregnancy and changes across these physiological scales. Such biomarkers may hence be useful as early and non-invasive predictors of neurodevelopmental trajectories influenced by the PS as well as follow-up indicators of success of therapeutic interventions to correct such altered neurodevelopmental trajectories. PS studies must be conducted on multiple scales derived from concerted observations in multiple animal models and human cohorts performed in an interactive and iterative manner and deploying machine learning for data synthesis, identification and validation of the best non-invasive detection and follow-up biomarkers, a prerequisite for designing effective therapeutic interventions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Augmenting Surgery via Multi-scale Modeling and Translational Systems Biology in the Era of Precision Medicine: A Multidisciplinary Perspective

PubMed Central

Kassab, Ghassan S.; An, Gary; Sander, Edward A.; Miga, Michael; Guccione, Julius M.; Ji, Songbai; Vodovotz, Yoram

2016-01-01

In this era of tremendous technological capabilities and increased focus on improving clinical outcomes, decreasing costs, and increasing precision, there is a need for a more quantitative approach to the field of surgery. Multiscale computational modeling has the potential to bridge the gap to the emerging paradigms of Precision Medicine and Translational Systems Biology, in which quantitative metrics and data guide patient care through improved stratification, diagnosis, and therapy. Achievements by multiple groups have demonstrated the potential for 1) multiscale computational modeling, at a biological level, of diseases treated with surgery and the surgical procedure process at the level of the individual and the population; along with 2) patient-specific, computationally-enabled surgical planning, delivery, and guidance and robotically-augmented manipulation. In this perspective article, we discuss these concepts, and cite emerging examples from the fields of trauma, wound healing, and cardiac surgery. PMID:27015816

Modeling natural emissions in the Community Multiscale Air Quality (CMAQ) Model-I: building an emissions data base

NASA Astrophysics Data System (ADS)

Smith, S. N.; Mueller, S. F.

2010-05-01

A natural emissions inventory for the continental United States and surrounding territories is needed in order to use the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ) Model for simulating natural air quality. The CMAQ air modeling system (including the Sparse Matrix Operator Kernel Emissions (SMOKE) emissions processing system) currently estimates non-methane volatile organic compound (NMVOC) emissions from biogenic sources, nitrogen oxide (NOx) emissions from soils, ammonia from animals, several types of particulate and reactive gas emissions from fires, as well as sea salt emissions. However, there are several emission categories that are not commonly treated by the standard CMAQ Model system. Most notable among these are nitrogen oxide emissions from lightning, reduced sulfur emissions from oceans, geothermal features and other continental sources, windblown dust particulate, and reactive chlorine gas emissions linked with sea salt chloride. A review of past emissions modeling work and existing global emissions data bases provides information and data necessary for preparing a more complete natural emissions data base for CMAQ applications. A model-ready natural emissions data base is developed to complement the anthropogenic emissions inventory used by the VISTAS Regional Planning Organization in its work analyzing regional haze based on the year 2002. This new data base covers a modeling domain that includes the continental United States plus large portions of Canada, Mexico and surrounding oceans. Comparing July 2002 source data reveals that natural emissions account for 16% of total gaseous sulfur (sulfur dioxide, dimethylsulfide and hydrogen sulfide), 44% of total NOx, 80% of reactive carbonaceous gases (NMVOCs and carbon monoxide), 28% of ammonia, 96% of total chlorine (hydrochloric acid, nitryl chloride and sea salt chloride), and 84% of fine particles (i.e., those smaller than 2.5 μm in size) released into the atmosphere. The seasonality and relative importance of the various natural emissions categories are described.

Modeling natural emissions in the Community Multiscale Air Quality (CMAQ) model - Part 1: Building an emissions data base

NASA Astrophysics Data System (ADS)

Smith, S. N.; Mueller, S. F.

2010-01-01

A natural emissions inventory for the continental United States and surrounding territories is needed in order to use the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ) Model for simulating natural air quality. The CMAQ air modeling system (including the Sparse Matrix Operator Kernel Emissions (SMOKE) emissions processing system) currently estimates volatile organic compound (VOC) emissions from biogenic sources, nitrogen oxide (NOx) emissions from soils, ammonia from animals, several types of particulate and reactive gas emissions from fires, as well as windblown dust and sea salt emissions. However, there are several emission categories that are not commonly treated by the standard CMAQ Model system. Most notable among these are nitrogen oxide emissions from lightning, reduced sulfur emissions from oceans, geothermal features and other continental sources, and reactive chlorine gas emissions linked with sea salt chloride. A review of past emissions modeling work and existing global emissions data bases provides information and data necessary for preparing a more complete natural emissions data base for CMAQ applications. A model-ready natural emissions data base is developed to complement the anthropogenic emissions inventory used by the VISTAS Regional Planning Organization in its work analyzing regional haze based on the year 2002. This new data base covers a modeling domain that includes the continental United States plus large portions of Canada, Mexico and surrounding oceans. Comparing July 2002 source data reveals that natural emissions account for 16% of total gaseous sulfur (sulfur dioxide, dimethylsulfide and hydrogen sulfide), 44% of total NOx, 80% of reactive carbonaceous gases (VOCs and carbon monoxide), 28% of ammonia, 96% of total chlorine (hydrochloric acid, nitryl chloride and sea salt chloride), and 84% of fine particles (i.e., those smaller than 2.5 μm in size) released into the atmosphere. The seasonality and relative importance of the various natural emissions categories are described.

Evaluating and Improving Cloud Processes in the Multi-Scale Modeling Framework

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

Ackerman, Thomas P.

2015-03-01

The research performed under this grant was intended to improve the embedded cloud model in the Multi-scale Modeling Framework (MMF) for convective clouds by using a 2-moment microphysics scheme rather than the single moment scheme used in all the MMF runs to date. The technical report and associated documents describe the results of testing the cloud resolving model with fixed boundary conditions and evaluation of model results with data. The overarching conclusion is that such model evaluations are problematic because errors in the forcing fields control the results so strongly that variations in parameterization values cannot be usefully constrained

Improvements in the Scalability of the NASA Goddard Multiscale Modeling Framework for Hurricane Climate Studies

NASA Technical Reports Server (NTRS)

Shen, Bo-Wen; Tao, Wei-Kuo; Chern, Jiun-Dar

2007-01-01

Improving our understanding of hurricane inter-annual variability and the impact of climate change (e.g., doubling CO2 and/or global warming) on hurricanes brings both scientific and computational challenges to researchers. As hurricane dynamics involves multiscale interactions among synoptic-scale flows, mesoscale vortices, and small-scale cloud motions, an ideal numerical model suitable for hurricane studies should demonstrate its capabilities in simulating these interactions. The newly-developed multiscale modeling framework (MMF, Tao et al., 2007) and the substantial computing power by the NASA Columbia supercomputer show promise in pursuing the related studies, as the MMF inherits the advantages of two NASA state-of-the-art modeling components: the GEOS4/fvGCM and 2D GCEs. This article focuses on the computational issues and proposes a revised methodology to improve the MMF's performance and scalability. It is shown that this prototype implementation enables 12-fold performance improvements with 364 CPUs, thereby making it more feasible to study hurricane climate.

A fast solver for the Helmholtz equation based on the generalized multiscale finite-element method

NASA Astrophysics Data System (ADS)

Fu, Shubin; Gao, Kai

2017-11-01

Conventional finite-element methods for solving the acoustic-wave Helmholtz equation in highly heterogeneous media usually require finely discretized mesh to represent the medium property variations with sufficient accuracy. Computational costs for solving the Helmholtz equation can therefore be considerably expensive for complicated and large geological models. Based on the generalized multiscale finite-element theory, we develop a novel continuous Galerkin method to solve the Helmholtz equation in acoustic media with spatially variable velocity and mass density. Instead of using conventional polynomial basis functions, we use multiscale basis functions to form the approximation space on the coarse mesh. The multiscale basis functions are obtained from multiplying the eigenfunctions of a carefully designed local spectral problem with an appropriate multiscale partition of unity. These multiscale basis functions can effectively incorporate the characteristics of heterogeneous media's fine-scale variations, thus enable us to obtain accurate solution to the Helmholtz equation without directly solving the large discrete system formed on the fine mesh. Numerical results show that our new solver can significantly reduce the dimension of the discrete Helmholtz equation system, and can also obviously reduce the computational time.

Multi-Scale Modeling of a Graphite-Epoxy-Nanotube System

NASA Technical Reports Server (NTRS)

Frankland, S. J. V.; Riddick, J. C.; Gates, T. S.

2005-01-01

A multi-scale method is utilized to determine some of the constitutive properties of a three component graphite-epoxy-nanotube system. This system is of interest because carbon nanotubes have been proposed as stiffening and toughening agents in the interlaminar regions of carbon fiber/epoxy laminates. The multi-scale method uses molecular dynamics simulation and equivalent-continuum modeling to compute three of the elastic constants of the graphite-epoxy-nanotube system: C11, C22, and C33. The 1-direction is along the nanotube axis, and the graphene sheets lie in the 1-2 plane. It was found that the C11 is only 4% larger than the C22. The nanotube therefore does have a small, but positive effect on the constitutive properties in the interlaminar region.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

A FSI computational framework for vascular physiopathology: A novel flow-tissue multiscale strategy.

PubMed

Bianchi, Daniele; Monaldo, Elisabetta; Gizzi, Alessio; Marino, Michele; Filippi, Simonetta; Vairo, Giuseppe

2017-09-01

A novel fluid-structure computational framework for vascular applications is herein presented. It is developed by combining the double multi-scale nature of vascular physiopathology in terms of both tissue properties and blood flow. Addressing arterial tissues, they are modelled via a nonlinear multiscale constitutive rationale, based only on parameters having a clear histological and biochemical meaning. Moreover, blood flow is described by coupling a three-dimensional fluid domain (undergoing physiological inflow conditions) with a zero-dimensional model, which allows to reproduce the influence of the downstream vasculature, furnishing a realistic description of the outflow proximal pressure. The fluid-structure interaction is managed through an explicit time-marching approach, able to accurately describe tissue nonlinearities within each computational step for the fluid problem. A case study associated to a patient-specific aortic abdominal aneurysmatic geometry is numerically investigated, highlighting advantages gained from the proposed multiscale strategy, as well as showing soundness and effectiveness of the established framework for assessing useful clinical quantities and risk indexes. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Introduction and application of the multiscale coefficient of variation analysis.

PubMed

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

2017-10-01

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

Multiscale analysis of information dynamics for linear multivariate processes.

PubMed

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

2016-08-01

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

Modelling multiscale aspects of colorectal cancer

NASA Astrophysics Data System (ADS)

van Leeuwen, Ingeborg M. M.; Byrne, Helen M.; Johnston, Matthew D.; Edwards, Carina M.; Chapman, S. Jonathan; Bodmer, Walter F.; Maini, Philip K.

2008-01-01

Colorectal cancer (CRC) is responsible for nearly half a million deaths annually world-wide [11]. We present a series of mathematical models describing the dynamics of the intestinal epithelium and the kinetics of the molecular pathway most commonly mutated in CRC, the Wnt signalling network. We also discuss how we are coupling such models to build a multiscale model of normal and aberrant guts. This will enable us to combine disparate experimental and clinical data, to investigate interactions between phenomena taking place at different levels of organisation and, eventually, to test the efficacy of new drugs on the system as a whole.

A Novel Multiscale Physics Based Progressive Failure Methodology for Laminated Composite Structures

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Waas, Anthony M.; Bednarcyk, Brett A.; Collier, Craig S.; Yarrington, Phillip W.

2008-01-01

A variable fidelity, multiscale, physics based finite element procedure for predicting progressive damage and failure of laminated continuous fiber reinforced composites is introduced. At every integration point in a finite element model, progressive damage is accounted for at the lamina-level using thermodynamically based Schapery Theory. Separate failure criteria are applied at either the global-scale or the microscale in two different FEM models. A micromechanics model, the Generalized Method of Cells, is used to evaluate failure criteria at the micro-level. The stress-strain behavior and observed failure mechanisms are compared with experimental results for both models.

Multiscale Cloud System Modeling

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Moncrieff, Mitchell W.

2009-01-01

The central theme of this paper is to describe how cloud system resolving models (CRMs) of grid spacing approximately 1 km have been applied to various important problems in atmospheric science across a wide range of spatial and temporal scales and how these applications relate to other modeling approaches. A long-standing problem concerns the representation of organized precipitating convective cloud systems in weather and climate models. Since CRMs resolve the mesoscale to large scales of motion (i.e., 10 km to global) they explicitly address the cloud system problem. By explicitly representing organized convection, CRMs bypass restrictive assumptions associated with convective parameterization such as the scale gap between cumulus and large-scale motion. Dynamical models provide insight into the physical mechanisms involved with scale interaction and convective organization. Multiscale CRMs simulate convective cloud systems in computational domains up to global and have been applied in place of contemporary convective parameterizations in global models. Multiscale CRMs pose a new challenge for model validation, which is met in an integrated approach involving CRMs, operational prediction systems, observational measurements, and dynamical models in a new international project: the Year of Tropical Convection, which has an emphasis on organized tropical convection and its global effects.

A Numerical Wind Tunnel Study of Viscous-Inviscid Interaction

DTIC Science & Technology

1992-01-01

partially successful. In Task 1 we devised surface boundary conditions for the multiscale model including effects of roughness and blowing. This work tied up ...directed at cleaning up some loose ends in de- veloping the Wilcox multiscale model (see Appendix R). The most significant issue was the development of...the following correlation between SR and k , will reproduce measured effects of sand-grain roughness for values of k up to about 400. ( k, ញ SiR (42

Multiscale Enaction Model (MEM): the case of complexity and “context-sensitivity” in vision

PubMed Central

Laurent, Éric

2014-01-01

I review the data on human visual perception that reveal the critical role played by non-visual contextual factors influencing visual activity. The global perspective that progressively emerges reveals that vision is sensitive to multiple couplings with other systems whose nature and levels of abstraction in science are highly variable. Contrary to some views where vision is immersed in modular hard-wired modules, rather independent from higher-level or other non-cognitive processes, converging data gathered in this article suggest that visual perception can be theorized in the larger context of biological, physical, and social systems with which it is coupled, and through which it is enacted. Therefore, any attempt to model complexity and multiscale couplings, or to develop a complex synthesis in the fields of mind, brain, and behavior, shall involve a systematic empirical study of both connectedness between systems or subsystems, and the embodied, multiscale and flexible teleology of subsystems. The conceptual model (Multiscale Enaction Model [MEM]) that is introduced in this paper finally relates empirical evidence gathered from psychology to biocomputational data concerning the human brain. Both psychological and biocomputational descriptions of MEM are proposed in order to help fill in the gap between scales of scientific analysis and to provide an account for both the autopoiesis-driven search for information, and emerging perception. PMID:25566115

Finite Dimensional Approximations for Continuum Multiscale Problems

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

Berlyand, Leonid

2017-01-24

The completed research project concerns the development of novel computational techniques for modeling nonlinear multiscale physical and biological phenomena. Specifically, it addresses the theoretical development and applications of the homogenization theory (coarse graining) approach to calculation of the effective properties of highly heterogenous biological and bio-inspired materials with many spatial scales and nonlinear behavior. This theory studies properties of strongly heterogeneous media in problems arising in materials science, geoscience, biology, etc. Modeling of such media raises fundamental mathematical questions, primarily in partial differential equations (PDEs) and calculus of variations, the subject of the PI’s research. The focus of completed researchmore » was on mathematical models of biological and bio-inspired materials with the common theme of multiscale analysis and coarse grain computational techniques. Biological and bio-inspired materials offer the unique ability to create environmentally clean functional materials used for energy conversion and storage. These materials are intrinsically complex, with hierarchical organization occurring on many nested length and time scales. The potential to rationally design and tailor the properties of these materials for broad energy applications has been hampered by the lack of computational techniques, which are able to bridge from the molecular to the macroscopic scale. The project addressed the challenge of computational treatments of such complex materials by the development of a synergistic approach that combines innovative multiscale modeling/analysis techniques with high performance computing.« less

Knowledge environments representing molecular entities for the virtual physiological human.

PubMed

Hofmann-Apitius, Martin; Fluck, Juliane; Furlong, Laura; Fornes, Oriol; Kolárik, Corinna; Hanser, Susanne; Boeker, Martin; Schulz, Stefan; Sanz, Ferran; Klinger, Roman; Mevissen, Theo; Gattermayer, Tobias; Oliva, Baldo; Friedrich, Christoph M

2008-09-13

In essence, the virtual physiological human (VPH) is a multiscale representation of human physiology spanning from the molecular level via cellular processes and multicellular organization of tissues to complex organ function. The different scales of the VPH deal with different entities, relationships and processes, and in consequence the models used to describe and simulate biological functions vary significantly. Here, we describe methods and strategies to generate knowledge environments representing molecular entities that can be used for modelling the molecular scale of the VPH. Our strategy to generate knowledge environments representing molecular entities is based on the combination of information extraction from scientific text and the integration of information from biomolecular databases. We introduce @neuLink, a first prototype of an automatically generated, disease-specific knowledge environment combining biomolecular, chemical, genetic and medical information. Finally, we provide a perspective for the future implementation and use of knowledge environments representing molecular entities for the VPH.

Detecting recurrent gene mutation in interaction network context using multi-scale graph diffusion.

PubMed

Babaei, Sepideh; Hulsman, Marc; Reinders, Marcel; de Ridder, Jeroen

2013-01-23

Delineating the molecular drivers of cancer, i.e. determining cancer genes and the pathways which they deregulate, is an important challenge in cancer research. In this study, we aim to identify pathways of frequently mutated genes by exploiting their network neighborhood encoded in the protein-protein interaction network. To this end, we introduce a multi-scale diffusion kernel and apply it to a large collection of murine retroviral insertional mutagenesis data. The diffusion strength plays the role of scale parameter, determining the size of the network neighborhood that is taken into account. As a result, in addition to detecting genes with frequent mutations in their genomic vicinity, we find genes that harbor frequent mutations in their interaction network context. We identify densely connected components of known and putatively novel cancer genes and demonstrate that they are strongly enriched for cancer related pathways across the diffusion scales. Moreover, the mutations in the clusters exhibit a significant pattern of mutual exclusion, supporting the conjecture that such genes are functionally linked. Using multi-scale diffusion kernel, various infrequently mutated genes are found to harbor significant numbers of mutations in their interaction network neighborhood. Many of them are well-known cancer genes. The results demonstrate the importance of defining recurrent mutations while taking into account the interaction network context. Importantly, the putative cancer genes and networks detected in this study are found to be significant at different diffusion scales, confirming the necessity of a multi-scale analysis.

Multiscale Modeling of Carbon Nanotube-Epoxy Nanocomposites

NASA Astrophysics Data System (ADS)

Fasanella, Nicholas A.

Epoxy-composites are widely used in the aerospace industry. In order to improve upon stiffness and thermal conductivity; carbon nanotube additives to epoxies are being explored. This dissertation presents multiscale modeling techniques to study the engineering properties of single walled carbon nanotube (SWNT)-epoxy nanocomposites, consisting of pristine and covalently functionalized systems. Using Molecular Dynamics (MD), thermomechanical properties were calculated for a representative polymer unit cell. Finite Element (FE) and orientation distribution function (ODF) based methods were used in a multiscale framework to obtain macroscale properties. An epoxy network was built using the dendrimer growth approach. The epoxy model was verified by matching the experimental glass transition temperature, density, and dilatation. MD, via the constant valence force field (CVFF), was used to explore the mechanical and dilatometric effects of adding pristine and functionalized SWNTs to epoxy. Full stiffness matrices and linear coefficient of thermal expansion vectors were obtained. The Green-Kubo method was used to investigate the thermal conductivity as a function of temperature for the various nanocomposites. Inefficient phonon transport at the ends of nanotubes is an important factor in the thermal conductivity of the nanocomposites, and for this reason discontinuous nanotubes were modeled in addition to long nanotubes. To obtain continuum-scale elastic properties from the MD data, multiscale modeling was considered to give better control over the volume fraction of nanotubes, and investigate the effects of nanotube alignment. Two methods were considered; an FE based method, and an ODF based method. The FE method probabilistically assigned elastic properties of elements from the MD lattice results based on the desired volume fraction and alignment of the nanotubes. For the ODF method, a distribution function was generated based on the desired amount of nanotube alignment; and the stiffness matrix was calculated. A rule of mixture approach was implemented in the ODF model to vary the SWNT volume fraction. Both the ODF and FE models are compared and contrasted. ODF analysis is significantly faster for nanocomposites and is a novel contribution in this thesis. Multiscale modeling allows for the effects of nanofillers in epoxy systems to be characterized without having to run costly experiments.

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study

PubMed Central

Vickers, T. Winston; Ernest, Holly B.; Boyce, Walter M.

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species. PMID:28609466

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study.

PubMed

Zeller, Katherine A; Vickers, T Winston; Ernest, Holly B; Boyce, Walter M

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species.

Differential Geometry Based Multiscale Models

PubMed Central

Wei, Guo-Wei

2010-01-01

Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atom-istic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier–Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson–Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson–Nernst–Planck equations that are coupled to generalized Navier–Stokes equations for fluid dynamics, Newton's equation for molecular dynamics, and potential and surface driving geometric flows for the micro-macro interface. For excessively large aqueous macromolecular complexes in chemistry and biology, we further develop differential geometry based multiscale fluid-electro-elastic models to replace the expensive molecular dynamics description with an alternative elasticity formulation. PMID:20169418

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

NASA Technical Reports Server (NTRS)

Thompson, Alexander; Lawson, John W.

2014-01-01

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

Integrative computational models of cardiac arrhythmias -- simulating the structurally realistic heart

PubMed Central

Trayanova, Natalia A; Tice, Brock M

2009-01-01

Simulation of cardiac electrical function, and specifically, simulation aimed at understanding the mechanisms of cardiac rhythm disorders, represents an example of a successful integrative multiscale modeling approach, uncovering emergent behavior at the successive scales in the hierarchy of structural complexity. The goal of this article is to present a review of the integrative multiscale models of realistic ventricular structure used in the quest to understand and treat ventricular arrhythmias. It concludes with the new advances in image-based modeling of the heart and the promise it holds for the development of individualized models of ventricular function in health and disease. PMID:20628585

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

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

NASA Astrophysics Data System (ADS)

Zeng, Yayun; Wang, Jun; Xu, Kaixuan

2017-04-01

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

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.

The role of continuity in residual-based variational multiscale modeling of turbulence

NASA Astrophysics Data System (ADS)

Akkerman, I.; Bazilevs, Y.; Calo, V. M.; Hughes, T. J. R.; Hulshoff, S.

2008-02-01

This paper examines the role of continuity of the basis in the computation of turbulent flows. We compare standard finite elements and non-uniform rational B-splines (NURBS) discretizations that are employed in Isogeometric Analysis (Hughes et al. in Comput Methods Appl Mech Eng, 194:4135 4195, 2005). We make use of quadratic discretizations that are C 0-continuous across element boundaries in standard finite elements, and C 1-continuous in the case of NURBS. The variational multiscale residual-based method (Bazilevs in Isogeometric analysis of turbulence and fluid-structure interaction, PhD thesis, ICES, UT Austin, 2006; Bazilevs et al. in Comput Methods Appl Mech Eng, submitted, 2007; Calo in Residual-based multiscale turbulence modeling: finite volume simulation of bypass transition. PhD thesis, Department of Civil and Environmental Engineering, Stanford University, 2004; Hughes et al. in proceedings of the XXI international congress of theoretical and applied mechanics (IUTAM), Kluwer, 2004; Scovazzi in Multiscale methods in science and engineering, PhD thesis, Department of Mechanical Engineering, Stanford Universty, 2004) is employed as a turbulence modeling technique. We find that C 1-continuous discretizations outperform their C 0-continuous counterparts on a per-degree-of-freedom basis. We also find that the effect of continuity is greater for higher Reynolds number flows.

Contour Tracking in Echocardiographic Sequences via Sparse Representation and Dictionary Learning

PubMed Central

Huang, Xiaojie; Dione, Donald P.; Compas, Colin B.; Papademetris, Xenophon; Lin, Ben A.; Bregasi, Alda; Sinusas, Albert J.; Staib, Lawrence H.; Duncan, James S.

2013-01-01

This paper presents a dynamical appearance model based on sparse representation and dictionary learning for tracking both endocardial and epicardial contours of the left ventricle in echocardiographic sequences. Instead of learning offline spatiotemporal priors from databases, we exploit the inherent spatiotemporal coherence of individual data to constraint cardiac contour estimation. The contour tracker is initialized with a manual tracing of the first frame. It employs multiscale sparse representation of local image appearance and learns online multiscale appearance dictionaries in a boosting framework as the image sequence is segmented frame-by-frame sequentially. The weights of multiscale appearance dictionaries are optimized automatically. Our region-based level set segmentation integrates a spectrum of complementary multilevel information including intensity, multiscale local appearance, and dynamical shape prediction. The approach is validated on twenty-six 4D canine echocardiographic images acquired from both healthy and post-infarct canines. The segmentation results agree well with expert manual tracings. The ejection fraction estimates also show good agreement with manual results. Advantages of our approach are demonstrated by comparisons with a conventional pure intensity model, a registration-based contour tracker, and a state-of-the-art database-dependent offline dynamical shape model. We also demonstrate the feasibility of clinical application by applying the method to four 4D human data sets. PMID:24292554

Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata.

PubMed

Leempoel, Kevin; Parisod, Christian; Geiser, Céline; Joost, Stéphane

2018-02-01

Plant species are known to adapt locally to their environment, particularly in mountainous areas where conditions can vary drastically over short distances. The climate of such landscapes being largely influenced by topography, using fine-scale models to evaluate environmental heterogeneity may help detecting adaptation to micro-habitats. Here, we applied a multiscale landscape genomic approach to detect evidence of local adaptation in the alpine plant Biscutella laevigata . The two gene pools identified, experiencing limited gene flow along a 1-km ridge, were different in regard to several habitat features derived from a very high resolution (VHR) digital elevation model (DEM). A correlative approach detected signatures of selection along environmental gradients such as altitude, wind exposure, and solar radiation, indicating adaptive pressures likely driven by fine-scale topography. Using a large panel of DEM-derived variables as ecologically relevant proxies, our results highlighted the critical role of spatial resolution. These high-resolution multiscale variables indeed indicate that the robustness of associations between genetic loci and environmental features depends on spatial parameters that are poorly documented. We argue that the scale issue is critical in landscape genomics and that multiscale ecological variables are key to improve our understanding of local adaptation in highly heterogeneous landscapes.

Imaging multi-scale dynamics in vivo with spiral volumetric optoacoustic tomography

NASA Astrophysics Data System (ADS)

Deán-Ben, X. Luís.; Fehm, Thomas F.; Ford, Steven J.; Gottschalk, Sven; Razansky, Daniel

2017-03-01

Imaging dynamics in living organisms is essential for the understanding of biological complexity. While multiple imaging modalities are often required to cover both microscopic and macroscopic spatial scales, dynamic phenomena may also extend over different temporal scales, necessitating the use of different imaging technologies based on the trade-off between temporal resolution and effective field of view. Optoacoustic (photoacoustic) imaging has been shown to offer the exclusive capability to link multiple spatial scales ranging from organelles to entire organs of small animals. Yet, efficient visualization of multi-scale dynamics remained difficult with state-of-the-art systems due to inefficient trade-offs between image acquisition and effective field of view. Herein, we introduce a spiral volumetric optoacoustic tomography (SVOT) technique that provides spectrally-enriched high-resolution optical absorption contrast across multiple spatio-temporal scales. We demonstrate that SVOT can be used to monitor various in vivo dynamics, from video-rate volumetric visualization of cardiac-associated motion in whole organs to high-resolution imaging of pharmacokinetics in larger regions. The multi-scale dynamic imaging capability thus emerges as a powerful and unique feature of the optoacoustic technology that adds to the multiple advantages of this technology for structural, functional and molecular imaging.

Multiscale Feature Analysis of Salivary Gland Branching Morphogenesis

PubMed Central

Baydil, Banu; Daley, William P.; Larsen, Melinda; Yener, Bülent

2012-01-01

Pattern formation in developing tissues involves dynamic spatio-temporal changes in cellular organization and subsequent evolution of functional adult structures. Branching morphogenesis is a developmental mechanism by which patterns are generated in many developing organs, which is controlled by underlying molecular pathways. Understanding the relationship between molecular signaling, cellular behavior and resulting morphological change requires quantification and categorization of the cellular behavior. In this study, tissue-level and cellular changes in developing salivary gland in response to disruption of ROCK-mediated signaling by are modeled by building cell-graphs to compute mathematical features capturing structural properties at multiple scales. These features were used to generate multiscale cell-graph signatures of untreated and ROCK signaling disrupted salivary gland organ explants. From confocal images of mouse submandibular salivary gland organ explants in which epithelial and mesenchymal nuclei were marked, a multiscale feature set capturing global structural properties, local structural properties, spectral, and morphological properties of the tissues was derived. Six feature selection algorithms and multiway modeling of the data was performed to identify distinct subsets of cell graph features that can uniquely classify and differentiate between different cell populations. Multiscale cell-graph analysis was most effective in classification of the tissue state. Cellular and tissue organization, as defined by a multiscale subset of cell-graph features, are both quantitatively distinct in epithelial and mesenchymal cell types both in the presence and absence of ROCK inhibitors. Whereas tensor analysis demonstrate that epithelial tissue was affected the most by inhibition of ROCK signaling, significant multiscale changes in mesenchymal tissue organization were identified with this analysis that were not identified in previous biological studies. We here show how to define and calculate a multiscale feature set as an effective computational approach to identify and quantify changes at multiple biological scales and to distinguish between different states in developing tissues. PMID:22403724

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

NASA Astrophysics Data System (ADS)

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

2008-09-01

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

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

NASA Astrophysics Data System (ADS)

Huang, Shiquan; Yi, Youping; Li, Pengchuan

2011-05-01

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

On inter-hemispheric coupling in the middle atmosphere

NASA Astrophysics Data System (ADS)

Karlsson, Bodil; Bailey, S.; Benze, S.; Gumbel, J.; Harvey, V. L.; Kürnich, H.; Lossow, S.; McLandress, D. Marsh, C.; Merkel, A. W.; Mills, M.; Randall, C. E.; Russell, J.; Shepherd, T. G.

On inter-hemispheric coupling in the middle atmosphere From recent studies it is evident that planetary wave activity in the winter hemisphere influences the high-latitude summer mesosphere on the opposite side of the globe. This is an extraordinary example of multi-scale wave-mean flow interaction. The first indication of this inter-hemispheric coupling came from a model study by Becker and Schmitz (2003). Since then, the results have been reproduced in several models, and observations have confirmed the existence of this link. We present current understanding of inter-hemispheric coupling and its consequences for the middle atmosphere, focusing on the summer mesosphere where polar mesospheric clouds (PMCs) form. The results shown are based on year-to-year and intra-seasonal variability in PMCs ob-served by the Odin satellite and the Aeronomy of Ice in the Mesosphere (AIM) satellite, as well as on model results from the extended Canadian Middle Atmosphere Model (CMAM), the Whole Atmosphere Community Climate Model (WACCM) and the Kühlungsborn Mechanis-u tic general Circulation Model (KMCM). The latter has been used to pinpoint the proposed mechanism behind the inter-hemispheric coupling.

Multi-scale Modeling of the Cardiovascular System: Disease Development, Progression, and Clinical Intervention.

PubMed

Zhang, Yanhang; Barocas, Victor H; Berceli, Scott A; Clancy, Colleen E; Eckmann, David M; Garbey, Marc; Kassab, Ghassan S; Lochner, Donna R; McCulloch, Andrew D; Tran-Son-Tay, Roger; Trayanova, Natalia A

2016-09-01

Cardiovascular diseases (CVDs) are the leading cause of death in the western world. With the current development of clinical diagnostics to more accurately measure the extent and specifics of CVDs, a laudable goal is a better understanding of the structure-function relation in the cardiovascular system. Much of this fundamental understanding comes from the development and study of models that integrate biology, medicine, imaging, and biomechanics. Information from these models provides guidance for developing diagnostics, and implementation of these diagnostics to the clinical setting, in turn, provides data for refining the models. In this review, we introduce multi-scale and multi-physical models for understanding disease development, progression, and designing clinical interventions. We begin with multi-scale models of cardiac electrophysiology and mechanics for diagnosis, clinical decision support, personalized and precision medicine in cardiology with examples in arrhythmia and heart failure. We then introduce computational models of vasculature mechanics and associated mechanical forces for understanding vascular disease progression, designing clinical interventions, and elucidating mechanisms that underlie diverse vascular conditions. We conclude with a discussion of barriers that must be overcome to provide enhanced insights, predictions, and decisions in pre-clinical and clinical applications.

Multi-scale Modeling of the Cardiovascular System: Disease Development, Progression, and Clinical Intervention

PubMed Central

Zhang, Yanhang; Barocas, Victor H.; Berceli, Scott A.; Clancy, Colleen E.; Eckmann, David M.; Garbey, Marc; Kassab, Ghassan S.; Lochner, Donna R.; McCulloch, Andrew D.; Tran-Son-Tay, Roger; Trayanova, Natalia A.

2016-01-01

Cardiovascular diseases (CVDs) are the leading cause of death in the western world. With the current development of clinical diagnostics to more accurately measure the extent and specifics of CVDs, a laudable goal is a better understanding of the structure-function relation in the cardiovascular system. Much of this fundamental understanding comes from the development and study of models that integrate biology, medicine, imaging, and biomechanics. Information from these models provides guidance for developing diagnostics, and implementation of these diagnostics to the clinical setting, in turn, provides data for refining the models. In this review, we introduce multi-scale and multi-physical models for understanding disease development, progression, and designing clinical interventions. We begin with multi-scale models of cardiac electrophysiology and mechanics for diagnosis, clinical decision support, personalized and precision medicine in cardiology with examples in arrhythmia and heart failure. We then introduce computational models of vasculature mechanics and associated mechanical forces for understanding vascular disease progression, designing clinical interventions, and elucidating mechanisms that underlie diverse vascular conditions. We conclude with a discussion of barriers that must be overcome to provide enhanced insights, predictions, and decisions in pre-clinical and clinical applications. PMID:27138523

Heat Source Characterization In A TREAT Fuel Particle Using Coupled Neutronics Binary Collision Monte-Carlo Calculations

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

Schunert, Sebastian; Schwen, Daniel; Ghassemi, Pedram

This work presents a multi-physics, multi-scale approach to modeling the Transient Test Reactor (TREAT) currently prepared for restart at the Idaho National Laboratory. TREAT fuel is made up of microscopic fuel grains (r ˜ 20µm) dispersed in a graphite matrix. The novelty of this work is in coupling a binary collision Monte-Carlo (BCMC) model to the Finite Element based code Moose for solving a microsopic heat-conduction problem whose driving source is provided by the BCMC model tracking fission fragment energy deposition. This microscopic model is driven by a transient, engineering scale neutronics model coupled to an adiabatic heating model. Themore » macroscopic model provides local power densities and neutron energy spectra to the microscpic model. Currently, no feedback from the microscopic to the macroscopic model is considered. TREAT transient 15 is used to exemplify the capabilities of the multi-physics, multi-scale model, and it is found that the average fuel grain temperature differs from the average graphite temperature by 80 K despite the low-power transient. The large temperature difference has strong implications on the Doppler feedback a potential LEU TREAT core would see, and it underpins the need for multi-physics, multi-scale modeling of a TREAT LEU core.« less

Defining and Modeling Known Adverse Outcome Pathways: Domoic Acid and Neuronal Signaling as a Case Study

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

Watanabe, Karen H.; Andersen, Melvin E.; Basu, Nil

2011-01-01

An adverse outcome pathway (AOP) is a sequence of key events from a molecular-level initiating event and an ensuing cascade of steps to an adverse outcome with population level significance. To implement a predictive strategy for ecotoxicology, the multiscale nature of an AOP requires computational models to link salient processes (e.g., in chemical uptake, toxicokinetics, toxicodynamics, and population dynamics). A case study with domoic acid was used to demonstrate strategies and enable generic recommendations for developing computational models in an effort to move toward a toxicity testing paradigm focused on toxicity pathway perturbations applicable to ecological risk assessment. Domoic acid,more » an algal toxin with adverse effects on both wildlife and humans, is a potent agonist for kainate receptors (ionotropic glutamate receptors whose activation leads to the influx of Na+ and Ca2+). Increased Ca2+ concentrations result in neuronal excitotoxicity and cell death primarily in the hippocampus, which produces seizures, impairs learning and memory, and alters behavior in some species. Altered neuronal Ca2+ is a key process in domoic acid toxicity which can be evaluated in vitro. Further, results of these assays would be amenable to mechanistic modeling for identifying domoic acid concentrations and Ca2+ perturbations that are normal, adaptive, or clearly toxic. In vitro assays with outputs amenable to measurement in exposed populations can link in vitro to in vivo conditions, and toxicokinetic information will aid in linking in vitro results to the individual organism. Development of an AOP required an iterative process with three important outcomes: (1) a critically reviewed, stressor-specific AOP; (2) identification of key processes suitable for evaluation with in vitro assays; and (3) strategies for model development.« less

Linking the influence and dependence of people on biodiversity across scales.

PubMed

Isbell, Forest; Gonzalez, Andrew; Loreau, Michel; Cowles, Jane; Díaz, Sandra; Hector, Andy; Mace, Georgina M; Wardle, David A; O'Connor, Mary I; Duffy, J Emmett; Turnbull, Lindsay A; Thompson, Patrick L; Larigauderie, Anne

2017-05-31

Biodiversity enhances many of nature's benefits to people, including the regulation of climate and the production of wood in forests, livestock forage in grasslands and fish in aquatic ecosystems. Yet people are now driving the sixth mass extinction event in Earth's history. Human dependence and influence on biodiversity have mainly been studied separately and at contrasting scales of space and time, but new multiscale knowledge is beginning to link these relationships. Biodiversity loss substantially diminishes several ecosystem services by altering ecosystem functioning and stability, especially at the large temporal and spatial scales that are most relevant for policy and conservation.

A new neuroinformatics approach to personalized medicine in neurology: The Virtual Brain

PubMed Central

Falcon, Maria I.; Jirsa, Viktor; Solodkin, Ana

2017-01-01

Purpose of review An exciting advance in the field of neuroimaging is the acquisition and processing of very large data sets (so called ‘big data’), permitting large-scale inferences that foster a greater understanding of brain function in health and disease. Yet what we are clearly lacking are quantitative integrative tools to translate this understanding to the individual level to lay the basis for personalized medicine. Recent findings Here we address this challenge through a review on how the relatively new field of neuroinformatics modeling has the capacity to track brain network function at different levels of inquiry, from microscopic to macroscopic and from the localized to the distributed. In this context, we introduce a new and unique multiscale approach, The Virtual Brain (TVB), that effectively models individualized brain activity, linking large-scale (macroscopic) brain dynamics with biophysical parameters at the microscopic level. We also show how TVB modeling provides unique biological interpretable data in epilepsy and stroke. Summary These results establish the basis for a deliberate integration of computational biology and neuroscience into clinical approaches for elucidating cellular mechanisms of disease. In the future, this can provide the means to create a collection of disease-specific models that can be applied on the individual level to personalize therapeutic interventions. Video abstract http://links.lww.com/CONR/A41 PMID:27224088

Cracking up (and down): Linking multi-domain hydraulic properties with multi-scale hydrological processes in shrink-swell soils

NASA Astrophysics Data System (ADS)

Stewart, R. D.; Rupp, D. E.; Abou Najm, M. R.; Selker, J. S.

2017-12-01

Shrink-swell soils, often classified as Vertisols or vertic intergrades, are found on every continent except Antarctica and within many agricultural and urban regions. These soils are characterized by cyclical shrinking and swelling, in which bulk density and porosity distributions vary as functions of time and soil moisture. Crack networks that form in these soils act as dominant environmental controls on the movement of water, contaminants, and gases, making it important to develop fundamental understanding and tractable models of their hydrologic characteristics and behaviors. In this study, which took place primarily in the Secano Interior region of South-Central Chile, we quantified soil-water interactions across scales using a diverse and innovative dataset. These measurements were then utilized to develop a set of parsimonious multi-domain models for describing hydraulic properties and hydrological processes in shrink-swell soils. In a series of examples, we show how this model can predict porosity distributions, crack widths, saturated hydraulic conductivities, and surface runoff (i.e., overland flow) thresholds, by capturing the dominant mechanisms by which water moves through and interacts with clayey soils. Altogether, these models successfully link small-scale shrinkage/swelling behaviors with large-scale thresholds, and can be applied to describe important processes such as infiltration, overland flow development, and the preferential flow and transport of fluids and gases.

Multi-scale modelling of elastic moduli of trabecular bone

PubMed Central

Hamed, Elham; Jasiuk, Iwona; Yoo, Andrew; Lee, YikHan; Liszka, Tadeusz

2012-01-01

We model trabecular bone as a nanocomposite material with hierarchical structure and predict its elastic properties at different structural scales. The analysis involves a bottom-up multi-scale approach, starting with nanoscale (mineralized collagen fibril) and moving up the scales to sub-microscale (single lamella), microscale (single trabecula) and mesoscale (trabecular bone) levels. Continuum micromechanics methods, composite materials laminate theory and finite-element methods are used in the analysis. Good agreement is found between theoretical and experimental results. PMID:22279160

Asymptotic-Preserving methods and multiscale models for plasma physics

NASA Astrophysics Data System (ADS)

Degond, Pierre; Deluzet, Fabrice

2017-05-01

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

The Discontinuous Galerkin Method for the Multiscale Modeling of Dynamics of Crystalline Solids

DTIC Science & Technology

2007-08-26

number. 1. REPORT DATE 26 AUG 2007 2 . REPORT TYPE 3. DATES COVERED 00-00-2007 to 00-00-2007 4. TITLE AND SUBTITLE The Discontinuous Galerkin...Dynamics method (MAAD) [ 2 ], the bridging scale method [47], the bridging domain methods [48], the heterogeneous multiscale method (HMM) [23, 36, 24], and...method consists of three components, 1. a macro solver for the continuum model, 2 . a micro solver to equilibrate the atomistic system locally to the appro

Composite annotations: requirements for mapping multiscale data and models to biomedical ontologies

PubMed Central

Cook, Daniel L.; Mejino, Jose L. V.; Neal, Maxwell L.; Gennari, John H.

2009-01-01

Current methods for annotating biomedical data resources rely on simple mappings between data elements and the contents of a variety of biomedical ontologies and controlled vocabularies. Here we point out that such simple mappings are inadequate for large-scale multiscale, multidomain integrative “virtual human” projects. For such integrative challenges, we describe a “composite annotation” schema that is simple yet sufficiently extensible for mapping the biomedical content of a variety of data sources and biosimulation models to available biomedical ontologies. PMID:19964601

Hybrid codes with finite electron mass

NASA Astrophysics Data System (ADS)

Lipatov, A. S.

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

Multiscale Persistent Functions for Biomolecular Structure Characterization

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

Xia, Kelin; Li, Zhiming; Mu, Lin

Here in this paper, we introduce multiscale persistent functions for biomolecular structure characterization. The essential idea is to combine our multiscale rigidity functions (MRFs) with persistent homology analysis, so as to construct a series of multiscale persistent functions, particularly multiscale persistent entropies, for structure characterization. To clarify the fundamental idea of our method, the multiscale persistent entropy (MPE) model is discussed in great detail. Mathematically, unlike the previous persistent entropy (Chintakunta et al. in Pattern Recognit 48(2):391–401, 2015; Merelli et al. in Entropy 17(10):6872–6892, 2015; Rucco et al. in: Proceedings of ECCS 2014, Springer, pp 117–128, 2016), a special resolutionmore » parameter is incorporated into our model. Various scales can be achieved by tuning its value. Physically, our MPE can be used in conformational entropy evaluation. More specifically, it is found that our method incorporates in it a natural classification scheme. This is achieved through a density filtration of an MRF built from angular distributions. To further validate our model, a systematical comparison with the traditional entropy evaluation model is done. Additionally, it is found that our model is able to preserve the intrinsic topological features of biomolecular data much better than traditional approaches, particularly for resolutions in the intermediate range. Moreover, by comparing with traditional entropies from various grid sizes, bond angle-based methods and a persistent homology-based support vector machine method (Cang et al. in Mol Based Math Biol 3:140–162, 2015), we find that our MPE method gives the best results in terms of average true positive rate in a classic protein structure classification test. More interestingly, all-alpha and all-beta protein classes can be clearly separated from each other with zero error only in our model. Finally, a special protein structure index (PSI) is proposed, for the first time, to describe the “regularity” of protein structures. Basically, a protein structure is deemed as regular if it has a consistent and orderly configuration. Our PSI model is tested on a database of 110 proteins; we find that structures with larger portions of loops and intrinsically disorder regions are always associated with larger PSI, meaning an irregular configuration, while proteins with larger portions of secondary structures, i.e., alpha-helix or beta-sheet, have smaller PSI. Essentially, PSI can be used to describe the “regularity” information in any systems.« less

Based on a multi-agent system for multi-scale simulation and application of household's LUCC: a case study for Mengcha village, Mizhi county, Shaanxi province.

PubMed

Chen, Hai; Liang, Xiaoying; Li, Rui

2013-01-01

Multi-Agent Systems (MAS) offer a conceptual approach to include multi-actor decision making into models of land use change. Through the simulation based on the MAS, this paper tries to show the application of MAS in the micro scale LUCC, and reveal the transformation mechanism of difference scale. This paper starts with a description of the context of MAS research. Then, it adopts the Nested Spatial Choice (NSC) method to construct the multi-scale LUCC decision-making model. And a case study for Mengcha village, Mizhi County, Shaanxi Province is reported. Finally, the potentials and drawbacks of the following approach is discussed and concluded. From our design and implementation of the MAS in multi-scale model, a number of observations and conclusions can be drawn on the implementation and future research directions. (1) The use of the LUCC decision-making and multi-scale transformation framework provides, according to us, a more realistic modeling of multi-scale decision making process. (2) By using continuous function, rather than discrete function, to construct the decision-making of the households is more realistic to reflect the effect. (3) In this paper, attempts have been made to give a quantitative analysis to research the household interaction. And it provides the premise and foundation for researching the communication and learning among the households. (4) The scale transformation architecture constructed in this paper helps to accumulate theory and experience for the interaction research between the micro land use decision-making and the macro land use landscape pattern. Our future research work will focus on: (1) how to rational use risk aversion principle, and put the rule on rotation between household parcels into model. (2) Exploring the methods aiming at researching the household decision-making over a long period, it allows us to find the bridge between the long-term LUCC data and the short-term household decision-making. (3) Researching the quantitative method and model, especially the scenario analysis model which may reflect the interaction among different household types.

An Unified Multiscale Framework for Planar, Surface, and Curve Skeletonization.

PubMed

Jalba, Andrei C; Sobiecki, Andre; Telea, Alexandru C

2016-01-01

Computing skeletons of 2D shapes, and medial surface and curve skeletons of 3D shapes, is a challenging task. In particular, there is no unified framework that detects all types of skeletons using a single model, and also produces a multiscale representation which allows to progressively simplify, or regularize, all skeleton types. In this paper, we present such a framework. We model skeleton detection and regularization by a conservative mass transport process from a shape's boundary to its surface skeleton, next to its curve skeleton, and finally to the shape center. The resulting density field can be thresholded to obtain a multiscale representation of progressively simplified surface, or curve, skeletons. We detail a numerical implementation of our framework which is demonstrably stable and has high computational efficiency. We demonstrate our framework on several complex 2D and 3D shapes.

Performance and diagnostic evaluation of ozone predictions by the Eta-Community Multiscale Air Quality Forecast System during the 2002 New England Air Quality Study.

PubMed

Yu, Shaocai; Mathur, Rohit; Kang, Daiwen; Schere, Kenneth; Eder, Brian; Pleim, Jonathan

2006-10-01

A real-time air quality forecasting system (Eta-Community Multiscale Air Quality [CMAQ] model suite) has been developed by linking the National Centers for Environmental Estimation Eta model to the U.S. Environmental Protection Agency (EPA) CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting ozone (O3) over the Northeastern United States during the 2002 New England Air Quality Study (NEAQS). Spatial and temporal performance of the Eta-CMAQ model for O3 was evaluated by comparison with observations from the EPA Air Quality System (AQS) network. This study also examines the ability of the model to simulate the processes governing the distributions of tropospheric O3 on the basis of the intensive datasets obtained at the four Atmospheric Investigation, Regional Modeling, Analysis, and Estimation (AIRMAP) and Harvard Forest (HF) surface sites. The episode analysis reveals that the model captured the buildup of O3 concentrations over the northeastern domain from August 11 and reproduced the spatial distributions of observed O3 very well for the daytime (8:00 p.m.) of both August 8 and 12 with most of normalized mean bias (NMB) within +/- 20%. The model reproduced 53.3% of the observed hourly O3 within a factor of 1.5 with NMB of 29.7% and normalized mean error of 46.9% at the 342 AQS sites. The comparison of modeled and observed lidar O3 vertical profiles shows that whereas the model reproduced the observed vertical structure, it tended to overestimate at higher altitude. The model reproduced 64-77% of observed NO2 photolysis rate values within a factor of 1.5 at the AIRMAP sites. At the HF site, comparison of modeled and observed O3/nitrogen oxide (NOx) ratios suggests that the site is mainly under strongly NOx-sensitive conditions (>53%). It was found that the modeled lower limits of the O3 production efficiency values (inferred from O3-CO correlation) are close to the observations.

A Multi-Scale Study on the Role of Trace Metals on Physiological and Pathological Mineralization

NASA Astrophysics Data System (ADS)

Rammelkamp, Derek

The work in this thesis provides mulit-scale contributions towards understanding the effects of trace metals on the pathological mineralization process relating to both the development of healthy bone tissue, the diseased state of osteoporosis, and microcalcifications which develop in breast cancers. A protein level study was performed on ECM protein fibronectin, which plays a role in cell adhesion. The protein studies showed zinc interactions with fibronectin and its fragment, anastellin, to influence protein structure. Zinc is also shown to decrease cell migration in vitro, which may be influenced by changes in fibronectin ECM structure. The effects of osteoporosis on micronutrient composition in vivo were examined using the technique of x-ray fluorescence (XRF) in an ovariectomized rat model. Compared to healthy bone, subtle difference are observed in zinc and iron in osteoporotic rat bones, showing micronutrients may play an important role in healthy bone regulation. Effects of micronutrient zinc was used to inhibit microcalcification formation in breast cancers. Microcalcifications have been linked malignancy of breast cancers, but the process of microcalcification formation has yet to be well understood. In this work, exogenous zinc is used to inhibit microcalcification formation, and metastatic potential in both a 2D and 3D spheroid environment. A novel in vitro self-assembled three dimensional multi-cellular tumor spheroid (MCTS) model for the study of breast cancer microcalcifications was developed for this experiment. A MCTS model for studying breast cancer microcalcifications has potential to be used in drug discovery, or for basic research applications studying mechanisms of microcalcification formation, which are still not fully understood. Taken together this study uses a multi-scale approach to gain a better understanding of micronutrients involved in pathological mineralization.

Differential geometry based solvation model. III. Quantum formulation

PubMed Central

Chen, Zhan; Wei, Guo-Wei

2011-01-01

Solvation is of fundamental importance to biomolecular systems. Implicit solvent models, particularly those based on the Poisson-Boltzmann equation for electrostatic analysis, are established approaches for solvation analysis. However, ad hoc solvent-solute interfaces are commonly used in the implicit solvent theory. Recently, we have introduced differential geometry based solvation models which allow the solvent-solute interface to be determined by the variation of a total free energy functional. Atomic fixed partial charges (point charges) are used in our earlier models, which depends on existing molecular mechanical force field software packages for partial charge assignments. As most force field models are parameterized for a certain class of molecules or materials, the use of partial charges limits the accuracy and applicability of our earlier models. Moreover, fixed partial charges do not account for the charge rearrangement during the solvation process. The present work proposes a differential geometry based multiscale solvation model which makes use of the electron density computed directly from the quantum mechanical principle. To this end, we construct a new multiscale total energy functional which consists of not only polar and nonpolar solvation contributions, but also the electronic kinetic and potential energies. By using the Euler-Lagrange variation, we derive a system of three coupled governing equations, i.e., the generalized Poisson-Boltzmann equation for the electrostatic potential, the generalized Laplace-Beltrami equation for the solvent-solute boundary, and the Kohn-Sham equations for the electronic structure. We develop an iterative procedure to solve three coupled equations and to minimize the solvation free energy. The present multiscale model is numerically validated for its stability, consistency and accuracy, and is applied to a few sets of molecules, including a case which is difficult for existing solvation models. Comparison is made to many other classic and quantum models. By using experimental data, we show that the present quantum formulation of our differential geometry based multiscale solvation model improves the prediction of our earlier models, and outperforms some explicit solvation model. PMID:22112067

Multi-scale lung modeling.

PubMed

Tawhai, Merryn H; Bates, Jason H T

2011-05-01

Multi-scale modeling of biological systems has recently become fashionable due to the growing power of digital computers as well as to the growing realization that integrative systems behavior is as important to life as is the genome. While it is true that the behavior of a living organism must ultimately be traceable to all its components and their myriad interactions, attempting to codify this in its entirety in a model misses the insights gained from understanding how collections of system components at one level of scale conspire to produce qualitatively different behavior at higher levels. The essence of multi-scale modeling thus lies not in the inclusion of every conceivable biological detail, but rather in the judicious selection of emergent phenomena appropriate to the level of scale being modeled. These principles are exemplified in recent computational models of the lung. Airways responsiveness, for example, is an organ-level manifestation of events that begin at the molecular level within airway smooth muscle cells, yet it is not necessary to invoke all these molecular events to accurately describe the contraction dynamics of a cell, nor is it necessary to invoke all phenomena observable at the level of the cell to account for the changes in overall lung function that occur following methacholine challenge. Similarly, the regulation of pulmonary vascular tone has complex origins within the individual smooth muscle cells that line the blood vessels but, again, many of the fine details of cell behavior average out at the level of the organ to produce an effect on pulmonary vascular pressure that can be described in much simpler terms. The art of multi-scale lung modeling thus reduces not to being limitlessly inclusive, but rather to knowing what biological details to leave out.

Multiscale Particle-Based Modeling of Flowing Platelets in Blood Plasma Using Dissipative Particle Dynamics and Coarse Grained Molecular Dynamics

PubMed Central

Zhang, Peng; Gao, Chao; Zhang, Na; Slepian, Marvin J.; Deng, Yuefan; Bluestein, Danny

2014-01-01

We developed a multiscale particle-based model of platelets, to study the transport dynamics of shear stresses between the surrounding fluid and the platelet membrane. This model facilitates a more accurate prediction of the activation potential of platelets by viscous shear stresses - one of the major mechanisms leading to thrombus formation in cardiovascular diseases and in prosthetic cardiovascular devices. The interface of the model couples coarse-grained molecular dynamics (CGMD) with dissipative particle dynamics (DPD). The CGMD handles individual platelets while the DPD models the macroscopic transport of blood plasma in vessels. A hybrid force field is formulated for establishing a functional interface between the platelet membrane and the surrounding fluid, in which the microstructural changes of platelets may respond to the extracellular viscous shear stresses transferred to them. The interaction between the two systems preserves dynamic properties of the flowing platelets, such as the flipping motion. Using this multiscale particle-based approach, we have further studied the effects of the platelet elastic modulus by comparing the action of the flow-induced shear stresses on rigid and deformable platelet models. The results indicate that neglecting the platelet deformability may overestimate the stress on the platelet membrane, which in turn may lead to erroneous predictions of the platelet activation under viscous shear flow conditions. This particle-based fluid-structure interaction multiscale model offers for the first time a computationally feasible approach for simulating deformable platelets interacting with viscous blood flow, aimed at predicting flow induced platelet activation by using a highly resolved mapping of the stress distribution on the platelet membrane under dynamic flow conditions. PMID:25530818

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

American Society of Composites, 32nd Technical Conference

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

Aitharaju, Venkat; Wollschlager, Jeffrey; Plakomytis2, Dimitrios

This paper will present a general methodology by which weave draping manufacturing simulation results can be utilized to include the effects of weave draping and scissor angle in a structural multiscale simulation. While the methodology developed is general in nature, this paper will specifically demonstrate the methodology applied to a truncated pyramid, utilizing manufacturing simulation weave draping results from ESI PAM-FORM, and multiscale simulation using Altair Multiscale Designer (MDS) and OptiStruct. From a multiscale simulation perspective, the weave draping manufacturing simulation results will be used to develop a series of woven unit cells which cover the range of weave scissormore » angles existing within the part. For each unit cell, a multiscale material model will be developed, and applied to the corresponding spatial locations within the structural simulation mesh. In addition, the principal material orientation will be mapped from the wave draping manufacturing simulation mesh to the structural simulation mesh using Altair HyperMesh mapping technology. Results of the coupled simulation will be compared and verified against experimental data of the same available via General Motors (GM) Department of Energy (DOE) project.« less

Research Advances on Radiation Transfer Modeling and Inversion for Multi-Scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.

2011-09-01

At first, research advances on radiation transfer modeling on multi-scale remote sensing data are presented: after a general overview of remote sensing radiation transfer modeling, several recent research advances are presented, including leaf spectrum model (dPROS-PECT), vegetation canopy BRDF models, directional thermal infrared emission models(TRGM, SLEC), rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed. The land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation etc. are taken as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is designed and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China will be introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

Hybrid wavelet-support vector machine approach for modelling rainfall-runoff process.

PubMed

Komasi, Mehdi; Sharghi, Soroush

2016-01-01

Because of the importance of water resources management, the need for accurate modeling of the rainfall-runoff process has rapidly grown in the past decades. Recently, the support vector machine (SVM) approach has been used by hydrologists for rainfall-runoff modeling and the other fields of hydrology. Similar to the other artificial intelligence models, such as artificial neural network (ANN) and adaptive neural fuzzy inference system, the SVM model is based on the autoregressive properties. In this paper, the wavelet analysis was linked to the SVM model concept for modeling the rainfall-runoff process of Aghchai and Eel River watersheds. In this way, the main time series of two variables, rainfall and runoff, were decomposed to multiple frequent time series by wavelet theory; then, these time series were imposed as input data on the SVM model in order to predict the runoff discharge one day ahead. The obtained results show that the wavelet SVM model can predict both short- and long-term runoff discharges by considering the seasonality effects. Also, the proposed hybrid model is relatively more appropriate than classical autoregressive ones such as ANN and SVM because it uses the multi-scale time series of rainfall and runoff data in the modeling process.

Multiscale modelling of hydraulic conductivity in vuggy porous media

PubMed Central

Daly, K. R.; Roose, T.

2014-01-01

Flow in both saturated and non-saturated vuggy porous media, i.e. soil, is inherently multiscale. The complex microporous structure of the soil aggregates and the wider vugs provides a multitude of flow pathways and has received significant attention from the X-ray computed tomography (CT) community with a constant drive to image at higher resolution. Using multiscale homogenization, we derive averaged equations to study the effects of the microscale structure on the macroscopic flow. The averaged model captures the underlying geometry through a series of cell problems and is verified through direct comparison to numerical simulations of the full structure. These methods offer significant reductions in computation time and allow us to perform three-dimensional calculations with complex geometries on a desktop PC. The results show that the surface roughness of the aggregate has a significantly greater effect on the flow than the microstructure within the aggregate. Hence, this is the region in which the resolution of X-ray CT for image-based modelling has the greatest impact. PMID:24511248

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Using CellML with OpenCMISS to Simulate Multi-Scale Physiology

PubMed Central

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

2014-01-01

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

Optimal Multi-scale Demand-side Management for Continuous Power-Intensive Processes

NASA Astrophysics Data System (ADS)

Mitra, Sumit

With the advent of deregulation in electricity markets and an increasing share of intermittent power generation sources, the profitability of industrial consumers that operate power-intensive processes has become directly linked to the variability in energy prices. Thus, for industrial consumers that are able to adjust to the fluctuations, time-sensitive electricity prices (as part of so-called Demand-Side Management (DSM) in the smart grid) offer potential economical incentives. In this thesis, we introduce optimization models and decomposition strategies for the multi-scale Demand-Side Management of continuous power-intensive processes. On an operational level, we derive a mode formulation for scheduling under time-sensitive electricity prices. The formulation is applied to air separation plants and cement plants to minimize the operating cost. We also describe how a mode formulation can be used for industrial combined heat and power plants that are co-located at integrated chemical sites to increase operating profit by adjusting their steam and electricity production according to their inherent flexibility. Furthermore, a robust optimization formulation is developed to address the uncertainty in electricity prices by accounting for correlations and multiple ranges in the realization of the random variables. On a strategic level, we introduce a multi-scale model that provides an understanding of the value of flexibility of the current plant configuration and the value of additional flexibility in terms of retrofits for Demand-Side Management under product demand uncertainty. The integration of multiple time scales leads to large-scale two-stage stochastic programming problems, for which we need to apply decomposition strategies in order to obtain a good solution within a reasonable amount of time. Hence, we describe two decomposition schemes that can be applied to solve two-stage stochastic programming problems: First, a hybrid bi-level decomposition scheme with novel Lagrangean-type and subset-type cuts to strengthen the relaxation. Second, an enhanced cross-decomposition scheme that integrates Benders decomposition and Lagrangean decomposition on a scenario basis. To demonstrate the effectiveness of our developed methodology, we provide several industrial case studies throughout the thesis.

Percolation properties of 3-D multiscale pore networks: how connectivity controls soil filtration processes

NASA Astrophysics Data System (ADS)

Perrier, E. M. A.; Bird, N. R. A.; Rieutord, T. B.

2010-04-01

Quantifying the connectivity of pore networks is a key issue not only for modelling fluid flow and solute transport in porous media but also for assessing the ability of soil ecosystems to filter bacteria, viruses and any type of living microorganisms as well inert particles which pose a contamination risk. Straining is the main mechanical component of filtration processes: it is due to size effects, when a given soil retains a conveyed entity larger than the pores through which it is attempting to pass. We postulate that the range of sizes of entities which can be trapped inside soils has to be associated with the large range of scales involved in natural soil structures and that information on the pore size distribution has to be complemented by information on a Critical Filtration Size (CFS) delimiting the transition between percolating and non percolating regimes in multiscale pore networks. We show that the mass fractal dimensions which are classically used in soil science to quantify scaling laws in observed pore size distributions can also be used to build 3-D multiscale models of pore networks exhibiting such a critical transition. We extend to the 3-D case a new theoretical approach recently developed to address the connectivity of 2-D fractal networks (Bird and Perrier, 2009). Theoretical arguments based on renormalisation functions provide insight into multi-scale connectivity and a first estimation of CFS. Numerical experiments on 3-D prefractal media confirm the qualitative theory. These results open the way towards a new methodology to estimate soil filtration efficiency from the construction of soil structural models to be calibrated on available multiscale data.

Percolation properties of 3-D multiscale pore networks: how connectivity controls soil filtration processes

NASA Astrophysics Data System (ADS)

Perrier, E. M. A.; Bird, N. R. A.; Rieutord, T. B.

2010-10-01

Quantifying the connectivity of pore networks is a key issue not only for modelling fluid flow and solute transport in porous media but also for assessing the ability of soil ecosystems to filter bacteria, viruses and any type of living microorganisms as well inert particles which pose a contamination risk. Straining is the main mechanical component of filtration processes: it is due to size effects, when a given soil retains a conveyed entity larger than the pores through which it is attempting to pass. We postulate that the range of sizes of entities which can be trapped inside soils has to be associated with the large range of scales involved in natural soil structures and that information on the pore size distribution has to be complemented by information on a critical filtration size (CFS) delimiting the transition between percolating and non percolating regimes in multiscale pore networks. We show that the mass fractal dimensions which are classically used in soil science to quantify scaling laws in observed pore size distributions can also be used to build 3-D multiscale models of pore networks exhibiting such a critical transition. We extend to the 3-D case a new theoretical approach recently developed to address the connectivity of 2-D fractal networks (Bird and Perrier, 2009). Theoretical arguments based on renormalisation functions provide insight into multi-scale connectivity and a first estimation of CFS. Numerical experiments on 3-D prefractal media confirm the qualitative theory. These results open the way towards a new methodology to estimate soil filtration efficiency from the construction of soil structural models to be calibrated on available multiscale data.

Multi-scale Modeling of the Impact Response of a Strain Rate Sensitive High-Manganese Austenitic Steel

NASA Astrophysics Data System (ADS)

Önal, Orkun; Ozmenci, Cemre; Canadinc, Demircan

2014-09-01

A multi-scale modeling approach was applied to predict the impact response of a strain rate sensitive high-manganese austenitic steel. The roles of texture, geometry and strain rate sensitivity were successfully taken into account all at once by coupling crystal plasticity and finite element (FE) analysis. Specifically, crystal plasticity was utilized to obtain the multi-axial flow rule at different strain rates based on the experimental deformation response under uniaxial tensile loading. The equivalent stress - equivalent strain response was then incorporated into the FE model for the sake of a more representative hardening rule under impact loading. The current results demonstrate that reliable predictions can be obtained by proper coupling of crystal plasticity and FE analysis even if the experimental flow rule of the material is acquired under uniaxial loading and at moderate strain rates that are significantly slower than those attained during impact loading. Furthermore, the current findings also demonstrate the need for an experiment-based multi-scale modeling approach for the sake of reliable predictions of the impact response.

Top down and bottom up engineering of bone.

PubMed

Knothe Tate, Melissa L

2011-01-11

The goal of this retrospective article is to place the body of my lab's multiscale mechanobiology work in context of top-down and bottom-up engineering of bone. We have used biosystems engineering, computational modeling and novel experimental approaches to understand bone physiology, in health and disease, and across time (in utero, postnatal growth, maturity, aging and death, as well as evolution) and length scales (a single bone like a femur, m; a sample of bone tissue, mm-cm; a cell and its local environment, μm; down to the length scale of the cell's own skeleton, the cytoskeleton, nm). First we introduce the concept of flow in bone and the three calibers of porosity through which fluid flows. Then we describe, in the context of organ-tissue, tissue-cell and cell-molecule length scales, both multiscale computational models and experimental methods to predict flow in bone and to understand the flow of fluid as a means to deliver chemical and mechanical cues in bone. Addressing a number of studies in the context of multiple length and time scales, the importance of appropriate boundary conditions, site specific material parameters, permeability measures and even micro-nanoanatomically correct geometries are discussed in context of model predictions and their value for understanding multiscale mechanobiology of bone. Insights from these multiscale computational modeling and experimental methods are providing us with a means to predict, engineer and manufacture bone tissue in the laboratory and in the human body. Copyright © 2010 Elsevier Ltd. All rights reserved.

Development of a Stochastically-driven, Forward Predictive Performance Model for PEMFCs

NASA Astrophysics Data System (ADS)

Harvey, David Benjamin Paul

A one-dimensional multi-scale coupled, transient, and mechanistic performance model for a PEMFC membrane electrode assembly has been developed. The model explicitly includes each of the 5 layers within a membrane electrode assembly and solves for the transport of charge, heat, mass, species, dissolved water, and liquid water. Key features of the model include the use of a multi-step implementation of the HOR reaction on the anode, agglomerate catalyst sub-models for both the anode and cathode catalyst layers, a unique approach that links the composition of the catalyst layer to key properties within the agglomerate model and the implementation of a stochastic input-based approach for component material properties. The model employs a new methodology for validation using statistically varying input parameters and statistically-based experimental performance data; this model represents the first stochastic input driven unit cell performance model. The stochastic input driven performance model was used to identify optimal ionomer content within the cathode catalyst layer, demonstrate the role of material variation in potential low performing MEA materials, provide explanation for the performance of low-Pt loaded MEAs, and investigate the validity of transient-sweep experimental diagnostic methods.

Virtual Patients and Sensitivity Analysis of the Guyton Model of Blood Pressure Regulation: Towards Individualized Models of Whole-Body Physiology

PubMed Central

Moss, Robert; Grosse, Thibault; Marchant, Ivanny; Lassau, Nathalie; Gueyffier, François; Thomas, S. Randall

2012-01-01

Mathematical models that integrate multi-scale physiological data can offer insight into physiological and pathophysiological function, and may eventually assist in individualized predictive medicine. We present a methodology for performing systematic analyses of multi-parameter interactions in such complex, multi-scale models. Human physiology models are often based on or inspired by Arthur Guyton's whole-body circulatory regulation model. Despite the significance of this model, it has not been the subject of a systematic and comprehensive sensitivity study. Therefore, we use this model as a case study for our methodology. Our analysis of the Guyton model reveals how the multitude of model parameters combine to affect the model dynamics, and how interesting combinations of parameters may be identified. It also includes a “virtual population” from which “virtual individuals” can be chosen, on the basis of exhibiting conditions similar to those of a real-world patient. This lays the groundwork for using the Guyton model for in silico exploration of pathophysiological states and treatment strategies. The results presented here illustrate several potential uses for the entire dataset of sensitivity results and the “virtual individuals” that we have generated, which are included in the supplementary material. More generally, the presented methodology is applicable to modern, more complex multi-scale physiological models. PMID:22761561

A Micromechanics-Based Method for Multiscale Fatigue Prediction

NASA Astrophysics Data System (ADS)

Moore, John Allan

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

Determining the multi-scale hedge ratios of stock index futures using the lower partial moments method

NASA Astrophysics Data System (ADS)

Dai, Jun; Zhou, Haigang; Zhao, Shaoquan

2017-01-01

This paper considers a multi-scale future hedge strategy that minimizes lower partial moments (LPM). To do this, wavelet analysis is adopted to decompose time series data into different components. Next, different parametric estimation methods with known distributions are applied to calculate the LPM of hedged portfolios, which is the key to determining multi-scale hedge ratios over different time scales. Then these parametric methods are compared with the prevailing nonparametric kernel metric method. Empirical results indicate that in the China Securities Index 300 (CSI 300) index futures and spot markets, hedge ratios and hedge efficiency estimated by the nonparametric kernel metric method are inferior to those estimated by parametric hedging model based on the features of sequence distributions. In addition, if minimum-LPM is selected as a hedge target, the hedging periods, degree of risk aversion, and target returns can affect the multi-scale hedge ratios and hedge efficiency, respectively.

Computer Laboratory for Multi-scale Simulations of Novel Nanomaterials

DTIC Science & Technology

2014-09-15

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

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

NASA Astrophysics Data System (ADS)

Belgasam, Tarek M.; Zbib, Hussein M.

2018-06-01

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

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

NASA Astrophysics Data System (ADS)

Belgasam, Tarek M.; Zbib, Hussein M.

2018-03-01

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

Asymptotic Expansion Homogenization for Multiscale Nuclear Fuel Analysis

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

Hales, J. D.; Tonks, M. R.; Chockalingam, K.

2015-03-01

Engineering scale nuclear fuel performance simulations can benefit by utilizing high-fidelity models running at a lower length scale. Lower length-scale models provide a detailed view of the material behavior that is used to determine the average material response at the macroscale. These lower length-scale calculations may provide insight into material behavior where experimental data is sparse or nonexistent. This multiscale approach is especially useful in the nuclear field, since irradiation experiments are difficult and expensive to conduct. The lower length-scale models complement the experiments by influencing the types of experiments required and by reducing the total number of experiments needed.more » This multiscale modeling approach is a central motivation in the development of the BISON-MARMOT fuel performance codes at Idaho National Laboratory. These codes seek to provide more accurate and predictive solutions for nuclear fuel behavior. One critical aspect of multiscale modeling is the ability to extract the relevant information from the lower length-scale sim- ulations. One approach, the asymptotic expansion homogenization (AEH) technique, has proven to be an effective method for determining homogenized material parameters. The AEH technique prescribes a system of equations to solve at the microscale that are used to compute homogenized material constants for use at the engineering scale. In this work, we employ AEH to explore the effect of evolving microstructural thermal conductivity and elastic constants on nuclear fuel performance. We show that the AEH approach fits cleanly into the BISON and MARMOT codes and provides a natural, multidimensional homogenization capability.« less

Automatic event detection in low SNR microseismic signals based on multi-scale permutation entropy and a support vector machine

NASA Astrophysics Data System (ADS)

Jia, Rui-Sheng; Sun, Hong-Mei; Peng, Yan-Jun; Liang, Yong-Quan; Lu, Xin-Ming

2017-07-01

Microseismic monitoring is an effective means for providing early warning of rock or coal dynamical disasters, and its first step is microseismic event detection, although low SNR microseismic signals often cannot effectively be detected by routine methods. To solve this problem, this paper presents permutation entropy and a support vector machine to detect low SNR microseismic events. First, an extraction method of signal features based on multi-scale permutation entropy is proposed by studying the influence of the scale factor on the signal permutation entropy. Second, the detection model of low SNR microseismic events based on the least squares support vector machine is built by performing a multi-scale permutation entropy calculation for the collected vibration signals, constructing a feature vector set of signals. Finally, a comparative analysis of the microseismic events and noise signals in the experiment proves that the different characteristics of the two can be fully expressed by using multi-scale permutation entropy. The detection model of microseismic events combined with the support vector machine, which has the features of high classification accuracy and fast real-time algorithms, can meet the requirements of online, real-time extractions of microseismic events.

Multiscale methods for gore curvature calculations from FSI modeling of spacecraft parachutes

NASA Astrophysics Data System (ADS)

Takizawa, Kenji; Tezduyar, Tayfun E.; Kolesar, Ryan; Boswell, Cody; Kanai, Taro; Montel, Kenneth

2014-12-01

There are now some sophisticated and powerful methods for computer modeling of parachutes. These methods are capable of addressing some of the most formidable computational challenges encountered in parachute modeling, including fluid-structure interaction (FSI) between the parachute and air flow, design complexities such as those seen in spacecraft parachutes, and operational complexities such as use in clusters and disreefing. One should be able to extract from a reliable full-scale parachute modeling any data or analysis needed. In some cases, however, the parachute engineers may want to perform quickly an extended or repetitive analysis with methods based on simplified models. Some of the data needed by a simplified model can very effectively be extracted from a full-scale computer modeling that serves as a pilot. A good example of such data is the circumferential curvature of a parachute gore, where a gore is the slice of the parachute canopy between two radial reinforcement cables running from the parachute vent to the skirt. We present the multiscale methods we devised for gore curvature calculation from FSI modeling of spacecraft parachutes. The methods include those based on the multiscale sequentially-coupled FSI technique and using NURBS meshes. We show how the methods work for the fully-open and two reefed stages of the Orion spacecraft main and drogue parachutes.

Adaptive Multiscale Modeling of Geochemical Impacts on Fracture Evolution

NASA Astrophysics Data System (ADS)

Molins, S.; Trebotich, D.; Steefel, C. I.; Deng, H.

2016-12-01

Understanding fracture evolution is essential for many subsurface energy applications, including subsurface storage, shale gas production, fracking, CO2 sequestration, and geothermal energy extraction. Geochemical processes in particular play a significant role in the evolution of fractures through dissolution-driven widening, fines migration, and/or fracture sealing due to precipitation. One obstacle to understanding and exploiting geochemical fracture evolution is that it is a multiscale process. However, current geochemical modeling of fractures cannot capture this multi-scale nature of geochemical and mechanical impacts on fracture evolution, and is limited to either a continuum or pore-scale representation. Conventional continuum-scale models treat fractures as preferential flow paths, with their permeability evolving as a function (often, a cubic law) of the fracture aperture. This approach has the limitation that it oversimplifies flow within the fracture in its omission of pore scale effects while also assuming well-mixed conditions. More recently, pore-scale models along with advanced characterization techniques have allowed for accurate simulations of flow and reactive transport within the pore space (Molins et al., 2014, 2015). However, these models, even with high performance computing, are currently limited in their ability to treat tractable domain sizes (Steefel et al., 2013). Thus, there is a critical need to develop an adaptive modeling capability that can account for separate properties and processes, emergent and otherwise, in the fracture and the rock matrix at different spatial scales. Here we present an adaptive modeling capability that treats geochemical impacts on fracture evolution within a single multiscale framework. Model development makes use of the high performance simulation capability, Chombo-Crunch, leveraged by high resolution characterization and experiments. The modeling framework is based on the adaptive capability in Chombo which not only enables mesh refinement, but also refinement of the model-pore scale or continuum Darcy scale-in a dynamic way such that the appropriate model is used only when and where it is needed. Explicit flux matching provides coupling betwen the scales.

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.

From single muscle fiber to whole muscle mechanics: a finite element model of a muscle bundle with fast and slow fibers.

PubMed

Marcucci, Lorenzo; Reggiani, Carlo; Natali, Arturo N; Pavan, Piero G

2017-12-01

Muscles exhibit highly complex, multi-scale architecture with thousands of muscle fibers, each with different properties, interacting with each other and surrounding connective structures. Consequently, the results of single-fiber experiments are scarcely linked to the macroscopic or whole muscle behavior. This is especially true for human muscles where it would be important to understand of how skeletal muscles disorders affect patients' life. In this work, we developed a mathematical model to study how fast and slow muscle fibers, well characterized in single-fiber experiments, work and generate together force and displacement in muscle bundles. We characterized the parameters of a Hill-type model, using experimental data on fast and slow single human muscle fibers, and comparing experimental data with numerical simulations obtained from finite element (FE) models of single fibers. Then, we developed a FE model of a bundle of 19 fibers, based on an immunohistochemically stained cross section of human diaphragm and including the corresponding properties of each slow or fast fiber. Simulations of isotonic contractions of the bundle model allowed the generation of its apparent force-velocity relationship. Although close to the average of the force-velocity curves of fast and slow fibers, the bundle curve deviates substantially toward the fast fibers at low loads. We believe that the present model and the characterization of the force-velocity curve of a fiber bundle represents the starting point to link the single-fiber properties to those of whole muscle with FE application in phenomenological models of human muscles.

Wavelet-based multiscale adjoint waveform-difference tomography using body and surface waves

NASA Astrophysics Data System (ADS)

Yuan, Y. O.; Simons, F. J.; Bozdag, E.

2014-12-01

We present a multi-scale scheme for full elastic waveform-difference inversion. Using a wavelet transform proves to be a key factor to mitigate cycle-skipping effects. We start with coarse representations of the seismogram to correct a large-scale background model, and subsequently explain the residuals in the fine scales of the seismogram to map the heterogeneities with great complexity. We have previously applied the multi-scale approach successfully to body waves generated in a standard model from the exploration industry: a modified two-dimensional elastic Marmousi model. With this model we explored the optimal choice of wavelet family, number of vanishing moments and decomposition depth. For this presentation we explore the sensitivity of surface waves in waveform-difference tomography. The incorporation of surface waves is rife with cycle-skipping problems compared to the inversions considering body waves only. We implemented an envelope-based objective function probed via a multi-scale wavelet analysis to measure the distance between predicted and target surface-wave waveforms in a synthetic model of heterogeneous near-surface structure. Our proposed method successfully purges the local minima present in the waveform-difference misfit surface. An elastic shallow model with 100~m in depth is used to test the surface-wave inversion scheme. We also analyzed the sensitivities of surface waves and body waves in full waveform inversions, as well as the effects of incorrect density information on elastic parameter inversions. Based on those numerical experiments, we ultimately formalized a flexible scheme to consider both body and surface waves in adjoint tomography. While our early examples are constructed from exploration-style settings, our procedure will be very valuable for the study of global network data.