NASA Astrophysics Data System (ADS)
Shen, Li; Wu, Linmei; Li, Zhipeng
2016-06-01
Multiscale segmentation is a key prerequisite step for object-based classification methods. However, it is often not possible to determine a sole optimal scale for the image to be classified because in many cases different geo-objects and even an identical geo-object may appear at different scales in one image. In this paper, an object-based classification method based on mutliscale segmentation results in the framework of topic modelling is proposed to classify VHR satellite images in an entirely unsupervised fashion. In the stage of topic modelling, grayscale histogram distributions for each geo-object class and each segment are learned in an unsupervised manner from multiscale segments. In the stage of classification, each segment is allocated a geo-object class label by the similarity comparison between the grayscale histogram distributions of each segment and each geo-object class. Experimental results show that the proposed method can perform better than the traditional methods based on topic modelling.
Lin, Ching-Long; Tawhai, Merryn H; Hoffman, Eric A
2013-01-01
Improved understanding of structure and function relationships in the human lungs in individuals and subpopulations is fundamentally important to the future of pulmonary medicine. Image-based measures of the lungs can provide sensitive indicators of localized features, however to provide a better prediction of lung response to disease, treatment, and environment, it is desirable to integrate quantifiable regional features from imaging with associated value-added high-level modeling. With this objective in mind, recent advances in computational fluid dynamics (CFD) of the bronchial airways-from a single bifurcation symmetric model to a multiscale image-based subject-specific lung model-will be reviewed. The interaction of CFD models with local parenchymal tissue expansion-assessed by image registration-allows new understanding of the interplay between environment, hot spots where inhaled aerosols could accumulate, and inflammation. To bridge ventilation function with image-derived central airway structure in CFD, an airway geometrical modeling method that spans from the model 'entrance' to the terminal bronchioles will be introduced. Finally, the effects of turbulent flows and CFD turbulence models on aerosol transport and deposition will be discussed.
A multiscale MDCT image-based breathing lung model with time-varying regional ventilation
Yin, Youbing; Choi, Jiwoong; Hoffman, Eric A.; Tawhai, Merryn H.; Lin, Ching-Long
2013-07-01
A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C{sub 1} continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.
A multiscale MDCT image-based breathing lung model with time-varying regional ventilation
NASA Astrophysics Data System (ADS)
Yin, Youbing; Choi, Jiwoong; Hoffman, Eric A.; Tawhai, Merryn H.; Lin, Ching-Long
2013-07-01
A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C1 continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.
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.
Sander, Edward A.; Stylianopoulos, Triantafyllos; Tranquillo, Robert T.; Barocas, Victor H.
2009-01-01
The mechanical environment plays an important role in cell signaling and tissue homeostasis. Unraveling connections between externally applied loads and the cellular response is often confounded by extracellular matrix (ECM) heterogeneity. Image-based multiscale models provide a foundation for examining the fine details of tissue behavior, but they require validation at multiple scales. In this study, we developed a multiscale model that captured the anisotropy and heterogeneity of a cell-compacted collagen gel subjected to an off-axis hold mechanical test and subsequently to biaxial extension. In both the model and experiments, the ECM reorganized in a nonaffine and heterogeneous manner that depended on multiscale interactions between the fiber networks. Simulations predicted that tensile and compressive fiber forces were produced to accommodate macroscopic displacements. Fiber forces in the simulation ranged from −11.3 to 437.7 nN, with a significant fraction of fibers under compression (12.1% during off-axis stretch). The heterogeneous network restructuring predicted by the model serves as an example of how multiscale modeling techniques provide a theoretical framework for understanding relationships between ECM structure and tissue-level mechanical properties and how microscopic fiber rearrangements could lead to mechanotransductive cell signaling. PMID:19805118
Image-based multi-scale modelling and validation of radio-frequency ablation in liver tumours.
Payne, Stephen; Flanagan, Ronan; Pollari, Mika; Alhonnoro, Tuomas; Bost, Claire; O'Neill, David; Peng, Tingying; Stiegler, Philipp
2011-11-13
The treatment of cancerous tumours in the liver remains clinically challenging, despite the wide range of treatment possibilities, including radio-frequency ablation (RFA), high-intensity focused ultrasound and resection, which are currently available. Each has its own advantages and disadvantages. For non- or minimally invasive modalities, such as RFA, considered here, it is difficult to monitor the treatment in vivo. This is particularly problematic in the liver, where large blood vessels act as heat sinks, dissipating delivered heat and shrinking the size of the lesion (the volume damaged by the heat treatment) locally; considerable experience is needed on the part of the clinician to optimize the heat treatment to prevent recurrence. In this paper, we outline our work towards developing a simulation tool kit that could be used both to optimize treatment protocols in advance and to train the less-experienced clinicians for RFA treatment of liver tumours. This tool is based on a comprehensive mathematical model of bio-heat transfer and cell death. We show how simulations of ablations in two pigs, based on individualized imaging data, compare directly with experimentally measured lesion sizes and discuss the likely sources of error and routes towards clinical implementation. This is the first time that such a 'loop' of mathematical modelling and experimental validation in vivo has been performed in this context, and such validation enables us to make quantitative estimates of error.
Change detection in high resolution SAR images based on multiscale texture features
NASA Astrophysics Data System (ADS)
Wen, Caihuan; Gao, Ziqiang
2011-12-01
This paper studied on change detection algorithm of high resolution (HR) Synthetic Aperture Radar (SAR) images based on multi-scale texture features. Firstly, preprocessed multi-temporal Terra-SAR images were decomposed by 2-D dual tree complex wavelet transform (DT-CWT), and multi-scale texture features were extracted from those images. Then, log-ratio operation was utilized to get difference images, and the Bayes minimum error theory was used to extract change information from difference images. Lastly, precision assessment was done. Meanwhile, we compared with the result of method based on texture features extracted from gray-level cooccurrence matrix (GLCM). We had a conclusion that, change detection algorithm based on multi-scale texture features has a great more improvement, which proves an effective method to change detect of high spatial resolution SAR images.
Guo, Xingye; Hu, Bin; Wei, Changdong; Sun, Jiangang; Jung, Yeon-Gil; Li, Li; Knapp, James; Zhang, Jing
2016-09-01
Lanthanum zirconate (La2Zr2O7) is a promising candidate material for thermal barrier coating (TBC) applications due to its low thermal conductivity and high-temperature phase stability. In this work, a novel image-based multi-scale simulation framework combining molecular dynamics (MD) and finite element (FE) calculations is proposed to study the thermal conductivity of La2Zr2O7 coatings. Since there is no experimental data of single crystal La2Zr2O7 thermal conductivity, a reverse non-equilibrium molecular dynamics (reverse NEMD) approach is first employed to compute the temperature-dependent thermal conductivity of single crystal La2Zr2O7. The single crystal data is then passed to a FE model which takes into account of realistic thermal barrier coating microstructures. The predicted thermal conductivities from the FE model are in good agreement with experimental validations using both flash laser technique and pulsed thermal imaging-multilayer analysis. The framework proposed in this work provides a powerful tool for future design of advanced coating systems. (C) 2016 Elsevier Ltd. All rights reserved.
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.
Multiscale modeling of proteins.
Tozzini, Valentina
2010-02-16
The activity within a living cell is based on a complex network of interactions among biomolecules, exchanging information and energy through biochemical processes. These events occur on different scales, from the nano- to the macroscale, spanning about 10 orders of magnitude in the space domain and 15 orders of magnitude in the time domain. Consequently, many different modeling techniques, each proper for a particular time or space scale, are commonly used. In addition, a single process often spans more than a single time or space scale. Thus, the necessity arises for combining the modeling techniques in multiscale approaches. In this Account, I first review the different modeling methods for bio-systems, from quantum mechanics to the coarse-grained and continuum-like descriptions, passing through the atomistic force field simulations. Special attention is devoted to their combination in different possible multiscale approaches and to the questions and problems related to their coherent matching in the space and time domains. These aspects are often considered secondary, but in fact, they have primary relevance when the aim is the coherent and complete description of bioprocesses. Subsequently, applications are illustrated by means of two paradigmatic examples: (i) the green fluorescent protein (GFP) family and (ii) the proteins involved in the human immunodeficiency virus (HIV) replication cycle. The GFPs are currently one of the most frequently used markers for monitoring protein trafficking within living cells; nanobiotechnology and cell biology strongly rely on their use in fluorescence microscopy techniques. A detailed knowledge of the actions of the virus-specific enzymes of HIV (specifically HIV protease and integrase) is necessary to study novel therapeutic strategies against this disease. Thus, the insight accumulated over years of intense study is an excellent framework for this Account. The foremost relevance of these two biomolecular systems was
MULTISCALE THERMOHYDROLOGIC MODEL
T.A. Buscheck
2001-12-21
The purpose of the Multiscale Thermohydrologic Model (MSTHM) is to describe the thermohydrologic evolution of the near-field environment (NFE) and engineered barrier system (EBS) throughout the potential high-level nuclear waste repository at Yucca Mountain for a particular engineering design (CRWMS M&O 2000c). The process-level model will provide thermohydrologic (TH) information and data (such as in-drift temperature, relative humidity, liquid saturation, etc.) for use in other technical products. This data is provided throughout the entire repository area as a function of time. The MSTHM couples the Smeared-heat-source Drift-scale Thermal-conduction (SDT), Line-average-heat-source Drift-scale Thermohydrologic (LDTH), Discrete-heat-source Drift-scale Thermal-conduction (DDT), and Smeared-heat-source Mountain-scale Thermal-conduction (SMT) submodels such that the flow of water and water vapor through partially-saturated fractured rock is considered. The MSTHM accounts for 3-D drift-scale and mountain-scale heat flow, repository-scale variability of stratigraphy and infiltration flux, and waste package (WP)-to-WP variability in heat output from WPs. All submodels use the nonisothermal unsaturated-saturated flow and transport (NUFT) simulation code. The MSTHM is implemented in several data-processing steps. The four major steps are: (1) submodel input-file preparation, (2) execution of the four submodel families with the use of the NUFT code, (3) execution of the multiscale thermohydrologic abstraction code (MSTHAC), and (4) binning and post-processing (i.e., graphics preparation) of the output from MSTHAC. Section 6 describes the MSTHM in detail. The objectives of this Analyses and Model Report (AMR) are to investigate near field (NF) and EBS thermohydrologic environments throughout the repository area at various evolution periods, and to provide TH data that may be used in other process model reports.
Multiscale Thermohydrologic Model
T. Buscheck
2004-10-12
The purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. Thus, the goal is to predict the range of possible thermal-hydrologic conditions across the repository; this is quite different from predicting a single expected thermal-hydrologic response. The MSTHM calculates the following thermal-hydrologic parameters: temperature, relative humidity, liquid-phase saturation, evaporation rate, air-mass fraction, gas-phase pressure, capillary pressure, and liquid- and gas-phase fluxes (Table 1-1). These thermal-hydrologic parameters are required to support ''Total System Performance Assessment (TSPA) Model/Analysis for the License Application'' (BSC 2004 [DIRS 168504]). The thermal-hydrologic parameters are determined as a function of position along each of the emplacement drifts and as a function of waste package type. These parameters are determined at various reference locations within the emplacement drifts, including the waste package and drip-shield surfaces and in the invert. The parameters are also determined at various defined locations in the adjoining host rock. The MSTHM uses data obtained from the data tracking numbers (DTNs) listed in Table 4.1-1. The majority of those DTNs were generated from the following analyses and model reports: (1) ''UZ Flow Model and Submodels'' (BSC 2004 [DIRS 169861]); (2) ''Development of Numerical Grids for UZ Flow and Transport Modeling'' (BSC 2004); (3) ''Calibrated Properties Model'' (BSC 2004 [DIRS 169857]); (4) ''Thermal Conductivity of the Potential Repository Horizon'' (BSC 2004 [DIRS 169854]); (5) ''Thermal Conductivity of the Non-Repository Lithostratigraphic Layers'' (BSC 2004 [DIRS 170033]); (6) ''Ventilation Model and Analysis Report'' (BSC 2004 [DIRS 169862]); (7) ''Heat Capacity
NASA Astrophysics Data System (ADS)
Arshadi, Amir
Image-based simulation of complex materials is a very important tool for understanding their mechanical behavior and an effective tool for successful design of composite materials. In this thesis an image-based multi-scale finite element approach is developed to predict the mechanical properties of asphalt mixtures. In this approach the "up-scaling" and homogenization of each scale to the next is critically designed to improve accuracy. In addition to this multi-scale efficiency, this study introduces an approach for consideration of particle contacts at each of the scales in which mineral particles exist. One of the most important pavement distresses which seriously affects the pavement performance is fatigue cracking. As this cracking generally takes place in the binder phase of the asphalt mixture, the binder fatigue behavior is assumed to be one of the main factors influencing the overall pavement fatigue performance. It is also known that aggregate gradation, mixture volumetric properties, and filler type and concentration can affect damage initiation and progression in the asphalt mixtures. This study was conducted to develop a tool to characterize the damage properties of the asphalt mixtures at all scales. In the present study the Viscoelastic continuum damage model is implemented into the well-known finite element software ABAQUS via the user material subroutine (UMAT) in order to simulate the state of damage in the binder phase under the repeated uniaxial sinusoidal loading. The inputs are based on the experimentally derived measurements for the binder properties. For the scales of mastic and mortar, the artificially 2-Dimensional images of mastic and mortar scales were generated and used to characterize the properties of those scales. Finally, the 2D scanned images of asphalt mixtures are used to study the asphalt mixture fatigue behavior under loading. In order to validate the proposed model, the experimental test results and the simulation results were
MULTISCALE THERMOHYDROLOGIC MODEL
T. Buscheck
2005-07-07
The intended purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. The goal of the MSTHM is to predict a reasonable range of possible thermal-hydrologic conditions within the emplacement drift. To be reasonable, this range includes the influence of waste-package-to-waste-package heat output variability relevant to the license application design, as well as the influence of uncertainty and variability in the geologic and hydrologic conditions relevant to predicting the thermal-hydrologic response in emplacement drifts. This goal is quite different from the goal of a model to predict a single expected thermal-hydrologic response. As a result, the development and validation of the MSTHM and the associated analyses using this model are focused on the goal of predicting a reasonable range of thermal-hydrologic conditions resulting from parametric uncertainty and waste-package-to-waste-package heat-output variability. Thermal-hydrologic conditions within emplacement drifts depend primarily on thermal-hydrologic conditions in the host rock at the drift wall and on the temperature difference between the drift wall and the drip-shield and waste-package surfaces. Thus, the ability to predict a reasonable range of relevant in-drift MSTHM output parameters (e.g., temperature and relative humidity) is based on valid predictions of thermal-hydrologic processes in the host rock, as well as valid predictions of heat-transfer processes between the drift wall and the drip-shield and waste-package surfaces. Because the invert contains crushed gravel derived from the host rock, the invert is, in effect, an extension of the host rock, with thermal and hydrologic properties that have been modified by virtue of the crushing (and the resulting
Multiscale modeling methods in biomechanics.
Bhattacharya, Pinaki; Viceconti, Marco
2017-01-19
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. For further resources related to this article, please visit the WIREs website.
Image-based modelling of organogenesis.
Iber, Dagmar; Karimaddini, Zahra; Ünal, Erkan
2016-07-01
One of the major challenges in biology concerns the integration of data across length and time scales into a consistent framework: how do macroscopic properties and functionalities arise from the molecular regulatory networks-and how can they change as a result of mutations? Morphogenesis provides an excellent model system to study how simple molecular networks robustly control complex processes on the macroscopic scale despite molecular noise, and how important functional variants can emerge from small genetic changes. Recent advancements in three-dimensional imaging technologies, computer algorithms and computer power now allow us to develop and analyse increasingly realistic models of biological control. Here, we present our pipeline for image-based modelling that includes the segmentation of images, the determination of displacement fields and the solution of systems of partial differential equations on the growing, embryonic domains. The development of suitable mathematical models, the data-based inference of parameter sets and the evaluation of competing models are still challenging, and current approaches are discussed.
Differential Geometry Based Multiscale Models
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
Differential geometry based multiscale models.
Wei, Guo-Wei
2010-08-01
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 atomistic 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
2014-12-01
Dimensional Haversian System Structure ............................. 48 2. Layered Composite Model...concentric layers forms an osteon, or Haversian system , and is the representative subunit of cortical bone [5]. They contain a Haversian canal, which...skeletal system , HA serves as the storage site for ions [16]. HA is responsible for 99%, 90%, 90% and 50% of the body’s store of calcium, phosphorus
Multiscale modelling of DNA mechanics
NASA Astrophysics Data System (ADS)
Dršata, Tomáš; Lankaš, Filip
2015-08-01
Mechanical properties of DNA are important not only in a wide range of biological processes but also in the emerging field of DNA nanotechnology. We review some of the recent developments in modeling these properties, emphasizing the multiscale nature of the problem. Modern atomic resolution, explicit solvent molecular dynamics simulations have contributed to our understanding of DNA fine structure and conformational polymorphism. These simulations may serve as data sources to parameterize rigid base models which themselves have undergone major development. A consistent buildup of larger entities involving multiple rigid bases enables us to describe DNA at more global scales. Free energy methods to impose large strains on DNA, as well as bead models and other approaches, are also briefly discussed.
Towards a Multiscale Approach to Cybersecurity Modeling
Hogan, Emilie A.; Hui, Peter SY; Choudhury, Sutanay; Halappanavar, Mahantesh; Oler, Kiri J.; Joslyn, Cliff A.
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 of 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.
MULTISCALE MODELING OF POLYMER NANOCOMPOSITES
Maiti, A
2007-07-16
Polymer Nanocomposites are an important class of nanomaterials with potential applications including but not limited to structural and cushion materials, electromagnetic and heat shields, conducting plastics, sensors, and catalysts for various chemical and bio processes. Success in most such applications hinges on molecular-level control of structure and assembly, and a deep understanding of how the overall morphology of various components and the interfaces between them affect the composite properties at the macroscale. The length and time-scales associated with such assemblies are prohibitively large for a full atomistic modeling. Instead we adopt a multiscale methodology in which atomic-level interactions between different components of a composite are incorporated into a coarse-grained simulation of the mesoscale morphology, which is then represented on a numerical grid and the macroscopic properties computed using a finite-elements method.
Multiscale Modeling of Hematologic Disorders
Fedosov, Dmitry A.; Pivkin, Igor; Pan, Wenxiao; Dao, Ming; Caswell, Bruce; Karniadakis, George E.
2012-01-28
Parasitic infectious diseases and other hereditary hematologic disorders are often associated with major changes in the shape and viscoelastic properties of red blood cells (RBCs). Such changes can disrupt blood flow and even brain perfusion, as in the case of cerebral malaria. Modeling of these hematologic disorders requires a seamless multiscale approach, where blood cells and blood flow in the entire arterial tree are represented accurately using physiologically consistent parameters. In this chapter, we present a computational methodology based on dissipative particle dynamics (DPD) which models RBCs as well as whole blood in health and disease. DPD is a Lagrangian method that can be derived from systematic coarse-graining of molecular dynamics but can scale efficiently up to small arteries and can also be used to model RBCs down to spectrin level. To this end, we present two complementary mathematical models for RBCs and describe a systematic procedure on extracting the relevant input parameters from optical tweezers and microfluidic experiments for single RBCs. We then use these validated RBC models to predict the behavior of whole healthy blood and compare with experimental results. The same procedure is applied to modeling malaria, and results for infected single RBCs and whole blood are presented.
Efficient postprocessing scheme for block-coded images based on multiscale edge detection
NASA Astrophysics Data System (ADS)
Wu, Shuanhu; Yan, Hong; Tan, Zheng
2001-09-01
The block discrete cosine transform (BDCT) is the most widely used technique for the compression of both still and moving images, a major problem related with the BDCT techniques is that the decoded images, especially at low bit rate, exhibit visually annoying blocking effects. In this paper, based on Mallets multiscale edge detection, we proposed an efficient deblocking algorithm to further improved the coding performance. The advantage of our algorithm is that it can efficiently preserve texture structure in the original decompressed images. Our method is similar to that of Z. Xiong's, where the Z.Xiong's method is not suitable for images with a large portion of texture; for instance, the Barbara Image. The difference of our method and the Z.Xiong's is that our method adopted a new thresholding scheme for multi-scale edge detection instead of exploiting cross-scale correlation for edge detection. Numerical experiment results show that our scheme not only outperforms Z.Xiong's for various images in the case of the same computational complexity, but also preserve texture structure in the decompressed images at the same time. Compared with the best iterative-based method (POCS) reported in the literature, our algorithm can achieve the same peak signal-to-noise ratio (PSNR) improvement and give visually very pleasing images as well.
A framework for multi-scale modelling
Chopard, B.; Borgdorff, Joris; Hoekstra, A. G.
2014-01-01
We review a methodology to design, implement and execute multi-scale and multi-science numerical simulations. We identify important ingredients of multi-scale modelling and give a precise definition of them. Our framework assumes that a multi-scale model can be formulated in terms of a collection of coupled single-scale submodels. With concepts such as the scale separation map, the generic submodel execution loop (SEL) and the coupling templates, one can define a multi-scale modelling language which is a bridge between the application design and the computer implementation. Our approach has been successfully applied to an increasing number of applications from different fields of science and technology. PMID:24982249
Feature and contrast enhancement of mammographic image based on multiscale analysis and morphology.
Wu, Shibin; Yu, Shaode; Yang, Yuhan; Xie, Yaoqin
2013-01-01
A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE) and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by contrast limited adaptive histogram equalization and mathematical morphology, respectively. The enhanced image is processed by global nonlinear operator. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is measured by contrast evaluation criterion for image, signal-noise-ratio (SNR), and contrast improvement index (CII).
Feature and Contrast Enhancement of Mammographic Image Based on Multiscale Analysis and Morphology
Wu, Shibin; Xie, Yaoqin
2013-01-01
A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE) and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by contrast limited adaptive histogram equalization and mathematical morphology, respectively. The enhanced image is processed by global nonlinear operator. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is measured by contrast evaluation criterion for image, signal-noise-ratio (SNR), and contrast improvement index (CII). PMID:24416072
Experience With Bayesian Image Based Surface Modeling
NASA Technical Reports Server (NTRS)
Stutz, John C.
2005-01-01
Bayesian surface modeling from images requires modeling both the surface and the image generation process, in order to optimize the models by comparing actual and generated images. Thus it differs greatly, both conceptually and in computational difficulty, from conventional stereo surface recovery techniques. But it offers the possibility of using any number of images, taken under quite different conditions, and by different instruments that provide independent and often complementary information, to generate a single surface model that fuses all available information. I describe an implemented system, with a brief introduction to the underlying mathematical models and the compromises made for computational efficiency. I describe successes and failures achieved on actual imagery, where we went wrong and what we did right, and how our approach could be improved. Lastly I discuss how the same approach can be extended to distinct types of instruments, to achieve true sensor fusion.
Image based modeling of tumor growth.
Meghdadi, N; Soltani, M; Niroomand-Oscuii, H; Ghalichi, F
2016-09-01
Tumors are a main cause of morbidity and mortality worldwide. Despite the efforts of the clinical and research communities, little has been achieved in the past decades in terms of improving the treatment of aggressive tumors. Understanding the underlying mechanism of tumor growth and evaluating the effects of different therapies are valuable steps in predicting the survival time and improving the patients' quality of life. Several studies have been devoted to tumor growth modeling at different levels to improve the clinical outcome by predicting the results of specific treatments. Recent studies have proposed patient-specific models using clinical data usually obtained from clinical images and evaluating the effects of various therapies. The aim of this review is to highlight the imaging role in tumor growth modeling and provide a worthwhile reference for biomedical and mathematical researchers with respect to tumor modeling using the clinical data to develop personalized models of tumor growth and evaluating the effect of different therapies.
Multiscale modelling of evolving foams
NASA Astrophysics Data System (ADS)
Saye, R. I.; Sethian, J. A.
2016-06-01
We present a set of multi-scale interlinked algorithms to model the dynamics of evolving foams. These algorithms couple the key effects of macroscopic bubble rearrangement, thin film drainage, and membrane rupture. For each of the mechanisms, we construct consistent and accurate algorithms, and couple them together to work across the wide range of space and time scales that occur in foam dynamics. These algorithms include second order finite difference projection methods for computing incompressible fluid flow on the macroscale, second order finite element methods to solve thin film drainage equations in the lamellae and Plateau borders, multiphase Voronoi Implicit Interface Methods to track interconnected membrane boundaries and capture topological changes, and Lagrangian particle methods for conservative liquid redistribution during rearrangement and rupture. We derive a full set of numerical approximations that are coupled via interface jump conditions and flux boundary conditions, and show convergence for the individual mechanisms. We demonstrate our approach by computing a variety of foam dynamics, including coupled evolution of three-dimensional bubble clusters attached to an anchored membrane and collapse of a foam cluster.
Image-Based Modeling of Trabecular Bones
NASA Astrophysics Data System (ADS)
Rajapakse, Chamith; Gunaratne, Gemunu
2004-10-01
Osteoporosis is a major health problem in the U.S. today. The detection and treatment of osteoporosis is currently based on Bone Mineral Density (BMD) measurements. Recent evidence suggests that the low bone mass alone does not account for the entire risk of osteoporotic fractures. It is also been known that the trabecular regions of bones play a major role in the bone strength . Trabecular bone has a complex structure with substantial heterogeneity, anisotropy and asymmetry. Although these properties effect BMD, the role of architecture and tissue material remain uncertain. Computer modeling of trabecular bone can be used predict responses that cannot be obtained experimentally, and they can compute responses that cannot be measured in-vivo. Due to the complexity of the Trabecular Architecture (TA) a model system based on scanned digital images is introduced to get substantial insight of TA and to predict the failure behavior. It is assumed that the added insight provided by these studies will lead to improved diagnostics and treatments of patient-specific osteoporotic fractures.
Multiscale Computational Models of Complex Biological Systems
Walpole, Joseph; Papin, Jason A.; Peirce, Shayn M.
2014-01-01
Integration of data across spatial, temporal, and functional scales is a primary focus of biomedical engineering efforts. The advent of powerful computing platforms, coupled with quantitative data from high-throughput experimental platforms, has allowed multiscale modeling to expand as a means to more comprehensively investigate biological phenomena in experimentally relevant ways. This review aims to highlight recently published multiscale models of biological systems while using their successes to propose the best practices for future model development. We demonstrate that coupling continuous and discrete systems best captures biological information across spatial scales by selecting modeling techniques that are suited to the task. Further, we suggest how to best leverage these multiscale models to gain insight into biological systems using quantitative, biomedical engineering methods to analyze data in non-intuitive ways. These topics are discussed with a focus on the future of the field, the current challenges encountered, and opportunities yet to be realized. PMID:23642247
A bidirectional coupling procedure applied to multiscale respiratory modeling
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
A Bidirectional Coupling Procedure Applied to Multiscale Respiratory Modeling
Kuprat, Andrew P.; Kabilan, Senthil; Carson, James P.; Corley, Richard A.; Einstein, Daniel 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 (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
A Bidirectional Coupling Procedure Applied to Multiscale Respiratory Modeling.
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 (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
Multiscale model approach for magnetization dynamics simulations
NASA Astrophysics Data System (ADS)
De Lucia, Andrea; Krüger, Benjamin; Tretiakov, Oleg A.; Kläui, Mathias
2016-11-01
Simulations of magnetization dynamics in a multiscale environment enable the rapid evaluation of the Landau-Lifshitz-Gilbert equation in a mesoscopic sample with nanoscopic accuracy in areas where such accuracy is required. We have developed a multiscale magnetization dynamics simulation approach that can be applied to large systems with spin structures that vary locally on small length scales. To implement this, the conventional micromagnetic simulation framework has been expanded to include a multiscale solving routine. The software selectively simulates different regions of a ferromagnetic sample according to the spin structures located within in order to employ a suitable discretization and use either a micromagnetic or an atomistic model. To demonstrate the validity of the multiscale approach, we simulate the spin wave transmission across the regions simulated with the two different models and different discretizations. We find that the interface between the regions is fully transparent for spin waves with frequency lower than a certain threshold set by the coarse scale micromagnetic model with no noticeable attenuation due to the interface between the models. As a comparison to exact analytical theory, we show that in a system with a Dzyaloshinskii-Moriya interaction leading to spin spirals, the simulated multiscale result is in good quantitative agreement with the analytical calculation.
Multiscale modeling of polymer nanocomposites
NASA Astrophysics Data System (ADS)
Sheidaei, Azadeh
In recent years, polymer nano-composites (PNCs) have increasingly gained more attention due to their improved mechanical, barrier, thermal, optical, electrical and biodegradable properties in comparison with the conventional micro-composites or pristine polymer. With a modest addition of nanoparticles (usually less than 5wt. %), PNCs offer a wide range of improvements in moduli, strength, heat resistance, biodegradability, as well as decrease in gas permeability and flammability. Although PNCs offer enormous opportunities to design novel material systems, development of an effective numerical modeling approach to predict their properties based on their complex multi-phase and multiscale structure is still at an early stage. Developing a computational framework to predict the mechanical properties of PNC is the focus of this dissertation. A computational framework has been developed to predict mechanical properties of polymer nano-composites. In chapter 1, a microstructure inspired material model has been developed based on statistical technique and this technique has been used to reconstruct the microstructure of Halloysite nanotube (HNT) polypropylene composite. This technique also has been used to reconstruct exfoliated Graphene nanoplatelet (xGnP) polymer composite. The model was able to successfully predict the material behavior obtained from experiment. Chapter 2 is the summary of the experimental work to support the numerical work. First, different processing techniques to make the polymer nanocomposites have been reviewed. Among them, melt extrusion followed by injection molding was used to manufacture high density polyethylene (HDPE)---xGnP nanocomposties. Scanning electron microscopy (SEM) also was performed to determine particle size and distribution and to examine fracture surfaces. Particle size was measured from these images and has been used for calculating the probability density function for GNPs in chapter 1. A series of nanoindentation tests have
Multiscale Modeling and Multifunctional Composites
2013-07-17
8) Here, Frs and Drs represent stress and the strain influence functions. The phase transformation fields, ,λ µ , appearing in Eqs...concentration factors Ar , Br , and influence functions Drs , Frs , , 1,=r s Q . Two applications are presented; one is a benchmark, classical...Journal for Multiscale Computational Engineering 8, 69-80. Berger, H., Kari S., Gabbert U., Rodriguez- Ramos , R., Guinovart, R., Otero, J.A., Bravo
Image based 3D city modeling : Comparative study
NASA Astrophysics Data System (ADS)
Singh, S. P.; Jain, K.; Mandla, V. R.
2014-06-01
3D city model is a digital representation of the Earth's surface and it's related objects such as building, tree, vegetation, and some manmade feature belonging to urban area. The demand of 3D city modeling is increasing rapidly for various engineering and non-engineering applications. Generally four main image based approaches were used for virtual 3D city models generation. In first approach, researchers were used Sketch based modeling, second method is Procedural grammar based modeling, third approach is Close range photogrammetry based modeling and fourth approach is mainly based on Computer Vision techniques. SketchUp, CityEngine, Photomodeler and Agisoft Photoscan are the main softwares to represent these approaches respectively. These softwares have different approaches & methods suitable for image based 3D city modeling. Literature study shows that till date, there is no complete such type of comparative study available to create complete 3D city model by using images. This paper gives a comparative assessment of these four image based 3D modeling approaches. This comparative study is mainly based on data acquisition methods, data processing techniques and output 3D model products. For this research work, study area is the campus of civil engineering department, Indian Institute of Technology, Roorkee (India). This 3D campus acts as a prototype for city. This study also explains various governing parameters, factors and work experiences. This research work also gives a brief introduction, strengths and weakness of these four image based techniques. Some personal comment is also given as what can do or what can't do from these softwares. At the last, this study shows; it concluded that, each and every software has some advantages and limitations. Choice of software depends on user requirements of 3D project. For normal visualization project, SketchUp software is a good option. For 3D documentation record, Photomodeler gives good result. For Large city
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.
Multiscale modeling for image analysis of brain tumor studies.
Bauer, Stefan; May, Christian; Dionysiou, Dimitra; Stamatakos, Georgios; Büchler, Philippe; Reyes, Mauricio
2012-01-01
Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multiscale, multiphysics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlas-based segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.
Towards multiscale modeling of influenza infection
Murillo, Lisa N.; Murillo, Michael S.; Perelson, Alan S.
2013-01-01
Aided by recent advances in computational power, algorithms, and higher fidelity data, increasingly detailed theoretical models of infection with influenza A virus are being developed. We review single scale models as they describe influenza infection from intracellular to global scales, and, in particular, we consider those models that capture details specific to influenza and can be used to link different scales. We discuss the few multiscale models of influenza infection that have been developed in this emerging field. In addition to discussing modeling approaches, we also survey biological data on influenza infection and transmission that is relevant for constructing influenza infection models. We envision that, in the future, multiscale models that capitalize on technical advances in experimental biology and high performance computing could be used to describe the large spatial scale epidemiology of influenza infection, evolution of the virus, and transmission between hosts more accurately. PMID:23608630
Multiscale modeling of mucosal immune responses
2015-01-01
Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM. Background Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Implementation Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. Conclusion We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut
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.
Multi-scale modeling in cell biology
Meier-Schellersheim, Martin; Fraser, Iain D. C.; Klauschen, Frederick
2009-01-01
Biomedical research frequently involves performing experiments and developing hypotheses that link different scales of biological systems such as, for instance, the scales of intracellular molecular interactions to the scale of cellular behavior and beyond to the behavior of cell populations. Computational modeling efforts that aim at exploring such multi-scale systems quantitatively with the help of simulations have to incorporate several different simulation techniques due to the different time and space scales involved. Here, we provide a non-technical overview of how different scales of experimental research can be combined with the appropriate computational modeling techniques. We also show that current modeling software permits building and simulating multi-scale models without having to become involved with the underlying technical details of computational modeling. PMID:20448808
Multiscale modelling of hydraulic conductivity in vuggy porous media.
Daly, K R; Roose, T
2014-02-08
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.
Multiscale Models of Breast Cancer Progression
Chakrabarti, Anirikh; Verbridge, Scott; Stroock, Abraham D.; Fischbach, Claudia; Varner, Jeffrey D.
2013-01-01
Breast cancer initiation, invasion and metastasis span multiple length and time scales. Molecular events at short length scales lead to an initial tumorigenic population, which left unchecked by immune action, acts at increasingly longer length scales until eventually the cancer cells escape from the primary tumor site. This series of events is highly complex, involving multiple cell types interacting with (and shaping) the microenvironment. Multiscale mathematical models have emerged as a powerful tool to quantitatively integrate the convective-diffusion-reaction processes occurring on the systemic scale, with the molecular signaling processes occurring on the cellular and subcellular scales. In this study, we reviewed the current state of the art in cancer modeling across multiple length scales, with an emphasis on the integration of intracellular signal transduction models with pro-tumorigenic chemical and mechanical microenvironmental cues. First, we reviewed the underlying biomolecular origin of breast cancer, with a special emphasis on angiogenesis. Then, we summarized the development of tissue engineering platforms which could provide highfidelity ex vivo experimental models to identify and validate multiscale simulations. Lastly, we reviewed top-down and bottom-up multiscale strategies that integrate subcellular networks with the microenvironment. We present models of a variety of cancers, in addition to breast cancer specific models. Taken together, we expect as the sophistication of the simulations increase, that multiscale modeling and bottom-up agent-based models in particular will become an increasingly important platform technology for basic scientific discovery, as well as the identification and validation of potentially novel therapeutic targets. PMID:23008097
Image based Monte Carlo Modeling for Computational Phantom
NASA Astrophysics Data System (ADS)
Cheng, Mengyun; Wang, Wen; Zhao, Kai; Fan, Yanchang; Long, Pengcheng; Wu, Yican
2014-06-01
The evaluation on the effects of ionizing radiation and the risk of radiation exposure on human body has been becoming one of the most important issues for radiation protection and radiotherapy fields, which is helpful to avoid unnecessary radiation and decrease harm to human body. In order to accurately evaluate the dose on human body, it is necessary to construct more realistic computational phantom. However, manual description and verfication of the models for Monte carlo(MC)simulation are very tedious, error-prone and time-consuming. In addiation, it is difficult to locate and fix the geometry error, and difficult to describe material information and assign it to cells. MCAM (CAD/Image-based Automatic Modeling Program for Neutronics and Radiation Transport Simulation) was developed as an interface program to achieve both CAD- and image-based automatic modeling by FDS Team (Advanced Nuclear Energy Research Team, http://www.fds.org.cn). The advanced version (Version 6) of MCAM can achieve automatic conversion from CT/segmented sectioned images to computational phantoms such as MCNP models. Imaged-based automatic modeling program(MCAM6.0) has been tested by several medical images and sectioned images. And it has been applied in the construction of Rad-HUMAN. Following manual segmentation and 3D reconstruction, a whole-body computational phantom of Chinese adult female called Rad-HUMAN was created by using MCAM6.0 from sectioned images of a Chinese visible human dataset. Rad-HUMAN contains 46 organs/tissues, which faithfully represented the average anatomical characteristics of the Chinese female. The dose conversion coefficients(Dt/Ka) from kerma free-in-air to absorbed dose of Rad-HUMAN were calculated. Rad-HUMAN can be applied to predict and evaluate dose distributions in the Treatment Plan System (TPS), as well as radiation exposure for human body in radiation protection.
Multiscale modeling of failure in composites under model parameter uncertainty
NASA Astrophysics Data System (ADS)
Bogdanor, Michael J.; Oskay, Caglar; Clay, Stephen B.
2015-09-01
This manuscript presents a multiscale stochastic failure modeling approach for fiber reinforced composites. A homogenization based reduced-order multiscale computational model is employed to predict the progressive damage accumulation and failure in the composite. Uncertainty in the composite response is modeled at the scale of the microstructure by considering the constituent material (i.e., matrix and fiber) parameters governing the evolution of damage as random variables. Through the use of the multiscale model, randomness at the constituent scale is propagated to the scale of the composite laminate. The probability distributions of the underlying material parameters are calibrated from unidirectional composite experiments using a Bayesian statistical approach. The calibrated multiscale model is exercised to predict the ultimate tensile strength of quasi-isotropic open-hole composite specimens at various loading rates. The effect of random spatial distribution of constituent material properties on the composite response is investigated.
Concurrent Multiscale Modeling of Embedded Nanomechanics
Rudd, R E
2001-04-13
We discuss concurrent multiscale simulations of dynamic and temperature-dependent processes found in nanomechanical systems coupled to larger scale surroundings. We focus on the behavior of sub-micron Micro-Electro-Mechanical Systems (MEMS), especially micro-resonators. The coupling of length scales methodology we have developed for MEMS employs an atomistic description of small but key regions of the system, consisting of millions of atoms, coupled concurrently to a finite element model of the periphery. The result is a model that accurately describes the behavior of the mechanical components of MEMS down to the atomic scale. This paper reviews some of the general issues involved in concurrent multiscale simulation, extends the methodology to metallic systems and describes how it has been used to identify atomistic effects in sub-micron resonators.
Stochastic multiscale model for carbonate rocks.
Biswal, B; Oren, P-E; Held, R J; Bakke, S; Hilfer, R
2007-06-01
A multiscale model for the diagenesis of carbonate rocks is proposed. It captures important pore scale characteristics of carbonate rocks: wide range of length scales in the pore diameters; large variability in the permeability; and strong dependence of the geometrical and transport parameters on the resolution. A pore scale microstructure of an oolithic dolostone with generic diagenetic features is successfully generated. The continuum representation of a reconstructed cubic sample of side length 2mm contains roughly 42 x 10{6} crystallites and pore diameters varying over many decades. Petrophysical parameters are computed on discretized samples of sizes up to 1000{3}. The model can be easily adapted to represent the multiscale microstructure of a wide variety of carbonate rocks.
PDF-based heterogeneous multiscale filtration model.
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.
Multiscale Gaussian network model (mGNM) and multiscale anisotropic network model (mANM)
NASA Astrophysics Data System (ADS)
Xia, Kelin; Opron, Kristopher; Wei, Guo-Wei
2015-11-01
Gaussian network model (GNM) and anisotropic network model (ANM) are some of the most popular methods for the study of protein flexibility and related functions. In this work, we propose generalized GNM (gGNM) and ANM methods and show that the GNM Kirchhoff matrix can be built from the ideal low-pass filter, which is a special case of a wide class of correlation functions underpinning the linear scaling flexibility-rigidity index (FRI) method. Based on the mathematical structure of correlation functions, we propose a unified framework to construct generalized Kirchhoff matrices whose matrix inverse leads to gGNMs, whereas, the direct inverse of its diagonal elements gives rise to FRI method. With this connection, we further introduce two multiscale elastic network models, namely, multiscale GNM (mGNM) and multiscale ANM (mANM), which are able to incorporate different scales into the generalized Kirchhoff matrices or generalized Hessian matrices. We validate our new multiscale methods with extensive numerical experiments. We illustrate that gGNMs outperform the original GNM method in the B-factor prediction of a set of 364 proteins. We demonstrate that for a given correlation function, FRI and gGNM methods provide essentially identical B-factor predictions when the scale value in the correlation function is sufficiently large. More importantly, we reveal intrinsic multiscale behavior in protein structures. The proposed mGNM and mANM are able to capture this multiscale behavior and thus give rise to a significant improvement of more than 11% in B-factor predictions over the original GNM and ANM methods. We further demonstrate the benefits of our mGNM through the B-factor predictions of many proteins that fail the original GNM method. We show that the proposed mGNM can also be used to analyze protein domain separations. Finally, we showcase the ability of our mANM for the analysis of protein collective motions.
Multiscale Gaussian network model (mGNM) and multiscale anisotropic network model (mANM).
Xia, Kelin; Opron, Kristopher; Wei, Guo-Wei
2015-11-28
Gaussian network model (GNM) and anisotropic network model (ANM) are some of the most popular methods for the study of protein flexibility and related functions. In this work, we propose generalized GNM (gGNM) and ANM methods and show that the GNM Kirchhoff matrix can be built from the ideal low-pass filter, which is a special case of a wide class of correlation functions underpinning the linear scaling flexibility-rigidity index (FRI) method. Based on the mathematical structure of correlation functions, we propose a unified framework to construct generalized Kirchhoff matrices whose matrix inverse leads to gGNMs, whereas, the direct inverse of its diagonal elements gives rise to FRI method. With this connection, we further introduce two multiscale elastic network models, namely, multiscale GNM (mGNM) and multiscale ANM (mANM), which are able to incorporate different scales into the generalized Kirchhoff matrices or generalized Hessian matrices. We validate our new multiscale methods with extensive numerical experiments. We illustrate that gGNMs outperform the original GNM method in the B-factor prediction of a set of 364 proteins. We demonstrate that for a given correlation function, FRI and gGNM methods provide essentially identical B-factor predictions when the scale value in the correlation function is sufficiently large. More importantly, we reveal intrinsic multiscale behavior in protein structures. The proposed mGNM and mANM are able to capture this multiscale behavior and thus give rise to a significant improvement of more than 11% in B-factor predictions over the original GNM and ANM methods. We further demonstrate the benefits of our mGNM through the B-factor predictions of many proteins that fail the original GNM method. We show that the proposed mGNM can also be used to analyze protein domain separations. Finally, we showcase the ability of our mANM for the analysis of protein collective motions.
Multiscale Models of Antibiotic Probiotics
Kaznessis, Yiannis N.
2014-01-01
The discovery of antibiotics is one of the most important advances in the history of humankind. For eighty years human life expectancy and standards of living improved greatly thanks to antibiotics. But bacteria have been fighting back, developing resistance to our most potent molecules. New, alternative strategies must be explored as antibiotic therapies become obsolete because of bacterial resistance. Mathematical models and simulations guide the development of complex technologies, such as aircrafts, bridges, communication systems and transportation systems. Herein, models are discussed that guide the development of new antibiotic technologies. These models span multiple molecular and cellular scales, and facilitate the development of a technology that addresses a significant societal challenge. We argue that simulations can be a creative source of knowledge. PMID:25313349
Multiscale Stochastic Simulation and Modeling
James Glimm; Xiaolin Li
2006-01-10
Acceleration driven instabilities of fluid mixing layers include the classical cases of Rayleigh-Taylor instability, driven by a steady acceleration and Richtmyer-Meshkov instability, driven by an impulsive acceleration. Our program starts with high resolution methods of numerical simulation of two (or more) distinct fluids, continues with analytic analysis of these solutions, and the derivation of averaged equations. A striking achievement has been the systematic agreement we obtained between simulation and experiment by using a high resolution numerical method and improved physical modeling, with surface tension. Our study is accompanies by analysis using stochastic modeling and averaged equations for the multiphase problem. We have quantified the error and uncertainty using statistical modeling methods.
Multiscale Modeling with Carbon Nanotubes
Maiti, A
2006-02-21
Technologically important nanomaterials come in all shapes and sizes. They can range from small molecules to complex composites and mixtures. Depending upon the spatial dimensions of the system and properties under investigation computer modeling of such materials can range from equilibrium and nonequilibrium Quantum Mechanics, to force-field-based Molecular Mechanics and kinetic Monte Carlo, to Mesoscale simulation of evolving morphology, to Finite-Element computation of physical properties. This brief review illustrates some of the above modeling techniques through a number of recent applications with carbon nanotubes: nano electromechanical sensors (NEMS), chemical sensors, metal-nanotube contacts, and polymer-nanotube composites.
Multiscale modeling of polyelectrolyte gels
NASA Astrophysics Data System (ADS)
Wallmersperger, Thomas; Wittel, Falk K.; Kröplin, Bernd H.
2006-03-01
Electrolyte polymer gels are a very attractive class of actuation materials with remarkable electronic and mechanical properties having a great similarity to biological contractile tissues. They consist of a polymer network with ionizable groups and a liquid phase with mobile ions. Absorption and delivery of solvent lead to a considerably large change of volume. Due to this capability, they can be used as actuators for technical applications, where large swelling and shrinkage is desired. In the present work chemically and electrically stimulated polymer gels in a solution bath are investigated. To describe the different complicated phenomena occurring in these gels adequately, the modeling can be conducted on different scales. Therefore, models based on the statistical theory and porous media theory, as well as a multi-field model and a discrete element formulation are derived. A refinement of the different theories from global macroscopic to microscopic are presented in this paper: The statistical theory is a macroscopic theory capable to describe the global swelling or bending e.g. of a gel film, while the general theory of porous media (TPM) is a macroscopic continuum theory which is based on the theory of mixtures extended by the concept of volume fractions. The TPM is a homogenized model, i.e. all geometrical and physical quantities can be seen as statistical averages of the real quantities. The presented chemo-electro-mechanical multi-field formulation is a mesoscopic theory. It is capable of giving the concentrations and the electric potential in the whole domain. Finally the (micromechanical) discrete element (DE) theory is employed. In this case, the continuum is represented by distributed particles with local interaction relations combined with balance equations for the chemical field. This method is predestined for problems involving large displacements, strains and discontinuities. The presented formulations are compared and conclusions on their
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 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 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 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
Institute for Multiscale Modeling of Biological Interactions
Paulaitis, Michael E; Garcia-Moreno, Bertrand; Lenhoff, Abraham
2009-12-26
The Institute for Multiscale Modeling of Biological Interactions (IMMBI) has two primary goals: Foster interdisciplinary collaborations among faculty and their research laboratories that will lead to novel applications of multiscale simulation and modeling methods in the biological sciences and engineering; and Building on the unique biophysical/biology-based engineering foundations of the participating faculty, train scientists and engineers to apply computational methods that collectively span multiple time and length scales of biological organization. The success of IMMBI will be defined by the following: Size and quality of the applicant pool for pre-doctoral and post-doctoral fellows; Academic performance; Quality of the pre-doctoral and post-doctoral research; Impact of the research broadly and to the DOE (ASCR program) mission; Distinction of the next career step for pre-doctoral and post-doctoral fellows; and Faculty collaborations that result from IMMBI activities. Specific details about accomplishments during the three years of DOE support for IMMBI have been documented in Annual Progress Reports (April 2005, June 2006, and March 2007) and a Report for a National Academy of Sciences Review (October 2005) that were submitted to DOE on the dates indicated. An overview of these accomplishments is provided.
A multiscale strength model in HYDRA
NASA Astrophysics Data System (ADS)
Marinak, M. M.; Barton, N. R.
2016-10-01
We describe a multiscale strength model recently implemented in HYDRA. The model incorporates results from a hierarchy of methods which span from the atomistic to the continuum level. Those are obtained from focused physics codes that treat density functional theory, molecular statics, molecular dynamics, dislocation dynamics and continuum mechanics. The model is designed to handle extreme pressures and temperatures, and is especially appropriate for strain rates in excess of 104 s-1. As such it can be used to provide insight into HEDP experimental observations. The model has demonstrated success in capturing planar Rayleigh-Taylor growth for 1 Mbar shocks in Ta and V. This work was performed under the auspices of the Lawrence Livermore National Security, LLC, (LLNS) under Contract No. DE-AC52-07NA27344.
Image-based modelling of skeletal muscle oxygenation.
Zeller-Plumhoff, B; Roose, T; Clough, G F; Schneider, P
2017-02-01
The supply of oxygen in sufficient quantity is vital for the correct functioning of all organs in the human body, in particular for skeletal muscle during exercise. Disease is often associated with both an inhibition of the microvascular supply capability and is thought to relate to changes in the structure of blood vessel networks. Different methods exist to investigate the influence of the microvascular structure on tissue oxygenation, varying over a range of application areas, i.e. biological in vivo and in vitro experiments, imaging and mathematical modelling. Ideally, all of these methods should be combined within the same framework in order to fully understand the processes involved. This review discusses the mathematical models of skeletal muscle oxygenation currently available that are based upon images taken of the muscle microvasculature in vivo and ex vivo Imaging systems suitable for capturing the blood vessel networks are discussed and respective contrasting methods presented. The review further informs the association between anatomical characteristics in health and disease. With this review we give the reader a tool to understand and establish the workflow of developing an image-based model of skeletal muscle oxygenation. Finally, we give an outlook for improvements needed for measurements and imaging techniques to adequately investigate the microvascular capability for oxygen exchange.
Image-based modelling of skeletal muscle oxygenation
Clough, G. F.
2017-01-01
The supply of oxygen in sufficient quantity is vital for the correct functioning of all organs in the human body, in particular for skeletal muscle during exercise. Disease is often associated with both an inhibition of the microvascular supply capability and is thought to relate to changes in the structure of blood vessel networks. Different methods exist to investigate the influence of the microvascular structure on tissue oxygenation, varying over a range of application areas, i.e. biological in vivo and in vitro experiments, imaging and mathematical modelling. Ideally, all of these methods should be combined within the same framework in order to fully understand the processes involved. This review discusses the mathematical models of skeletal muscle oxygenation currently available that are based upon images taken of the muscle microvasculature in vivo and ex vivo. Imaging systems suitable for capturing the blood vessel networks are discussed and respective contrasting methods presented. The review further informs the association between anatomical characteristics in health and disease. With this review we give the reader a tool to understand and establish the workflow of developing an image-based model of skeletal muscle oxygenation. Finally, we give an outlook for improvements needed for measurements and imaging techniques to adequately investigate the microvascular capability for oxygen exchange. PMID:28202595
Multiscale Models in the Biomechanics of Plant Growth
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
Variational multiscale models for charge transport
Wei, Guo-Wei; Zheng, Qiong; Chen, Zhan; Xia, Kelin
2012-01-01
This work presents a few variational multiscale models for charge transport in complex physical, chemical and biological systems and engineering devices, such as fuel cells, solar cells, battery cells, nanofluidics, transistors and ion channels. An essential ingredient of the present models, introduced in an earlier paper (Bulletin of Mathematical Biology, 72, 1562-1622, 2010), is the use of differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain from the microscopic domain, meanwhile, dynamically couple discrete and continuum descriptions. Our main strategy is to construct the total energy functional of a charge transport system to encompass the polar and nonpolar free energies of solvation, and chemical potential related energy. By using the Euler-Lagrange variation, coupled Laplace-Beltrami and Poisson-Nernst-Planck (LB-PNP) equations are derived. The solution of the LB-PNP equations leads to the minimization of the total free energy, and explicit profiles of electrostatic potential and densities of charge species. To further reduce the computational complexity, the Boltzmann distribution obtained from the Poisson-Boltzmann (PB) equation is utilized to represent the densities of certain charge species so as to avoid the computationally expensive solution of some Nernst-Planck (NP) equations. Consequently, the coupled Laplace-Beltrami and Poisson-Boltzmann-Nernst-Planck (LB-PBNP) equations are proposed for charge transport in heterogeneous systems. A major emphasis of the present formulation is the consistency between equilibrium LB-PB theory and non-equilibrium LB-PNP theory at equilibrium. Another major emphasis is the capability of the reduced LB-PBNP model to fully recover the prediction of the LB-PNP model at non-equilibrium settings. To account for the fluid impact on the charge transport, we derive coupled Laplace-Beltrami, Poisson-Nernst-Planck and Navier-Stokes equations from the variational principle
Multiscale measurement error models for aggregated small area health data.
Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin
2016-08-01
Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates.
Multiscale agent-based consumer market modeling.
North, M. J.; Macal, C. M.; St. Aubin, J.; Thimmapuram, P.; Bragen, M.; Hahn, J.; Karr, J.; Brigham, N.; Lacy, M. E.; Hampton, D.; Decision and Information Sciences; Procter & Gamble Co.
2010-05-01
Consumer markets have been studied in great depth, and many techniques have been used to represent them. These have included regression-based models, logit models, and theoretical market-level models, such as the NBD-Dirichlet approach. Although many important contributions and insights have resulted from studies that relied on these models, there is still a need for a model that could more holistically represent the interdependencies of the decisions made by consumers, retailers, and manufacturers. When the need is for a model that could be used repeatedly over time to support decisions in an industrial setting, it is particularly critical. Although some existing methods can, in principle, represent such complex interdependencies, their capabilities might be outstripped if they had to be used for industrial applications, because of the details this type of modeling requires. However, a complementary method - agent-based modeling - shows promise for addressing these issues. Agent-based models use business-driven rules for individuals (e.g., individual consumer rules for buying items, individual retailer rules for stocking items, or individual firm rules for advertizing items) to determine holistic, system-level outcomes (e.g., to determine if brand X's market share is increasing). We applied agent-based modeling to develop a multi-scale consumer market model. We then conducted calibration, verification, and validation tests of this model. The model was successfully applied by Procter & Gamble to several challenging business problems. In these situations, it directly influenced managerial decision making and produced substantial cost savings.
Multiscale modelling of nucleosome core particle aggregation
NASA Astrophysics Data System (ADS)
Lyubartsev, Alexander P.; Korolev, Nikolay; Fan, Yanping; Nordenskiöld, Lars
2015-02-01
The nucleosome core particle (NCP) is the basic building block of chromatin. Under the influence of multivalent cations, isolated mononucleosomes exhibit a rich phase behaviour forming various columnar phases with characteristic NCP-NCP stacking. NCP stacking is also a regular element of chromatin structure in vivo. Understanding the mechanism of nucleosome stacking and the conditions leading to self-assembly of NCPs is still incomplete. Due to the complexity of the system and the need to describe electrostatics properly by including the explicit mobile ions, novel modelling approaches based on coarse-grained (CG) methods at the multiscale level becomes a necessity. In this work we present a multiscale CG computer simulation approach to modelling interactions and self-assembly of solutions of NCPs induced by the presence of multivalent cations. Starting from continuum simulations including explicit three-valent cobalt(III)hexammine (CoHex3+) counterions and 20 NCPs, based on a previously developed advanced CG NCP model with one bead per amino acid and five beads per two DNA base pair unit (Fan et al 2013 PLoS One 8 e54228), we use the inverse Monte Carlo method to calculate effective interaction potentials for a ‘super-CG’ NCP model consisting of seven beads for each NCP. These interaction potentials are used in large-scale simulations of up to 5000 NCPs, modelling self-assembly induced by CoHex3+. The systems of ‘super-CG’ NCPs form a single large cluster of stacked NCPs without long-range order in agreement with experimental data for NCPs precipitated by the three-valent polyamine, spermidine3+.
An approach to multiscale modelling with graph grammars
Ong, Yongzhi; Streit, Katarína; Henke, Michael; Kurth, Winfried
2014-01-01
Background and Aims Functional–structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. Methods A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Key Results Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. Conclusions The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models. PMID:25134929
NASA Astrophysics Data System (ADS)
Yoon, Jayoung; Kim, Gerard J.
2003-04-01
Traditionally, three dimension models have been used for building virtual worlds, and a data structure called the "scene graph" is often employed to organize these 3D objects in the virtual space. On the other hand, image-based rendering has recently been suggested as a probable alternative VR platform for its photo-realism, however, due to limited interactivity, it has only been used for simple navigation systems. To combine the merits of these two approaches to object/scene representations, this paper proposes for a scene graph structure in which both 3D models and various image-based scenes/objects can be defined, traversed, and rendered together. In fact, as suggested by Shade et al., these different representations can be used as different LOD's for a given object. For instance, an object might be rendered using a 3D model at close range, a billboard at an intermediate range, and as part of an environment map at far range. The ultimate objective of this mixed platform is to breath more interactivity into the image based rendered VE's by employing 3D models as well. There are several technical challenges in devising such a platform: designing scene graph nodes for various types of image based techniques, establishing criteria for LOD/representation selection, handling their transitions, implementing appropriate interaction schemes, and correctly rendering the overall scene. Currently, we have extended the scene graph structure of the Sense8's WorldToolKit, to accommodate new node types for environment maps billboards, moving textures and sprites, "Tour-into-the-Picture" structure, and view interpolated objects. As for choosing the right LOD level, the usual viewing distance and image space criteria are used, however, the switching between the image and 3D model occurs at a distance from the user where the user starts to perceive the object's internal depth. Also, during interaction, regardless of the viewing distance, a 3D representation would be used, it if
Multiscale modeling of three-dimensional genome
NASA Astrophysics Data System (ADS)
Zhang, Bin; Wolynes, Peter
The genome, the blueprint of life, contains nearly all the information needed to build and maintain an entire organism. A comprehensive understanding of the genome is of paramount interest to human health and will advance progress in many areas, including life sciences, medicine, and biotechnology. The overarching goal of my research is to understand the structure-dynamics-function relationships of the human genome. In this talk, I will be presenting our efforts in moving towards that goal, with a particular emphasis on studying the three-dimensional organization, the structure of the genome with multi-scale approaches. Specifically, I will discuss the reconstruction of genome structures at both interphase and metaphase by making use of data from chromosome conformation capture experiments. Computationally modeling of chromatin fiber at atomistic level from first principles will also be presented as our effort for studying the genome structure from bottom up.
Multiscale models for vertebrate limb development.
Newman, Stuart A; Christley, Scott; Glimm, Tilmann; Hentschel, H G E; Kazmierczak, Bogdan; Zhang, Yong-Tao; Zhu, Jianfeng; Alber, Mark
2008-01-01
Dynamical systems in which geometrically extended model cells produce and interact with diffusible (morphogen) and nondiffusible (extracellular matrix) chemical fields have proved very useful as models for developmental processes. The embryonic vertebrate limb is an apt system for such mathematical and computational modeling since it has been the subject of hundreds of experimental studies, and its normal and variant morphologies and spatiotemporal organization of expressed genes are well known. Because of its stereotypical proximodistally generated increase in the number of parallel skeletal elements, the limb lends itself to being modeled by Turing-type systems which are capable of producing periodic, or quasiperiodic, arrangements of spot- and stripe-like elements. This chapter describes several such models, including, (i) a system of partial differential equations in which changing cell density enters into the dynamics explicitly, (ii) a model for morphogen dynamics alone, derived from the latter system in the "morphostatic limit" where cell movement relaxes on a much slower time-scale than cell differentiation, (iii) a discrete stochastic model for the simplified pattern formation that occurs when limb cells are placed in planar culture, and (iv) several hybrid models in which continuum morphogen systems interact with cells represented as energy-minimizing mesoscopic entities. Progress in devising computational methods for handling 3D, multiscale, multimodel simulations of organogenesis is discussed, as well as for simulating reaction-diffusion dynamics in domains of irregular shape.
NASA Astrophysics Data System (ADS)
Li, Dengwang; Li, Hongsheng; Wan, Honglin; Chen, Jinhu; Gong, Guanzhong; Wang, Hongjun; Wang, Liming; Yin, Yong
2012-08-01
Mutual information (MI) is a well-accepted similarity measure for image registration in medical systems. However, MI-based registration faces the challenges of high computational complexity and a high likelihood of being trapped into local optima due to an absence of spatial information. In order to solve these problems, multi-scale frameworks can be used to accelerate registration and improve robustness. Traditional Gaussian pyramid representation is one such technique but it suffers from contour diffusion at coarse levels which may lead to unsatisfactory registration results. In this work, a new multi-scale registration framework called edge preserving multiscale registration (EPMR) was proposed based upon an edge preserving total variation L1 norm (TV-L1) scale space representation. TV-L1 scale space is constructed by selecting edges and contours of images according to their size rather than the intensity values of the image features. This ensures more meaningful spatial information with an EPMR framework for MI-based registration. Furthermore, we design an optimal estimation of the TV-L1 parameter in the EPMR framework by training and minimizing the transformation offset between the registered pairs for automated registration in medical systems. We validated our EPMR method on both simulated mono- and multi-modal medical datasets with ground truth and clinical studies from a combined positron emission tomography/computed tomography (PET/CT) scanner. We compared our registration framework with other traditional registration approaches. Our experimental results demonstrated that our method outperformed other methods in terms of the accuracy and robustness for medical images. EPMR can always achieve a small offset value, which is closer to the ground truth both for mono-modality and multi-modality, and the speed can be increased 5-8% for mono-modality and 10-14% for multi-modality registration under the same condition. Furthermore, clinical application by adaptive
Multiscale retinocortical model of contrast processing
NASA Astrophysics Data System (ADS)
Moorhead, Ian R.; Haig, Nigel D.
1996-04-01
Visual performance models have in the past, typically been empirical, relying on the user to supply numerical values such as target contrast and background luminance to describe the performance of the visual system, when undertaking a specified task. However, it is becoming increasingly easy to obtain computer images using for example digital cameras, scanners, imaging photometers and radiometers. We have therefore been examining the possibility of producing a quantitative model of human vision that is capable of directly processing images in order to provide predictions of performance. We are particularly interested in being able to process images of 'real' scenes. The model is inspired by human vision and the components have analogies with parts of the human visual system but their properties are governed primarily by existing psychophysical data. The first stage of the model generates a multiscale, difference of Gaussian (DoG) representation of the image (Burton, Haig and Moorhead), with a central foveal region of high resolution, and with a resolution that declines with eccentricity as the scale of the filter increases. Incorporated into this stage is a gain control process which ensures that the contrast sensitivity is consistent with the psychophysical data of van Nes and Bouman. The second stage incorporates a model of perceived contrast proposed by Cannon and Fullenkamp. Their model assumes the image is analyzed by oriented (Gabor) filters and produces a representation of the image in terms of perceived contrast.
Multi-scale modeling of chemotactic interactions
NASA Astrophysics Data System (ADS)
Grima, Ramon
Biological complexity emerges from the synthesis of biochemical, chemical and physical phenomena. In recent years there has been an intense effort in modeling various cellular systems of interest to understand how the observed complexity emerges from the underlying mechanisms. Most modeling approaches are based on a population description of the cells: these methods, though usually amenable to calculation, are only valid in the limit of large numbers of interacting cells. Many systems of interest involve the interaction of a relatively small number of cells; even biological systems composed of thousands of cells have spatially extended regions over which the number density of cells is small. For the latter cases, population descriptions are not valid and individual based models become a necessity. Such models, usually cellular automaton models, have been numerically studied in recent years; however, these models are not usually amenable to analytic calculation. The work presented in this thesis seeks to fulfill a gap in modeling approaches to the understanding of biocomplexity by constructing an individual based model on which analysis is possible, through the methods of statistical physics and the theory of stochastic processes. This model will be used to study the differences between individual based and population based models and the range of applicability of the latter. For the sake of comparison of the two, new efficient computational algorithms are devised for the simulation of both types of models. We finally complete our multiscale study of modeling by investigating the robustness of individual based models; this meaning a comparison of the results of different microscopic descriptions modeling the same underlying phenomena.
Integrating Multiscale Modeling with Drug Effects for Cancer Treatment
Li, Xiangfang L.; Oduola, Wasiu O.; Qian, Lijun; Dougherty, Edward R.
2015-01-01
In this paper, we review multiscale modeling for cancer treatment with the incorporation of drug effects from an applied system’s pharmacology perspective. Both the classical pharmacology and systems biology are inherently quantitative; however, systems biology focuses more on networks and multi factorial controls over biological processes rather than on drugs and targets in isolation, whereas systems pharmacology has a strong focus on studying drugs with regard to the pharmacokinetic (PK) and pharmacodynamic (PD) relations accompanying drug interactions with multiscale physiology as well as the prediction of dosage-exposure responses and economic potentials of drugs. Thus, it requires multiscale methods to address the need for integrating models from the molecular levels to the cellular, tissue, and organism levels. It is a common belief that tumorigenesis and tumor growth can be best understood and tackled by employing and integrating a multifaceted approach that includes in vivo and in vitro experiments, in silico models, multiscale tumor modeling, continuous/discrete modeling, agent-based modeling, and multiscale modeling with PK/PD drug effect inputs. We provide an example application of multiscale modeling employing stochastic hybrid system for a colon cancer cell line HCT-116 with the application of Lapatinib drug. It is observed that the simulation results are similar to those observed from the setup of the wet-lab experiments at the Translational Genomics Research Institute. PMID:26792977
Modelling approaches for evaluating multiscale tendon mechanics
Fang, Fei; Lake, Spencer P.
2016-01-01
Tendon exhibits anisotropic, inhomogeneous and viscoelastic mechanical properties that are determined by its complicated hierarchical structure and varying amounts/organization of different tissue constituents. Although extensive research has been conducted to use modelling approaches to interpret tendon structure–function relationships in combination with experimental data, many issues remain unclear (i.e. the role of minor components such as decorin, aggrecan and elastin), and the integration of mechanical analysis across different length scales has not been well applied to explore stress or strain transfer from macro- to microscale. This review outlines mathematical and computational models that have been used to understand tendon mechanics at different scales of the hierarchical organization. Model representations at the molecular, fibril and tissue levels are discussed, including formulations that follow phenomenological and microstructural approaches (which include evaluations of crimp, helical structure and the interaction between collagen fibrils and proteoglycans). Multiscale modelling approaches incorporating tendon features are suggested to be an advantageous methodology to understand further the physiological mechanical response of tendon and corresponding adaptation of properties owing to unique in vivo loading environments. PMID:26855747
Multiscale approach to equilibrating model polymer melts
NASA Astrophysics Data System (ADS)
Svaneborg, Carsten; Karimi-Varzaneh, Hossein Ali; Hojdis, Nils; Fleck, Frank; Everaers, Ralf
2016-09-01
We present an effective and simple multiscale method for equilibrating Kremer Grest model polymer melts of varying stiffness. In our approach, we progressively equilibrate the melt structure above the tube scale, inside the tube and finally at the monomeric scale. We make use of models designed to be computationally effective at each scale. Density fluctuations in the melt structure above the tube scale are minimized through a Monte Carlo simulated annealing of a lattice polymer model. Subsequently the melt structure below the tube scale is equilibrated via the Rouse dynamics of a force-capped Kremer-Grest model that allows chains to partially interpenetrate. Finally the Kremer-Grest force field is introduced to freeze the topological state and enforce correct monomer packing. We generate 15 melts of 500 chains of 10.000 beads for varying chain stiffness as well as a number of melts with 1.000 chains of 15.000 monomers. To validate the equilibration process we study the time evolution of bulk, collective, and single-chain observables at the monomeric, mesoscopic, and macroscopic length scales. Extension of the present method to longer, branched, or polydisperse chains, and/or larger system sizes is straightforward.
Multiscale Modeling of Cavitating Bubbly Flows
NASA Astrophysics Data System (ADS)
Ma, J.; Hsiao, C.-T.; Chahine, G. L.
2013-03-01
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 Bubble Model for dispersed microbubbles and a level set N-S solver for macro cavities, along with a mesoscale transition model to bridge the two. This approach was implemented in 3DYNAFScopyright and used to simulate sheet-to-cloud cavitation over a hydrofoil. The hybrid model captures well the full cavitation process starting from free field nuclei and nucleation from solid surfaces. In low pressure region of the foil small nuclei are seen to grow large and eventually merge to form a large scale sheet cavity. A reentrant jet forms under the cavity, travels upstream, and breaks it, resulting in a bubble cloud of a large amount of microbubbles as the broken pockets shrink and travel downstream. This is in good agreement with experimental observations based of sheet lengths and frequency of lift force oscillation. DOE-SBIR, ONR (monitored by Dr. Ki-Han Kim)
Structurally Governed Cell Mechanotransduction through Multiscale Modeling
Kang, John; Puskar, Kathleen M.; Ehrlicher, Allen J.; LeDuc, Philip R.; Schwartz, Russell S.
2015-01-01
Mechanotransduction has been divided into mechanotransmission, mechanosensing, and mechanoresponse, although how a cell performs all three functions using the same set of structural components is still highly debated. Here, we bridge the gap between emerging molecular and systems-level understandings of mechanotransduction through a multiscale model linking these three phases. Our model incorporates a discrete network of actin filaments and associated proteins that responds to stretching through geometric relaxation. We assess three potential activating mechanisms at mechanosensitive crosslinks as inputs to a mixture model of molecular release and benchmark each using experimental data of mechanically-induced Rho GTPase FilGAP release from actin-filamin crosslinks. Our results suggest that filamin-FilGAP mechanotransduction response is best explained by a bandpass mechanism favoring release when crosslinking angles fall outside of a specific range. Our model further investigates the difference between ordered versus disordered networks and finds that a more disordered actin network may allow a cell to more finely tune control of molecular release enabling a more robust response. PMID:25722249
Multiscale physics-based modeling of friction
NASA Astrophysics Data System (ADS)
Eriten, Melih
Frictional contacts between solids exist in nature and in a wide range of engineering applications. Friction causes energy loss, and it is the main source of wear and surface degradation which limits the lifetime of mechanical systems. Yet, friction is needed to walk, run, accelerate, slow down or stop moving systems. Whether desirable or not, friction is a very complex physical phenomenon. The behavior of systems with friction is nonlinear, and the physical mechanisms governing friction behavior span a wide range of spatial and temporal scales. A thorough study of friction should employ experimentalists and theoreticians in chemistry, materials science, tribology, mechanics, dynamics, and structural engineering. High spatial and temporal resolutions are required to capture and model essential physics of a frictional contact. However, such a detailed model is impractical in large-scale structural dynamics simulations; especially since frictional contacts can be numerous in a given application. Reduced-order models (ROMs) achieve broader applicability by compromising several aspects and accounting for the important physics. Hence, rather simple Coulomb friction is still the most ubiquitous model in the modeling and simulation literature. As an alternative, a reduced-order friction model built-up from micromechanics of surfaces is proposed in this work. Continuum-scale formulation of pre-sliding friction behavior is combined with material-strength-based friction coefficients to develop a physics-based friction model at asperity-scale. Then, the statistical summation technique is utilized to build a multiscale modeling framework. A novel joint fretting setup is designed for friction experiments in a practical setting, and the developed models are tested. Both asperity and rough surface friction models show good agreement with experimental data. The influences of materials, surface roughness and contact contamination on the friction are also studied. Finally, the
Multiscale imaging and computational modeling of blood flow in the tumor vasculature.
Kim, Eugene; Stamatelos, Spyros; Cebulla, Jana; Bhujwalla, Zaver M; Popel, Aleksander S; Pathak, Arvind P
2012-11-01
The evolution in our understanding of tumor angiogenesis has been the result of pioneering imaging and computational modeling studies spanning the endothelial cell, microvasculature and tissue levels. Many of these primary data on the tumor vasculature are in the form of images from pre-clinical tumor models that provide a wealth of qualitative and quantitative information in many dimensions and across different spatial scales. However, until recently, the visualization of changes in the tumor vasculature across spatial scales remained a challenge due to a lack of techniques for integrating micro- and macroscopic imaging data. Furthermore, the paucity of three-dimensional (3-D) tumor vascular data in conjunction with the challenges in obtaining such data from patients presents a serious hurdle for the development and validation of predictive, multiscale computational models of tumor angiogenesis. In this review, we discuss the development of multiscale models of tumor angiogenesis, new imaging techniques capable of reproducing the 3-D tumor vascular architecture with high fidelity, and the emergence of "image-based models" of tumor blood flow and molecular transport. Collectively, these developments are helping us gain a fundamental understanding of the cellular and molecular regulation of tumor angiogenesis that will benefit the development of new cancer therapies. Eventually, we expect this exciting integration of multiscale imaging and mathematical modeling to have widespread application beyond the tumor vasculature to other diseases involving a pathological vasculature, such as stroke and spinal cord injury.
Multiscale Concrete Modeling of Aging Degradation
Hammi, Yousseff; Gullett, Philipp; Horstemeyer, Mark F.
2015-07-31
In this work a numerical finite element framework is implemented to enable the integration of coupled multiscale and multiphysics transport processes. A User Element subroutine (UEL) in Abaqus is used to simultaneously solve stress equilibrium, heat conduction, and multiple diffusion equations for 2D and 3D linear and quadratic elements. Transport processes in concrete structures and their degradation mechanisms are presented along with the discretization of the governing equations. The multiphysics modeling framework is theoretically extended to the linear elastic fracture mechanics (LEFM) by introducing the eXtended Finite Element Method (XFEM) and based on the XFEM user element implementation of Giner et al. [2009]. A damage model that takes into account the damage contribution from the different degradation mechanisms is theoretically developed. The total contribution of damage is forwarded to a Multi-Stage Fatigue (MSF) model to enable the assessment of the fatigue life and the deterioration of reinforced concrete structures in a nuclear power plant. Finally, two examples are presented to illustrate the developed multiphysics user element implementation and the XFEM implementation of Giner et al. [2009].
Multiscale modeling of polyisoprene on graphite
Pandey, Yogendra Narayan; Brayton, Alexander; Doxastakis, Manolis; Burkhart, Craig; Papakonstantopoulos, George J.
2014-02-07
The local dynamics and the conformational properties of polyisoprene next to a smooth graphite surface constructed by graphene layers are studied by a multiscale methodology. First, fully atomistic molecular dynamics simulations of oligomers next to the surface are performed. Subsequently, Monte Carlo simulations of a systematically derived coarse-grained model generate numerous uncorrelated structures for polymer systems. A new reverse backmapping strategy is presented that reintroduces atomistic detail. Finally, multiple extensive fully atomistic simulations with large systems of long macromolecules are employed to examine local dynamics in proximity to graphite. Polyisoprene repeat units arrange close to a parallel configuration with chains exhibiting a distribution of contact lengths. Efficient Monte Carlo algorithms with the coarse-grain model are capable of sampling these distributions for any molecular weight in quantitative agreement with predictions from atomistic models. Furthermore, molecular dynamics simulations with well-equilibrated systems at all length-scales support an increased dynamic heterogeneity that is emerging from both intermolecular interactions with the flat surface and intramolecular cooperativity. This study provides a detailed comprehensive picture of polyisoprene on a flat surface and consists of an effort to characterize such systems in atomistic detail.
Multiscale Imaging and Computational Modeling of Blood Flow in the Tumor Vasculature
Kim, Eugene; Stamatelos, Spyros; Cebulla, Jana; Bhujwalla, Zaver M.; Popel, Aleksander S.; Pathak, Arvind P.
2013-01-01
The evolution in our understanding of tumor angiogenesis has been the result of pioneering imaging and computational modeling studies spanning the endothelial cell, microvasculature and tissue levels. Many of these primary data on the tumor vasculature are in the form of images from pre-clinical tumor models that provide a wealth of qualitative and quantitative information in many dimensions and across different spatial scales. However, until recently, the visualization of changes in the tumor vasculature across spatial scales remained a challenge due to a lack of techniques for integrating micro- and macroscopic imaging data. Furthermore, the paucity of three-dimensional (3-D) tumor vascular data in conjunction with the challenges in obtaining such data from patients presents a serious hurdle for the development and validation of predictive, multiscale computational models of tumor angiogenesis. In this review, we discuss the development of multiscale models of tumor angiogenesis, new imaging techniques capable of reproducing the 3-D tumor vascular architecture with high fidelity, and the emergence of “image-based models”of tumor blood flow and molecular transport. Collectively, these developments are helping us gain a fundamental understanding of the cellular and molecular regulation of tumor angiogenesis that will benefit the development of new cancer therapies. Eventually, we expect this exciting integration of multiscale imaging and mathematical modeling to have widespread application beyond the tumor vasculature to other diseases involving a pathological vasculature, such as stroke and spinal cord injury. PMID:22565817
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.
Multiscale Modeling of UHTC: Thermal Conductivity
NASA Technical Reports Server (NTRS)
Lawson, John W.; Murry, Daw; Squire, Thomas; Bauschlicher, Charles W.
2012-01-01
We are developing a multiscale framework in computational modeling for the ultra high temperature ceramics (UHTC) ZrB2 and HfB2. These materials are characterized by high melting point, good strength, and reasonable oxidation resistance. They are candidate materials for a number of applications in extreme environments including sharp leading edges of hypersonic aircraft. In particular, we used a combination of ab initio methods, atomistic simulations and continuum computations to obtain insights into fundamental properties of these materials. Ab initio methods were used to compute basic structural, mechanical and thermal properties. From these results, a database was constructed to fit a Tersoff style interatomic potential suitable for atomistic simulations. These potentials were used to evaluate the lattice thermal conductivity of single crystals and the thermal resistance of simple grain boundaries. Finite element method (FEM) computations using atomistic results as inputs were performed with meshes constructed on SEM images thereby modeling the realistic microstructure. These continuum computations showed the reduction in thermal conductivity due to the grain boundary network.
Multiscale model of platelet translocation and collision
NASA Astrophysics Data System (ADS)
Wang, Weiwei; Mody, Nipa A.; King, Michael R.
2013-07-01
The tethering of platelets on the injured vessel surface mediated by glycoprotein Ibα (GPIbα) - Von Willebrand factor (vWF) bonds, as well as the interaction between flowing platelets and adherent platelets, are two key events that take place immediately following blood vessel injury. This early-stage platelet deposition and accumulation triggers the initiation of hemostasis, a self-defensive mechanism to prevent the body from excessive blood loss. To understand and predict this complex process, one must integrate experimentally determined information on the mechanics and biochemical kinetics of participating receptors over very small time frames (1-1000 μs) and length scales (10-100 nm), to collective phenomena occurring over seconds and tens of microns. In the present study, a unique three dimensional multiscale computational model, Platelet Adhesive Dynamics (PAD), was applied to elucidate the unique physics of (i) a non-spherical, disk-shaped platelet interacting and tethering onto the damaged vessel wall followed by (ii) collisional interactions between a flowing platelet with a downstream adherent platelet. By analyzing numerous simulations under different physiological conditions, we conclude that the platelet's unique spheroid-shape provides heterogeneous, orientation-dependent translocation (rolling) behavior which enhances cell-wall interactions. We also conclude that platelet-platelet near field interactions are critical for cell-cell communication during the initiation of microthrombi. The PAD model described here helps to identify the physical factors that control the initial stages of platelet capture during this process.
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.
Multiscale mechanical modeling of soft biological tissues
NASA Astrophysics Data System (ADS)
Stylianopoulos, Triantafyllos
2008-10-01
Soft biological tissues include both native and artificial tissues. In the human body, tissues like the articular cartilage, arterial wall, and heart valve leaflets are examples of structures composed of an underlying network of collagen fibers, cells, proteins and molecules. Artificial tissues are less complex than native tissues and mainly consist of a fiber polymer network with the intent of replacing lost or damaged tissue. Understanding of the mechanical function of these materials is essential for many clinical treatments (e.g. arterial clamping, angioplasty), diseases (e.g. arteriosclerosis) and tissue engineering applications (e.g. engineered blood vessels or heart valves). This thesis presents the derivation and application of a multiscale methodology to describe the macroscopic mechanical function of soft biological tissues incorporating directly their structural architecture. The model, which is based on volume averaging theory, accounts for structural parameters such as the network volume fraction and orientation, the realignment of the fibers in response to strain, the interactions among the fibers and the interactions between the fibers and the interstitial fluid in order to predict the overall tissue behavior. Therefore, instead of using a constitutive equation to relate strain to stress, the tissue microstructure is modeled within a representative volume element (RVE) and the macroscopic response at any point in the tissue is determined by solving a micromechanics problem in the RVE. The model was applied successfully to acellular collagen gels, native blood vessels, and electrospun polyurethane scaffolds and provided accurate predictions for permeability calculations in isotropic and oriented fiber networks. The agreement of model predictions with experimentally determined mechanical properties provided insights into the mechanics of tissues and tissue constructs, while discrepancies revealed limitations of the model framework.
Multi-scale models for cell adhesion
NASA Astrophysics Data System (ADS)
Wu, Yinghao; Chen, Jiawen; Xie, Zhong-Ru
2014-03-01
The interactions of membrane receptors during cell adhesion play pivotal roles in tissue morphogenesis during development. Our lab focuses on developing multi-scale models to decompose the mechanical and chemical complexity in cell adhesion. Recent experimental evidences show that clustering is a generic process for cell adhesive receptors. However, the physical basis of such receptor clustering is not understood. We introduced the effect of molecular flexibility to evaluate the dynamics of receptors. By delivering new theory to quantify the changes of binding free energy in different cellular environments, we revealed that restriction of molecular flexibility upon binding of membrane receptors from apposing cell surfaces (trans) causes large entropy loss, which dramatically increases their lateral interactions (cis). This provides a new molecular mechanism to initialize receptor clustering on the cell-cell interface. By using the subcellular simulations, we further found that clustering is a cooperative process requiring both trans and cis interactions. The detailed binding constants during these processes are calculated and compared with experimental data from our collaborator's lab.
Computational technology of multiscale modeling the gas flows in microchannels
NASA Astrophysics Data System (ADS)
Podryga, V. O.
2016-11-01
The work is devoted to modeling the gas mixture flows in engineering microchannels under conditions of many scales of computational domain. The computational technology of using the multiscale approach combining macro - and microscopic models is presented. At macrolevel the nature of the flow and the external influence on it are considered. As a model the system of quasigasdynamic equations is selected. At microlevel the correction of gasdynamic parameters and the determination of boundary conditions are made. As a numerical model the Newton's equations and the molecular dynamics method are selected. Different algorithm types used for implementation of multiscale modeling are considered. The results of the model problems for separate stages are given.
AUGUSTO'S Sundial: Image-Based Modeling for Reverse Engeneering Purposes
NASA Astrophysics Data System (ADS)
Baiocchi, V.; Barbarella, M.; Del Pizzo, S.; Giannone, F.; Troisi, S.; Piccaro, C.; Marcantonio, D.
2017-02-01
A photogrammetric survey of a unique archaeological site is reported in this paper. The survey was performed using both a panoramic image-based solution and by classical procedure. The panoramic image-based solution was carried out employing a commercial solution: the Trimble V10 Imaging Rover (IR). Such instrument is an integrated cameras system that captures 360 degrees digital panoramas, composed of 12 images, with a single push. The direct comparison of the point clouds obtained with traditional photogrammetric procedure and V10 stations, using the same GCP coordinates has been carried out in Cloud Compare, open source software that can provide the comparison between two point clouds supplied by all the main statistical data. The site is a portion of the dial plate of the "Horologium Augusti" inaugurated in 9 B.C.E. in the area of Campo Marzio and still present intact in the same position, in a cellar of a building in Rome, around 7 meter below the present ground level.
Multiscale Modeling in the Clinic: Drug Design and Development
Clancy, Colleen E.; An, Gary; Cannon, William R.; Liu, Yaling; May, Elebeoba E.; Ortoleva, Peter; Popel, Aleksander S.; Sluka, James P.; Su, Jing; Vicini, Paolo; Zhou, Xiaobo; Eckmann, David M.
2016-02-17
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 to 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.
Multiscale modeling of growth plate cartilage mechanobiology.
Gao, Jie; Williams, John L; Roan, Esra
2017-04-01
Growth plate chondrocytes are responsible for bone growth through proliferation and differentiation. However, the way they experience physiological loads and regulate bone formation, especially during the later developmental phase in the mature growth plate, is still under active investigation. In this study, a previously developed multiscale finite element model of the growth plate is utilized to study the stress and strain distributions within the cartilage at the cellular level when rapidly compressed to 20 %. Detailed structures of the chondron are included in the model to examine the hypothesis that the same combination of mechanoregulatory signals shown to maintain cartilage or stimulate osteogenesis or fibrogenesis in the cartilage anlage or fracture callus also performs the same function at the cell level within the chondrons of growth plate cartilage. Our cell-level results are qualitatively and quantitatively in agreement with tissue-level theories when both hydrostatic cellular stress and strain are considered simultaneously in a mechanoregulatory phase diagram similar to that proposed at the tissue level by Claes and Heigele for fracture healing. Chondrocytes near the reserve/proliferative zone border are subjected to combinations of high compressive hydrostatic stresses ([Formula: see text] MPa), and cell height and width strains of [Formula: see text] to [Formula: see text] respectively, that maintain cartilage and keep chondrocytes from differentiating and provide conditions favorable for cell division, whereas chondrocytes closer to the hypertrophic/calcified zone undergo combinations of lower compressive hydrostatic stress ([Formula: see text] MPa) and cell height and width strains as low as [Formula: see text] to +4 %, respectively, that promote cell differentiation toward osteogenesis; cells near the outer periphery of the growth plate structure experience a combination of low compressive hydrostatic stress (0 to [Formula: see text] MPa) and
Stochastic multiscale modeling of polycrystalline materials
NASA Astrophysics Data System (ADS)
Wen, Bin
provides a new outlook to multi-scale materials modeling accounting for microstructure and process uncertainties. Predictive materials modeling will accelerate the development of new materials and processes for critical applications in industry.
Nanomechanics and Multiscale Modeling of Sustainable Concretes
NASA Astrophysics Data System (ADS)
Zanjani Zadeh, Vahid
The work presented in this dissertation is aimed to implement and further develop the recent advances in material characterization for porous and heterogeneous materials and apply these advances to sustainable concretes. The studied sustainable concretes were concrete containing fly ash and slag, Kenaf fiber reinforced concrete, and lightweight aggregate concrete. All these cement-based materials can be categorized as sustainable concrete, by achieving concrete with high strength while reducing cement consumption. The nanoindentation technique was used to infer the nanomechanical properties of the active hydration phases in bulk cement paste. Moreover, the interfacial transition zone (ITZ) of lightweight aggregate, normal aggregate, and Kenaf fibers were investigated using nanoindentation and imagine techniques, despite difficulties regarding characterizing this region. Samples were also tested after exposure to high temperature to evaluate the damage mechanics of sustainable concretes. It has been shown that there is a direct correlation between the nature of the nanoscale structure of a cement-based material with its macroscopic properties. This was addressed in two steps in this dissertation: (i) Nanoscale characterization of sustainable cementitious materials to understand the different role of fly ash, slag, lightweight aggregate, and Kenaf fibers on nanoscale (ii) Link the nanoscale mechanical properties to macroscale ones with multiscale modeling. The grid indentation technique originally developed for normal concrete was extended to sustainable concretes with more complex microstructure. The relation between morphology of cement paste materials and submicron mechanical properties, indentation modulus, hardness, and dissipated energy is explained in detail. Extensive experimental and analytical approaches were focused on description of the materials' heterogeneous microstructure as function of their composition and physical phenomenon. Quantitative
A Multiscale Meshfree Approach for Modeling Fragment Penetration into Ultra High-Strength Concrete
2011-09-01
material deformation and damage mechanisms, multiscale homogenization based on the energy bridging theory pertinent to fragment penetration modeling...problems associated with contact-impact simulations as well as multiscale modeling of material damage have been performed to examine the effectiveness...15 3 Multiscale Microcrack Informed Damage Model..................................................................... 18 Model
Multiscale Constitutive Modeling of Asphalt Concrete
NASA Astrophysics Data System (ADS)
Underwood, Benjamin Shane
Multiscale modeling of asphalt concrete has become a popular technique for gaining improved insight into the physical mechanisms that affect the material's behavior and ultimately its performance. This type of modeling considers asphalt concrete, not as a homogeneous mass, but rather as an assemblage of materials at different characteristic length scales. For proper modeling these characteristic scales should be functionally definable and should have known properties. Thus far, research in this area has not focused significant attention on functionally defining what the characteristic scales within asphalt concrete should be. Instead, many have made assumptions on the characteristic scales and even the characteristic behaviors of these scales with little to no support. This research addresses these shortcomings by directly evaluating the microstructure of the material and uses these results to create materials of different characteristic length scales as they exist within the asphalt concrete mixture. The objectives of this work are to; 1) develop mechanistic models for the linear viscoelastic (LVE) and damage behaviors in asphalt concrete at different length scales and 2) develop a mechanistic, mechanistic/empirical, or phenomenological formulation to link the different length scales into a model capable of predicting the effects of microstructural changes on the linear viscoelastic behaviors of asphalt concrete mixture, e.g., a microstructure association model for asphalt concrete mixture. Through the microstructural study it is found that asphalt concrete mixture can be considered as a build-up of three different phases; asphalt mastic, fine aggregate matrix (FAM), and finally the coarse aggregate particles. The asphalt mastic is found to exist as a homogenous material throughout the mixture and FAM, and the filler content within this material is consistent with the volumetric averaged concentration, which can be calculated from the job mix formula. It is also
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.
Representative Structural Element - A New Paradigm for Multi-Scale Structural Modeling
2016-07-05
approach for efficient high-fidelity modeling of aerospace structures featuring multiscale heterogeneities and anisotropy. The proposed approach uses... efficiency ; representative structural element; micromechanics. 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF PAGES 469 19a...multiscale structural modeling to provide a systematic approach for efficient high-fidelity modeling of aerospace structures featuring multiscale
A Liver-centric Multiscale Modeling Framework for Xenobiotics ...
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.
Multiscale modeling of thermal conductivity of polycrystalline graphene sheets.
Mortazavi, Bohayra; Pötschke, Markus; Cuniberti, Gianaurelio
2014-03-21
We developed a multiscale approach to explore the effective thermal conductivity of polycrystalline graphene sheets. By performing equilibrium molecular dynamics (EMD) simulations, the grain size effect on the thermal conductivity of ultra-fine grained polycrystalline graphene sheets is investigated. Our results reveal that the ultra-fine grained graphene structures have thermal conductivity one order of magnitude smaller than that of pristine graphene. Based on the information provided by the EMD simulations, we constructed finite element models of polycrystalline graphene sheets to probe the thermal conductivity of samples with larger grain sizes. Using the developed multiscale approach, we also investigated the effects of grain size distribution and thermal conductivity of grains on the effective thermal conductivity of polycrystalline graphene. The proposed multiscale approach on the basis of molecular dynamics and finite element methods could be used to evaluate the effective thermal conductivity of polycrystalline graphene and other 2D structures.
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.
Multiscale modeling and simulation of brain blood flow
Perdikaris, Paris; Grinberg, Leopold; Karniadakis, George Em
2016-02-15
The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process taking place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.
Multiscale modeling and simulation of brain blood flow
Perdikaris, Paris; Grinberg, Leopold; Karniadakis, George Em
2016-01-01
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. PMID:26909005
Multiscale modeling and simulation of brain blood flow.
Perdikaris, Paris; Grinberg, Leopold; Karniadakis, George Em
2016-02-01
The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process taking place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.
Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites
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
Development of Improved Algorithms and Multiscale Modeling Capability with SUNTANS
2015-09-30
1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Development of Improved Algorithms and Multiscale...a wide range of scales through use of accurate numerical methods and high- performance computational algorithms . The tool will be applied to study...dissipation. OBJECTIVES The primary objective is to enhance the capabilities of the SUNTANS model through development of algorithms to study
A Liver-centric Multiscale Modeling Framework for Xenobiotics
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...
Image-Based Empirical Modeling of the Plasmasphere
NASA Technical Reports Server (NTRS)
Adrian, Mark L.; Gallagher, D. L.
2008-01-01
A new suite of empirical models of plasmaspheric plasma based on remote, global images from the IMAGE EUV instrument is proposed for development. The purpose of these empirical models is to establish the statistical properties of the plasmasphere as a function of conditions. This suite of models will mark the first time the plasmaspheric plume is included in an empirical model. Development of these empirical plasmaspheric models will support synoptic studies (such as for wave propagation and growth, energetic particle loss through collisions and dust transport as influenced by charging) and serves as a benchmark against which physical models can be tested. The ability to know that a specific global density distribution occurs in response to specific magnetospheric and solar wind factors is a huge advantage over all previous in-situ based empirical models. The consequence of creating these new plasmaspheric models will be to provide much higher fidelity and much richer quantitative descriptions of the statistical properties of plasmaspheric plasma in the inner magnetosphere, whether that plasma is in the main body of the plasmasphere, nearby during recovery or in the plasmaspheric plume. Model products to be presented include statistical probabilities for being in the plasmasphere, near thermal He+ density boundaries and the complexity of its spatial structure.
Image-based modeling of objects and human faces
NASA Astrophysics Data System (ADS)
Zhang, Zhengyou
2000-12-01
In this paper, provided is an overview of our project on 3D object and face modeling from images taken by a free-moving camera. We strive to advance the state of the art in 3D computer vision, and develop flexible and robust techniques for ordinary users to gain 3D experience from a ste of casually collected 2D images. Applications include product advertisement on the Web, virtual conference, and interactive games. We briefly cover the following topics: camera calibration, stereo rectification, image matching, 3D photo editing, object modeling, and face modeling. Demos on the last three topics will be shown during the conference.
NASA Astrophysics Data System (ADS)
Lan, Hongzhi; Merkow, Jameson; Updegrove, Adam; Schiavazzi, Daniele; Wilson, Nathan; Shadden, Shawn; Marsden, Alison
2015-11-01
SimVascular (www.simvascular.org) is currently the only fully open source software package that provides a complete pipeline from medical image based modeling to patient specific blood flow simulation and analysis. It was initially released in 2007 and has contributed to numerous advances in fundamental hemodynamics research, surgical planning, and medical device design. However, early versions had several major barriers preventing wider adoption by new users, large-scale application in clinical and research studies, and educational access. In the past years, SimVascular 2.0 has made significant progress by integrating open source alternatives for the expensive commercial libraries previously required for anatomic modeling, mesh generation and the linear solver. In addition, it simplified the across-platform compilation process, improved the graphical user interface and launched a comprehensive documentation website. Many enhancements and new features have been incorporated for the whole pipeline, such as 3-D segmentation, Boolean operation for discrete triangulated surfaces, and multi-scale coupling for closed loop boundary conditions. In this presentation we will briefly overview the modeling/simulation pipeline and advances of the new SimVascular 2.0.
Mathematical and Numerical Analyses of Peridynamics for Multiscale Materials Modeling
Du, Qiang
2014-11-12
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 which 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
Image-Based Structural Modeling of the Cardiac Purkinje Network
Liu, Benjamin R.; Cherry, Elizabeth M.
2015-01-01
The Purkinje network is a specialized conduction system within the heart that ensures the proper activation of the ventricles to produce effective contraction. Its role during ventricular arrhythmias is less clear, but some experimental studies have suggested that the Purkinje network may significantly affect the genesis and maintenance of ventricular arrhythmias. Despite its importance, few structural models of the Purkinje network have been developed, primarily because current physical limitations prevent examination of the intact Purkinje network. In previous modeling efforts Purkinje-like structures have been developed through either automated or hand-drawn procedures, but these networks have been created according to general principles rather than based on real networks. To allow for greater realism in Purkinje structural models, we present a method for creating three-dimensional Purkinje networks based directly on imaging data. Our approach uses Purkinje network structures extracted from photographs of dissected ventricles and projects these flat networks onto realistic endocardial surfaces. Using this method, we create models for the combined ventricle-Purkinje system that can fully activate the ventricles through a stimulus delivered to the Purkinje network and can produce simulated activation sequences that match experimental observations. The combined models have the potential to help elucidate Purkinje network contributions during ventricular arrhythmias. PMID:26583120
Modeling Crack Propagation in Polycrystalline Microstructure Using Variational Multiscale Method
Sun, S.; Sundararaghavan, V.
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. 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
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.
Final Report for Integrated Multiscale Modeling of Molecular Computing Devices
Glotzer, Sharon C.
2013-08-28
In collaboration with researchers at Vanderbilt University, North Carolina State University, Princeton and Oakridge National Laboratory we developed multiscale modeling and simulation methods capable of modeling the synthesis, assembly, and operation of molecular electronics devices. Our role in this project included the development of coarse-grained molecular and mesoscale models and simulation methods capable of simulating the assembly of millions of organic conducting molecules and other molecular components into nanowires, crossbars, and other organized patterns.
Multiscale numerical modeling of the spherically symmetric cryosurgery problem
NASA Astrophysics Data System (ADS)
Kudryashov, N. A.; Shilnikov, K. E.
2017-01-01
The work is concerned with the numerical studying of the cryogenic biotissue destruction by a spherically symmetric tip. The multiscale bioheat transfer model is used for the describing of the biological solutions crystallization features. An explicit finite volume based approximation is applied for the numerical modeling of the processes taking place during the cryosurgery. The phase averaging method is applied as an computationally economic approach for the numerical modeling of the problem under study.
Multiscale Combination of Physically-Based Registration and Deformation Modeling
Tsap, L.; Goldgof, D.B.; Sarkar, S.
1999-11-08
In this paper the authors present a novel multiscale approach to recovery of nonrigid motion from sequences of registered intensity and range images. The main idea of the approach is that a finite element (FEM) model can naturally handle both registration and deformation modeling using a single model-driving strategy. The method includes a multiscale iterative algorithm based on analysis of the undirected Hausdorff distance to recover correspondences. The method is evaluated with respect to speed, accuracy, and noise sensitivity. Advantages of the proposed approach are demonstrated using man-made elastic materials and human skin motion. Experiments with regular grid features are used for performance comparison with a conventional approach (separate snakes and FEM models). It is shown that the new method does not require a grid and can adapt the model to available object features.
Image-based numerical modeling of HIFU-induced lesions
NASA Astrophysics Data System (ADS)
Almekkaway, Mohamed K.; Shehata, Islam A.; Haritonova, Alyona; Ballard, John; Casper, Andrew; Ebbini, Emad
2017-03-01
Atherosclerosis is a chronic vascular disease affecting large and medium sized arteries. Several treatment options are already available for treatment of this disease. Targeting atherosclerotic plaques by high intensity focused ultrasound (HIFU) using dual mode ultrasound arrays (DMUA) was recently introduced in literature. We present a finite difference time domain (FDTD) simulation modeling of the wave propagation in heterogeneous medium from the surface of a 3.5 MHz array prototype with 32-elements. After segmentation of the ultrasound image obtained for the treatment region in-vivo, we integrated this anatomical information into our simulation to account for different parameters that may be caused by these multi-region anatomical complexities. The simulation program showed that HIFU was able to induce damage in the prefocal region instead of the target area. The HIFU lesions, as predicted by our simulation, were well correlated with the actual damage detected in histology.
Blood Flow: Multi-scale Modeling and Visualization (July 2011)
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 blood 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.
Multiscale geometric modeling of macromolecules II: Lagrangian representation
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
Image-based modeling of radiation-induced foci
NASA Astrophysics Data System (ADS)
Costes, Sylvain; Cucinotta, Francis A.; Ponomarev, Artem; Barcellos-Hoff, Mary Helen; Chen, James; Chou, William; Gascard, Philippe
Several proteins involved in the response to DNA double strand breaks (DSB) form microscopically visible nuclear domains, or foci, after exposure to ionizing radiation. Radiation-induced foci (RIF) are believed to be located where DNA damage occurs. To test this assumption, we used Monte Carlo simulations to predict the spatial distribution of DSB in human nuclei exposed to high or low-LET radiation. We then compared these predictions to the distribution patterns of three DNA damage sensing proteins, i.e. 53BP1, phosphorylated ATM and γH2AX in human mammary epithelial. The probability to induce DSB can be derived from DNA fragment data measured experimentally by pulsed-field gel electrophoresis. We first used this probability in Monte Carlo simulations to predict DSB locations in synthetic nuclei geometrically described by a complete set of human chromosomes, taking into account microscope optics from real experiments. Simulations showed a very good agreement for high-LET, predicting 0.7 foci/µm along the path of a 1 GeV/amu Fe particle against measurement of 0.69 to 0.82 foci/µm for various RIF 5 min following exposure (LET 150 keV/µm). On the other hand, discrepancies were shown in foci frequency for low-LET, with measurements 20One drawback using a theoretical model for the nucleus is that it assumes a simplistic and static pattern for DNA densities. However DNA damage pattern is highly correlated to DNA density pattern (i.e. the more DNA, the more likely to have a break). Therefore, we generalized our Monte Carlo approach to real microscope images, assuming pixel intensity of DAPI in the nucleus was directly proportional to the amount of DNA in that pixel. With such approach we could predict DNA damage pattern in real images on a per nucleus basis. Since energy is randomly deposited along high-LET particle paths, RIF along these paths should also be randomly distributed. As expected, simulations produced DNA-weighted random (Poisson) distributions. In
Tawhai, Merryn; Bischoff, Jeff; Einstein, Daniel R.; Erdemir, Ahmet; Guess, Trent; Reinbolt, Jeff
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.
Automatic brain segmentation and validation: image-based versus atlas-based deformable models
NASA Astrophysics Data System (ADS)
Aboutanos, Georges B.; Dawant, Benoit M.
1997-04-01
Due to the complexity of the brain surface, there is at present no segmentation method that proves to work automatically and consistently on any 3-D magnetic resonance (MR) images of the head. There is a definite lack of validation studies related to automatic brain extraction. In this work we present an image-base automatic method for brain segmentation and use its results as an input to a deformable model method which we call image-based deformable model. Combining image-based methods with a deformable model can lead to a robust segmentation method without requiring registration of the image volumes into a standardized space, the automation of which remains challenging for pathological cases. We validate our segmentation results on 3-D MP-RAGE (magnetization-prepared rapid gradient-echo) volumes for the image model prior- and post-deformation and compare it to an atlas model prior- and post-deformation. Our validation is based on volume measurement comparison to manually segmented data. Our analysis shows that the improvement afforded by the deformable model methods are statistically significant, however there are no significant differences between the image-based and atlas-based deformable model methods.
Moist multi-scale models for the hurricane embryo
Majda, Andrew J.; Xing, Yulong; Mohammadian, Majid
2010-01-01
Determining the finite-amplitude preconditioned states in the hurricane embryo, which lead to tropical cyclogenesis, is a central issue in contemporary meteorology. In the embryo there is competition between different preconditioning mechanisms involving hydrodynamics and moist thermodynamics, which can lead to cyclogenesis. Here systematic asymptotic methods from applied mathematics are utilized to develop new simplified moist multi-scale models starting from the moist anelastic equations. Three interesting multi-scale models emerge in the analysis. The balanced mesoscale vortex (BMV) dynamics and the microscale balanced hot tower (BHT) dynamics involve simplified balanced equations without gravity waves for vertical vorticity amplification due to moist heat sources and incorporate nonlinear advective fluxes across scales. The BMV model is the central one for tropical cyclogenesis in the embryo. The moist mesoscale wave (MMW) dynamics involves simplified equations for mesoscale moisture fluctuations, as well as linear hydrostatic waves driven by heat sources from moisture and eddy flux divergences. A simplified cloud physics model for deep convection is introduced here and used to study moist axisymmetric plumes in the BHT model. A simple application in periodic geometry involving the effects of mesoscale vertical shear and moist microscale hot towers on vortex amplification is developed here to illustrate features of the coupled multi-scale models. These results illustrate the use of these models in isolating key mechanisms in the embryo in a simplified content.
Blood Flow: Multi-scale Modeling and Visualization
2010-01-01
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 developing methods for multi-scale computations, techniques for multi-scale visualizations must be designed. This animation presents early results of joint efforts of teams from Brown University and Argonne National Laboratory to develop a multi-scale visualization methodology. It illustrates a flow of healthy (red) and diseased (blue) blood cells with a Dissipative Particle Dynamics (DPD) method. Each blood cell is represented by a mesh made of 500 DPD-particles, and small spheres show a sub-set of the DPD particles representing the blood plasma, while instantaneous streamlines and slices represent the ensemble average velocity. Credits: Science: Leopold Grinberg and George Karniadakis, Brown University Visualization: Joseph A. Insley and Michael E. Papka, Argonne National Laboratory This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-06CH11357. This research was supported in part by the National Science Foundation through the PetaApps program and used TeraGrid resources provided by National Institute for Computational Sciences.
Multiscale Models for Reactive Transport in Porous Media
NASA Astrophysics Data System (ADS)
Tartakovsky, A. M.
2012-12-01
Under certain conditions, Darcy-scale reactive transport equations cannot provide sufficiently accurate predictions of multiphase flow and reactive transport. Pore-scale models are based on fundamental conservation laws and, in general, are more accurate than the Darcy-scale models. But, for domains of practical importance, number of unknowns in the pore-sale models may be on the order of billions or trillions and a direct solution of the pore-scale equations is often unfeasible even on modern super-computes. Several novel multiscale methods including a Langevin approach and a dimension reduction method based on a computational closure will be presented. The purpose of these methods is to provide an accurate description of the system averages while retaining critical pore-scale information. The advantages, range of applicability and limitations of the mentioned above multiscale methods will be discussed.
Multiscale Modeling of Irradiation effects in Fusion Materials
Hussein Zbib
2004-12-23
The aim of this collaborative research work was to apply predictive, physically based multiscale modeling to improve understanding of the underlying mechanisms of material changes in the fusion environment, with the ultimate objective to aid development of advanced materials. The multiscale modeling methodology involved a hierarchical approach, integrating ab initio electronic structure calculations, molecular dynamics (MD) simulations, kinetic Monte Carlo (KMC), and three dimensional dislocation dynamics (DD) simulations, over the relevant length and time scales to model the fates of defects and solutes (including hydrogen and helium) and thus, predict microstructural evolution in ferritic/martensitic and vanadium based alloys. The main task at WSU was to investigate changes in mechanical properties as a result of the production of a varied population of nanostructural features and to be obtained from three dimensional dislocation dynamics simulation (DD). The initial dislocation structure and microstructure could be obtained from electron microscopy characterization and the appropriate nanostructural features produced during irradiation are introduced from predictions of the multiscale modeling. The dislocation structure was then allowed to evolve under an applied load, taking into account all possible forces and reactions between the dislocations with the radiation induced nanostructure as well as network dislocations. In this manner, quantitative predictions of irradiation hardening would result without the use of empirical constants within the framework of dispersed barrier hardening models.
Multiscale Modeling of Particles Embedded in High Speed Flows
NASA Astrophysics Data System (ADS)
Davis, Sean; Sen, Oishik; Jacobs, Gustaaf; Udaykumar, H. S.
2015-06-01
Problems involving propagation of shock waves through a cloud of particles are inherently multiscale. The system scale is governed by macro-scale conservation equations, which average over solid and fluid phases. The averaging process results in source terms that represent the unresolved momentum exchange between the solid phase and the fluid phase. Typically, such source terms are modeled using empirical correlations derived from physical experiments conducted in a limited parameter space. The focus of the current research is to advance the multiscale modeling of shocked particle-laden gas flows; particle- (i.e. meso-)scale computations are performed to resolve the dynamics of ensembles of particles and closure laws are obtained from the meso-scale for use in the macro-scale equations. Closure models are constructed from meso-scale simulations using the Dynamic Kriging method. The presentation will demonstrate the multiscale approach by connecting meso-scale simulations to an Eulerian-Lagrangian macro-scale model of particle laden flows. The technique is applied to study shock interactions with particle curtains in shock tubes and the results are compared with experimental data in such systems. We gratefully acknowledge the financial support by the Air Force Office of Scientific Research under Grant Number FA9550-12-1-0115 and the National Science Foundation under grant number DMS-115631.
Cohesive Zone Approach to Multiscale Modeling of Nanotube Reinforced Composites
2007-11-18
2007 FINAL Aug 1, 2004 to July 31 , 2005 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Cohesive Zone Approach to Multiscale Modeling of Nanotube Reinforced... 8050 11. SPONSOR/MONITOR’S REPORT ~ NUMBER(S) 12. DISTRIBUTION I AVAILABILITY STATEMENT Unlimited AFRL-SR-AR-TR-07_0 43 6 13. SUPPLEMENTARY NOTES 14...been applied to study CNTs and CNT based composites, which are essentially nanoscale systems. For example, Yakobson [ 5 ] has shown that predictions of
Multiscale Modeling of Armor Ceramics: Focus on AlON
2011-09-01
2003: Multiple Material Marching Cubes Algorithm . Int. J. Numer . Meth. Eng., 58(2), 189–207. NO. OF COPIES ORGANIZATION 9 1 DEFENSE...Army Science Conference, Orlando, FL, 29 November–2 December 2010. 14. ABSTRACT The computational modeling linkage from the atomistic to the...controlled processing. This report will review results from an internal multiscale computational program in first-principles design of armor ceramics
Multiscale Aspects of Modeling Gas-Phase Nanoparticle Synthesis
Buesser, B.; Gröhn, A.J.
2013-01-01
Aerosol reactors are utilized to manufacture nanoparticles in industrially relevant quantities. The development, understanding and scale-up of aerosol reactors can be facilitated with models and computer simulations. This review aims to provide an overview of recent developments of models and simulations and discuss their interconnection in a multiscale approach. A short introduction of the various aerosol reactor types and gas-phase particle dynamics is presented as a background for the later discussion of the models and simulations. Models are presented with decreasing time and length scales in sections on continuum, mesoscale, molecular dynamics and quantum mechanics models. PMID:23729992
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.; Kumar, S.; Lapenta, W.; Li, X.; Matsui, T.; Rienecker, M.; Shen, B.W.; Shi, J.J.; Simpson, J.; Zeng, X.
2008-01-01
Numerical cloud resolving models (CRMs), which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that CRMs agree with observations in simulating various types of clouds and cloud systems from different geographic locations. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that Numerical Weather Prediction (NWP) and regional scale model can be run in grid size similar to cloud resolving model through nesting technique. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a szrper-parameterization or multi-scale modeling -framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign can provide initial conditions as well as validation through utilizing the Earth Satellite simulators. At Goddard, we have developed a multi-scale modeling system with unified physics. The modeling system consists a coupled GCM-CRM (or MMF); a state-of-the-art weather research forecast model (WRF) and a cloud-resolving model (Goddard Cumulus Ensemble model). In these models, the same microphysical schemes (2ICE, several 3ICE), radiation (including explicitly calculated cloud optical properties), and surface models are applied. In addition, a comprehensive unified Earth Satellite
Multiscale modeling for materials design: Molecular square catalysts
NASA Astrophysics Data System (ADS)
Majumder, Debarshi
In a wide variety of materials, including a number of heterogeneous catalysts, the properties manifested at the process scale are a consequence of phenomena that occur at different time and length scales. Recent experimental developments allow materials to be designed precisely at the nanometer scale. However, the optimum design of such materials requires capabilities to predict the properties at the process scale based on the phenomena occurring at the relevant scales. The thesis research reported here addresses this need to develop multiscale modeling strategies for the design of new materials. As a model system, a new system of materials called molecular squares was studied in this research. Both serial and parallel multiscale strategies and their components were developed as parts of this work. As a serial component, a parameter estimation tool was developed that uses a hierarchical protocol and consists of two different search elements: a global search method implemented using a genetic algorithm that is capable of exploring large parametric space, and a local search method using gradient search techniques that accurately finds the optimum in a localized space. As an essential component of parallel multiscale modeling, different standard as well as specialized computational fluid dynamics (CFD) techniques were explored and developed in order to identify a technique that is best suited to solve a membrane reactor model employing layered films of molecular squares as the heterogeneous catalyst. The coupled set of non-linear partial differential equations (PDEs) representing the continuum model was solved numerically using three different classes of methods: a split-step method using finite difference (FD); domain decomposition in two different forms, one involving three overlapping subdomains and the other involving a gap-tooth scheme; and the multiple-timestep method that was developed in this research. The parallel multiscale approach coupled continuum
Multiscale model updating of a curved highway bridge
NASA Astrophysics Data System (ADS)
Mensah-Bonsu, Priscilla; Jang, Shinae
2012-04-01
Finite element model updating based on a multi-scale data is demonstrated on a skewed in-service highway bridge. The multi-scale data approach provides an evidence-based method to create a bound of model class to ensure that the optimum model retains physical connectivity to the real structure. The need for this hybrid approach to model selection comes from the challenges of applying model updating to online structural health monitoring (SHM) strategy based on output-only measurements of in-service highway bridges, which should consider various uncertainties. In vibration-based FE model updating methods, the optimum model is selected by minimizing the error between modal parameters of the model and the real structure. A major drawback of model selection is the probability that the optimum model has no physical connectivity with the real structure. This is because a large set of updating parameters is required to increase accuracy. In this paper, an evidence-based approach to model selection using temperature-induced tilts is implemented in which the cyclical static behavior of a bridge is used to create a bound of possible models. This approach has a strong potential to be applicable to large civil structures with sparse array of sensors.
LLNL's program on multiscale modeling of polycrystal plasticity
Diaz De La Rubia, T.; Holmes, N. H.; King, W. E.; Lassila, D. H.; Moriarty, J. A.; Nikkel, D. J.
1998-04-27
At LLNL a multiscale modeling program based on information-passing has been established for modeling the strength properties of a body-centered-cubic metal (tantalum) ,. under conditions of extreme plastic deformation. The plastic deformation experienced by an explosively-formed shaped-charge jet is an example of "extreme deformation". The shaped charge liner material undergoes high strain rate deformation at high hydrostatic pressure. The constitutive model for flow stress, which describes the deformation, is highly dependent on pressure, temperature, and strain-rate. Current material models can not be extrapolated to these extreme conditions because the underlying mechanisms of plastic deformation are poorly reflected in the models and laboratory experiments are limited to pressures orders of magnitude less than actual pressures. This disparity between actual deformation conditions and those that can be attained in laboratory experiments is the principle motivation behind the multiscale modeling program. The fundamental elements of LLNL's multiscale modeling program are distinct models at the atomistic, microscale and mesoscale/continuum length scales. The information that needs to be passed from the lower to higher length scales has been carefully defined to bound the levels of effort required to ''bridge'' length scales. Information that needs to be generated by the different simulations has been specified by a multidisciplinary steering group comprised of physicists, materials scientists and engineers. The ultimate goal of the program is to provide critical information on strength properties to be used in continuum computer code simulations. The technical work-plan involves three principle areas which are highly coupled: 1) simulation development, 2) deformation experiments and 3) characterizations of deformed crystals. The three work areas are presented which provide examples of the progress of LLNL's program.
Multi-scale modeling for sustainable chemical production.
Zhuang, Kai; Bakshi, Bhavik R; Herrgård, Markus J
2013-09-01
With recent advances in metabolic engineering, it is now technically possible to produce a wide portfolio of existing petrochemical products from biomass feedstock. In recent years, a number of modeling approaches have been developed to support the engineering and decision-making processes associated with the development and implementation of a sustainable biochemical industry. The temporal and spatial scales of modeling approaches for sustainable chemical production vary greatly, ranging from metabolic models that aid the design of fermentative microbial strains to material and monetary flow models that explore the ecological impacts of all economic activities. Research efforts that attempt to connect the models at different scales have been limited. Here, we review a number of existing modeling approaches and their applications at the scales of metabolism, bioreactor, overall process, chemical industry, economy, and ecosystem. In addition, we propose a multi-scale approach for integrating the existing models into a cohesive framework. The major benefit of this proposed framework is that the design and decision-making at each scale can be informed, guided, and constrained by simulations and predictions at every other scale. In addition, the development of this multi-scale framework would promote cohesive collaborations across multiple traditionally disconnected modeling disciplines to achieve sustainable chemical production.
Multiscale Modeling of Red Blood Cells Squeezing through Submicron Slits
NASA Astrophysics Data System (ADS)
Peng, Zhangli; Lu, Huijie
2016-11-01
A multiscale model is applied to study the dynamics of healthy red blood cells (RBCs), RBCs in hereditary spherocytosis, and sickle cell disease squeezing through submicron slits. This study is motivated by the mechanical filtration of RBCs by inter-endothelial slits in the spleen. First, the model is validated by comparing the simulation results with experiments. Secondly, the deformation of the cytoskeleton in healthy RBCs is investigated. Thirdly, the mechanisms of damage in hereditary spherocytosis are investigated. Finally, the effects of cytoplasm and membrane viscosities, especially in sickle cell disease, are examined. The simulations results provided guidance for future experiments to explore the dynamics of RBCs under extreme deformation.
Community Multiscale Air Quality (CMAQ) Modeling for ...
The CMAQ model is a Eulerian model that produces gridded values of atmospheric concentration and deposition. Recent updates to the model are highlighted that impact estimates of dry and wet deposition of nitrogen, sulfur and base cations. Output from the CMAQ model is used in the measurement-model fusion method used to create the National Atmospheric Program's (NADP) Total Deposition (TDEP) map product. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.
Multiscale modeling of chemotaxis in homogeneous porous media
NASA Astrophysics Data System (ADS)
Porter, Mark L.; ValdéS-Parada, Francisco J.; Wood, Brian D.
2011-06-01
We present a predictive, multiscale modeling framework for chemotaxis in porous media. This model results from volume averaging the governing equations for bacterial transport at the microscale and is expressed in terms of effective medium coefficients that are predicted from the solution of the associated closure problems. As a result, the averaged chemotactic velocity is an explicit function of the attractant concentration field and diffusivity, rather than an empirical effective chemotactic sensitivity coefficient. The model was validated by comparing the transverse bacterial concentration profiles with experimental measurements for Escherichia coli HCB1 in a T-sensor. The averaged chemotactic velocity predicted by the model was found to be within the range of values reported in the literature. Reasonable agreement (approximately 10% mean absolute error) between theory and experiments was found for several flow rates. In order to assess the potential for decreasing the computational demands of the model, the macroscale domain was divided into subdomains for the coupling of bacterial transport to that of the attractant. Sensitivity analysis was performed regarding the number of subdomains chosen, and the results indicate that bacterial transport (as measured by concentration profiles) was not highly affected by this choice. Overall, these results suggest that the predictive, multiscale modeling framework is reliable for modeling chemotaxis in porous media when chemotactic transport is significant compared to convective transport.
Multiscale modeling of bone tissue with surface and permeability control.
Gonçalves Coelho, Pedro; Rui Fernandes, Paulo; Carriço Rodrigues, Helder
2011-01-11
Natural biological materials usually present a hierarchical arrangement with various structural levels. The biomechanical behavior of the complex hierarchical structure of bone is investigated with models that address the various levels corresponding to different scales. Models that simulate the bone remodeling process concurrently at different scales are in development. We present a multiscale model for bone tissue adaptation that considers the two top levels, whole bone and trabecular architecture. The bone density distribution is calculated at the macroscale (whole bone) level, and the trabecular structure at the microscale level takes into account its mechanical properties as well as surface density and permeability. The bone remodeling process is thus formulated as a material distribution problem at both scales. At the local level, the biologically driven information of surface density and permeability characterizes the trabecular structure. The model is tested by a three-dimensional simulation of bone tissue adaptation for the human femur. The density distribution of the model shows good agreement with the actual bone density distribution. Permeability at the microstructural level assures interconnectivity of pores, which mimics the interconnectivity of trabecular bone essential for vascularization and transport of nutrients. The importance of this multiscale model relays on the flexibility to control the morphometric parameters that characterize the trabecular structure. Therefore, the presented model can be a valuable tool to define bone quality, to assist with diagnosis of osteoporosis, and to support the development of bone substitutes.
Multiscale Eulerian Model Within NCEP's National Environmental Modeling System
NASA Astrophysics Data System (ADS)
Janjic, Z.; Black, T.; Vasic, R.; Rogers, E.; Dimego, G.
2010-12-01
The unified Non-hydrostatic Multi-scale Model on the B grid (NMMB) is being developed at NCEP as a part of the National Environmental Modeling System (NEMS). The finite-volume horizontal differencing employed in the model preserves important properties of differential operators and conserves a variety of basic and derived dynamical and quadratic quantities. Among these, conservation of energy and enstrophy improves the accuracy of nonlinear dynamics. The nonhydrostatic dynamics were formulated in such a way as to avoid overspecification. In the global limit, “across the pole” polar boundary conditions are used, and the polar filter selectively slows down the wave components that would otherwise propagate faster in the zonal direction than the fastest wave propagating in the meridional direction. The physical package of the model has been developed from the standard NCEP’s WRF NMM physics. A global forecasting system based on the NMMB was run for more than a year in order to test and tune the model, and in particular, to examine its potential for medium range weather forecasting. The system was initialized and verified using the analyses of NCEP’s Global Forecasting System (GFS). The skill of the large scale medium range forecasts produced by the system has been comparable to that of other major medium range forecasting systems. The computational efficiency of the model on parallel computers has been competitive with that of other major global systems. Interestingly, even though the NMMB and GFS were starting from the same analyses, the skill of the two individual medium range forecasts was often disparate. When one model produced a bad forecast, the forecast from the other model could be quite good. Such behavior appears potentially advantageous for application of the two models for ensemble forecasting. On the mesoscales, the NMMB is planned to replace the WRF NMM in operations as the North American Model (NAM), and in a number of nested high resolution
Multiscale geometric modeling of macromolecules I: Cartesian representation
NASA Astrophysics Data System (ADS)
Xia, Kelin; Feng, Xin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei
2014-01-01
This paper focuses on the geometric modeling and computational algorithm development of biomolecular structures from two data sources: Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in the Eulerian (or Cartesian) representation. Molecular surface (MS) contains non-smooth geometric singularities, such as cusps, tips and self-intersecting facets, which often lead to computational instabilities in molecular simulations, and violate the physical principle of surface free energy minimization. Variational multiscale surface definitions are proposed based on geometric flows and solvation analysis of biomolecular systems. Our approach leads to geometric and potential driven Laplace-Beltrami flows for biomolecular surface evolution and formation. The resulting surfaces are free of geometric singularities and minimize the total free energy of the biomolecular system. High order partial differential equation (PDE)-based nonlinear filters are employed for EMDB data processing. We show the efficacy of this approach in feature-preserving noise reduction. After the construction of protein multiresolution surfaces, we explore the analysis and characterization of surface morphology by using a variety of curvature definitions. Apart from the classical Gaussian curvature and mean curvature, maximum curvature, minimum curvature, shape index, and curvedness are also applied to macromolecular surface analysis for the first time. Our curvature analysis is uniquely coupled to the analysis of electrostatic surface potential, which is a by-product of our variational multiscale solvation models. As an expository investigation, we particularly emphasize the numerical algorithms and computational protocols for practical applications of the above multiscale geometric models. Such information may otherwise be scattered over the vast literature on this topic. Based on the curvature and electrostatic analysis from our multiresolution surfaces, we introduce a new concept, the
Multiscale geometric modeling of macromolecules I: Cartesian representation
Xia, Kelin; Feng, Xin; Chen, Zhan; Tong, Yiying; Wei, Guo Wei
2013-01-01
This paper focuses on the geometric modeling and computational algorithm development of biomolecular structures from two data sources: Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in the Eulerian (or Cartesian) representation. Molecular surface (MS) contains non-smooth geometric singularities, such as cusps, tips and self-intersecting facets, which often lead to computational instabilities in molecular simulations, and violate the physical principle of surface free energy minimization. Variational multiscale surface definitions are proposed based on geometric flows and solvation analysis of biomolecular systems. Our approach leads to geometric and potential driven Laplace-Beltrami flows for biomolecular surface evolution and formation. The resulting surfaces are free of geometric singularities and minimize the total free energy of the biomolecular system. High order partial differential equation (PDE)-based nonlinear filters are employed for EMDB data processing. We show the efficacy of this approach in feature-preserving noise reduction. After the construction of protein multiresolution surfaces, we explore the analysis and characterization of surface morphology by using a variety of curvature definitions. Apart from the classical Gaussian curvature and mean curvature, maximum curvature, minimum curvature, shape index, and curvedness are also applied to macromolecular surface analysis for the first time. Our curvature analysis is uniquely coupled to the analysis of electrostatic surface potential, which is a by-product of our variational multiscale solvation models. As an expository investigation, we particularly emphasize the numerical algorithms and computational protocols for practical applications of the above multiscale geometric models. Such information may otherwise be scattered over the vast literature on this topic. Based on the curvature and electrostatic analysis from our multiresolution surfaces, we introduce a new concept, the
Multi-scale modelling of elastic moduli of trabecular bone
Hamed, Elham; Jasiuk, Iwona; Yoo, Andrew; Lee, YikHan; Liszka, Tadeusz
2012-01-01
We model trabecular bone as a nanocomposite material with hierarchical structure and predict its elastic properties at different structural scales. The analysis involves a bottom-up multi-scale approach, starting with nanoscale (mineralized collagen fibril) and moving up the scales to sub-microscale (single lamella), microscale (single trabecula) and mesoscale (trabecular bone) levels. Continuum micromechanics methods, composite materials laminate theory and finite-element methods are used in the analysis. Good agreement is found between theoretical and experimental results. PMID:22279160
The Total Variation Regularized L1 Model for Multiscale Decomposition
2006-01-01
measure theory approach, and Vixie and Esedoglu’s [43] work on characterizing the solutions of (1.2) below. In this paper we extend the existing...no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control ...2r . THE TV-L1 MODEL FOR MULTISCALE DECOMPOSITION 5 In general the minimizer of the TV-L1 is nonunique . In the above disk example, if λ = 2/r
Multiscale Materials Modeling in an Industrial Environment.
Weiß, Horst; Deglmann, Peter; In 't Veld, Pieter J; Cetinkaya, Murat; Schreiner, Eduard
2016-06-07
In this review, we sketch the materials modeling process in industry. We show that predictive and fast modeling is a prerequisite for successful participation in research and development processes in the chemical industry. Stable and highly automated workflows suitable for handling complex systems are a must. In particular, we review approaches to build and parameterize soft matter systems. By satisfying these prerequisites, efficiency for the development of new materials can be significantly improved, as exemplified here for formulation polymer development. This is in fact in line with recent Materials Genome Initiative efforts sponsored by the US government. Valuable contributions to product development are possible today by combining existing modeling techniques in an intelligent fashion, provided modeling and experiment work hand in hand.
Community Multiscale Air Quality Modeling System (CMAQ)
CMAQ is a computational tool used for air quality management. It models air pollutants including ozone, particulate matter and other air toxics to help determine optimum air quality management scenarios.
Multiscale Models of Melting Arctic Sea Ice
2014-09-30
represent sea ice more rigorously in climate models. OBJECTIVES Viewed from high above, the melting sea ice surface can be thought of as a two phase ...composite of ice and melt water. The boundaries between the two phases evolve with increasing complexity and a rapid onset of large scale...connectivity, or percolation of the melt phase . We plan to document this phenomenon with photographic imagery and to develop percolation and other models to
Standard Model in multiscale theories and observational constraints
NASA Astrophysics Data System (ADS)
Calcagni, Gianluca; Nardelli, Giuseppe; Rodríguez-Fernández, David
2016-08-01
We construct and analyze the Standard Model of electroweak and strong interactions in multiscale spacetimes with (i) weighted derivatives and (ii) q -derivatives. Both theories can be formulated in two different frames, called fractional and integer picture. By definition, the fractional picture is where physical predictions should be made. (i) In the theory with weighted derivatives, it is shown that gauge invariance and the requirement of having constant masses in all reference frames make the Standard Model in the integer picture indistinguishable from the ordinary one. Experiments involving only weak and strong forces are insensitive to a change of spacetime dimensionality also in the fractional picture, and only the electromagnetic and gravitational sectors can break the degeneracy. For the simplest multiscale measures with only one characteristic time, length and energy scale t*, ℓ* and E*, we compute the Lamb shift in the hydrogen atom and constrain the multiscale correction to the ordinary result, getting the absolute upper bound t*<10-23 s . For the natural choice α0=1 /2 of the fractional exponent in the measure, this bound is strengthened to t*<10-29 s , corresponding to ℓ*<10-20 m and E*>28 TeV . Stronger bounds are obtained from the measurement of the fine-structure constant. (ii) In the theory with q -derivatives, considering the muon decay rate and the Lamb shift in light atoms, we obtain the independent absolute upper bounds t*<10-13 s and E*>35 MeV . For α0=1 /2 , the Lamb shift alone yields t*<10-27 s , ℓ*<10-19 m and E*>450 GeV .
A Goddard Multi-Scale Modeling System with Unified Physics
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2008-01-01
A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. The following is presented in this report: (1) a brief review of the GCE model and its applications on the impact of aerosols on deep precipitation processes, (2) the Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) a discussion on the Goddard WRF version (its developments and applications).
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.
MODELS-3 COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL AEROSOL COMPONENT 1: MODEL DESCRIPTION
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...
Multiscale modeling of brain blow flow
NASA Astrophysics Data System (ADS)
Karniadakis, George
2014-11-01
Cardiovascular pathologies, such as brain aneurysms, 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, 3D or 1D) 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 will present a physical model of the brain vasculature consisting at the macro level of all major arteries (about 200 down to 0.5 mm), at the mesoscale the fractal arteriolar tree (more than 10 millions down to 20 nm) and at the microscale the capillary bed. Correspondingly, we employ three different methods to model the total brain vasculature by developing proper interface conditions at each level. We will present examples from aneurysms and other hematological diseases, where red blood cell rheology is modeled explicitly.
Multi-scale modelling and dynamics
NASA Astrophysics Data System (ADS)
Müller-Plathe, Florian
Moving from a fine-grained particle model to one of lower resolution leads, with few exceptions, to an acceleration of molecular mobility, higher diffusion coefficient, lower viscosities and more. On top of that, the level of acceleration is often different for different dynamical processes as well as for different state points. While the reasons are often understood, the fact that coarse-graining almost necessarily introduces unpredictable acceleration of the molecular dynamics severely limits its usefulness as a predictive tool. There are several attempts under way to remedy these shortcoming of coarse-grained models. On the one hand, we follow bottom-up approaches. They attempt already when the coarse-graining scheme is conceived to estimate their impact on the dynamics. This is done by excess-entropy scaling. On the other hand, we also pursue a top-down development. Here we start with a very coarse-grained model (dissipative particle dynamics) which in its native form produces qualitatively wrong polymer dynamics, as its molecules cannot entangle. This model is modified by additional temporary bonds, so-called slip springs, to repair this defect. As a result, polymer melts and solutions described by the slip-spring DPD model show correct dynamical behaviour. Read more: ``Excess entropy scaling for the segmental and global dynamics of polyethylene melts'', E. Voyiatzis, F. Müller-Plathe, and M.C. Böhm, Phys. Chem. Chem. Phys. 16, 24301-24311 (2014). [DOI: 10.1039/C4CP03559C] ``Recovering the Reptation Dynamics of Polymer Melts in Dissipative Particle Dynamics Simulations via Slip-Springs'', M. Langeloth, Y. Masubuchi, M. C. Böhm, and F. Müller-Plathe, J. Chem. Phys. 138, 104907 (2013). [DOI: 10.1063/1.4794156].
Multiscale Models of Melting Arctic Sea Ice
2013-09-30
provides a general technique for computing horizontal flow properties, as well as other parameters of interest. Voter model and the fractal geometry ...grow, coalesce, and become more complex, they exhibit a transition in fractal dimension from about 1 to 2, near a critical length scale of 100...composite geometry . In the previous sub-project the importance of horizontal fluid transport is described, and computation of these spectral measures
A Predictive Multiscale Model of Wear
2011-03-09
theoretical tensile strength, and by fitting the calculated data to universal binding energy relationships ( UBERs ), which permit the extrapolation of the...calculated results to arbitrary length scales. The results demonstrate the ability of an UBER that accounts for fracture surface relaxation to yield a...materials subjected to shear up to the point at which slip occurs. The model we devised is analogous to the tensile-load UBER and leads to a size
Multi-Scale Modeling of Magnetospheric Dynamics
NASA Technical Reports Server (NTRS)
Kuznetsova, M. M.; Hesse, M.; Toth, G.
2012-01-01
Magnetic reconnection is a key element in many phenomena in space plasma, e.g. Coronal mass Ejections, Magnetosphere substorms. One of the major challenges in modeling the dynamics of large-scale systems involving magnetic reconnection is to quantifY the interaction between global evolution of the magnetosphere and microphysical kinetic processes in diffusion regions near reconnection sites. Recent advances in small-scale kinetic modeling of magnetic reconnection significantly improved our understanding of physical mechanisms controlling the dissipation in the vicinity of the reconnection site in collisionless plasma. However the progress in studies of small-scale geometries was not very helpful for large scale simulations. Global magnetosphere simulations usually include non-ideal processes in terms of numerical dissipation and/or ad hoc anomalous resistivity. Comparative studies of magnetic reconnection in small scale geometries demonstrated that MHD simulations that included non-ideal processes in terms of a resistive term 11 J did not produce fast reconnection rates observed in kinetic simulations. In collisionless magnetospheric plasma, the primary mechanism controlling the dissipation in the vicinity of the reconnection site is nongyrotropic pressure effects with spatial scales comparable with the particle Larmor radius. We utilize the global MHD code BATSRUS and replace ad hoc parameters such as "critical current density" and "anomalous resistivity" with a physically motivated model of dissipation. The primary mechanism controlling the dissipation in the vicinity of the reconnection site in incorporated into MHD description in terms of non-gyrotropic corrections to the induction equation. We will demonstrate that kinetic nongyrotropic effects can significantly alter the global magnetosphere evolution. Our approach allowed for the first time to model loading/unloading cycle in response to steady southward IMF driving. The role of solar wind parameters and
Stochastic Multiscale Modeling of Polycrystalline Materials
2013-01-01
2.16 Explicit structure of a (γ+γ′) grain and its equivalent homoge- nized model. The gray background on the left grain represents γ matrix, while...effective strength . . . . . . . . . . . . . . . . . . . . . . . 129 3.14 Convergence test of the mean field of the properties of the forged product...microstructure input. The variabil- ity of strain, stress and strength fields over the workpiece after forging is inves- tigated. The microstructures in the
A new approach towards image based virtual 3D city modeling by using close range photogrammetry
NASA Astrophysics Data System (ADS)
Singh, S. P.; Jain, K.; Mandla, V. R.
2014-05-01
3D city model is a digital representation of the Earth's surface and it's related objects such as building, tree, vegetation, and some manmade feature belonging to urban area. The demand of 3D city modeling is increasing day to day for various engineering and non-engineering applications. Generally three main image based approaches are using for virtual 3D city models generation. In first approach, researchers used Sketch based modeling, second method is Procedural grammar based modeling and third approach is Close range photogrammetry based modeling. Literature study shows that till date, there is no complete solution available to create complete 3D city model by using images. These image based methods also have limitations This paper gives a new approach towards image based virtual 3D city modeling by using close range photogrammetry. This approach is divided into three sections. First, data acquisition process, second is 3D data processing, and third is data combination process. In data acquisition process, a multi-camera setup developed and used for video recording of an area. Image frames created from video data. Minimum required and suitable video image frame selected for 3D processing. In second section, based on close range photogrammetric principles and computer vision techniques, 3D model of area created. In third section, this 3D model exported to adding and merging of other pieces of large area. Scaling and alignment of 3D model was done. After applying the texturing and rendering on this model, a final photo-realistic textured 3D model created. This 3D model transferred into walk-through model or in movie form. Most of the processing steps are automatic. So this method is cost effective and less laborious. Accuracy of this model is good. For this research work, study area is the campus of department of civil engineering, Indian Institute of Technology, Roorkee. This campus acts as a prototype for city. Aerial photography is restricted in many country
NASA Astrophysics Data System (ADS)
Trinks, I.; Wallner, M.; Kucera, M.; Verhoeven, G.; Torrejón Valdelomar, J.; Löcker, K.; Nau, E.; Sevara, C.; Aldrian, L.; Neubauer, E.; Klein, M.
2017-02-01
The excavated architecture of the exceptional prehistoric site of Akrotiri on the Greek island of Thera/Santorini is endangered by gradual decay, damage due to accidents, and seismic shocks, being located on an active volcano in an earthquake-prone area. Therefore, in 2013 and 2014 a digital documentation project has been conducted with support of the National Geographic Society in order to generate a detailed digital model of Akrotiri's architecture using terrestrial laser scanning and image-based modeling. Additionally, non-invasive geophysical prospection has been tested in order to investigate its potential to explore and map yet buried archaeological remains. This article describes the project and the generated results.
Multiscale Model for the Dielectric Permittivity
NASA Astrophysics Data System (ADS)
Pérez-Madrid, Agustín; Lapas, Luciano C.; Rubí, J. Miguel
2017-02-01
We present a generalisation of the Debye relaxation model for the dielectric permittivity in the case in which the global relaxation process is the result of many elementary excitations. The relaxation dynamics is in this case non-Markovian. In the case of many events, for which the central limit theorem holds and Gaussianity as well as the assumption of independency are both plausible, the global relaxation time is given by a log-normal function. The hierarchy of relaxation times leads to a generalised expression of the dielectric permittivity.
Multiscale modeling for fluid transport in nanosystems.
Lee, Jonathan W.; Jones, Reese E.; Mandadapu, Kranthi Kiran; Templeton, Jeremy Alan; Zimmerman, Jonathan A.
2013-09-01
Atomistic-scale behavior drives performance in many micro- and nano-fluidic systems, such as mircrofludic mixers and electrical energy storage devices. Bringing this information into the traditionally continuum models used for engineering analysis has proved challenging. This work describes one such approach to address this issue by developing atomistic-to-continuum multi scale and multi physics methods to enable molecular dynamics (MD) representations of atoms to incorporated into continuum simulations. Coupling is achieved by imposing constraints based on fluxes of conserved quantities between the two regions described by one of these models. The impact of electric fields and surface charges are also critical, hence, methodologies to extend finite-element (FE) MD electric field solvers have been derived to account for these effects. Finally, the continuum description can have inconsistencies with the coarse-grained MD dynamics, so FE equations based on MD statistics were derived to facilitate the multi scale coupling. Examples are shown relevant to nanofluidic systems, such as pore flow, Couette flow, and electric double layer.
Quantitative modeling of multiscale neural activity
NASA Astrophysics Data System (ADS)
Robinson, Peter A.; Rennie, Christopher J.
2007-01-01
The electrical activity of the brain has been observed for over a century and is widely used to probe brain function and disorders, chiefly through the electroencephalogram (EEG) recorded by electrodes on the scalp. However, the connections between physiology and EEGs have been chiefly qualitative until recently, and most uses of the EEG have been based on phenomenological correlations. A quantitative mean-field model of brain electrical activity is described that spans the range of physiological and anatomical scales from microscopic synapses to the whole brain. Its parameters measure quantities such as synaptic strengths, signal delays, cellular time constants, and neural ranges, and are all constrained by independent physiological measurements. Application of standard techniques from wave physics allows successful predictions to be made of a wide range of EEG phenomena, including time series and spectra, evoked responses to stimuli, dependence on arousal state, seizure dynamics, and relationships to functional magnetic resonance imaging (fMRI). Fitting to experimental data also enables physiological parameters to be infered, giving a new noninvasive window into brain function, especially when referenced to a standardized database of subjects. Modifications of the core model to treat mm-scale patchy interconnections in the visual cortex are also described, and it is shown that resulting waves obey the Schroedinger equation. This opens the possibility of classical cortical analogs of quantum phenomena.
Multiscale computational modelling of the heart
NASA Astrophysics Data System (ADS)
Smith, N. P.; Nickerson, D. P.; Crampin, E. J.; Hunter, P. J.
A computational framework is presented for integrating the electrical, mechanical and biochemical functions of the heart. Finite element techniques are used to solve the large-deformation soft tissue mechanics using orthotropic constitutive laws based in the measured fibre-sheet structure of myocardial (heart muscle) tissue. The reaction-diffusion equations governing electrical current flow in the heart are solved on a grid of deforming material points which access systems of ODEs representing the cellular processes underlying the cardiac action potential. Navier-Stokes equations are solved for coronary blood flow in a system of branching blood vessels embedded in the deforming myocardium and the delivery of oxygen and metabolites is coupled to the energy-dependent cellular processes. The framework presented here for modelling coupled physical conservation laws at the tissue and organ levels is also appropriate for other organ systems in the body and we briefly discuss applications to the lungs and the musculo-skeletal system. The computational framework is also designed to reach down to subcellular processes, including signal transduction cascades and metabolic pathways as well as ion channel electrophysiology, and we discuss the development of ontologies and markup language standards that will help link the tissue and organ level models to the vast array of gene and protein data that are now available in web-accessible databases.
Multi-Scale Modeling of Magnetospheric Reconnection
NASA Technical Reports Server (NTRS)
Kuznetsova, M. M.; Hesse, M.; Rastatter, L.; Toth, G.; Dezeeuw, D.; Gomobosi, T.
2007-01-01
One of the major challenges in modeling the magnetospheric magnetic reconnection is to quantify the interaction between large-scale global magnetospheric dynamics and microphysical processes in diffusion regions near reconnection sites. There is still considerable debate as to what degree microphysical processes on kinetic scales affect the global evolution and how important it is to substitute numerical dissipation and/or ad hoc anomalous resistivity by a physically motivated model of dissipation. Comparative studies of magnetic reconnection in small scale geometries demonstrated that MHD simulations that included non-ideal processes in terms of a resistive term $\\eta J$ did not produce the fast reconnection rates observed in kinetic simulations. For a broad range of physical parameters in collisionless magnetospheric plasma, the primary mechanism controlling the dissipation in the vicinity of the reconnection site is non-gyrotropic effects with spatial scales comparable with the particle Larmor radius. We utilize the global MHD code BATSRUS and incorporate nongyrotropic effects in diffusion regions in terms of corrections to the induction equation. We developed an algorithm to search for magnetotail reconnection sites, specifically where the magnetic field components perpendicular to the local current direction approaches zero and form an X-type configuration. Spatial scales of the diffusion region and magnitude of the reconnection electric field are calculated selfconsistently using MHD plasma and field parameters in the vicinity of the reconnection site. The location of the reconnection sites is updated during the simulations. To clarify the role of nongyrotropic effects in diffusion region on the global magnetospheric dynamic we perform simulations with steady southward IMF driving of the magnetosphere. Ideal MHD simulations with magnetic reconnection supported by numerical resistivity produce steady configuration with almost stationary near-earth neutral
Multiscale modeling and computation of optically manipulated nano devices
Bao, Gang; Liu, Di; Luo, Songting
2016-07-01
We present a multiscale modeling and computational scheme for optical-mechanical responses of nanostructures. The multi-physical nature of the problem is a result of the interaction between the electromagnetic (EM) field, the molecular motion, and the electronic excitation. To balance accuracy and complexity, we adopt the semi-classical approach that the EM field is described classically by the Maxwell equations, and the charged particles follow the Schrödinger equations quantum mechanically. To overcome the numerical challenge of solving the high dimensional multi-component many-body Schrödinger equations, we further simplify the model with the Ehrenfest molecular dynamics to determine the motion of the nuclei, and use the Time-Dependent Current Density Functional Theory (TD-CDFT) to calculate the excitation of the electrons. This leads to a system of coupled equations that computes the electromagnetic field, the nuclear positions, and the electronic current and charge densities simultaneously. In the regime of linear responses, the resonant frequencies initiating the out-of-equilibrium optical-mechanical responses can be formulated as an eigenvalue problem. A self-consistent multiscale method is designed to deal with the well separated space scales. The isomerization of azobenzene is presented as a numerical example.
Multiscale thermohydrologic model sensitivity analysis/011/011/011
Buscheck, T.A., LLNL
1998-07-31
A multiscale, thermohydrologic (TH) modeling approach (or methodology) has been developed that integrates the results from one- dimensional (1-D), two-dimensional (2-D), and three-dimensional (3-D) drift-scale models and a 3-D mountain-scale model to calculate the near-field TH variables affecting the performance of the engineered barrier system (EBS) of the potential repository at Yucca Mountain. This information is required by Total System Performance Assessment- Viability Assessment (TSPA-VA) to assess waste-package (WP) corrosion, waste-form dissolution, and radionuclide transport in the EBS. This methodology is a computationally efficient, flexible means of determining EBS TH conditions; such determination would otherwise require millions of grid blocks if a brute-force numerical model were used. The methodology determines EBS TH conditions as a function of location within the repository and WP type.
Multi-Scale Modeling of Plasma Thrusters
NASA Astrophysics Data System (ADS)
Batishchev, Oleg
2004-11-01
Plasma thrusters are characterized with multiple spatial and temporal scales, which are due to the intrinsic physical processes such as gas ionization, wall effects and plasma acceleration. Characteristic times for hot plasma and cold gas are differing by 6-7 orders of magnitude. The typical collisional mean-free-paths vary by 3-5 orders along the devices. These make questionable a true self-consistent modeling of the thrusters. The latter is vital to the understanding of complex physics, non-linear dynamics and optimization of the performance. To overcome this problem we propose the following approach. All processes are divided into two groups: fast and slow. The slow ones include gas evolution with known sources and ionization sink. The ionization rate, transport coefficients, energy sources are defined during "fast step". Both processes are linked through external iterations. Multiple spatial scales are handled using moving adaptive mesh. Development and application of this method to the VASIMR helicon plasma source and other thrusters will be discussed. Supported by NASA.
Modeling Damage in Composite Materials Using an Enrichment Based Multiscale Method
2015-03-01
Multiscale Enrichment Technique The approach to implementing structural based enrichment varies depending on the governing method . In this...the two simulations. Using the enrichment method without any damaged RVEs still reduced the error by 6% over the homogenization approaches . When using...Technical Report ARWSB-TR-15002 Modeling Damage in Composite Materials Using an Enrichment Based Multiscale Method Michael F
Integrated Multiscale Modeling of Molecular Computing Devices
Jerzy Bernholc
2011-02-03
will some day reach a miniaturization limit, forcing designers of Si-based electronics to pursue increased performance by other means. Any other alternative approach would have the unenviable task of matching the ability of Si technology to pack more than a billion interconnected and addressable devices on a chip the size of a thumbnail. Nevertheless, the prospects of developing alternative approaches to fabricate electronic devices have spurred an ever-increasing pace of fundamental research. One of the promising possibilities is molecular electronics (ME), self-assembled molecular-based electronic systems composed of single-molecule devices in ultra dense, ultra fast molecular-sized components. This project focused on developing accurate, reliable theoretical modeling capabilities for describing molecular electronics devices. The participants in the project are given in Table 1. The primary outcomes of this fundamental computational science grant are publications in the open scientific literature. As listed below, 62 papers have been published from this project. In addition, the research has also been the subject of more than 100 invited talks at conferences, including several plenary or keynote lectures. Many of the goals of the original proposal were completed. Specifically, the multi-disciplinary group developed a unique set of capabilities and tools for investigating electron transport in fabricated and self-assembled nanostructures at multiple length and time 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.
A High-Order Multiscale Global Atmospheric Model
NASA Astrophysics Data System (ADS)
Nair, R. D.
2015-12-01
The High-Order Method Modeling Environment (HOMME), developed at NCAR, is a petascale hydrostatic framework, which employs the cubed-sphere grid system and high-order continuous or discontinuous Galerkin (DG) methods. Recently, the HOMME framework is being extended to a non-hydrostatic dynamical core, named as the "High-Order Multiscale Atmospheric Model (HOMAM)." The spatial discretization for HOMAM is based on DG or high-order finite-volume methods. Orography is handled by the terrain-following height-based coordinate system. To alleviate the stringent CFL stability requirement resulting from the vertical aspects of the dynamics, an operator-splitting time integration scheme based on the horizontally explicit and vertically implicit (HEVI) philosophy is adopted for HOMAM. Preliminary results with the benchmark test cases proposed in the Dynamical Core Model Intercomparison project (DCMIP) test-suite will be presented in the seminar.
A High-Order Multiscale Global Atmospheric Model
NASA Astrophysics Data System (ADS)
Nair, Ram
2016-04-01
The High-Order Method Modeling Environment (HOMME), developed at NCAR, is a petascale hydrostatic framework, which employs the cubed-sphere grid system and high-order continuous or discontinuous Galerkin (DG) methods. Recently, the HOMME framework is being extended to a non-hydrostatic dynamical core, named as the "High-Order Multiscale Atmospheric Model (HOMAM)." The spatial discretization is based on DG or high-order finite-volume methods. Orography is handled by the terrain-following height-based coordinate system. To alleviate the stringent CFL stability requirement resulting from the vertical aspects of the dynamics, an operator-splitting time integration scheme based on the horizontally explicit and vertically implicit (HEVI) philosophy is adopted for HOMAM. Preliminary results with the benchmark test cases proposed in the Dynamical Core Model Intercomparison project (DCMIP) test-suite will be presented in the seminar.
Identity in agent-based models : modeling dynamic multiscale social processes.
Ozik, J.; Sallach, D. L.; Macal, C. M.; Decision and Information Sciences; Univ. of Chicago
2008-07-01
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
Three-Dimensional Multiscale MHD Model of Cometary Plasma Environments
NASA Technical Reports Server (NTRS)
Gombosi, Tamas I.; DeZeeuw, Darren L.; Haberli, Roman M.; Powell, Kenneth G.
1996-01-01
First results of a three-dimensional multiscale MHD model of the interaction of an expanding cometary atmosphere with the magnetized solar wind are presented. The model starts with a supersonic and super-Alfvenic solar wind far upstream of the comet (25 Gm upstream of the nucleus) with arbitrary interplanetary magnetic field orientation. The solar wind is continuously mass loaded with cometary ions originating from a 10-km size nucleus. The effects of photoionization, electron impact ionization, recombination, and ion-neutral frictional drag are taken into account in the model. The governing equations are solved on an adaptively refined unstructured Cartesian grid using our new multiscale upwind scalar conservation laws-type numerical technique (MUSCL). We have named this the multiscale adaptive upwind scheme for MHD (MAUS-MHD). The combination of the adaptive refinement with the MUSCL-scheme allows the entire cometary atmosphere to be modeled, while still resolving both the shock and the diamagnetic cavity of the comet. The main findings are the following: (1) Mass loading decelerates the solar wind flow upstream of the weak cometary shock wave (M approximately equals 2, M(sub A) approximately equals 2), which forms at a subsolar standoff distance of about 0.35 Gm. (2) A cometary plasma cavity is formed at around 3 x 10(exp 3) km from the nucleus. Inside this cavity the plasma expands outward due to the frictional interaction between ions and neutrals. On the nightside this plasma cavity considerably narrows and a relatively fast and dense cometary plasma beam is ejected into the tail. (3) Inside the plasma cavity a teardrop-shaped inner shock is formed, which is terminated by a Mach disk on the nightside. Only the region inside the inner shock is the 'true' diamagnetic cavity. (4) The model predicts four distinct current systems in the inner coma: the density peak current, the cavity boundary current, the inner shock current, and finally the cross-tail current
A Novel Spectral Approach to Multi-Scale Modeling
NASA Astrophysics Data System (ADS)
Landi, Giacomo
2011-12-01
In this work, we present a novel approach for predicting the elastic, thermo-elastic and plastic fields in three-dimensional (3-D) voxel-based microstructure datasets subjected to uniform periodic boundary conditions. Such localization relationships (linkages) lie at the core of all multi-scale modeling frameworks and can be efficiently formulated in a Discrete Fourier Transforms (DFT) -based knowledge system. This new formalism has its theoretical roots in the statistical continuum theories developed originally by Kroner [1]. However, in the approach described by Kroner, the terms in the series were established by selecting a reference medium and numerically evaluating a complex series of nested convolution integrals. This approach is largely hampered by the principal value problem, and exhibits high sensitivity to the properties of the selected reference medium. In the present work, the same series expressions have been recast into much more computationally efficient representations using DFTs. The spectral analysis transforms the complex integral relations into relatively simple algebraic expressions involving polynomials of structure parameters and morphology-independent influence coefficients. These coefficients need to be established only once for a given material system. The main advantage of the new DFT-based framework is that it allows easy calibration of Kroner's expansions to results from finite element methods, thereby overcoming all of the main obstacles associated with the principal value problem and the need to select a reference medium. This approach can be seen as an efficient procedure for data-mining the results from computationally expensive numerical models and establishing the underlying knowledge systems at a selected length scale in multi-scale modeling problems. The set of influence coefficients described above constitutes the underlying knowledge for a given deformation and can be easily stored and recalled as and when needed in a multi-scale
A Liver-Centric Multiscale Modeling Framework for Xenobiotics
Swat, Maciej; Cosmanescu, Alin; Clendenon, Sherry G.; Wambaugh, John F.; Glazier, James A.
2016-01-01
We describe a multi-scale, liver-centric in silico modeling framework for acetaminophen pharmacology and metabolism. We focus on a computational model to characterize whole body uptake and clearance, liver transport and phase I and phase II metabolism. We do this by incorporating sub-models that span three scales; Physiologically Based Pharmacokinetic (PBPK) modeling of acetaminophen uptake and distribution at the whole body level, cell and blood flow modeling at the tissue/organ level and metabolism at the sub-cellular level. We have used standard modeling modalities at each of the three scales. In particular, we have used the Systems Biology Markup Language (SBML) to create both the whole-body and sub-cellular scales. Our modeling approach allows us to run the individual sub-models separately and allows us to easily exchange models at a particular scale without the need to extensively rework the sub-models at other scales. In addition, the use of SBML greatly facilitates the inclusion of biological annotations directly in the model code. The model was calibrated using human in vivo data for acetaminophen and its sulfate and glucuronate metabolites. We then carried out extensive parameter sensitivity studies including the pairwise interaction of parameters. We also simulated population variation of exposure and sensitivity to acetaminophen. Our modeling framework can be extended to the prediction of liver toxicity following acetaminophen overdose, or used as a general purpose pharmacokinetic model for xenobiotics. PMID:27636091
A Liver-Centric Multiscale Modeling Framework for Xenobiotics.
Sluka, James P; Fu, Xiao; Swat, Maciej; Belmonte, Julio M; Cosmanescu, Alin; Clendenon, Sherry G; Wambaugh, John F; Glazier, James A
2016-01-01
We describe a multi-scale, liver-centric in silico modeling framework for acetaminophen pharmacology and metabolism. We focus on a computational model to characterize whole body uptake and clearance, liver transport and phase I and phase II metabolism. We do this by incorporating sub-models that span three scales; Physiologically Based Pharmacokinetic (PBPK) modeling of acetaminophen uptake and distribution at the whole body level, cell and blood flow modeling at the tissue/organ level and metabolism at the sub-cellular level. We have used standard modeling modalities at each of the three scales. In particular, we have used the Systems Biology Markup Language (SBML) to create both the whole-body and sub-cellular scales. Our modeling approach allows us to run the individual sub-models separately and allows us to easily exchange models at a particular scale without the need to extensively rework the sub-models at other scales. In addition, the use of SBML greatly facilitates the inclusion of biological annotations directly in the model code. The model was calibrated using human in vivo data for acetaminophen and its sulfate and glucuronate metabolites. We then carried out extensive parameter sensitivity studies including the pairwise interaction of parameters. We also simulated population variation of exposure and sensitivity to acetaminophen. Our modeling framework can be extended to the prediction of liver toxicity following acetaminophen overdose, or used as a general purpose pharmacokinetic model for xenobiotics.
A virtual coiling technique for image-based aneurysm models by dynamic path planning.
Morales, Hernán G; Larrabide, Ignacio; Geers, Arjan J; San Román, Luis; Blasco, Jordi; Macho, Juan M; Frangi, Alejandro F
2013-01-01
Computational algorithms modeling the insertion of endovascular devices, such as coil or stents, have gained an increasing interest in recent years. This scientific enthusiasm is due to the potential impact that these techniques have to support clinicians by understanding the intravascular hemodynamics and predicting treatment outcomes. In this work, a virtual coiling technique for treating image-based aneurysm models is proposed. A dynamic path planning was used to mimic the structure and distribution of coils inside aneurysm cavities, and to reach high packing densities, which is desirable by clinicians when treating with coils. Several tests were done to evaluate the performance on idealized and image-based aneurysm models. The proposed technique was validated using clinical information of real coiled aneurysms. The virtual coiling technique reproduces the macroscopic behavior of inserted coils and properly captures the densities, shapes and coil distributions inside aneurysm cavities. A practical application was performed by assessing the local hemodynamic after coiling using computational fluid dynamics (CFD). Wall shear stress and intra-aneurysmal velocities were reduced after coiling. Additionally, CFD simulations show that coils decrease the amount of contrast entering the aneurysm and increase its residence time.
Predictive Multiscale Modeling of Nanocellulose Based Materials and Systems
NASA Astrophysics Data System (ADS)
Kovalenko, Andriy
2014-08-01
Cellulose Nanocrysals (CNC) is a renewable biodegradable biopolymer with outstanding mechanical properties made from highly abundant natural source, and therefore is very attractive as reinforcing additive to replace petroleum-based plastics in biocomposite materials, foams, and gels. Large-scale applications of CNC are currently limited due to its low solubility in non-polar organic solvents used in existing polymerization technologies. The solvation properties of CNC can be improved by chemical modification of its surface. Development of effective surface modifications has been rather slow because extensive chemical modifications destabilize the hydrogen bonding network of cellulose and deteriorate the mechanical properties of CNC. We employ predictive multiscale theory, modeling, and simulation to gain a fundamental insight into the effect of CNC surface modifications on hydrogen bonding, CNC crystallinity, solvation thermodynamics, and CNC compatibilization with the existing polymerization technologies, so as to rationally design green nanomaterials with improved solubility in non-polar solvents, controlled liquid crystal ordering and optimized extrusion properties. An essential part of this multiscale modeling approach is the statistical- mechanical 3D-RISM-KH molecular theory of solvation, coupled with quantum mechanics, molecular mechanics, and multistep molecular dynamics simulation. The 3D-RISM-KH theory provides predictive modeling of both polar and non-polar solvents, solvent mixtures, and electrolyte solutions in a wide range of concentrations and thermodynamic states. It properly accounts for effective interactions in solution such as steric effects, hydrophobicity and hydrophilicity, hydrogen bonding, salt bridges, buffer, co-solvent, and successfully predicts solvation effects and processes in bulk liquids, solvation layers at solid surface, and in pockets and other inner spaces of macromolecules and supramolecular assemblies. This methodology
Multi-Scale Modeling of Hypersonic Gas Flow
NASA Astrophysics Data System (ADS)
Boyd, Iain D.
On March 27, 2004, NASA successfully flew the X-43A hypersonic test flight vehicle at a velocity of 5000 mph to break the aeronautics speed record that had stood for over 35 years. The final flight of the X-43A on November 16, 2004 further increased the speed record to 6,600 mph which is almost ten times the speed of sound. The very high speed attainable by hypersonic airplanes could revolutionize air travel by dramatically reducing inter-continental flight times. For example, a hypersonic flight from New York to Sydney, Australia, a distance of 10,000 miles, would take less than 2 h. Reusable hypersonic vehicles are also being researched to significantly reduce the cost of access to space. Computer modeling of the gas flows around hypersonic vehicles will play a critical part in their development. This article discusses the conditions that can prevail in certain hypersonic gas flows that require a multi-scale modeling approach.
This paper proposes a general procedure to link meteorological data with air quality models, such as U.S. EPA's Models-3 Community Multi-scale Air Quality (CMAQ) modeling system. CMAQ is intended to be used for studying multi-scale (urban and regional) and multi-pollutant (ozon...
Multiscale modeling for clinical translation in neuropsychiatric disease
Lytton, William W.; Neymotin, Samuel A.; Kerr, Cliff C.
2015-01-01
Multiscale modeling of neuropsychiatric illness bridges scales of clinical importance: from the highest scales (presentation of behavioral signs and symptoms), through intermediate scales (clinical testing and surgical intervention), down to the molecular scale of pharmacotherapy. Modeling of brain disease is difficult compared to modeling of other organs, because dysfunction manifests at scales where measurements are rudimentary due both to inadequate access (memory and cognition) and to complexity (behavior). Nonetheless, we can begin to explore these aspects through the use of information-theoretic measures as stand-ins for meaning at the top scales. We here describe efforts across five disorders: Parkinson’s, Alzheimer’s, stroke, schizophrenia, and epilepsy. We look at the use of therapeutic brain stimulation to replace lost neural signals, a loss that produces diaschisis, defined as activity changes in other brain areas due to missing inputs. These changes may in some cases be compensatory, hence beneficial, but in many cases a primary pathology, whether itself static or dynamic, sets in motion a series of dynamic consequences that produce further pathology. The simulations presented here suggest how diaschisis can be reversed by using a neuroprosthetic signal. Despite having none of the information content of the lost physiological signal, the simplified neuroprosthetic signal can restore a diaschitic area to near-normal patterns of activity. Computer simulation thus begins to explain the remarkable success of stimulation technologies - deep brain stimulation, transcranial magnetic stimulation, ultrasound stimulation, transcranial direct current stimulation - across an extremely broad range of pathologies. Multiscale modeling can help us to optimize and integrate these neuroprosthetic therapies by taking into consideration effects of different stimulation protocols, combinations of stimulation with neuropharmacological therapy, and interplay of these
Nonhydrostatic adaptive mesh dynamics for multiscale climate models (Invited)
NASA Astrophysics Data System (ADS)
Collins, W.; Johansen, H.; McCorquodale, P.; Colella, P.; Ullrich, P. A.
2013-12-01
Many of the atmospheric phenomena with the greatest potential impact in future warmer climates are inherently multiscale. Such meteorological systems include hurricanes and tropical cyclones, atmospheric rivers, and other types of hydrometeorological extremes. These phenomena are challenging to simulate in conventional climate models due to the relatively coarse uniform model resolutions relative to the native nonhydrostatic scales of the phenomonological dynamics. To enable studies of these systems with sufficient local resolution for the multiscale dynamics yet with sufficient speed for climate-change studies, we have adapted existing adaptive mesh dynamics for the DOE-NSF Community Atmosphere Model (CAM). In this talk, we present an adaptive, conservative finite volume approach for moist non-hydrostatic atmospheric dynamics. The approach is based on the compressible Euler equations on 3D thin spherical shells, where the radial direction is treated implicitly (using a fourth-order Runga-Kutta IMEX scheme) to eliminate time step constraints from vertical acoustic waves. Refinement is performed only in the horizontal directions. The spatial discretization is the equiangular cubed-sphere mapping, with a fourth-order accurate discretization to compute flux averages on faces. By using both space-and time-adaptive mesh refinement, the solver allocates computational effort only where greater accuracy is needed. The resulting method is demonstrated to be fourth-order accurate for model problems, and robust at solution discontinuities and stable for large aspect ratios. We present comparisons using a simplified physics package for dycore comparisons of moist physics. Hadley cell lifting an advected tracer into upper atmosphere, with horizontal adaptivity
Transferring Multi-Scale Approaches from 3d City Modeling to Ifc-Based Tunnel Modeling
NASA Astrophysics Data System (ADS)
Borrmann, A.; Kolbe, T. H.; Donaubauer, A.; Steuer, H.; Jubierre, J. R.
2013-09-01
A multi-scale representation of the built environment is required to provide information with the adequate level of detail (LoD) for different use cases and objectives. This applies not only to the visualization of city and building models, but in particular to their use in the context of planning and analysis tasks. While in the field of Geographic Information Systems, the handling of multi-scale representations is well established and understood, no formal approaches for incorporating multi-scale methods exist in the field of Building Information Modeling (BIM) so far. However, these concepts are much needed to better support highly dynamic planning processes that make use of very rough information about the facility under design in the early stages and provide increasingly detailed and fine-grained information in later stages. To meet these demands, this paper presents a comprehensive concept for incorporating multi-scale representations with infrastructural building information models, with a particular focus on the representation of shield tunnels. Based on a detailed analysis of the data modeling methods used in CityGML for capturing multiscale representations and the requirements present in the context of infrastructure planning projects, we discuss potential extensions to the BIM data model Industry Foundation Classes (IFC). Particular emphasis is put on providing means for preserving the consistency of the representation across the different Levels-of-Detail (LoD). To this end we make use of a procedural geometry description which makes it possible to define explicit dependencies between geometric entities on different LoDs. The modification of an object on a coarse level consequently results in an automated update of all dependent objects on the finer levels. Finally we discuss the transformation of the IFC-based multi-scale tunnel model into a CityGML compliant tunnel representation.
Concurrent multiscale modelling of atomistic and hydrodynamic processes in liquids.
Markesteijn, Anton; Karabasov, Sergey; Scukins, Arturs; Nerukh, Dmitry; Glotov, Vyacheslav; Goloviznin, Vasily
2014-08-06
Fluctuations of liquids at the scales where the hydrodynamic and atomistic descriptions overlap are considered. The importance of these fluctuations for atomistic motions is discussed and examples of their accurate modelling with a multi-space-time-scale fluctuating hydrodynamics scheme are provided. To resolve microscopic details of liquid systems, including biomolecular solutions, together with macroscopic fluctuations in space-time, a novel hybrid atomistic-fluctuating hydrodynamics approach is introduced. For a smooth transition between the atomistic and continuum representations, an analogy with two-phase hydrodynamics is used that leads to a strict preservation of macroscopic mass and momentum conservation laws. Examples of numerical implementation of the new hybrid approach for the multiscale simulation of liquid argon in equilibrium conditions are provided.
Multi-Scale Coupling in Ocean and Climate Modeling
Zhengyu Liu, Leslie Smith
2009-08-14
We have made significant progress on several projects aimed at understanding multi-scale dynamics in geophysical flows. Large-scale flows in the atmosphere and ocean are influenced by stable density stratification and rotation. The presence of stratification and rotation has important consequences through (i) the conservation of potential vorticity q = {omega} {center_dot} {del} {rho}, where {omega} is the total vorticity and {rho} is the density, and (ii) the existence of waves that affect the redistribution of energy from a given disturbance to the flow. Our research is centered on quantifying the effects of potential vorticity conservation and of wave interactions for the coupling of disparate time and space scales in the oceans and the atmosphere. Ultimately we expect the work to help improve predictive capabilities of atmosphere, ocean and climate modelers. The main findings of our research projects are described.
Concurrent multiscale modelling of atomistic and hydrodynamic processes in liquids
Markesteijn, Anton; Karabasov, Sergey; Scukins, Arturs; Nerukh, Dmitry; Glotov, Vyacheslav; Goloviznin, Vasily
2014-01-01
Fluctuations of liquids at the scales where the hydrodynamic and atomistic descriptions overlap are considered. The importance of these fluctuations for atomistic motions is discussed and examples of their accurate modelling with a multi-space–time-scale fluctuating hydrodynamics scheme are provided. To resolve microscopic details of liquid systems, including biomolecular solutions, together with macroscopic fluctuations in space–time, a novel hybrid atomistic–fluctuating hydrodynamics approach is introduced. For a smooth transition between the atomistic and continuum representations, an analogy with two-phase hydrodynamics is used that leads to a strict preservation of macroscopic mass and momentum conservation laws. Examples of numerical implementation of the new hybrid approach for the multiscale simulation of liquid argon in equilibrium conditions are provided. PMID:24982246
Multiscale Modeling of Metallic Materials Containing Embedded Particles
NASA Technical Reports Server (NTRS)
Phillips, Dawn R.; Iesulauro, Erin; Glaessgen, Edward H.
2004-01-01
Multiscale modeling at small length scales (10(exp -9) to 10(exp -3) m) is discussed for aluminum matrices with embedded particles. A configuration containing one particle surrounded by about 50 grains and subjected to uniform tension and lateral constraint is considered. The analyses are performed to better understand the effects of material configuration on the initiation and progression of debonding of the particles from the surrounding aluminum matrix. Configurational parameters considered include particle aspect ratio and orientation within the surrounding matrix. Both configurational parameters are shown to have a significant effect on the behavior of the materials as a whole. For elliptical particles with the major axis perpendicular to the direction of loading, a particle with a 1:1 aspect ratio completely debonds from the surrounding matrix at higher loads than particles with higher aspect ratios. As the particle major axis is aligned with the direction of the applied load, increasing amounts of load are required to completely debond the particles.
Image-Based Airborne LiDAR Point Cloud Encoding for 3d Building Model Retrieval
NASA Astrophysics Data System (ADS)
Chen, Yi-Chen; Lin, Chao-Hung
2016-06-01
With the development of Web 2.0 and cyber city modeling, an increasing number of 3D models have been available on web-based model-sharing platforms with many applications such as navigation, urban planning, and virtual reality. Based on the concept of data reuse, a 3D model retrieval system is proposed to retrieve building models similar to a user-specified query. The basic idea behind this system is to reuse these existing 3D building models instead of reconstruction from point clouds. To efficiently retrieve models, the models in databases are compactly encoded by using a shape descriptor generally. However, most of the geometric descriptors in related works are applied to polygonal models. In this study, the input query of the model retrieval system is a point cloud acquired by Light Detection and Ranging (LiDAR) systems because of the efficient scene scanning and spatial information collection. Using Point clouds with sparse, noisy, and incomplete sampling as input queries is more difficult than that by using 3D models. Because that the building roof is more informative than other parts in the airborne LiDAR point cloud, an image-based approach is proposed to encode both point clouds from input queries and 3D models in databases. The main goal of data encoding is that the models in the database and input point clouds can be consistently encoded. Firstly, top-view depth images of buildings are generated to represent the geometry surface of a building roof. Secondly, geometric features are extracted from depth images based on height, edge and plane of building. Finally, descriptors can be extracted by spatial histograms and used in 3D model retrieval system. For data retrieval, the models are retrieved by matching the encoding coefficients of point clouds and building models. In experiments, a database including about 900,000 3D models collected from the Internet is used for evaluation of data retrieval. The results of the proposed method show a clear superiority
Multiscale and Multiphysics Modeling of Additive Manufacturing of Advanced Materials
NASA Technical Reports Server (NTRS)
Liou, Frank; Newkirk, Joseph; Fan, Zhiqiang; Sparks, Todd; Chen, Xueyang; Fletcher, Kenneth; Zhang, Jingwei; Zhang, Yunlu; Kumar, Kannan Suresh; Karnati, Sreekar
2015-01-01
The objective of this proposed project is to research and develop a prediction tool for advanced additive manufacturing (AAM) processes for advanced materials and develop experimental methods to provide fundamental properties and establish validation data. Aircraft structures and engines demand materials that are stronger, useable at much higher temperatures, provide less acoustic transmission, and enable more aeroelastic tailoring than those currently used. Significant improvements in properties can only be achieved by processing the materials under nonequilibrium conditions, such as AAM processes. AAM processes encompass a class of processes that use a focused heat source to create a melt pool on a substrate. Examples include Electron Beam Freeform Fabrication and Direct Metal Deposition. These types of additive processes enable fabrication of parts directly from CAD drawings. To achieve the desired material properties and geometries of the final structure, assessing the impact of process parameters and predicting optimized conditions with numerical modeling as an effective prediction tool is necessary. The targets for the processing are multiple and at different spatial scales, and the physical phenomena associated occur in multiphysics and multiscale. In this project, the research work has been developed to model AAM processes in a multiscale and multiphysics approach. A macroscale model was developed to investigate the residual stresses and distortion in AAM processes. A sequentially coupled, thermomechanical, finite element model was developed and validated experimentally. The results showed the temperature distribution, residual stress, and deformation within the formed deposits and substrates. A mesoscale model was developed to include heat transfer, phase change with mushy zone, incompressible free surface flow, solute redistribution, and surface tension. Because of excessive computing time needed, a parallel computing approach was also tested. In addition
A multiscale strength model for extreme loading conditions
NASA Astrophysics Data System (ADS)
Barton, N. R.; Bernier, J. V.; Becker, R.; Arsenlis, A.; Cavallo, R.; Marian, J.; Rhee, M.; Park, H.-S.; Remington, B. A.; Olson, R. T.
2011-04-01
We present a multiscale strength model in which strength depends on pressure, strain rate, temperature, and evolving dislocation density. Model construction employs an information passing paradigm to span from the atomistic level to the continuum level. Simulation methods in the overall hierarchy include density functional theory, molecular statics, molecular dynamics, dislocation dynamics, and continuum based approaches. Given the nature of the subcontinuum simulations upon which the strength model is based, the model is particularly appropriate to strain rates in excess of 104 s-1. Strength model parameters are obtained entirely from the hierarchy of simulation methods to obtain a full strength model in a range of loading conditions that so far has been inaccessible to direct measurement of material strength. Model predictions compare favorably with relevant high energy density physics (HEDP) experiments that have bearing on material strength. The model is used to provide insight into HEDP experimental observations and to make predictions of what might be observable using dynamic x-ray diffraction based experimental methods.
Simulating cancer growth with multiscale agent-based modeling.
Wang, Zhihui; Butner, Joseph D; Kerketta, Romica; Cristini, Vittorio; Deisboeck, Thomas S
2015-02-01
There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models.
A MULTISCALE, CELL-BASED FRAMEWORK FOR MODELING CANCER DEVELOPMENT
JIANG, YI
2007-01-16
Cancer remains to be one of the leading causes of death due to diseases. We use a systems approach that combines mathematical modeling, numerical simulation, in vivo and in vitro experiments, to develop a predictive model that medical researchers can use to study and treat cancerous tumors. The multiscale, cell-based model includes intracellular regulations, cellular level dynamics and intercellular interactions, and extracellular level chemical dynamics. The intracellular level protein regulations and signaling pathways are described by Boolean networks. The cellular level growth and division dynamics, cellular adhesion and interaction with the extracellular matrix is described by a lattice Monte Carlo model (the Cellular Potts Model). The extracellular dynamics of the signaling molecules and metabolites are described by a system of reaction-diffusion equations. All three levels of the model are integrated through a hybrid parallel scheme into a high-performance simulation tool. The simulation results reproduce experimental data in both avasular tumors and tumor angiogenesis. By combining the model with experimental data to construct biologically accurate simulations of tumors and their vascular systems, this model will enable medical researchers to gain a deeper understanding of the cellular and molecular interactions associated with cancer progression and treatment.
Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J
2014-01-01
The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work.
NASA Astrophysics Data System (ADS)
Mizokami, Naoya; Nakahata, Kazuyuki; Ogi, Keiji; Yamawaki, Hisashi; Shiwa, Mitsuharu
2017-02-01
The use of fiber reinforced plastics (FRPs) as structural components has significantly increased in recent years. FRPs are made of stacks of plies, each of which is reinforced by fibers. When modeling ultrasonic wave propagation in FRPs, it is important to introduce three-dimensional mesoscopic and microscopic structures to account for the anisotropy and heterogeneity caused by fiber orientation and the lay-up of laminates. In this study, a finite element method using an image-based modeling is applied to simulation of ultrasonic wave propagation in a carbon FRP (CFRP). Here, the elastic stiffness of a single ply is determined using a homogenization method, where a CFRP microstructure is incorporated on the basis of a two-scale asymptotic expansion. The wave propagation in a CFRP specimen composed of unidirectionally aligned fibers is calculated, and the simulation results are compared to visualization results obtained for ultrasonic wave propagation using a laser scanning device.
Use of Image Based Modelling for Documentation of Intricately Shaped Objects
NASA Astrophysics Data System (ADS)
Marčiš, M.; Barták, P.; Valaška, D.; Fraštia, M.; Trhan, O.
2016-06-01
In the documentation of cultural heritage, we can encounter three dimensional shapes and structures which are complicated to measure. Such objects are for example spiral staircases, timber roof trusses, historical furniture or folk costume where it is nearly impossible to effectively use the traditional surveying or the terrestrial laser scanning due to the shape of the object, its dimensions and the crowded environment. The actual methods of digital photogrammetry can be very helpful in such cases with the emphasis on the automated processing of the extensive image data. The created high resolution 3D models and 2D orthophotos are very important for the documentation of architectural elements and they can serve as an ideal base for the vectorization and 2D drawing documentation. This contribution wants to describe the various usage of image based modelling in specific interior spaces and specific objects. The advantages and disadvantages of the photogrammetric measurement of such objects in comparison to other surveying methods are reviewed.
Linear theory for filtering nonlinear multiscale systems with model error
Berry, Tyrus; Harlim, John
2014-01-01
In this paper, we study filtering of multiscale dynamical systems with model error arising from limitations in resolving the smaller scale processes. In particular, the analysis assumes the availability of continuous-time noisy observations of all components of the slow variables. Mathematically, this paper presents new results on higher order asymptotic expansion of the first two moments of a conditional measure. In particular, we are interested in the application of filtering multiscale problems in which the conditional distribution is defined over the slow variables, given noisy observation of the slow variables alone. From the mathematical analysis, we learn that for a continuous time linear model with Gaussian noise, there exists a unique choice of parameters in a linear reduced model for the slow variables which gives the optimal filtering when only the slow variables are observed. Moreover, these parameters simultaneously give the optimal equilibrium statistical estimates of the underlying system, and as a consequence they can be estimated offline from the equilibrium statistics of the true signal. By examining a nonlinear test model, we show that the linear theory extends in this non-Gaussian, nonlinear configuration as long as we know the optimal stochastic parametrization and the correct observation model. However, when the stochastic parametrization model is inappropriate, parameters chosen for good filter performance may give poor equilibrium statistical estimates and vice versa; this finding is based on analytical and numerical results on our nonlinear test model and the two-layer Lorenz-96 model. Finally, even when the correct stochastic ansatz is given, it is imperative to estimate the parameters simultaneously and to account for the nonlinear feedback of the stochastic parameters into the reduced filter estimates. In numerical experiments on the two-layer Lorenz-96 model, we find that the parameters estimated online, as part of a filtering procedure
A Goddard Multi-Scale Modeling System with Unified Physics
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2010-01-01
A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. In this talk, I will present: (1) A brief review on GCE model and its applications on the impact of the aerosol on deep precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications). We are also performing the inline tracer calculation to comprehend the physical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems. In addition, high - resolution (spatial. 2km, and temporal, I minute) visualization showing the model results will be presented.
Quasi-3D Multi-scale Modeling Framework Development
NASA Astrophysics Data System (ADS)
Arakawa, A.; Jung, J.
2008-12-01
When models are truncated in or near an energetically active range of the spectrum, model physics must be changed as the resolution changes. The model physics of GCMs and that of CRMs are, however, quite different from each other and at present there is no unified formulation of model physics that automatically provides transition between these model physics. The Quasi-3D (Q3D) Multi-scale Modeling Framework (MMF) is an attempt to bridge this gap. Like the recently proposed Heterogeneous Multiscale Method (HMM) (E and Engquist 2003), MMF combines a macroscopic model, GCM, and a microscopic model, CRM. Unlike the traditional multiscale methods such as the multi-grid and adapted mesh refinement techniques, HMM and MMF are for solving multi-physics problems. They share the common objective "to design combined macroscopic-microscopic computational methods that are much more efficient than solving the full microscopic model and at the same time give the information we need" (E et al. 2008). The question is then how to meet this objective in practice, which can be highly problem dependent. In HHM, the efficiency is gained typically by localization of the microscale problem. Following the pioneering work by Grabowski and Smolarkiewicz (1999) and Grabowski (2001), MMF takes advantage of the fact that 2D CRMs are reasonably successful in simulating deep clouds. In this approach, the efficiency is gained by sacrificing the three-dimensionality of cloud-scale motion. It also "localizes" the algorithm through embedding a CRM in each GCM grid box using cyclic boundary condition. The Q3D MMF is an attempt to reduce the expense due to these constraints by partially including the cloud-scale 3D effects and extending the CRM beyond individual GCM grid boxes. As currently formulated, the Q3D MMF is a 4D estimation/prediction framework that combines a GCM with a 3D anelastic cloud-resolving vector vorticity equation model (VVM) applied to a network of horizontal grids. The network
Systematic multiscale models for deep convection on mesoscales
NASA Astrophysics Data System (ADS)
Klein, Rupert; Majda, Andrew J.
2006-11-01
This paper builds on recent developments of a unified asymptotic approach to meteorological modeling [ZAMM, 80: 765 777, 2000, SIAM Proc. App. Math. 116, 227 289, 2004], which was used successfully in the development of Systematic multiscale models for the tropics in Majda and Klein [J. Atmosph. Sci. 60: 393 408, 2003] and Majda and Biello [PNAS, 101: 4736 4741, 2004]. Biello and Majda [J. Atmosph. Sci. 62: 1694 1720, 2005]. Here we account for typical bulk microphysics parameterizations of moist processes within this framework. The key steps are careful nondimensionalization of the bulk microphysics equations and the choice of appropriate distinguished limits for the various nondimensional small parameters that appear. We are then in a position to study scale interactions in the atmosphere involving moist physics. We demonstrate this by developing two systematic multiscale models that are motivated by our interest in mesoscale organized convection. The emphasis here is on multiple length scales but common time scales. The first of these models describes the short-time evolution of slender, deep convective hot towers with horizontal scale ~ 1 km interacting with the linearized momentum balance on length and time scales of (10 km/3 min). We expect this model to describe how convective inhibition may be overcome near the surface, how the onset of deep convection triggers convective-scale gravity waves, and that it will also yield new insight into how such local convective events may conspire to create larger-scale strong storms. The second model addresses the next larger range of length and time scales (10 km, 100 km, and 20 min) and exhibits mathematical features that are strongly reminiscent of mesoscale organized convection. In both cases, the asymptotic analysis reveals how the stiffness of condensation/evaporation processes induces highly nonlinear dynamics. Besides providing new theoretical insights, the derived models may also serve as a theoretical devices
Multiscale Model of Colorectal Cancer Using the Cellular Potts Framework
Osborne, James M
2015-01-01
Colorectal cancer (CRC) is one of the major causes of death in the developed world and forms a canonical example of tumorigenesis. CRC arises from a string of mutations of individual cells in the colorectal crypt, making it particularly suited for multiscale multicellular modeling, where mutations of individual cells can be clearly represented and their effects readily tracked. In this paper, we present a multicellular model of the onset of colorectal cancer, utilizing the cellular Potts model (CPM). We use the model to investigate how, through the modification of their mechanical properties, mutant cells colonize the crypt. Moreover, we study the influence of mutations on the shape of cells in the crypt, suggesting possible cell- and tissue-level indicators for identifying early-stage cancerous crypts. Crucially, we discuss the effect that the motility parameters of the model (key factors in the behavior of the CPM) have on the distribution of cells within a homeostatic crypt, resulting in an optimal parameter regime that accurately reflects biological assumptions. In summary, the key results of this paper are 1) how to couple the CPM with processes occurring on other spatial scales, using the example of the crypt to motivate suitable motility parameters; 2) modeling mutant cells with the CPM; 3) and investigating how mutations influence the shape of cells in the crypt. PMID:26461973
Multi-scale modeling of the CD8 immune response
NASA Astrophysics Data System (ADS)
Barbarroux, Loic; Michel, Philippe; Adimy, Mostafa; Crauste, Fabien
2016-06-01
During the primary CD8 T-Cell immune response to an intracellular pathogen, CD8 T-Cells undergo exponential proliferation and continuous differentiation, acquiring cytotoxic capabilities to address the infection and memorize the corresponding antigen. After cleaning the organism, the only CD8 T-Cells left are antigen-specific memory cells whose role is to respond stronger and faster in case they are presented this very same antigen again. That is how vaccines work: a small quantity of a weakened pathogen is introduced in the organism to trigger the primary response, generating corresponding memory cells in the process, giving the organism a way to defend himself in case it encounters the same pathogen again. To investigate this process, we propose a non linear, multi-scale mathematical model of the CD8 T-Cells immune response due to vaccination using a maturity structured partial differential equation. At the intracellular scale, the level of expression of key proteins is modeled by a delay differential equation system, which gives the speeds of maturation for each cell. The population of cells is modeled by a maturity structured equation whose speeds are given by the intracellular model. We focus here on building the model, as well as its asymptotic study. Finally, we display numerical simulations showing the model can reproduce the biological dynamics of the cell population for both the primary response and the secondary responses.
Bayesian Multiscale Modeling of Closed Curves in Point Clouds.
Gu, Kelvin; Pati, Debdeep; Dunson, David B
2014-10-01
Modeling object boundaries based on image or point cloud data is frequently necessary in medical and scientific applications ranging from detecting tumor contours for targeted radiation therapy, to the classification of organisms based on their structural information. In low-contrast images or sparse and noisy point clouds, there is often insufficient data to recover local segments of the boundary in isolation. Thus, it becomes critical to model the entire boundary in the form of a closed curve. To achieve this, we develop a Bayesian hierarchical model that expresses highly diverse 2D objects in the form of closed curves. The model is based on a novel multiscale deformation process. By relating multiple objects through a hierarchical formulation, we can successfully recover missing boundaries by borrowing structural information from similar objects at the appropriate scale. Furthermore, the model's latent parameters help interpret the population, indicating dimensions of significant structural variability and also specifying a 'central curve' that summarizes the collection. Theoretical properties of our prior are studied in specific cases and efficient Markov chain Monte Carlo methods are developed, evaluated through simulation examples and applied to panorex teeth images for modeling teeth contours and also to a brain tumor contour detection problem.
A Goddard Multi-Scale Modeling System with Unified Physics
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2010-01-01
A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. In this talk, I will present: (1) A brief review on GCE model and its applications on the impact of the aerosol on deep precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications). We are also performing the inline tracer calculation to comprehend the ph ysical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems.
Multiscale forward electromagnetic model of uterine contractions during pregnancy
2012-01-01
Background Analyzing and monitoring uterine contractions during pregnancy is relevant to the field of reproductive health assessment. Its clinical importance is grounded in the need to reliably predict the onset of labor at term and pre-term. Preterm births can cause health problems or even be fatal for the fetus. Currently, there are no objective methods for consistently predicting the onset of labor based on sensing of the mechanical or electrophysiological aspects of uterine contractions. Therefore, modeling uterine contractions could help to better interpret such measurements and to develop more accurate methods for predicting labor. In this work, we develop a multiscale forward electromagnetic model of myometrial contractions during pregnancy. In particular, we introduce a model of myometrial current source densities and compute its magnetic field and action potential at the abdominal surface, using Maxwell’s equations and a four-compartment volume conductor geometry. To model the current source density at the myometrium we use a bidomain approach. We consider a modified version of the Fitzhugh-Nagumo (FHN) equation for modeling ionic currents in each myocyte, assuming a plateau-type transmembrane potential, and we incorporate the anisotropic nature of the uterus by designing conductivity-tensor fields. Results We illustrate our modeling approach considering a spherical uterus and one pacemaker located in the fundus. We obtained a travelling transmembrane potential depolarizing from −56 mV to −16 mV and an average potential in the plateau area of −25 mV with a duration, before hyperpolarization, of 35 s, which is a good approximation with respect to the average recorded transmembrane potentials at term reported in the technical literature. Similarly, the percentage of myometrial cells contracting as a function of time had the same symmetric properties and duration as the intrauterine pressure waveforms of a pregnant human myometrium at term
Statistical Inverse Ray Tracing for Image-Based 3D Modeling.
Liu, Shubao; Cooper, David B
2014-10-01
This paper proposes a new formulation and solution to image-based 3D modeling (aka "multi-view stereo") based on generative statistical modeling and inference. The proposed new approach, named statistical inverse ray tracing, models and estimates the occlusion relationship accurately through optimizing a physically sound image generation model based on volumetric ray tracing. Together with geometric priors, they are put together into a Bayesian formulation known as Markov random field (MRF) model. This MRF model is different from typical MRFs used in image analysis in the sense that the ray clique, which models the ray-tracing process, consists of thousands of random variables instead of two to dozens. To handle the computational challenges associated with large clique size, an algorithm with linear computational complexity is developed by exploiting, using dynamic programming, the recursive chain structure of the ray clique. We further demonstrate the benefit of exact modeling and accurate estimation of the occlusion relationship by evaluating the proposed algorithm on several challenging data sets.
Cummings, P. T.
2010-02-08
This document reports the outcomes of the Computational Nanoscience Project, "Integrated Multiscale Modeling of Molecular Computing Devices". It includes a list of participants and publications arising from the research supported.
Bayesian Multiscale Modeling of Closed Curves in Point Clouds
Gu, Kelvin; Pati, Debdeep; Dunson, David B.
2014-01-01
Modeling object boundaries based on image or point cloud data is frequently necessary in medical and scientific applications ranging from detecting tumor contours for targeted radiation therapy, to the classification of organisms based on their structural information. In low-contrast images or sparse and noisy point clouds, there is often insufficient data to recover local segments of the boundary in isolation. Thus, it becomes critical to model the entire boundary in the form of a closed curve. To achieve this, we develop a Bayesian hierarchical model that expresses highly diverse 2D objects in the form of closed curves. The model is based on a novel multiscale deformation process. By relating multiple objects through a hierarchical formulation, we can successfully recover missing boundaries by borrowing structural information from similar objects at the appropriate scale. Furthermore, the model’s latent parameters help interpret the population, indicating dimensions of significant structural variability and also specifying a ‘central curve’ that summarizes the collection. Theoretical properties of our prior are studied in specific cases and efficient Markov chain Monte Carlo methods are developed, evaluated through simulation examples and applied to panorex teeth images for modeling teeth contours and also to a brain tumor contour detection problem. PMID:25544786
Multiscale modeling of droplet interface bilayer membrane networks
Freeman, Eric C.; Farimani, Amir B.; Aluru, Narayana R.; Philen, Michael K.
2015-01-01
Droplet interface bilayer (DIB) networks are considered for the development of stimuli-responsive membrane-based materials inspired by cellular mechanics. These DIB networks are often modeled as combinations of electrical circuit analogues, creating complex networks of capacitors and resistors that mimic the biomolecular structures. These empirical models are capable of replicating data from electrophysiology experiments, but these models do not accurately capture the underlying physical phenomena and consequently do not allow for simulations of material functionalities beyond the voltage-clamp or current-clamp conditions. The work presented here provides a more robust description of DIB network behavior through the development of a hierarchical multiscale model, recognizing that the macroscopic network properties are functions of their underlying molecular structure. The result of this research is a modeling methodology based on controlled exchanges across the interfaces of neighboring droplets. This methodology is validated against experimental data, and an extension case is provided to demonstrate possible future applications of droplet interface bilayer networks. PMID:26594262
Extreme Precipitation in a Multi-Scale Modeling Framework
NASA Astrophysics Data System (ADS)
Phillips, M.; Denning, S.; Arabi, M.
2015-12-01
Extreme precipitation events are characterized by infrequent but large magnitude accummulatations that generally occur on scales belowthat resolved by the typical Global Climate Model. The Multi-scale Modeling Framework allows for information about the precipitation on these scales to be simulated for long periods of time without the large computational resources required for the use of a full cloud permitting model. The Community Earth System Model was run for 30 years in both its MMF and GCM modes, and the annual maximum series of 24 hour precipitation accumulations were used to estimate the parameters of statistical distributions. The distributions generated from model ouput were then fit to a General Extreme Value distribution and evaluated against observations. These results indicate that the MMF produces extreme precipitation with a statistical distribution that closely resembles that of observations and motivates the continued use of the MMF for analysis of extreme precipitation, and shows an improvement over the traditional GCM. The improvement in statistical distributions of annual maxima is greatest in regions that are dominated by convective precipitation where the small-scale information provided by the MMF heavily influences precipitation processes.
Relational grounding facilitates development of scientifically useful multiscale models
2011-01-01
We review grounding issues that influence the scientific usefulness of any biomedical multiscale model (MSM). Groundings are the collection of units, dimensions, and/or objects to which a variable or model constituent refers. To date, models that primarily use continuous mathematics rely heavily on absolute grounding, whereas those that primarily use discrete software paradigms (e.g., object-oriented, agent-based, actor) typically employ relational grounding. We review grounding issues and identify strategies to address them. We maintain that grounding issues should be addressed at the start of any MSM project and should be reevaluated throughout the model development process. We make the following points. Grounding decisions influence model flexibility, adaptability, and thus reusability. Grounding choices should be influenced by measures, uncertainty, system information, and the nature of available validation data. Absolute grounding complicates the process of combining models to form larger models unless all are grounded absolutely. Relational grounding facilitates referent knowledge embodiment within computational mechanisms but requires separate model-to-referent mappings. Absolute grounding can simplify integration by forcing common units and, hence, a common integration target, but context change may require model reengineering. Relational grounding enables synthesis of large, composite (multi-module) models that can be robust to context changes. Because biological components have varying degrees of autonomy, corresponding components in MSMs need to do the same. Relational grounding facilitates achieving such autonomy. Biomimetic analogues designed to facilitate translational research and development must have long lifecycles. Exploring mechanisms of normal-to-disease transition requires model components that are grounded relationally. Multi-paradigm modeling requires both hyperspatial and relational grounding. PMID:21951817
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.
Multi-Scale Modeling of Global of Magnetospheric Dynamics
NASA Technical Reports Server (NTRS)
Kuznetsova, M. M.; Hesse, M.; Rastatter, L.; Toth, G.; DeZeeuw, D.; Gombosi, T.
2010-01-01
To understand the role of magnetic reconnection in global evolution of magnetosphere and to place spacecraft observations into global context it is essential to perform global simulations with physically motivated model of dissipation that is capable to reproduce reconnection rates predicted by kinetic models. In our efforts to bridge the gap between small scale kinetic modeling and global simulations we introduced an approach that allows to quantify the interaction between large-scale global magnetospheric dynamics and microphysical processes in diffusion regions near reconnection sites. We utilized the high resolution global MHD code BATSRUS and incorporate primary mechanism controlling the dissipation in the vicinity of reconnection sites in terms of kinetic corrections to induction and energy equations. One of the key elements of the multiscale modeling of magnetic reconnection is identification of reconnection sites and boundaries of surrounding diffusion regions where non-MHD corrections are required. Reconnection site search in the equatorial plane implemented in our previous studies is extended to cusp and magnetopause reconnection, as well as for magnetotail reconnection in realistic asymmetric configurations. The role of feedback between the non-ideal effects in diffusion regions and global magnetosphere structure and dynamics will be discussed.
Improving NASA's Multiscale Modeling Framework for Tropical Cyclone Climate Study
NASA Technical Reports Server (NTRS)
Shen, Bo-Wen; Nelson, Bron; Cheung, Samson; Tao, Wei-Kuo
2013-01-01
One of the current challenges in tropical cyclone (TC) research is how to improve our understanding of TC interannual variability and the impact of climate change on TCs. Recent advances in global modeling, visualization, and supercomputing technologies at NASA show potential for such studies. In this article, the authors discuss recent scalability improvement to the multiscale modeling framework (MMF) that makes it feasible to perform long-term TC-resolving simulations. The MMF consists of the finite-volume general circulation model (fvGCM), supplemented by a copy of the Goddard cumulus ensemble model (GCE) at each of the fvGCM grid points, giving 13,104 GCE copies. The original fvGCM implementation has a 1D data decomposition; the revised MMF implementation retains the 1D decomposition for most of the code, but uses a 2D decomposition for the massive copies of GCEs. Because the vast majority of computation time in the MMF is spent computing the GCEs, this approach can achieve excellent speedup without incurring the cost of modifying the entire code. Intelligent process mapping allows differing numbers of processes to be assigned to each domain for load balancing. The revised parallel implementation shows highly promising scalability, obtaining a nearly 80-fold speedup by increasing the number of cores from 30 to 3,335.
A multiscale model of Earth's inner-core anisotropy
NASA Astrophysics Data System (ADS)
Merkel, Sébastien; Lincot, Ainhoa; Deguen, Renaud; Cardin, Philippe
2016-04-01
The Earth's solid inner-core exhibits a global seismic anisotropy of several percents. It results from a coherent alignment of anisotropic Fe-alloy crystals through the inner-core history that can be sampled by present-day seismic observations. By combining self-consistent polycrystal plasticity, inner-core formation models, Monte-Carlo search for elastic moduli, and simulations of seismic measurements, we introduce a multiscale model that can reproduce a global seismic anisotropy of several percents aligned with the Earth's rotation axis. Cubic-structured Fe-alloy fail at producing significant global scale anisotropy. Conditions for a successful model are an hexagonal-close-packed structure for the inner-core Fe-alloy, plastic deformation by pyramidal ⟨c + a⟩ slip, and large-scale flow induced by a low-degree inner-core formation model. For global anisotropies ranging between 1 and 3%, the elastic anisotropy in the single crystal ranges from 5 to 20% with larger velocities along the c-axis.
Upscalling processes in an ocean-atmosphere multiscale coupled model
NASA Astrophysics Data System (ADS)
Masson, S. G.; Berthet, S.; Samson, G.; Crétat, J.; Colas, F.; Echevin, V.; Jullien, S.; Hourdin, C.
2015-12-01
This work explores new pathways toward a better representation of the multi-scale physics that drive climate variability. We are analysing the key upscaling processes by which small-scale localized errors have a knock-on effect onto global climate. We focus on the Peru-Chilli coastal upwelling, an area known to hold among the strongest models biases in the Tropics. Our approach is based on the development of a multiscale coupling interface allowing us to couple WRF with the NEMO oceanic model in a configuration including 2-way nested zooms in the oceanic and/or the atmospheric component of the coupled model. Upscalling processes are evidenced and quantified by comparing three 20-year long simulations of a tropical channel (45°S-45°N), which differ by their horizontal resolution: 0.75° everywhere, 0.75°+0.25° zoom in the southeastern Pacific or 0.25° everywhere. This set of three 20-year long simulations was repeated with 3 different sets of parameterizations to assess the robustness of our results. Our results show that adding an embedded zoom over the southeastern Pacific only in the atmosphere cools down the SST along the Peru-Chili coast, which is a clear improvement. This change is associated with a displacement of the low-level cloud cover, which moves closer to the coast cooling further the coastal area SST. Offshore, we observe the opposite effect with a reduction of the cloud cover with higher resolution, which increases solar radiation and warms the SST. Increasing the resolution in the oceanic component show contrasting results according to the different set parameterization used in the experiments. Some experiment shows a coastal cooling as expected, whereas, in other cases, we observe a counterintuitive response with a warming of the coastal SST. Using at the same time an oceanic and an atmospheric zoom mostly combines the results obtained when using the 2-way nesting in only one component of the coupled model. In the best case, we archive by this
Image-based models of cardiac structure in health and disease
Vadakkumpadan, Fijoy; Arevalo, Hermenegild; Prassl, Anton J.; Chen, Junjie; Kickinger, Ferdinand; Kohl, Peter; Plank, Gernot; Trayanova, Natalia
2010-01-01
Computational approaches to investigating the electromechanics of healthy and diseased hearts are becoming essential for the comprehensive understanding of cardiac function. In this article, we first present a brief review of existing image-based computational models of cardiac structure. We then provide a detailed explanation of a processing pipeline which we have recently developed for constructing realistic computational models of the heart from high resolution structural and diffusion tensor (DT) magnetic resonance (MR) images acquired ex vivo. The presentation of the pipeline incorporates a review of the methodologies that can be used to reconstruct models of cardiac structure. In this pipeline, the structural image is segmented to reconstruct the ventricles, normal myocardium, and infarct. A finite element mesh is generated from the segmented structural image, and fiber orientations are assigned to the elements based on DTMR data. The methods were applied to construct seven different models of healthy and diseased hearts. These models contain millions of elements, with spatial resolutions in the order of hundreds of microns, providing unprecedented detail in the representation of cardiac structure for simulation studies. PMID:20582162
Multiscale modelling of hydrothermal biomass pretreatment for chip size optimization.
Hosseini, Seyed Ali; Shah, Nilay
2009-05-01
The objective of this work is to develop a relationship between biomass chip size and the energy requirement of hydrothermal pretreatment processes using a multiscale modelling approach. The severity factor or modified severity factor is currently used to characterize some hydrothermal pretreatment methods. Although these factors enable an easy comparison of experimental results to facilitate process design and operation, they are not representative of all the factors affecting the efficiency of pretreatment, because processes with the same temperature, residence time, and pH will not have same effect on biomass chips of different size. In our study, a model based on the diffusion of liquid or steam in the biomass that takes into account the interrelationship between chip size and time is developed. With the aid of our developed model, a method to find the optimum chip size that minimizes the energy requirement of grinding and pretreatment processes is proposed. We show that with the proposed optimization method, an average saving equivalent to a 5% improvement in the yield of biomass to ethanol conversion process can be achieved.
Multiscale Modeling of Heat Conduction in Carbon Nanotube Aerogels
NASA Astrophysics Data System (ADS)
Gong, Feng; Papavassiliou, Dimitrios; Duong, Hai
Carbon nanotube (CNT) aerogels have attracted a lot of interest due to their ultrahigh strength/weight and surface area/weight ratios. They are promising advanced materials used in energy storage systems, hydrogen storage media and weight-conscious devices such as satellites, because of their ultralight and highly porous quality. CNT aerogels can have excellent electrical conductivity and mechanical strength. However, the thermal conductivity of CNT aerogels are as low as 0.01-0.1 W/mK, which is five orders of magnitude lower than that of CNT (2000-5000 W/mK). To investigate the mechanisms for the low thermal conductivity of CNT aerogels, multiscale models are built in this study. Molecular dynamic (MD) simulations are first carried out to investigate the heat transfer between CNT and different gases (e.g. nitrogen and hydrogen), and the thermal conductance at CNT-CNT interface. The interfacial thermal resistances of CNT-gas and CNT-CNT are estimated from the MD simulations. Mesoscopic modeling of CNT aerogels are then built using an off-lattice Monte Carlo (MC) simulations to replicate the realistic CNT aerogels. The interfacial thermal resistances estimated from MD simulations are used as inputs in the MC models to predict the thermal conductivity of CNT aerogels. The volume fractions and the complex morphologies of CNTs are also quantified to study their effects on the thermal conductivity of CNT aerogels. The quantitative findings may help researchers to obtain the CNT aerogels with expected thermal conductivity.
Multi-Scale Modeling of Cross-Linked Nanotube Materials
NASA Technical Reports Server (NTRS)
Frankland, S. J. V.; Odegard, G. M.; Herzog, M. N.; Gates, T. S.; Fay, C. C.
2005-01-01
The effect of cross-linking single-walled carbon nanotubes on the Young's modulus of a nanotube-reinforced composite is modeled with a multi-scale method. The Young's modulus is predicted as a function of nanotube volume fraction and cross-link density. In this method, the constitutive properties of molecular representative volume elements are determined using molecular dynamics simulation and equivalent-continuum modeling. The Young's modulus is subsequently calculated for cross-linked nanotubes in a matrix which consists of the unreacted cross-linking agent. Two different cross-linking agents are used in this study, one that is short and rigid (Molecule A), and one that is long and flexible (Molecule B). Direct comparisons between the predicted elastic constants are made for the models in which the nanotubes are either covalently bonded or not chemically bonded to the cross-linking agent. At a nanotube volume fraction of 10%, the Young's modulus of Material A is not affected by nanotube crosslinking, while the Young's modulus of Material B is reduced by 64% when the nanotubes are cross-linked relative to the non-cross-linked material with the same matrix.
Image-based Modeling of PSF Deformation with Application to Limited Angle PET Data.
Matej, Samuel; Li, Yusheng; Panetta, Joseph; Karp, Joel S; Surti, Suleman
2016-10-01
The point-spread-functions (PSFs) of reconstructed images can be deformed due to detector effects such as resolution blurring and parallax error, data acquisition geometry such as insufficient sampling or limited angular coverage in dual-panel PET systems, or reconstruction imperfections/simplifications. PSF deformation decreases quantitative accuracy and its spatial variation lowers consistency of lesion uptake measurement across the imaging field-of-view (FOV). This can be a significant problem with dual panel PET systems even when using TOF data and image reconstruction models of the detector and data acquisition process. To correct for the spatially variant reconstructed PSF distortions we propose to use an image-based resolution model (IRM) that includes such image PSF deformation effects. Originally the IRM was mostly used for approximating data resolution effects of standard PET systems with full angular coverage in a computationally efficient way, but recently it was also used to mitigate effects of simplified geometric projectors. Our work goes beyond this by including into the IRM reconstruction imperfections caused by combination of the limited angle, parallax errors, and any other (residual) deformation effects and testing it for challenging dual panel data with strongly asymmetric and variable PSF deformations. We applied and tested these concepts using simulated data based on our design for a dedicated breast imaging geometry (B-PET) consisting of dual-panel, time-of-flight (TOF) detectors. We compared two image-based resolution models; i) a simple spatially invariant approximation to PSF deformation, which captures only the general PSF shape through an elongated 3D Gaussian function, and ii) a spatially variant model using a Gaussian mixture model (GMM) to more accurately capture the asymmetric PSF shape in images reconstructed from data acquired with the B-PET scanner geometry. Results demonstrate that while both IRMs decrease the overall uptake
Multi-scale Modeling of Plasticity in Tantalum.
Lim, Hojun; Battaile, Corbett Chandler.; Carroll, Jay; Buchheit, Thomas E.; Boyce, Brad; Weinberger, Christopher
2015-12-01
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 describing 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
Multiscale mathematical modeling of the hypothalamo-pituitary-gonadal axis.
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
Multiscale modeling and simulation of microtubule-motor-protein assemblies
NASA Astrophysics Data System (ADS)
Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; Betterton, M. D.; Shelley, Michael J.
2015-12-01
Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate-consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation.
Multiscale modeling and simulation of microtubule-motor-protein assemblies.
Gao, Tong; Blackwell, Robert; Glaser, Matthew A; Betterton, M D; Shelley, Michael J
2015-01-01
Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate-consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation.
Theory and Modeling for the Magnetospheric Multiscale Mission
NASA Astrophysics Data System (ADS)
Hesse, M.; Aunai, N.; Birn, J.; Cassak, P.; Denton, R. E.; Drake, J. F.; Gombosi, T.; Hoshino, M.; Matthaeus, W.; Sibeck, D.; Zenitani, S.
2016-03-01
The Magnetospheric Multiscale (MMS) mission will provide measurement capabilities, which will exceed those of earlier and even contemporary missions by orders of magnitude. MMS will, for the first time, be able to measure directly and with sufficient resolution key features of the magnetic reconnection process, down to the critical electron scales, which need to be resolved to understand how reconnection works. Owing to the complexity and extremely high spatial resolution required, no prior measurements exist, which could be employed to guide the definition of measurement requirements, and consequently set essential parameters for mission planning and execution. Insight into expected details of the reconnection process could hence only been obtained from theory and modern kinetic modeling. This situation was recognized early on by MMS leadership, which supported the formation of a fully integrated Theory and Modeling Team (TMT). The TMT participated in all aspects of mission planning, from the proposal stage to individual aspects of instrument performance characteristics. It provided and continues to provide to the mission the latest insights regarding the kinetic physics of magnetic reconnection, as well as associated particle acceleration and turbulence, assuring that, to the best of modern knowledge, the mission is prepared to resolve the inner workings of the magnetic reconnection process. The present paper provides a summary of key recent results or reconnection research by TMT members.
Multiscale modeling and simulation of microtubule–motor-protein assemblies
Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; Betterton, M. D.; Shelley, Michael J.
2016-01-01
Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate–consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation. PMID:26764729
Multiscale computational modeling of a radiantly driven solar thermal collector
NASA Astrophysics Data System (ADS)
Ponnuru, Koushik
The objectives of the master's thesis are to present, discuss and apply sequential multiscale modeling that combines analytical, numerical (finite element-based) and computational fluid dynamic (CFD) analysis to assist in the development of a radiantly driven macroscale solar thermal collector for energy harvesting. The solar thermal collector is a novel green energy system that converts solar energy to heat and utilizes dry air as a working heat transfer fluid (HTF). This energy system has important advantages over competitive technologies: it is self-contained (no energy sources are needed), there are no moving parts, no oil or supplementary fluids are needed and it is environmentally friendly since it is powered by solar radiation. This work focuses on the development of multi-physics and multiscale models for predicting the performance of the solar thermal collector. Model construction and validation is organized around three distinct and complementary levels. The first level involves an analytical analysis of the thermal transpiration phenomenon and models for predicting the associated mass flow pumping that occurs in an aerogel membrane in the presence of a large thermal gradient. Within the aerogel, a combination of convection, conduction and radiation occurs simultaneously in a domain where the pore size is comparable to the mean free path of the gas molecules. CFD modeling of thermal transpiration is not possible because all the available commercial CFD codes solve the Navier Stokes equations only for continuum flow, which is based on the assumption that the net molecular mass diffusion is zero. However, thermal transpiration occurs in a flow regime where a non-zero net molecular mass diffusion exists. Thus these effects are modeled by using Sharipov's [2] analytical expression for gas flow characterized by high Knudsen number. The second level uses a detailed CFD model solving Navier Stokes equations for momentum, heat and mass transfer in the various
MIDA: A Multimodal Imaging-Based Detailed Anatomical Model of the Human Head and Neck
Iacono, Maria Ida; Neufeld, Esra; Akinnagbe, Esther; Bower, Kelsey; Wolf, Johanna; Vogiatzis Oikonomidis, Ioannis; Sharma, Deepika; Lloyd, Bryn; Wilm, Bertram J.; Wyss, Michael; Pruessmann, Klaas P.; Jakab, Andras; Makris, Nikos; Cohen, Ethan D.; Kuster, Niels; Kainz, Wolfgang; Angelone, Leonardo M.
2015-01-01
Computational modeling and simulations are increasingly being used to complement experimental testing for analysis of safety and efficacy of medical devices. Multiple voxel- and surface-based whole- and partial-body models have been proposed in the literature, typically with spatial resolution in the range of 1–2 mm and with 10–50 different tissue types resolved. We have developed a multimodal imaging-based detailed anatomical model of the human head and neck, named “MIDA”. The model was obtained by integrating three different magnetic resonance imaging (MRI) modalities, the parameters of which were tailored to enhance the signals of specific tissues: i) structural T1- and T2-weighted MRIs; a specific heavily T2-weighted MRI slab with high nerve contrast optimized to enhance the structures of the ear and eye; ii) magnetic resonance angiography (MRA) data to image the vasculature, and iii) diffusion tensor imaging (DTI) to obtain information on anisotropy and fiber orientation. The unique multimodal high-resolution approach allowed resolving 153 structures, including several distinct muscles, bones and skull layers, arteries and veins, nerves, as well as salivary glands. The model offers also a detailed characterization of eyes, ears, and deep brain structures. A special automatic atlas-based segmentation procedure was adopted to include a detailed map of the nuclei of the thalamus and midbrain into the head model. The suitability of the model to simulations involving different numerical methods, discretization approaches, as well as DTI-based tensorial electrical conductivity, was examined in a case-study, in which the electric field was generated by transcranial alternating current stimulation. The voxel- and the surface-based versions of the models are freely available to the scientific community. PMID:25901747
MIDA: A Multimodal Imaging-Based Detailed Anatomical Model of the Human Head and Neck.
Iacono, Maria Ida; Neufeld, Esra; Akinnagbe, Esther; Bower, Kelsey; Wolf, Johanna; Vogiatzis Oikonomidis, Ioannis; Sharma, Deepika; Lloyd, Bryn; Wilm, Bertram J; Wyss, Michael; Pruessmann, Klaas P; Jakab, Andras; Makris, Nikos; Cohen, Ethan D; Kuster, Niels; Kainz, Wolfgang; Angelone, Leonardo M
2015-01-01
Computational modeling and simulations are increasingly being used to complement experimental testing for analysis of safety and efficacy of medical devices. Multiple voxel- and surface-based whole- and partial-body models have been proposed in the literature, typically with spatial resolution in the range of 1-2 mm and with 10-50 different tissue types resolved. We have developed a multimodal imaging-based detailed anatomical model of the human head and neck, named "MIDA". The model was obtained by integrating three different magnetic resonance imaging (MRI) modalities, the parameters of which were tailored to enhance the signals of specific tissues: i) structural T1- and T2-weighted MRIs; a specific heavily T2-weighted MRI slab with high nerve contrast optimized to enhance the structures of the ear and eye; ii) magnetic resonance angiography (MRA) data to image the vasculature, and iii) diffusion tensor imaging (DTI) to obtain information on anisotropy and fiber orientation. The unique multimodal high-resolution approach allowed resolving 153 structures, including several distinct muscles, bones and skull layers, arteries and veins, nerves, as well as salivary glands. The model offers also a detailed characterization of eyes, ears, and deep brain structures. A special automatic atlas-based segmentation procedure was adopted to include a detailed map of the nuclei of the thalamus and midbrain into the head model. The suitability of the model to simulations involving different numerical methods, discretization approaches, as well as DTI-based tensorial electrical conductivity, was examined in a case-study, in which the electric field was generated by transcranial alternating current stimulation. The voxel- and the surface-based versions of the models are freely available to the scientific community.
Multiscale models for synoptic-mesoscale interactions in the ocean
NASA Astrophysics Data System (ADS)
Grooms, Ian; Shafer Smith, K.; Majda, Andrew J.
2012-11-01
Multiscale analysis is used to derive two sets of coupled models, each based on the same distinguished limit, to represent the interaction of the midlatitude oceanic synoptic scale-where coherent features such as jets and rings form-and the mesoscale, defined by the internal deformation scale. The synoptic scale and mesoscale overlap at low and mid latitudes, and are hence synonymous in much of the oceanographic literature; at higher latitudes the synoptic scale can be an order of magnitude larger than the deformation scale, which motivates our asymptotic approach and our nonstandard terminology. In the first model the synoptic dynamics are described by ‘Large Amplitude Geostrophic’ (LAG) equations while the eddy dynamics are quasigeostrophic. This model has order one isopycnal variation on the synoptic scale; the synoptic dynamics respond to an eddy momentum flux while the eddy dynamics respond to the baroclinically unstable synoptic density gradient. The second model assumes small isopycnal variation on the synoptic scale, but allows for a planetary scale background density gradient that may be fixed or evolved on a slower time scale. Here the large-scale equations are just the barotropic quasigeostrophic equations, and the mesoscale is modeled by the baroclinic quasigeostrophic equations. The synoptic dynamics now respond to both eddy momentum and buoyancy fluxes, but the small-scale eddy dynamics are simply advected by the synoptic-scale flow-there is no baroclinic production term in the eddy equations. The energy budget is closed by deriving an equation for the slow evolution of the eddy energy, which ensures that energy gained or lost by the synoptic-scale flow is reflected in a corresponding loss or gain by the eddies. This latter model, aided by the eddy energy equation-a key result of this paper-provides a conceptual basis through which to understand the classic baroclinic turbulence cycle.
Facing the challenges of multiscale modelling of bacterial and fungal pathogen-host interactions.
Schleicher, Jana; Conrad, Theresia; Gustafsson, Mika; Cedersund, Gunnar; Guthke, Reinhard; Linde, Jörg
2016-02-08
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.
Modeling of Multi-Scale Channeling Phenomena in Porous Flow
NASA Astrophysics Data System (ADS)
Räss, Ludovic; Omlin, Samuel; Yarushina, Viktoriya; Simon, Nina; Podladchikov, Yuri
2015-04-01
Predictive modeling of fluid percolation through tight porous rocks is critical to evaluate environmental risks associated with waste storage and reservoir operations. To understand the evolution of two-phase mixtures of fluid and solid it is insufficient to only combine single-phase fluid flow methods and solid mechanics. A proper coupling of these two different multi-scales physical processes is required to describe the complex evolution of permeability and porosity in space and in time. We conduct numerical modeling experiments in geometrically simple but physically complex systems of stressed rocks containing self-focusing porous flow. Our model is physically and thermodynamically consistent and describes the formation and evolution of fluid pathways. The model consists of a system of coupled equations describing poro-elasto-viscous deformation and flow. Nonlinearity of the solid rheology is also taken into account. We have developed a numerical application based on an iterative finite difference scheme that runs on mutli-GPUs cluster in parallel. In order to validate these models, we consider the largest CO2 sequestration project in operation at the Sleipner field in the Norwegian North Sea. Attempts to match the observations at Sleipner using conventional reservoir simulations fail to capture first order observations, such as the seemingly effortless vertical flow of CO2 through low permeability shale layers and the formation of focused flow channels or chimneys. Conducted high-resolution three-dimensional numerical simulations predict the formation of dynamically evolving high porosity and permeability pathways as a natural outcome of porous flow nonlinearly coupled with rock deformation, which may trigger leakage through low permeability barriers.
Zhao, Fu; Landis, Heather R; Skerlos, Steven J
2005-01-01
A methodology for producing a pore-scale, 3D computational model of porous filter permeability is developed that is based on the analysis of 2D images of the filter matrix and first principles. The computationally reconstructed porous filter model retains statistical details of porosity and the spatial correlations of porosity within the filter and can be used to calculate permeability for either isotropic or 1D anisotropic porous filters. In the isotropic case, validation of the methodology was conducted using 0.2 and 0.8 microm ceramic membrane filters,forwhich it is shown that the image-based computational models provide a viable statistical reproduction of actual porosity characteristics. It is also shown that these models can predict water flux directly from first principles with deviations from experimental measurements in the range of experimental error. In the anisotropic case, validation of the methodology was conducted using a natural river sand filter. For this case, it is shown that the methodology yields predictions of filtration velocity that are similar or better than predictions offered by existing filtration models. It was found for the sand filter that the deviation between observation and prediction was mostly due to swelling during the preparation of the sand filter for imaging and can be reduced significantly using alternative methods reported in the literature. On the basis of these results, it is concluded that the computational reconstruction methodology is valid for porous filter modeling, and given that it captures pore-scale details, it has potential application to the investigation of permeability decline underthe influence of pore-scale fouling mechanisms.
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.
Multi-scale model of food drying: Current status and challenges.
Rahman, M M; Joardder, Mohammad U H; Khan, M I H; Nghia, Duc Pham; Karim, M A
2016-09-19
For a long time, food engineers have been trying to describe the physical phenomena that occur during food processing especially drying. Physics-based theoretical modeling is an important tool for the food engineers to reduce the hurdles of experimentation. Drying of food is a multi-physics phenomenon such as coupled heat and mass transfer. Moreover, food structure is multi-scale in nature, and the microstructural features play a great role in the food processing specially in drying. Previously simple macroscopic model was used to describe the drying phenomena which can give a little description about the smaller scale. The multiscale modeling technique can handle all the phenomena that occur during drying. In this special kind of modeling approach, the single scale models from bigger to smaller scales are interconnected. With the help of multiscale modeling framework, the transport process associated with drying can be studied on a smaller scale and the resulting information can be transferred to the bigger scale. This article is devoted to discussing the state of the art multi-scale modeling, its prospect and challenges in the field of drying technology. This article has also given some directions to how to overcome the challenges for successful implementation of multi-scale modeling.
Full field spatially-variant image-based resolution modelling reconstruction for the HRRT.
Angelis, Georgios I; Kotasidis, Fotis A; Matthews, Julian C; Markiewicz, Pawel J; Lionheart, William R; Reader, Andrew J
2015-03-01
Accurate characterisation of the scanner's point spread function across the entire field of view (FOV) is crucial in order to account for spatially dependent factors that degrade the resolution of the reconstructed images. The HRRT users' community resolution modelling reconstruction software includes a shift-invariant resolution kernel, which leads to transaxially non-uniform resolution in the reconstructed images. Unlike previous work to date in this field, this work is the first to model the spatially variant resolution across the entire FOV of the HRRT, which is the highest resolution human brain PET scanner in the world. In this paper we developed a spatially variant image-based resolution modelling reconstruction dedicated to the HRRT, using an experimentally measured shift-variant resolution kernel. Previously, the system response was measured and characterised in detail across the entire FOV of the HRRT, using a printed point source array. The newly developed resolution modelling reconstruction was applied on measured phantom, as well as clinical data and was compared against the HRRT users' community resolution modelling reconstruction, which is currently in use. Results demonstrated improvements both in contrast and resolution recovery, particularly for regions close to the edges of the FOV, with almost uniform resolution recovery across the entire transverse FOV. In addition, because the newly measured resolution kernel is slightly broader with wider tails, compared to the deliberately conservative kernel employed in the HRRT users' community software, the reconstructed images appear to have not only improved contrast recovery (up to 20% for small regions), but also better noise characteristics.
Research on texture feature of RS image based on cloud model
NASA Astrophysics Data System (ADS)
Wang, Zuocheng; Xue, Lixia
2008-10-01
This paper presents a new method applied to texture feature representation in RS image based on cloud model. Aiming at the fuzziness and randomness of RS image, we introduce the cloud theory into RS image processing in a creative way. The digital characteristics of clouds well integrate the fuzziness and randomness of linguistic terms in a unified way and map the quantitative and qualitative concepts. We adopt texture multi-dimensions cloud to accomplish vagueness and randomness handling of texture feature in RS image. The method has two steps: 1) Correlativity analyzing of texture statistical parameters in Grey Level Co-occurrence Matrix (GLCM) and parameters fuzzification. GLCM can be used to representing the texture feature in many aspects perfectly. According to the expressive force of texture statistical parameters and by Correlativity analyzing of texture statistical parameters, we can abstract a few texture statistical parameters that can best represent the texture feature. By the fuzziness algorithm, the texture statistical parameters can be mapped to fuzzy cloud space. 2) Texture multi-dimensions cloud model constructing. Based on the abstracted texture statistical parameters and fuzziness cloud space, texture multi-dimensions cloud model can be constructed in micro-windows of image. According to the membership of texture statistical parameters, we can achieve the samples of cloud-drop. By backward cloud generator, the digital characteristics of texture multi-dimensions cloud model can be achieved and the Mathematical Expected Hyper Surface(MEHS) of multi-dimensions cloud of micro-windows can be constructed. At last, the weighted sum of the 3 digital characteristics of micro-window cloud model was proposed and used in texture representing in RS image. The method we develop is demonstrated by applying it to texture representing in many RS images, various performance studies testify that the method is both efficient and effective. It enriches the cloud
A multiscale model of the bone marrow and hematopoiesis
Silva, Ariosto S; Anderson, Alexander R.A.
2013-01-01
The bone marrow is necessary for renewal of all hematopoietic cells and critical for maintenance of a wide range of physiologic functions. Multiple human diseases result from bone marrow dysfunction. It is also the site in which “liquid” tumors, including leukemia and multiple myeloma, develop as well as a frequent site of metastases. Understanding the complex cellular and microenvironmental interactions that govern normal bone marrow function as well as diseases and cancers of the bone marrow would be a valuable medical advance. Our goal is the development of a spatially-explicit in silico model of the bone marrow to understand both its normal function and the evolutionary dynamics that govern the emergence of bone marrow malignancy. Here we introduce a multiscale computational model of the bone marrow that incorporates three distinct spatial scales, cell, hematopoietic subunit, whole marrow. Implemented as a fixed lattice 3D cellular automaton, it reproduces the spatial characteristics of the normal bone marrow and is validated against data from the daily production of mature blood cells and response of hematopoiesis after irradiation. The major mechanisms modeled in this work are: (1) replication, specialization and migration of hematopoietic cells, (2) optimized spatial configuration of sinuses and hematopoietic compartments and, (3) intravasation of mature hematopoietic cells into sinuses. Our results, using parameter estimates from literature, recapitulates normal bone marrow function and suggest an explanation for the fractal-like structure of trabeculae and sinuses in the marrow, which would be an optimization of the hematopoietic function in order to maximize the number of mature blood cells produced daily within the volumetric restrictions of the marrow. PMID:21631151
Multiscale Model for the Assembly Kinetics of Protein Complexes.
Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao
2016-02-04
The assembly of proteins into high-order complexes is a general mechanism for these biomolecules to implement their versatile functions in cells. Natural evolution has developed various assembling pathways for specific protein complexes to maintain their stability and proper activities. Previous studies have provided numerous examples of the misassembly of protein complexes leading to severe biological consequences. Although the research focusing on protein complexes has started to move beyond the static representation of quaternary structures to the dynamic aspect of their assembly, the current understanding of the assembly mechanism of protein complexes is still largely limited. To tackle this problem, we developed a new multiscale modeling framework. This framework combines a lower-resolution rigid-body-based simulation with a higher-resolution Cα-based simulation method so that protein complexes can be assembled with both structural details and computational efficiency. We applied this model to a homotrimer and a heterotetramer as simple test systems. Consistent with experimental observations, our simulations indicated very different kinetics between protein oligomerization and dimerization. The formation of protein oligomers is a multistep process that is much slower than dimerization but thermodynamically more stable. Moreover, we showed that even the same protein quaternary structure can have very diverse assembly pathways under different binding constants between subunits, which is important for regulating the functions of protein complexes. Finally, we revealed that the binding between subunits in a complex can be synergistically strengthened during assembly without considering allosteric regulation or conformational changes. Therefore, our model provides a useful tool to understand the general principles of protein complex assembly.
Jagiella, Nick; Rickert, Dennis; Theis, Fabian J; Hasenauer, Jan
2017-02-22
Mechanistic understanding of multi-scale biological processes, such as cell proliferation in a changing biological tissue, is readily facilitated by computational models. While tools exist to construct and simulate multi-scale models, the statistical inference of the unknown model parameters remains an open problem. Here, we present and benchmark a parallel approximate Bayesian computation sequential Monte Carlo (pABC SMC) algorithm, tailored for high-performance computing clusters. pABC SMC is fully automated and returns reliable parameter estimates and confidence intervals. By running the pABC SMC algorithm for ∼10(6) hr, we parameterize multi-scale models that accurately describe quantitative growth curves and histological data obtained in vivo from individual tumor spheroid growth in media droplets. The models capture the hybrid deterministic-stochastic behaviors of 10(5)-10(6) of cells growing in a 3D dynamically changing nutrient environment. The pABC SMC algorithm reliably converges to a consistent set of parameters. Our study demonstrates a proof of principle for robust, data-driven modeling of multi-scale biological systems and the feasibility of multi-scale model parameterization through statistical inference.
A neotropical Miocene pollen database employing image-based search and semantic modeling1
Han, Jing Ginger; Cao, Hongfei; Barb, Adrian; Punyasena, Surangi W.; Jaramillo, Carlos; Shyu, Chi-Ren
2014-01-01
• Premise of the study: Digital microscopic pollen images are being generated with increasing speed and volume, producing opportunities to develop new computational methods that increase the consistency and efficiency of pollen analysis and provide the palynological community a computational framework for information sharing and knowledge transfer. • Methods: Mathematical methods were used to assign trait semantics (abstract morphological representations) of the images of neotropical Miocene pollen and spores. Advanced database-indexing structures were built to compare and retrieve similar images based on their visual content. A Web-based system was developed to provide novel tools for automatic trait semantic annotation and image retrieval by trait semantics and visual content. • Results: Mathematical models that map visual features to trait semantics can be used to annotate images with morphology semantics and to search image databases with improved reliability and productivity. Images can also be searched by visual content, providing users with customized emphases on traits such as color, shape, and texture. • Discussion: Content- and semantic-based image searches provide a powerful computational platform for pollen and spore identification. The infrastructure outlined provides a framework for building a community-wide palynological resource, streamlining the process of manual identification, analysis, and species discovery. PMID:25202648
Multiscale modeling and surgical planning for single ventricle heart patients
NASA Astrophysics Data System (ADS)
Marsden, Alison
2011-11-01
Single ventricle heart patients are among the most challenging for pediatric cardiologists to treat, and typically undergo a palliative course of three open-heart surgeries starting immediately after birth. We will present recent tools for modeling blood flow in single ventricle heart patients using a multiscale approach that couples a 3D Navier-Stokes domain to a 0D closed loop lumped parameter network comprised of circuit elements. This coupling allows us to capture the effect of changes in local geometry, such as shunt sizes, on global circulatory dynamics, such as cardiac output. A semi-implicit numerical method is formulated to solve the coupled system in which flow and pressure information is passed between the two domains at the inlets and outlets of the model. A finite element method with outflow stabilization is applied in the 3D Navier-Stokes domain, and the LPN system of ordinary differential equations is solved numerically using a Runge-Kutta method. These tools are coupled via automated scripts to a derivative-free optimization method. Optimization is used to systematically explore surgical designs using clinically relevant cost functions for two stages of single ventricle repair. First, we will present results from optimization of the first stage Blalock Taussig Shunt. Second, we will present results from optimization of a new Y-graft design for the third stage of single ventricle repair called the Fontan surgery. The Y-graft is shown, in simulations, to successfully improve hepatic flow distribution, a known clinical problem. Preliminary clinical experience with the Y-graft will be discussed.
NASA Astrophysics Data System (ADS)
Fwu, Peter Tramyeon
The medical image is very complex by its nature. Modeling built upon the medical image is challenging due to the lack of analytical solution. Finite element method (FEM) is a numerical technique which can be used to solve the partial differential equations. It utilized the transformation from a continuous domain into solvable discrete sub-domains. In three-dimensional space, FEM has the capability dealing with complicated structure and heterogeneous interior. That makes FEM an ideal tool to approach the medical-image based modeling problems. In this study, I will address the three modeling in (1) photon transport inside the human breast by implanting the radiative transfer equation to simulate the diffuse optical spectroscopy imaging (DOSI) in order to measurement the percent density (PD), which has been proven as a cancer risk factor in mammography. Our goal is to use MRI as the ground truth to optimize the DOSI scanning protocol to get a consistent measurement of PD. Our result shows DOSI measurement is position and depth dependent and proper scanning scheme and body configuration are needed; (2) heat flow in the prostate by implementing the Penne's bioheat equation to evaluate the cooling performance of regional hypothermia during the robot assisted radical prostatectomy for the individual patient in order to achieve the optimal cooling setting. Four factors are taken into account during the simulation: blood abundance, artery perfusion, cooling balloon temperature, and the anatomical distance. The result shows that blood abundance, prostate size, and anatomical distance are significant factors to the equilibrium temperature of neurovascular bundle; (3) shape analysis in hippocampus by using the radial distance mapping, and two registration methods to find the correlation between sub-regional change to the age and cognition performance, which might not reveal in the volumetric analysis. The result gives a fundamental knowledge of normal distribution in young
Morpheus: a user-friendly modeling environment for multiscale and multicellular systems biology.
Starruß, Jörn; de Back, Walter; Brusch, Lutz; Deutsch, Andreas
2014-05-01
Morpheus is a modeling environment for the simulation and integration of cell-based models with ordinary differential equations and reaction-diffusion systems. It allows rapid development of multiscale models in biological terms and mathematical expressions rather than programming code. Its graphical user interface supports the entire workflow from model construction and simulation to visualization, archiving and batch processing.
NASA Astrophysics Data System (ADS)
Bhattacharjee, Satyaki; Matouš, Karel
2016-05-01
A new manifold-based reduced order model for nonlinear problems in multiscale modeling of heterogeneous hyperelastic materials is presented. The model relies on a global geometric framework for nonlinear dimensionality reduction (Isomap), and the macroscopic loading parameters are linked to the reduced space using a Neural Network. The proposed model provides both homogenization and localization of the multiscale solution in the context of computational homogenization. To construct the manifold, we perform a number of large three-dimensional simulations of a statistically representative unit cell using a parallel finite strain finite element solver. The manifold-based reduced order model is verified using common principles from the machine-learning community. Both homogenization and localization of the multiscale solution are demonstrated on a large three-dimensional example and the local microscopic fields as well as the homogenized macroscopic potential are obtained with acceptable engineering accuracy.
Multiscale Multiphysics and Multidomain Models I: Basic Theory.
Wei, Guo-Wei
2013-12-01
This work extends our earlier two-domain formulation of a differential geometry based multiscale paradigm into a multidomain theory, which endows us the ability to simultaneously accommodate multiphysical descriptions of aqueous chemical, physical and biological systems, such as fuel cells, solar cells, nanofluidics, ion channels, viruses, RNA polymerases, molecular motors and large macromolecular complexes. The essential idea is to make use of the differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain of solvent from the microscopic domain of solute, and dynamically couple continuum and discrete descriptions. Our main strategy is to construct energy functionals to put on an equal footing of multiphysics, including polar (i.e., electrostatic) solvation, nonpolar solvation, chemical potential, quantum mechanics, fluid mechanics, molecular mechanics, coarse grained dynamics and elastic dynamics. The variational principle is applied to the energy functionals to derive desirable governing equations, such as multidomain Laplace-Beltrami (LB) equations for macromolecular morphologies, multidomain Poisson-Boltzmann (PB) equation or Poisson equation for electrostatic potential, generalized Nernst-Planck (NP) equations for the dynamics of charged solvent species, generalized Navier-Stokes (NS) equation for fluid dynamics, generalized Newton's equations for molecular dynamics (MD) or coarse-grained dynamics and equation of motion for elastic dynamics. Unlike the classical PB equation, our PB equation is an integral-differential equation due to solvent-solute interactions. To illustrate the proposed formalism, we have explicitly constructed three models, a multidomain solvation model, a multidomain charge transport model and a multidomain chemo-electro-fluid-MD-elastic model. Each solute domain is equipped with distinct surface tension, pressure, dielectric function, and charge density distribution. In addition to long
Multiscale Multiphysics and Multidomain Models I: Basic Theory
Wei, Guo-Wei
2013-01-01
This work extends our earlier two-domain formulation of a differential geometry based multiscale paradigm into a multidomain theory, which endows us the ability to simultaneously accommodate multiphysical descriptions of aqueous chemical, physical and biological systems, such as fuel cells, solar cells, nanofluidics, ion channels, viruses, RNA polymerases, molecular motors and large macromolecular complexes. The essential idea is to make use of the differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain of solvent from the microscopic domain of solute, and dynamically couple continuum and discrete descriptions. Our main strategy is to construct energy functionals to put on an equal footing of multiphysics, including polar (i.e., electrostatic) solvation, nonpolar solvation, chemical potential, quantum mechanics, fluid mechanics, molecular mechanics, coarse grained dynamics and elastic dynamics. The variational principle is applied to the energy functionals to derive desirable governing equations, such as multidomain Laplace-Beltrami (LB) equations for macromolecular morphologies, multidomain Poisson-Boltzmann (PB) equation or Poisson equation for electrostatic potential, generalized Nernst-Planck (NP) equations for the dynamics of charged solvent species, generalized Navier-Stokes (NS) equation for fluid dynamics, generalized Newton's equations for molecular dynamics (MD) or coarse-grained dynamics and equation of motion for elastic dynamics. Unlike the classical PB equation, our PB equation is an integral-differential equation due to solvent-solute interactions. To illustrate the proposed formalism, we have explicitly constructed three models, a multidomain solvation model, a multidomain charge transport model and a multidomain chemo-electro-fluid-MD-elastic model. Each solute domain is equipped with distinct surface tension, pressure, dielectric function, and charge density distribution. In addition to long
Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J
2014-01-01
The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. WIREs Syst Biol Med 2014, 6:225–245. doi:10.1002/wsbm.1270 How to cite this article: WIREs Syst Biol Med 2014, 6:289–309. doi:10.1002/wsbm.1270 PMID:24810243
Multi-scale modelling of rubber-like materials and soft tissues: an appraisal
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
Radiation induced genome instability: multiscale modelling and data analysis
NASA Astrophysics Data System (ADS)
Andreev, Sergey; Eidelman, Yuri
2012-07-01
Genome instability (GI) is thought to be an important step in cancer induction and progression. Radiation induced GI is usually defined as genome alterations in the progeny of irradiated cells. The aim of this report is to demonstrate an opportunity for integrative analysis of radiation induced GI on the basis of multiscale modelling. Integrative, systems level modelling is necessary to assess different pathways resulting in GI in which a variety of genetic and epigenetic processes are involved. The multilevel modelling includes the Monte Carlo based simulation of several key processes involved in GI: DNA double strand breaks (DSBs) generation in cells initially irradiated as well as in descendants of irradiated cells, damage transmission through mitosis. Taking the cell-cycle-dependent generation of DNA/chromosome breakage into account ensures an advantage in estimating the contribution of different DNA damage response pathways to GI, as to nonhomologous vs homologous recombination repair mechanisms, the role of DSBs at telomeres or interstitial chromosomal sites, etc. The preliminary estimates show that both telomeric and non-telomeric DSB interactions are involved in delayed effects of radiation although differentially for different cell types. The computational experiments provide the data on the wide spectrum of GI endpoints (dicentrics, micronuclei, nonclonal translocations, chromatid exchanges, chromosome fragments) similar to those obtained experimentally for various cell lines under various experimental conditions. The modelling based analysis of experimental data demonstrates that radiation induced GI may be viewed as processes of delayed DSB induction/interaction/transmission being a key for quantification of GI. On the other hand, this conclusion is not sufficient to understand GI as a whole because factors of DNA non-damaging origin can also induce GI. Additionally, new data on induced pluripotent stem cells reveal that GI is acquired in normal mature
Jiang, Lijian Li, Xinping
2015-08-01
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 each 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
Modular-based multiscale modeling on viscoelasticity of polymer nanocomposites
NASA Astrophysics Data System (ADS)
Li, Ying; Liu, Zeliang; Jia, Zheng; Liu, Wing Kam; Aldousari, Saad M.; Hedia, Hassan S.; Asiri, Saeed A.
2017-02-01
Polymer nanocomposites have been envisioned as advanced materials for improving the mechanical performance of neat polymers used in aerospace, petrochemical, environment and energy industries. With the filler size approaching the nanoscale, composite materials tend to demonstrate remarkable thermomechanical properties, even with addition of a small amount of fillers. These observations confront the classical composite theories and are usually attributed to the high surface-area-to-volume-ratio of the fillers, which can introduce strong nanoscale interfacial effect and relevant long-range perturbation on polymer chain dynamics. Despite decades of research aimed at understanding interfacial effect and improving the mechanical performance of composite materials, it is not currently possible to accurately predict the mechanical properties of polymer nanocomposites directly from their molecular constituents. To overcome this challenge, different theoretical, experimental and computational schemes will be used to uncover the key physical mechanisms at the relevant spatial and temporal scales for predicting and tuning constitutive behaviors in silico, thereby establishing a bottom-up virtual design principle to achieve unprecedented mechanical performance of nanocomposites. A modular-based multiscale modeling approach for viscoelasticity of polymer nanocomposites has been proposed and discussed in this study, including four modules: (A) neat polymer toolbox; (B) interphase toolbox; (C) microstructural toolbox and (D) homogenization toolbox. Integrating these modules together, macroscopic viscoelasticity of polymer nanocomposites could be directly predicted from their molecular constituents. This will maximize the computational ability to design novel polymer composites with advanced performance. More importantly, elucidating the viscoelasticity of polymer nanocomposites through fundamental studies is a critical step to generate an integrated computational material
Modular-based multiscale modeling on viscoelasticity of polymer nanocomposites
NASA Astrophysics Data System (ADS)
Li, Ying; Liu, Zeliang; Jia, Zheng; Liu, Wing Kam; Aldousari, Saad M.; Hedia, Hassan S.; Asiri, Saeed A.
2016-10-01
Polymer nanocomposites have been envisioned as advanced materials for improving the mechanical performance of neat polymers used in aerospace, petrochemical, environment and energy industries. With the filler size approaching the nanoscale, composite materials tend to demonstrate remarkable thermomechanical properties, even with addition of a small amount of fillers. These observations confront the classical composite theories and are usually attributed to the high surface-area-to-volume-ratio of the fillers, which can introduce strong nanoscale interfacial effect and relevant long-range perturbation on polymer chain dynamics. Despite decades of research aimed at understanding interfacial effect and improving the mechanical performance of composite materials, it is not currently possible to accurately predict the mechanical properties of polymer nanocomposites directly from their molecular constituents. To overcome this challenge, different theoretical, experimental and computational schemes will be used to uncover the key physical mechanisms at the relevant spatial and temporal scales for predicting and tuning constitutive behaviors in silico, thereby establishing a bottom-up virtual design principle to achieve unprecedented mechanical performance of nanocomposites. A modular-based multiscale modeling approach for viscoelasticity of polymer nanocomposites has been proposed and discussed in this study, including four modules: (A) neat polymer toolbox; (B) interphase toolbox; (C) microstructural toolbox and (D) homogenization toolbox. Integrating these modules together, macroscopic viscoelasticity of polymer nanocomposites could be directly predicted from their molecular constituents. This will maximize the computational ability to design novel polymer composites with advanced performance. More importantly, elucidating the viscoelasticity of polymer nanocomposites through fundamental studies is a critical step to generate an integrated computational material
Multiscale Modeling of Chemistry in Water: Are We There Yet?
Bulo, Rosa E; Michel, Carine; Fleurat-Lessard, Paul; Sautet, Philippe
2013-12-10
This paper critically evaluates the state of the art in combined quantum mechanical/molecular mechanical (QM/MM) approaches to the computational description of chemistry in water and supplies guidelines for the setup of customized multiscale simulations of aqueous processes. We differentiate between structural and dynamic performance, since some tasks, e.g., the reproduction of NMR or UV-vis spectra, require only structural accuracy, while others, i.e., reaction mechanisms, require accurate dynamic data as well. As a model system for aqueous solutions in general, the approaches were tested on a QM water cluster in an environment of MM water molecules. The key difficulty is the description of the possible diffusion of QM molecules into the MM region and vice versa. The flexible inner region ensemble separator (FIRES) approach constrains QM solvent molecules within an active (QM) region. Sorted adaptive partitioning (SAP), difference-based adaptive solvation (DAS), and buffered-force (BF) are all adaptive approaches that use a buffer zone in which solvent molecules gradually adapt from QM to MM (or vice versa). The costs of SAP and DAS are relatively high, while BF is fast but sacrifices conservation of both energy and momentum. Simulations in the limit of an infinitely small buffer zone, where DAS and SAP become equivalent, are discussed as well and referred to as ABRUPT. The best structural accuracy is obtained with DAS, BF, and ABRUPT, all three of similar quality. FIRES performs very well for dynamic properties localized deep within the QM region. By means of elimination DAS emerges as the best overall compromise between structural and dynamic performance. Eliminating the buffer zone (ABRUPT) improves efficiency and still leads to surprisingly good results. While none of the many new flavors are perfect, all together this new field already allows accurate description of a wide range of structural and dynamic properties of aqueous solutions.
Multiscale modeling of crack initiation and propagation at the nanoscale
NASA Astrophysics Data System (ADS)
Shiari, Behrouz; Miller, Ronald E.
2016-03-01
Fracture occurs on multiple interacting length scales; atoms separate on the atomic scale while plasticity develops on the microscale. A dynamic multiscale approach (CADD: coupled atomistics and discrete dislocations) is employed to investigate an edge-cracked specimen of single-crystal nickel, Ni, (brittle failure) and aluminum, Al, (ductile failure) subjected to mode-I loading. The dynamic model couples continuum finite elements to a fully atomistic region, with key advantages such as the ability to accommodate discrete dislocations in the continuum region and an algorithm for automatically detecting dislocations as they move from the atomistic region to the continuum region and then correctly "converting" the atomistic dislocations into discrete dislocations, or vice-versa. An ad hoc computational technique is also applied to dissipate localized waves formed during crack advance in the atomistic zone, whereby an embedded damping zone at the atomistic/continuum interface effectively eliminates the spurious reflection of high-frequency phonons, while allowing low-frequency phonons to pass into the continuum region. The simulations accurately capture the essential physics of the crack propagation in a Ni specimen at different temperatures, including the formation of nano-voids and the sudden acceleration of the crack tip to a velocity close to the material Rayleigh wave speed. The nanoscale brittle fracture happens through the crack growth in the form of nano-void nucleation, growth and coalescence ahead of the crack tip, and as such resembles fracture at the microscale. When the crack tip behaves in a ductile manner, the crack does not advance rapidly after the pre-opening process but is blunted by dislocation generation from its tip. The effect of temperature on crack speed is found to be perceptible in both ductile and brittle specimens.
Bottom-up model of adsorption and transport in multiscale porous media.
Boţan, Alexandru; Ulm, Franz-Josef; Pellenq, Roland J-M; Coasne, Benoit
2015-03-01
We develop a model of transport in multiscale porous media which accounts for adsorption in the different porosity scales. This model employs statistical mechanics to upscale molecular simulation and describe adsorption and transport at larger time and length scales. Using atom-scale simulations, which capture the changes in adsorption and transport with temperature, pressure, pore size, etc., this approach does not assume any adsorption or flow type. Moreover, by relating the local chemical potential μ(r) and density ρ(r), the present model accounts for adsorption effects and possible changes in the confined fluid state upon transport. This model constitutes a bottom-up framework of adsorption and transport in multiscale materials as it (1) describes the adsorption-transport interplay, (2) accounts for the hydrodynamics breakdown at the nm scale, and (3) is multiscale.
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.
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.
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.
WE-E-17A-01: Characterization of An Imaging-Based Model of Tumor Angiogenesis
Adhikarla, V; Jeraj, R
2014-06-15
Purpose: Understanding the transient dynamics of tumor oxygenation is important when evaluating tumor-vasculature response to anti-angiogenic therapies. An imaging-based tumor-vasculature model was used to elucidate factors that affect these dynamics. Methods: Tumor growth depends on its doubling time (Td). Hypoxia increases pro-angiogenic factor (VEGF) concentration which is modeled to reduce vessel perfusion, attributing to its effect of increasing vascular permeability. Perfused vessel recruitment depends on the existing perfused vasculature, VEGF concentration and maximum VEGF concentration (VEGFmax) for vessel dysfunction. A convolution-based algorithm couples the tumor to the normal tissue vessel density (VD-nt). The parameters are benchmarked to published pre-clinical data and a sensitivity study evaluating the changes in the peak and time to peak tumor oxygenation characterizes them. The model is used to simulate changes in hypoxia and proliferation PET imaging data obtained using [Cu- 61]Cu-ATSM and [F-18]FLT respectively. Results: Td and VD-nt were found to be the most influential on peak tumor pO2 while VEGFmax was marginally influential. A +20 % change in Td, VD-nt and VEGFmax resulted in +50%, +25% and +5% increase in peak pO2. In contrast, Td was the most influential on the time to peak oxygenation with VD-nt and VEGFmax playing marginal roles. A +20% change in Td, VD-nt and VEGFmax increased the time to peak pO2 by +50%, +5% and +0%. A −20% change in the above parameters resulted in comparable decreases in the peak and time to peak pO2. Model application to the PET data was able to demonstrate the voxel-specific changes in hypoxia of the imaged tumor. Conclusion: Tumor-specific doubling time and vessel density are important parameters to be considered when evaluating hypoxia transients. While the current model simulates the oxygen dynamics of an untreated tumor, incorporation of therapeutic effects can make the model a potent tool for analyzing
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.
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.
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.
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.
Evaluation of the Community Multiscale Air Quality model version 5.1
The Community Multiscale Air Quality model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Atmospheric Modeling and Analysis Division (AMAD) of the U.S. Environment...
Modeling and simulation of high dimensional stochastic multiscale PDE systems at the exascale
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.
Quasi-3D Algorithm in Multi-scale Modeling Framework
NASA Astrophysics Data System (ADS)
Jung, J.; Arakawa, A.
2008-12-01
As discussed in the companion paper by Arakawa and Jung, the Quasi-3D (Q3D) Multi-scale Modeling Framework (MMF) is a 4D estimation/prediction framework that combines a GCM with a 3D anelastic vector vorticity equation model (VVM) applied to a Q3D network of horizontal grid points. This paper presents an outline of the recently revised Q3D algorithm and a highlight of the results obtained by application of the algorithm to an idealized model setting. The Q3D network of grid points consists of two sets of grid-point arrays perpendicular to each other. For a scalar variable, for example, each set consists of three parallel rows of grid points. Principal and supplementary predictions are made on the central and the two adjacent rows, respectively. The supplementary prediction is to allow the principal prediction be three-dimensional at least to the second-order accuracy. To accommodate a higher-order accuracy and to make the supplementary predictions formally three-dimensional, a few rows of ghost points are added at each side of the array. Values at these ghost points are diagnostically determined by a combination of statistical estimation and extrapolation. The basic structure of the estimation algorithm is determined in view of the global stability of Q3D advection. The algorithm is calibrated using the statistics of past data at and near the intersections of the two sets of grid- point arrays. Since the CRM in the Q3D MMF extends beyond individual GCM boxes, the CRM can be a GCM by itself. However, it is better to couple the CRM with the GCM because (1) the CRM is a Q3D CRM based on a highly anisotropic network of grid points and (2) coupling with a GCM makes it more straightforward to inherit our experience with the conventional GCMs. In the coupled system we have selected, prediction of thermdynamic variables is almost entirely done by the Q3D CRM with no direct forcing by the GCM. The coupling of the dynamics between the two components is through mutual
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 Personalized Cardiology: Multi-Scale Modeling of the Failing Heart
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
Multiscale multiphysics and multidomain models--flexibility and rigidity.
Xia, Kelin; Opron, Kristopher; Wei, Guo-Wei
2013-11-21
The emerging complexity of large macromolecules has led to challenges in their full scale theoretical description and computer simulation. Multiscale multiphysics and multidomain models have been introduced to reduce the number of degrees of freedom while maintaining modeling accuracy and achieving computational efficiency. A total energy functional is constructed to put energies for polar and nonpolar solvation, chemical potential, fluid flow, molecular mechanics, and elastic dynamics on an equal footing. The variational principle is utilized to derive coupled governing equations for the above mentioned multiphysical descriptions. Among these governing equations is the Poisson-Boltzmann equation which describes continuum electrostatics with atomic charges. The present work introduces the theory of continuum elasticity with atomic rigidity (CEWAR). The essence of CEWAR is to formulate the shear modulus as a continuous function of atomic rigidity. As a result, the dynamics complexity of a macromolecular system is separated from its static complexity so that the more time-consuming dynamics is handled with continuum elasticity theory, while the less time-consuming static analysis is pursued with atomic approaches. We propose a simple method, flexibility-rigidity index (FRI), to analyze macromolecular flexibility and rigidity in atomic detail. The construction of FRI relies on the fundamental assumption that protein functions, such as flexibility, rigidity, and energy, are entirely determined by the structure of the protein and its environment, although the structure is in turn determined by all the interactions. As such, the FRI measures the topological connectivity of protein atoms or residues and characterizes the geometric compactness of the protein structure. As a consequence, the FRI does not resort to the interaction Hamiltonian and bypasses matrix diagonalization, which underpins most other flexibility analysis methods. FRI's computational complexity is of O
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.
Multiscale modeling of nanostructures for electronic and energy-related applications
NASA Astrophysics Data System (ADS)
Kaxiras, Efthimios
2013-03-01
The optimization of materials properties for opto-electronic and energy-related applications is a crucial component in the design of new devices. To this end, multiscale modeling of nanostructures is essential in understanding and predicting materials properties ranging from optical response to the mechanical failure. We present a number of examples where multiscale modeling has yielded useful information concerning the optimal choices for nanostructured device elements. These include the excitation and charge transfer processes in hybrid photovoltaic devices, the tuning of optical and electrical properties of layered materials like graphene and transition-metal-dichalcogenides, and the mechanical response and deformation of silicon-based high-energy-density electrodes.
Multiscale modeling in nanostructures: Physical and biological systems
NASA Astrophysics Data System (ADS)
Dearden, Albert Karcz
With the advent of more powerful computer systems, theoretical modeling of nanoscale systems has quickly become a vital part of scientific research in a multitude of disciplines. From the understanding of semiconductor devices to describing the mechanistic details of protein interactions, theoretical studies on systems of various scales have provided great insight into how nature behaves in each scenario. While at a macroscopic level the differences between biological and non-biological systems are apparent, the underlying principles that dictate their behavior are quite similar. Indeed, modeling these two distinct classes of systems have similar challenges. In both cases, the system sizes typically correspond to nanometer length scales and due to the lack of periodicity in the system, one needs to study a relatively larger number of atoms in simulations in order to represent their behavior. Nonetheless, systems that are much smaller than what exists in experiment may be used to describe specific properties of interest, such as how system stability scales with varying size or describing a reaction process of a large biological structure through the modeling of only the reaction site and not the entire protein. Thus, it is important to be able to correctly and efficiently model various systems at multiple scales in order to provide proper insight and understanding so models and tools developed in one area could be applied to another discipline. Indeed, lessons learned during the process are quite valuable for the general scheme of multiscale modeling in materials. To facilitate this, we have investigated two separate cases involving the efficient use of multiscale modeling through ab initio density functional theory calculations. For the first half of this work, we investigate the effect of size on the net magnetization of zero dimensional graphene based structures with differing edge states. Currently, we have shown that for zigzag edged triangular graphene
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
Evaluation of the Community Multi-scale Air Quality Model Version 5.2
The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...
Evaluation of the Community Multi-scale Air Quality (CMAQ) Model Version 5.2
The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...
COMMUNITY MULTISCALE AIR QUALITY ( CMAQ ) MODEL - QUALITY ASSURANCE AND VERSION CONTROL
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 Multi-scale Air Quality (CMAQ) Model Version 5.1
The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...
Overview and Evaluation of the Community Multiscale Air Quality Model Version 5.2
The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...
PECASE - Multi-Scale Experiments and Modeling in Wall Turbulence
2014-12-23
characterizing the three-dimensional spectrum of the streamwise velocity fluctuations using time-resolved particle image velocimetry at a range of...spectrum of the streamwise velocity fluctuations using time-resolved particle image velocimetry at a range of wall-normal locations, and extending a two...in canonical and non-canonical turbulent boundary layers using fast Particle Image Velocimetry in order to identify the influence of multi-scale
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.
Multiscale computational modeling of defects in uranium dioxide
NASA Astrophysics Data System (ADS)
Goyal, Anuj
Manufacturing, extreme operation conditions, and storage introduce large variety of defects into uranium dioxide (UO2) nuclear fuel, which have diverse effects on fuel properties. In this study, a multiscale computational approach to model defect behavior in UO2 is presented, by passing information in stages from electronic structure and atomistic calculations to a stochastic kinetic method. Understanding the interaction of fission products with dislocations is critical to interpret their interaction with fuel microstructure. Atomistic simulations are employed to predict the segregation of ruthenium and cesium, both fission products, to edge and screw dislocations. Dislocation loops of different shapes and sizes are simulated to investigate their atomic structure. To understand the segregation behavior, comparisons are made between atomistic simulations and continuum-elastic based results. Segregation behavior is found to be directly related to the elastic strain field around the dislocation core and is affected by the orientation of dislocation and electrostatic interactions at the atomic defect site. A detailed mechanism of, and the effect of homogeneous strains on, the migration of uranium vacancies in UO2 is presented. Migration pathways and barriers are identified using density functional theory and the effect of strain fields are accounted for using a dipole tensor approach. This information is then passed to the kinetic Monte Carlo simulations, to compute the diffusivities in the presence of external strain fields. We report complex migration pathways for uranium vacancy and show under homogeneous strain, only the dipole tensor of the saddle with respect to the minimum is required to correctly predict the change in energy barrier between the strained and the unstrained case. Homogeneous strains as small as 2% have considerable effect on diffusivity of both single and di-vacancies, with the effect of strain more pronounced for single vacancies than di
Advanced computational workflow for the multi-scale modeling of the bone metabolic processes.
Dao, Tien Tuan
2016-09-16
Multi-scale modeling of the musculoskeletal system plays an essential role in the deep understanding of complex mechanisms underlying the biological phenomena and processes such as bone metabolic processes. Current multi-scale models suffer from the isolation of sub-models at each anatomical scale. The objective of this present work was to develop a new fully integrated computational workflow for simulating bone metabolic processes at multi-scale levels. Organ-level model employs multi-body dynamics to estimate body boundary and loading conditions from body kinematics. Tissue-level model uses finite element method to estimate the tissue deformation and mechanical loading under body loading conditions. Finally, cell-level model includes bone remodeling mechanism through an agent-based simulation under tissue loading. A case study on the bone remodeling process located on the human jaw was performed and presented. The developed multi-scale model of the human jaw was validated using the literature-based data at each anatomical level. Simulation outcomes fall within the literature-based ranges of values for estimated muscle force, tissue loading and cell dynamics during bone remodeling process. This study opens perspectives for accurately simulating bone metabolic processes using a fully integrated computational workflow leading to a better understanding of the musculoskeletal system function from multiple length scales as well as to provide new informative data for clinical decision support and industrial applications.
Optimization of Focused Ultrasound and Image Based Modeling in Image Guided Interventions
NASA Astrophysics Data System (ADS)
Almekkawy, Mohamed Khaled Ibrahim
Image-guided high intensity focused ultrasound (HIFU) is becoming increasingly accepted as a form of noninvasive ablative therapy for the treatment of prostate cancer, uterine fibroids and other tissue abnormalities. In principle, HIFU beams can be focused within small volumes which results in forming precise lesions within the target volume (e.g. tumor, atherosclerotic plaque) while sparing the intervening tissue. With this precision, HIFU offers the promise of noninvasive tumor therapy. The goal of this thesis is to develop an image-guidance mode with an interactive image-based computational modeling of tissue response to HIFU. This model could be used in treatment planning and post-treatment retrospective evaluation of treatment outcome(s). Within the context of treatment planning, the challenge of using HIFU to target tumors in organs partially obscured by the rib cage are addressed. Ribs distort HIFU beams in a manner that reduces the focusing gain at the target (tumor) and could cause a treatment-limiting collateral damage. We present a refocusing algorithms to efficiently steer higher power towards the target while limiting power deposition on the ribs, improving the safety and efficacy of tumor ablation. Our approach is based on an approximation of a non-convex to a convex optimization known as the semidefinite relaxation (SDR) technique. An important advantage of the SDR method over previously proposed optimization methods is the explicit control of the sidelobes in the focal plane. A finite-difference time domain (FDTD) heterogeneous propagation model of a 1-MHz concave phased array was used to model the acoustic propagation and temperature simulations in different tissues including ribs. The numerical methods developed for the refocusing problem are also used for retrospective analysis of targeting of atherosclerotic plaques using HIFU. Cases were simulated where seven adjacent HIFU shots (5000 W/cm2, 2 sec exposure time) were focused at the plaque
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.
A second gradient theoretical framework for hierarchical multiscale modeling of materials
Luscher, Darby J; Bronkhorst, Curt A; Mc Dowell, David L
2009-01-01
A theoretical framework for the hierarchical multiscale modeling of inelastic response of heterogeneous materials has been presented. Within this multiscale framework, the second gradient is used as a non local kinematic link between the response of a material point at the coarse scale and the response of a neighborhood of material points at the fine scale. Kinematic consistency between these scales results in specific requirements for constraints on the fluctuation field. The wryness tensor serves as a second-order measure of strain. The nature of the second-order strain induces anti-symmetry in the first order stress at the coarse scale. The multiscale ISV constitutive theory is couched in the coarse scale intermediate configuration, from which an important new concept in scale transitions emerges, namely scale invariance of dissipation. Finally, a strategy for developing meaningful kinematic ISVs and the proper free energy functions and evolution kinetics is presented.
Luscher, Darby J.
2010-04-01
All materials are heterogeneous at various scales of observation. The influence of material heterogeneity on nonuniform response and microstructure evolution can have profound impact on continuum thermomechanical response at macroscopic “engineering” scales. In many cases, it is necessary to treat this behavior as a multiscale process thus integrating the physical understanding of material behavior at various physical (length and time) scales in order to more accurately predict the thermomechanical response of materials as their microstructure evolves. The intent of the dissertation is to provide a formal framework for multiscale hierarchical homogenization to be used in developing constitutive models.
Castro, Marcelo A; Ahumada Olivares, María C; Putman, Christopher M; Cebral, Juan R
2014-10-01
The aim of this work was to determine whether or not Newtonian rheology assumption in image-based patient-specific computational fluid dynamics (CFD) cerebrovascular models harboring cerebral aneurysms may affect the hemodynamics characteristics, which have been previously associated with aneurysm progression and rupture. Ten patients with cerebral aneurysms with lobulations were considered. CFD models were reconstructed from 3DRA and 4DCTA images by means of region growing, deformable models, and an advancing front technique. Patient-specific FEM blood flow simulations were performed under Newtonian and Casson rheological models. Wall shear stress (WSS) maps were created and distributions were compared at the end diastole. Regions of lower WSS (lobulation) and higher WSS (neck) were identified. WSS changes in time were analyzed. Maximum, minimum and time-averaged values were calculated and statistically compared. WSS characterization remained unchanged. At high WSS regions, Casson rheology systematically produced higher WSS minimum, maximum and time-averaged values. However, those differences were not statistically significant. At low WSS regions, when averaging over all cases, the Casson model produced higher stresses, although in some cases the Newtonian model did. However, those differences were not significant either. There is no evidence that Newtonian model overestimates WSS. Differences are not statistically significant.
A nonlocal multiscale discrete-continuum digital rock physics model at pendular regime
NASA Astrophysics Data System (ADS)
Sun, W.; Liu, Y.; Yuan, Z.; Fish, J.
2014-12-01
We propose a nonlocal multiscale framework that couples grain-scale micro-structural simulations of porous media with a macroscopic continuum-based finite element model at pendular regime. The upshot of this nonlocal coupling model is that it retains the simplicity and efficiency of the continuum-based finite element model, while possessing the original length scale of the microstructure. In particular, the collective mechanical responses of grains at material points are homogenized via a staggered nonlocal operator applied on local regions such that the multiscale simulations exhibit no pathological mesh dependence. Since granular materials may appear to be incompressible at critical state, we employ a one-point quadrature integration rule to relax the solution, while using hourglass control to eliminate the zero-energy modes. Numerical examples are used to analyze the onset and propagation of shear bands in granular materials. Finally, the robustness and accuracy of the proposed multiscale model are verified in comparisons with single-scale benchmark microstructural simulations. The nonlocal multiscale coupling scheme is able to capture the plastic dilatancy and pressure-sensitive frictional responses commonly observed inside dilatant shear bands, and replicate the anisotropy induced by the liquid-bridge and contact fabrics, without employing any phenomenological plasticity model or water-retention curve at macroscopic level.
Multiscale Modeling of Hall Thrusters. Chapter 7: Plume Modeling
2012-03-06
NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON Justin W. Koo, Ph.D. a. REPORT Unclassified b. ABSTRACT Unclassified c. THIS PAGE...public release; distribution unlimited. 20 [28] J. Fife and M. Martinez -Sanchez, “Two-dimensional hybrid particle-in-cell (pic) modeling of hall thrusters...in 24th International Electric Propulsion Conference, Moscow, Russia, pp. 1213–1224, 1995. [29] F. Parra, E. Ahedo, J. Fife, and M. Martinez -Sanchez
NASA Astrophysics Data System (ADS)
Iacobellis, Vincent
Composite and nanocomposite materials exhibit behaviour which is inherently multiscale, extending from the atomistic to continuum levels. In composites, damage growth tends to occur at the nano and microstructural scale by means of crack growth and fibre-matrix debonding. Concurrent multiscale modeling provides a means of efficiently solving such localized phenomena, however its use in this application has been limited due to a number of existing issues in the multiscale field. These include the seamless transfer of information between continuum and atomistic domains, the small timesteps required for dynamic simulation, and limited research into concurrent multiscale modeling of amorphous polymeric materials. The objective of this thesis is thus twofold: to formulate a generalized approach to solving a coupled atomistic-to-continuum system that addresses these issues and to extend the application space of concurrent multiscale modeling to damage modeling in composite microstructures. To achieve these objectives, a finite element based multiscale technique termed the Bridging Cell Method (BCM), has been formulated with a focus on crystalline material systems. Case studies are then presented that show the effectiveness of the developed technique with respect to full atomistic simulations. The BCM is also demonstrated for applications of stress around a nanovoid, nanoindentation, and crack growth due to monotonic and cyclic loading. Next, the BCM is extended to modeling amorphous polymeric material systems where an adaptive solver and a two-step iterative solution algorithm are introduced. Finally, the amorphous and crystalline BCM is applied to modeling a polymer-graphite interface. This interface model is used to obtain cohesive zone parameters which are used in a cohesive zone model of fibre-matrix interfacial cracking in a composite microstructure. This allows for an investigation of the temperature dependent damage mechanics from the nano to microscale within
Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model
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,...
Recent Enhancements to the Community Multiscale Air Quality Modeling System (CMAQ)
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...
NASA Technical Reports Server (NTRS)
Vlachos, Dion G.
2002-01-01
The focus of this presentation is on multiscale modeling in order to link processing, microstructure, and properties of materials. Overview of problems we study includes: Growth mechanisms in chemical and physical vapor epitaxy; thin films of zeolites for separation and sensing; thin Pd films for hydrogen separation and pattern formation by self-regulation routes.
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...
1999-08-24
Page 1 Center for Auditory and Acoustic Research Sound Classification and Localization Based on Biology Hearing Models and Multiscale Vector...Quantization John S. Baras Center for Auditory and Acoustic Research Electrical and Computer Engineering Department and the Institute for Systems... Acoustic Microsensors Workshop held on August 24 and 25, 1999 in Crystal City, VA., The original document contains color images. 14. ABSTRACT 15
Multiscale musculoskeletal modelling, data-model fusion and electromyography-informed modelling.
Fernandez, J; Zhang, J; Heidlauf, T; Sartori, M; Besier, T; Röhrle, O; Lloyd, D
2016-04-06
This paper proposes methods and technologies that advance the state of the art for modelling the musculoskeletal system across the spatial and temporal scales; and storing these using efficient ontologies and tools. We present population-based modelling as an efficient method to rapidly generate individual morphology from only a few measurements and to learn from the ever-increasing supply of imaging data available. We present multiscale methods for continuum muscle and bone models; and efficient mechanostatistical methods, both continuum and particle-based, to bridge the scales. Finally, we examine both the importance that muscles play in bone remodelling stimuli and the latest muscle force prediction methods that use electromyography-assisted modelling techniques to compute musculoskeletal forces that best reflect the underlying neuromuscular activity. Our proposal is that, in order to have a clinically relevant virtual physiological human, (i) bone and muscle mechanics must be considered together; (ii) models should be trained on population data to permit rapid generation and use underlying principal modes that describe both muscle patterns and morphology; and (iii) these tools need to be available in an open-source repository so that the scientific community may use, personalize and contribute to the database of models.
Multiscale musculoskeletal modelling, data–model fusion and electromyography-informed modelling
Zhang, J.; Heidlauf, T.; Sartori, M.; Besier, T.; Röhrle, O.; Lloyd, D.
2016-01-01
This paper proposes methods and technologies that advance the state of the art for modelling the musculoskeletal system across the spatial and temporal scales; and storing these using efficient ontologies and tools. We present population-based modelling as an efficient method to rapidly generate individual morphology from only a few measurements and to learn from the ever-increasing supply of imaging data available. We present multiscale methods for continuum muscle and bone models; and efficient mechanostatistical methods, both continuum and particle-based, to bridge the scales. Finally, we examine both the importance that muscles play in bone remodelling stimuli and the latest muscle force prediction methods that use electromyography-assisted modelling techniques to compute musculoskeletal forces that best reflect the underlying neuromuscular activity. Our proposal is that, in order to have a clinically relevant virtual physiological human, (i) bone and muscle mechanics must be considered together; (ii) models should be trained on population data to permit rapid generation and use underlying principal modes that describe both muscle patterns and morphology; and (iii) these tools need to be available in an open-source repository so that the scientific community may use, personalize and contribute to the database of models. PMID:27051510
Modeling of Multiscale and Multiphase Phenomena in Materials Processing
NASA Astrophysics Data System (ADS)
Ludwig, Andreas; Kharicha, Abdellah; Wu, Menghuai
2013-03-01
In order to demonstrate how CFD can help scientists and engineers to better understand the fundamentals of engineering processes, a number of examples are shown and discussed. The paper covers (i) special aspects of continuous casting of steel including turbulence, motion and entrapment of non-metallic inclusions, and impact of soft reduction; (ii) multiple flow phenomena and multiscale aspects during casting of large ingots including flow-induced columnar-to-equiaxed transition and 3D formation of channel segregation; (iii) multiphase magneto-hydrodynamics during electro-slag remelting; and (iv) melt flow and solidification of thin but large centrifugal castings.
Multiscale Interactions in a 3D Model of the Contracting Ventricle.
Amar, Ani; Zlochiver, Sharon; Barnea, Ofer
2015-12-01
A biophysical detailed multiscale model of the myocardium is presented. The model was used to study the contribution of interrelated cellular mechanisms to global myocardial function. The multiscale model integrates cellular electrophysiology, excitation propagation dynamics and force development models into a geometrical fiber based model of the ventricle. The description of the cellular electrophysiology in this study was based on the Ten Tusscher-Noble-Noble-Panfilov heterogeneous model for human ventricular myocytes. A four-state model of the sarcomeric control of contraction developed by Negroni and Lascano was employed to model the intracellular mechanism of force generation. The propagation of electrical excitation was described by a reaction-diffusion equation. The 3D geometrical model of the ventricle, based on single fiber contraction was used as a platform for the evaluation of proposed models. The model represents the myocardium as an anatomically oriented array of contracting fibers with individual fiber parameters such as size, spatial location, orientation and mechanical properties. Moreover, the contracting ventricle model interacts with intraventricular blood elements linking the contractile elements to the heart's preload and afterload, thereby producing the corresponding pressure-volume loop. The results show that the multiscale ventricle model is capable of simulating mechanical contraction, pressure generation and load interactions as well as demonstrating the individual contribution of each ion current.
Multiscale Modeling of Deformation Twinning Based on Field Theory of Multiscale Plasticity (FTMP)
2013-09-01
Simulations: HCP Magnesium (Mg) 13 6.1 Model, Results, and Discussion...for hexagonal close-packed ( HCP ) metals (here HCP refers to any hexagonal metal, not necessarily one with the ideal c/a ratio for closest packing...constitutive model applicable to FCC, BCC, and HCP metals based on statistical mechanics and dislocation dynamics. The rate of plastic distortion is
Multiscale modeling and simulation of soft adhesion and contact of stem cells.
Zeng, Xiaowei; Li, Shaofan
2011-02-01
Recently, we have developed a multiscale soft matter model for stem cells or primitive cells in general, aiming at improving the understanding of mechanotransduction mechanism of cells that is responsible for information exchange between cells and their extracellular environment. In this paper, we report the preliminary results of our research on multiscale modeling and simulation of soft contact and adhesion of cells. The proposed multiscale soft matter cell model may be used to model soft contact and adhesion between cells and their extracellular substrates. This model is a generalization of the Fluid Mosaic Model (Singer and Nicolson, 1972), or an extension of Helfrich's liquid crystal membrane model (Helfrich, 1973). To the best of the authors' knowledge, this may be the first time that a soft matter model is developed for cell contact and adhesion. Moreover we have developed and implemented a Lagrange type meshfree Galerkin formulation and the computational algorithm for the proposed cell model. Comparison study with experimental data has been conducted to validate the parameters of the model. By using the soft matter cell model, we have simulated the soft adhesive contact process between cells and their extracellular substrates. The simulation shows that the cell can sense substrate elasticity by responding in different manners from cell spreading motion to cell contact configurations.
On the multiscale modeling of heart valve biomechanics in health and disease.
Weinberg, Eli J; Shahmirzadi, Danial; Mofrad, Mohammad Reza Kaazempur
2010-08-01
Theoretical models of the human heart valves are useful tools for understanding and characterizing the dynamics of healthy and diseased valves. Enabled by advances in numerical modeling and in a range of disciplines within experimental biomechanics, recent models of the heart valves have become increasingly comprehensive and accurate. In this paper, we first review the fundamentals of native heart valve physiology, composition and mechanics in health and disease. We will then furnish an overview of the development of theoretical and experimental methods in modeling heart valve biomechanics over the past three decades. Next, we will emphasize the necessity of using multiscale modeling approaches in order to provide a comprehensive description of heart valve biomechanics able to capture general heart valve behavior. Finally, we will offer an outlook for the future of valve multiscale modeling, the potential directions for further developments and the challenges involved.
Dynamic roughness model for LES of turbulent flow over multiscale urban-like topography
NASA Astrophysics Data System (ADS)
Zhu, Xiaowei; Anderson, William
2016-11-01
Urban-like topographies are composed of a wide spectrum of topographic elements, which results in multiscale, fractal-like distributions. This has important implications for microscale numerical weather prediction in urban environments, or urban meteorology: the range of scales inhibits the use of numerical schemes where the topography is fully resolved, but the self-similar nature of the topography inspires development of closures that leverage such self-similarity to parameterize unresolved information. That is, a natural urban landscape can be low-pass filtered at the large-eddy simulation grid scale, thereby removing details between the grid scale and the smallest scale of the landscape, but the effects of these truncated topographic modes can be modeled based on details of the large scale. LES has been used to investigate the effects of subgrid-scale (SGS) topography on the roughness length of multiscale urban-like topographies. First, high-resolution multiscale urban-like topographies were generated with random distribution function. Then, the high-resolution multiscale topography was filtered and separated into large- and small-scale topographies with the Reynolds decomposition. Thus, the topography was decomposed into resolved (scale larger than the grid scale) and SGS part (scale smaller than the filter scale). The resolved part was resolved in LES, while the SGS terrain must be parameterized. New models for urban roughness will be used to parameterize SGS topography. Army Research Office, Grant # W911NF-15-1-0231.
The deep crust beneath the Trans-European Suture Zone from a multiscale magnetic model
NASA Astrophysics Data System (ADS)
Milano, Maurizio; Fedi, Maurizio; Fairhead, J. Derek
2016-09-01
We present a 3-D interpretation of the deep magnetic sources beneath the main geological structure of central-eastern Europe, the "Trans-European Suture Zone" (TESZ). We used a multiscale analysis of aeromagnetic data, based on a multiscale data set generated by upward continuation of the European and Mediterranean Magnetic Project data set from 5 to 100 km altitude. We also computed the multiscale total gradient |∇T| of the multiscale field. Both of the multiscale data sets allow us to discriminate the main crustal contributions to the field at various scales, and we showed that at large altitudes the field is dominated by the sole effect of the TESZ. The multiridge geometric method was very useful in studying the complex features of the main crustal interfaces, either shallow or deep. The interpreted interfaces are largely agreement with geological models based on seismic surveys and, in some cases, complete the models out of the analyzed region. In order to estimate the deepest source depths in the TESZ region, we applied the multiridge method to the large scales (50-100 km altitude), obtaining a set of singular points at depths ranging between 35 and 40 km. Considering the heat flow trend and the geological models around the TESZ area, we found a meaningful correspondence among the location of the estimated singular points and the most abrupt variations and complex morphology features of the Moho boundary. The multiridge estimates are consistent with known structural information and can be used for a 3-D representation of the Moho depth along the TESZ.
A multiscale approach to model hydrogen bonding: The case of polyamide
Gowers, Richard J. Carbone, Paola
2015-06-14
We present a simple multiscale model for polymer chains in which it is possible to selectively remove degrees of freedom. The model integrates all-atom and coarse-grained potentials in a simple and systematic way and allows a fast sampling of the complex conformational energy surface typical of polymers whilst maintaining a realistic description of selected atomistic interactions. In particular, we show that it is possible to simultaneously reproduce the structure of highly directional non-bonded interactions such as hydrogen bonds and efficiently explore the large number of conformations accessible to the polymer chain. We apply the method to a melt of polyamide removing from the model only the degrees of freedom associated to the aliphatic segments and keeping at atomistic resolution the amide groups involved in the formation of the hydrogen bonds. The results show that the multiscale model produces structural properties that are comparable with the fully atomistic model despite being five times faster to simulate.
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
Multiscale modeling of turbulent channel flow over porous walls
NASA Astrophysics Data System (ADS)
Yogaraj, Sudhakar; Lacis, Ugis; Bagheri, Shervin
2016-11-01
We perform direct numerical simulations of fully developed turbulent flow through a channel coated with a porous material. The Navier-stokes equations governing the fluid domain and the Darcy equations of the porous medium are coupled using an iterative partitioned scheme. At the interface between the two media, boundary conditions derived using a multiscale homogenization approach are enforced. The main feature of this approach is that the anisotropic micro-structural pore features are directly taken into consideration to derive the constitutive coefficients of the porous media as well as of the interface. The focus of the present work is to study the influence of micro-structure pore geometry on the dynamics of turbulent flows. Detailed turbulence statistics and instantaneous flow field are presented. For comparison, flow through impermeable channel flows are included. Supported by the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant agreement No 708281.
Simulation of Left Atrial Function Using a Multi-Scale Model of the Cardiovascular System
Pironet, Antoine; Dauby, Pierre C.; Paeme, Sabine; Kosta, Sarah; Chase, J. Geoffrey; Desaive, Thomas
2013-01-01
During a full cardiac cycle, the left atrium successively behaves as a reservoir, a conduit and a pump. This complex behavior makes it unrealistic to apply the time-varying elastance theory to characterize the left atrium, first, because this theory has known limitations, and second, because it is still uncertain whether the load independence hypothesis holds. In this study, we aim to bypass this uncertainty by relying on another kind of mathematical model of the cardiac chambers. In the present work, we describe both the left atrium and the left ventricle with a multi-scale model. The multi-scale property of this model comes from the fact that pressure inside a cardiac chamber is derived from a model of the sarcomere behavior. Macroscopic model parameters are identified from reference dog hemodynamic data. The multi-scale model of the cardiovascular system including the left atrium is then simulated to show that the physiological roles of the left atrium are correctly reproduced. This include a biphasic pressure wave and an eight-shaped pressure-volume loop. We also test the validity of our model in non basal conditions by reproducing a preload reduction experiment by inferior vena cava occlusion with the model. We compute the variation of eight indices before and after this experiment and obtain the same variation as experimentally observed for seven out of the eight indices. In summary, the multi-scale mathematical model presented in this work is able to correctly account for the three roles of the left atrium and also exhibits a realistic left atrial pressure-volume loop. Furthermore, the model has been previously presented and validated for the left ventricle. This makes it a proper alternative to the time-varying elastance theory if the focus is set on precisely representing the left atrial and left ventricular behaviors. PMID:23755183
Stochastic multiscale modelling of cortical bone elasticity based on high-resolution imaging.
Sansalone, Vittorio; Gagliardi, Davide; Desceliers, Christophe; Bousson, Valérie; Laredo, Jean-Denis; Peyrin, Françoise; Haïat, Guillaume; Naili, Salah
2016-02-01
Accurate and reliable assessment of bone quality requires predictive methods which could probe bone microstructure and provide information on bone mechanical properties. Multiscale modelling and simulation represent a fast and powerful way to predict bone mechanical properties based on experimental information on bone microstructure as obtained through X-ray-based methods. However, technical limitations of experimental devices used to inspect bone microstructure may produce blurry data, especially in in vivo conditions. Uncertainties affecting the experimental data (input) may question the reliability of the results predicted by the model (output). Since input data are uncertain, deterministic approaches are limited and new modelling paradigms are required. In this paper, a novel stochastic multiscale model is developed to estimate the elastic properties of bone while taking into account uncertainties on bone composition. Effective elastic properties of cortical bone tissue were computed using a multiscale model based on continuum micromechanics. Volume fractions of bone components (collagen, mineral, and water) were considered as random variables whose probabilistic description was built using the maximum entropy principle. The relevance of this approach was proved by analysing a human bone sample taken from the inferior femoral neck. The sample was imaged using synchrotron radiation micro-computed tomography. 3-D distributions of Haversian porosity and tissue mineral density extracted from these images supplied the experimental information needed to build the stochastic models of the volume fractions. Thus, the stochastic multiscale model provided reliable statistical information (such as mean values and confidence intervals) on bone elastic properties at the tissue scale. Moreover, the existence of a simpler "nominal model", accounting for the main features of the stochastic model, was investigated. It was shown that such a model does exist, and its relevance
Asynchronous coupling of hybrid models for efficient simulation of multiscale systems
NASA Astrophysics Data System (ADS)
Lockerby, Duncan A.; Patronis, Alexander; Borg, Matthew K.; Reese, Jason M.
2015-03-01
We present a new coupling approach for the time advancement of multi-physics models of multiscale systems. This extends the method of E et al. (2009) [5] to deal with an arbitrary number of models. Coupling is performed asynchronously, with each model being assigned its own timestep size. This enables accurate long timescale predictions to be made at the computational cost of the short timescale simulation. We propose a method for selecting appropriate timestep sizes based on the degree of scale separation that exists between models. A number of example applications are used for testing and benchmarking, including a comparison with experimental data of a thermally driven rarefied gas flow in a micro capillary. The multiscale simulation results are in very close agreement with the experimental data, but are produced almost 50,000 times faster than from a conventionally-coupled simulation.
Anatomy and Physiology of Multiscale Modeling and Simulation in Systems Medicine.
Mizeranschi, Alexandru; Groen, Derek; Borgdorff, Joris; Hoekstra, Alfons G; Chopard, Bastien; Dubitzky, Werner
2016-01-01
Systems medicine is the application of systems biology concepts, methods, and tools to medical research and practice. It aims to integrate data and knowledge from different disciplines into biomedical models and simulations for the understanding, prevention, cure, and management of complex diseases. Complex diseases arise from the interactions among disease-influencing factors across multiple levels of biological organization from the environment to molecules. To tackle the enormous challenges posed by complex diseases, we need a modeling and simulation framework capable of capturing and integrating information originating from multiple spatiotemporal and organizational scales. Multiscale modeling and simulation in systems medicine is an emerging methodology and discipline that has already demonstrated its potential in becoming this framework. The aim of this chapter is to present some of the main concepts, requirements, and challenges of multiscale modeling and simulation in systems medicine.
A multi-scale modeling framework for instabilities of film/substrate systems
NASA Astrophysics Data System (ADS)
Xu, Fan; Potier-Ferry, Michel
2016-01-01
Spatial pattern formation in stiff thin films on soft substrates is investigated from a multi-scale point of view based on a technique of slowly varying Fourier coefficients. A general macroscopic modeling framework is developed and then a simplified macroscopic model is derived. The model incorporates Asymptotic Numerical Method (ANM) as a robust path-following technique to trace the post-buckling evolution path and to predict secondary bifurcations. The proposed multi-scale finite element framework allows sinusoidal and square checkerboard patterns as well as their bifurcation portraits to be described from a quantitative standpoint. Moreover, it provides an efficient way to compute large-scale instability problems with a significant reduction of computational cost compared to full models.
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.
Wirth, B; Asoka-Kumar, P; Denison, A; Glade, S; Howell, R; Marian, J; Odette, G; Sterne, P
2004-04-06
The objective of this work is to determine the chemical composition of nanometer precipitates responsible for irradiation hardening and embrittlement of reactor pressure vessel steels, which threaten to limit the operating lifetime of nuclear power plants worldwide. The scientific approach incorporates computational multiscale modeling of radiation damage and microstructural evolution in Fe-Cu-Ni-Mn alloys, and experimental characterization by positron annihilation spectroscopy and small angle neutron scattering. The modeling and experimental results are
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.
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...
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...
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...
The adaptation of the Community Multiscale Air Quality (CMAQ) modeling system to simulate O_{3}, particulate matter, and related precursor distributions over the northern hemisphere is presented. Hemispheric simulations with CMAQ and the Weather Research and Forecasting (...
Stress and strain localization in stretched collagenous tissues via a multiscale modelling approach.
Marino, Michele; Vairo, Giuseppe
2014-01-01
Mechanobiology of cells in soft collagenous tissues is highly affected by both tissue response at the macroscale and stress/strain localization mechanisms due to features at lower scales. In this paper, the macroscale mechanical behaviour of soft collagenous tissues is modelled by a three-level multiscale approach, based on a multi-step homogenisation technique from nanoscale up to the macroscale. Nanoscale effects, related to both intermolecular cross-links and collagen mechanics, are accounted for, together with geometric nonlinearities at the microscale. Moreover, an effective submodelling procedure is conceived in order to evaluate the local stress and strain fields at the microscale, which is around and within cells. Numerical results, obtained by using an incremental finite element formulation and addressing stretched tendinous tissues, prove consistency and accuracy of the model at both macroscale and microscale, confirming also the effectiveness of the multiscale modelling concept for successfully analysing physiopathological processes in biological tissues.
Multiscale modeling of membrane rearrangement, drainage, and rupture in evolving foams.
Saye, Robert I; Sethian, James A
2013-05-10
Modeling the physics of foams and foamlike materials, such as soapy froths, fire retardants, and lightweight crash-absorbent structures, presents challenges, because of the vastly different time and space scales involved. By separating and coupling these disparate scales, we have designed a multiscale framework to model dry foam dynamics. This leads to a predictive and flexible computational methodology linking, with a few simplifying assumptions, foam drainage, rupture, and topological rearrangement, to coupled interface-fluid motion under surface tension, gravity, and incompressible fluid dynamics. Our computed results match theoretical analyses and experimentally observed physical effects, including thin-film drainage and interference, and are used to study bubble rupture cascades and macroscopic rearrangement. The developed multiscale model allows quantitative computation of complex foam evolution phenomena.
NASA Astrophysics Data System (ADS)
Roberts, A. J.
2007-12-01
A persistent feature of complex systems in engineering and science is the emergence of macroscopic, coarse grained, coherent behaviour from microscale interactions. In current modeling, ranging from ecology to materials science, the underlying microscopic mechanisms are known, but the closures to translate microscale knowledge to a large scale macroscopic description are rarely available in closed form. Kevrekidis proposes new 'equation free' computational methodologies to circumvent this stumbling block in multiscale modelling. Nonlinear coordinate transforms underpin analytic techniques that support these computational methodologies. But to do so we must cross multiple space and time scales, in both deterministic and stochastic systems, and where the microstructure is either smooth or detailed. Using examples, I describe progress in using nonlinear coordinate transforms to illuminate such multiscale modelling issues.
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.
Developing a multiscale, multi-resolution agent-based brain tumor model by graphics processing units
2011-01-01
Multiscale agent-based modeling (MABM) has been widely used to simulate Glioblastoma Multiforme (GBM) and its progression. At the intracellular level, the MABM approach employs a system of ordinary differential equations to describe quantitatively specific intracellular molecular pathways that determine phenotypic switches among cells (e.g. from migration to proliferation and vice versa). At the intercellular level, MABM describes cell-cell interactions by a discrete module. At the tissue level, partial differential equations are employed to model the diffusion of chemoattractants, which are the input factors of the intracellular molecular pathway. Moreover, multiscale analysis makes it possible to explore the molecules that play important roles in determining the cellular phenotypic switches that in turn drive the whole GBM expansion. However, owing to limited computational resources, MABM is currently a theoretical biological model that uses relatively coarse grids to simulate a few cancer cells in a small slice of brain cancer tissue. In order to improve this theoretical model to simulate and predict actual GBM cancer progression in real time, a graphics processing unit (GPU)-based parallel computing algorithm was developed and combined with the multi-resolution design to speed up the MABM. The simulated results demonstrated that the GPU-based, multi-resolution and multiscale approach can accelerate the previous MABM around 30-fold with relatively fine grids in a large extracellular matrix. Therefore, the new model has great potential for simulating and predicting real-time GBM progression, if real experimental data are incorporated. PMID:22176732
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.
Daily reservoir inflow forecasting using multiscale deep feature learning with hybrid models
NASA Astrophysics Data System (ADS)
Bai, Yun; Chen, Zhiqiang; Xie, Jingjing; Li, Chuan
2016-01-01
Inflow forecasting applies data supports for the operations and managements of reservoirs. A multiscale deep feature learning (MDFL) method with hybrid models is proposed in this paper to deal with the daily reservoir inflow forecasting. Ensemble empirical mode decomposition and Fourier spectrum are first employed to extract multiscale (trend, period and random) features, which are then represented by three deep belief networks (DBNs), respectively. The weights of each DBN are subsequently applied to initialize a neural network (D-NN). The outputs of the three-scale D-NNs are finally reconstructed using a sum-up strategy toward the forecasting results. A historical daily inflow series (from 1/1/2000 to 31/12/2012) of the Three Gorges reservoir, China, is investigated by the proposed MDFL with hybrid models. For comparison, four peer models are adopted for the same task. The results show that, the present model overwhelms all the peer models in terms of mean absolute percentage error (MAPE = 11.2896%), normalized root-mean-square error (NRMSE = 0.2292), determination coefficient criteria (R2 = 0.8905), and peak percent threshold statistics (PPTS(5) = 10.0229%). The addressed method integrates the deep framework with multiscale and hybrid observations, and therefore being good at exploring sophisticated natures in the reservoir inflow forecasting.
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 modelling of uranyl chloride solutions
Nguyen, Thanh-Nghi; Duvail, Magali Villard, Arnaud; Dufrêche, Jean-François; Molina, John Jairo; Guilbaud, Philippe
2015-01-14
Classical molecular dynamics simulations with explicit polarization have been successfully used to determine the structural and thermodynamic properties of binary aqueous solutions of uranyl chloride (UO{sub 2}Cl{sub 2}). Concentrated aqueous solutions of uranyl chloride have been studied to determine the hydration properties and the ion-ion interactions. The bond distances and the coordination number of the hydrated uranyl are in good agreement with available experimental data. Two stable positions of chloride in the second hydration shell of uranyl have been identified. The UO{sub 2}{sup 2+}-Cl{sup −} association constants have also been calculated using a multi-scale approach. First, the ion-ion potential averaged over the solvent configurations at infinite dilution (McMillan-Mayer potential) was calculated to establish the dissociation/association processes of UO{sub 2}{sup 2+}-Cl{sup −} ion pairs in aqueous solution. Then, the association constant was calculated from this potential. The value we obtained for the association constant is in good agreement with the experimental result (K{sub UO{sub 2Cl{sup +}}} = 1.48 l mol{sup −1}), but the resulting activity coefficient appears to be too low at molar concentration.
Multiscale Model Predicts Tissue-Level Failure From Collagen Fiber-Level Damage
Hadi, Mohammad F.; Sander, Edward A.; Barocas, Victor H.
2013-01-01
Excessive tissue-level forces communicated to the microstructure and extracellular matrix of soft tissues can lead to damage and failure through poorly understood physical processes that are multiscale in nature. In this work, we propose a multiscale mechanical model for the failure of collagenous soft tissues that incorporates spatial heterogeneity in the microstructure and links the failure of discrete collagen fibers to the material response of the tissue. The model, which is based on experimental failure data derived from different collagen gel geometries, was able to predict the mechanical response and failure of type I collagen gels, and it demonstrated that a fiber-based rule (at the micrometer scale) for discrete failure can strongly shape the macroscale failure response of the gel (at the millimeter scale). The model may be a useful tool in predicting the macroscale failure conditions for soft tissues and engineered tissue analogs. In addition, the multiscale model provides a framework for the study of failure in complex fiber-based mechanical systems in general. PMID:22938372
Integration of regional to outcrop digital data: 3D visualisation of multi-scale geological models
NASA Astrophysics Data System (ADS)
Jones, R. R.; McCaffrey, K. J. W.; Clegg, P.; Wilson, R. W.; Holliman, N. S.; Holdsworth, R. E.; Imber, J.; Waggott, S.
2009-01-01
Multi-scale geological models contain three-dimensional, spatially referenced data, typically spanning at least six orders of magnitude from outcrop to regional scale. A large number of different geological and geophysical data sources can be combined into a single model. Established 3D visualisation methods that are widely used in hydrocarbon exploration and production for sub-surface data have been adapted for onshore surface geology through a combination of methods for digital data acquisition, 3D visualisation, and geospatial analysis. The integration of georeferenced data across a wider than normal range in scale helps to address several of the existing limitations that are inherent in traditional methods of map production and publishing. The primary advantage of a multi-scale approach is that spatial precision and dimensionality (which are generally degraded when data are displayed in 2D at a single scale) can be preserved at all scales. Real-time, immersive, interactive software, based on a "3D geospatial" graphical user interface (GUI), allows complex geological architectures to be depicted, and is more inherently intuitive than software based on a standard "desktop" GUI metaphor. The continuing convergence of different kinds of geo-modelling, GIS, and visualisation software, as well as industry acceptance of standardised middleware, has helped to make multi-scale geological models a practical reality. This is illustrated with two case studies from NE England and NW Scotland.
mRM - multiscale Routing Model for Land Surface and Hydrologic Models
NASA Astrophysics Data System (ADS)
Cuntz, M.; Thober, S.; Mai, J.; Samaniego, L. E.; Gochis, D. J.; Kumar, R.
2015-12-01
Routing streamflow through a river network is a basic step within any distributed hydrologic model. It integrates the generated runoff and allows comparison with observed discharge at the outlet of a catchment. The Muskingum routing is a textbook river routing scheme that has been implemented in Earth System Models (e.g., WRF-HYDRO), stand-alone routing schemes (e.g., RAPID), and hydrologic models (e.g., the mesoscale Hydrologic Model). Most implementations suffer from a high computational demand because the spatial routing resolution is fixed to that of the elevation model irrespective of the hydrologic modeling resolution. This is because the model parameters are scale-dependent and cannot be used at other resolutions without re-estimation. Here, we present the multiscale Routing Model (mRM) that allows for a flexible choice of the routing resolution. mRM exploits the Multiscale Parameter Regionalization (MPR) included in the open-source mesoscale Hydrologic Model (mHM, www.ufz.de/mhm) that relates model parameters to physiographic properties and allows to estimate scale-independent model parameters. mRM is currently coupled to mHM and is presented here as stand-alone Free and Open Source Software (FOSS). The mRM source code is highly modular and provides a subroutine for internal re-use in any land surface scheme. mRM is coupled in this work to the state-of-the-art land surface model Noah-MP. Simulation results using mRM are compared with those available in WRF-HYDRO for the Red River during the period 1990-2000. mRM allows to increase the routing resolution from 100m to more than 10km without deteriorating the model performance. Therefore, it speeds up model calculation by reducing the contribution of routing to total runtime from over 80% to less than 5% in the case of WRF-HYDRO. mRM thus makes discharge data available to land surface modeling with only little extra calculations.
2006-09-01
neighboring grains cannot be spa- tially resolved. 3.5. Homogenization of damage Effects from mechanisms modeled individually— elastoplasticity within each...crystal plasticity routines are available, as the damage computations are effectively uncoupled from the constitutive update of the elastoplastic response... elastoplasticity and damage : multiscale kinematics, Int. J. Solids Struct. 40 (2003) 5669–5688. [17] C. Teodosiu, F. Sidoroff, A finite theory of
Multiscale Modeling of the Impact of Textile Fabrics Based on Hybrid Element Analysis
2010-05-19
Leighton RB, Sands M. The Feynman lectures on physics , definitive edition, vol. 1. Addison-Wesley Publishing Company; 2006. ISBN 0- 8053-9046-4. [21...model with distance away from the impact zone based on the multiscale nature of the fabric architecture and the physics of the impact event. Solid...nature of the fabric architecture and the physics of the impact event. Solid elements are used to discretize the yarns around the impact region
Nonlinear Multiscale Modeling of 3D Woven Fiber Composites under Ballistic Loading
2013-07-11
advanced composites like 3D -OWC. On the other hand, a microscale simulation with resolution of individual fiber filament is impractical due to enormous...REPORT Nonlinear Multiscale Modeling of 3D Woven Fiber Composites under Ballistic Loading 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: The objective of...analysis of 3D woven fiber composites under ballistic loading. Since material behavior is determined by its microstructure, it is essential to
Multi-Scale Modeling, Design Strategies and Physical Properties of 2D Composite Sheets
2015-01-15
of Pennsylvania. The breakthrough results obtained are 1) prediction and subsequent experimental observation of strain induced changes in electronic...structure of TMD materials 2) Prediction and experimental observation of using defects in 2D materials to enhance charge storage capacity and 3...221 Philadelphia , PA 19104 -6205 4-Mar-2014 ABSTRACT Final Report: 9.4: Multi-scale modeling, design strategies and physical properties of 2D
Physics-Based Multi-Scale Modeling of Shear Initiated Reactions in Energetic and Reactive Materials
2010-04-01
Physics-based Multi-scale Modeling of Shear Initiated Reactions in Energetic and Reactive Materials by John K. Brennan, Müge Fermen -Coker...Energetic and Reactive Materials John K. Brennan and Müge Fermen -Coker Weapons and Materials Research Directorate, ARL and Linhbao Tran Shock...Materials 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) John K. Brennan, Müge Fermen -Coker, and Linhbao Tran 5d
Multiscale Modeling of the Deformation of Advanced Ferritic Steels for Generation IV Nuclear Energy
Nasr M. Ghoniem; Nick Kioussis
2009-04-18
The objective of this project is to use the multi-scale modeling of materials (MMM) approach to develop an improved understanding of the effects of neutron irradiation on the mechanical properties of high-temperature structural materials that are being developed or proposed for Gen IV applications. In particular, the research focuses on advanced ferritic/ martensitic steels to enable operation up to 650-700°C, compared to the current 550°C limit on high-temperature steels.
Physics-Based Multi-Scale Modeling of Shear Initiated Reactions in Energetic and Reactive Materials
2009-03-01
Phys. 1972, 5, 1921. 7. McQuarrie , D. A., Statistical Mechanics , Harper: New York, 1976. 8. Chase, M. W.; Davies, C. A.; Downey, J. R.; Frurip, D. J...munitions due to fragment impact. Present computational capabilities in continuum mechanics codes used by Army designers do not possess the capability to...into the continuum mechanics code CTH, and perform simulations for HEs and RMs. 2 Figure 1. Schematic of multi-scale shear initiation model. As
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.
Jeraj, Robert
2010-01-01
A multiscale tumour simulation model employing cell-line-specific biological parameters and functional information derived from pre-therapy PET/CT imaging data was developed to investigate effects of different oxygenation levels on the response to radiation therapy. For each tumour voxel, stochastic simulations were performed to model cellular growth and therapeutic response. Model parameters were fitted to published preclinical experiments of head and neck squamous cell carcinoma (HNSCC). Using the obtained parameters, the model was applied to a human HNSCC case to investigate effects of different uniform and non-uniform oxygenation levels and results were compared for treatment efficacy. Simulations of the preclinical studies showed excellent agreement with published data and underlined the model’s ability to quantitatively reproduce tumour behaviour within experimental uncertainties. When using a simplified transformation to derive non-uniform oxygenation levels from molecular imaging data, simulations of the clinical case showed heterogeneous tumour response and variability in radioresistance with decreasing oxygen levels. Once clinically validated, this model could be used to transform patient-specific data into voxel-based biological objectives for treatment planning and to investigate biologically optimized dose prescriptions. PMID:18677042
Evaluating and Improving Cloud Processes in the Multi-Scale Modeling Framework
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
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.
NASA Astrophysics Data System (ADS)
Liu, Kuang
Advanced composites are being widely used in aerospace applications due to their high stiffness, strength and energy absorption capabilities. However, the assurance of structural reliability is a critical issue because a damage event will compromise the integrity of composite structures and lead to ultimate failure. In this dissertation a novel homogenization based multiscale modeling framework using semi-analytical micromechanics is presented to simulate the response of textile composites. The novelty of this approach lies in the three scale homogenization/localization framework bridging between the constituent (micro), the fiber tow scale (meso), weave scale (macro), and the global response. The multiscale framework, named Multiscale Generalized Method of Cells (MSGMC), continuously bridges between the micro to the global scale as opposed to approaches that are top-down and bottom-up. This framework is fully generalized and capable of modeling several different weave and braids without reformulation. Particular emphasis in this dissertation is placed on modeling the nonlinearity and failure of both polymer matrix and ceramic matrix composites. Results are presented for the cases of plain, twill, satin, and triaxially braided composites. Inelastic, failure, strain rate and damage effects are included at the microscale and propagated to the global scale. MSGMC was successfully used to predict the in-plane material response plain and five harness satin woven polymer composites, triaxially braided polymer composite and both the in-plane and out-of-plane response of silicon carbide ceramic matrix composites.
Multiscale Enaction Model (MEM): the case of complexity and “context-sensitivity” in vision
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
A semi-automatic image-based close range 3D modeling pipeline using a multi-camera configuration.
Rau, Jiann-Yeou; Yeh, Po-Chia
2012-01-01
The generation of photo-realistic 3D models is an important task for digital recording of cultural heritage objects. This study proposes an image-based 3D modeling pipeline which takes advantage of a multi-camera configuration and multi-image matching technique that does not require any markers on or around the object. Multiple digital single lens reflex (DSLR) cameras are adopted and fixed with invariant relative orientations. Instead of photo-triangulation after image acquisition, calibration is performed to estimate the exterior orientation parameters of the multi-camera configuration which can be processed fully automatically using coded targets. The calibrated orientation parameters of all cameras are applied to images taken using the same camera configuration. This means that when performing multi-image matching for surface point cloud generation, the orientation parameters will remain the same as the calibrated results, even when the target has changed. Base on this invariant character, the whole 3D modeling pipeline can be performed completely automatically, once the whole system has been calibrated and the software was seamlessly integrated. Several experiments were conducted to prove the feasibility of the proposed system. Images observed include that of a human being, eight Buddhist statues, and a stone sculpture. The results for the stone sculpture, obtained with several multi-camera configurations were compared with a reference model acquired by an ATOS-I 2M active scanner. The best result has an absolute accuracy of 0.26 mm and a relative accuracy of 1:17,333. It demonstrates the feasibility of the proposed low-cost image-based 3D modeling pipeline and its applicability to a large quantity of antiques stored in a museum.
A Semi-Automatic Image-Based Close Range 3D Modeling Pipeline Using a Multi-Camera Configuration
Rau, Jiann-Yeou; Yeh, Po-Chia
2012-01-01
The generation of photo-realistic 3D models is an important task for digital recording of cultural heritage objects. This study proposes an image-based 3D modeling pipeline which takes advantage of a multi-camera configuration and multi-image matching technique that does not require any markers on or around the object. Multiple digital single lens reflex (DSLR) cameras are adopted and fixed with invariant relative orientations. Instead of photo-triangulation after image acquisition, calibration is performed to estimate the exterior orientation parameters of the multi-camera configuration which can be processed fully automatically using coded targets. The calibrated orientation parameters of all cameras are applied to images taken using the same camera configuration. This means that when performing multi-image matching for surface point cloud generation, the orientation parameters will remain the same as the calibrated results, even when the target has changed. Base on this invariant character, the whole 3D modeling pipeline can be performed completely automatically, once the whole system has been calibrated and the software was seamlessly integrated. Several experiments were conducted to prove the feasibility of the proposed system. Images observed include that of a human being, eight Buddhist statues, and a stone sculpture. The results for the stone sculpture, obtained with several multi-camera configurations were compared with a reference model acquired by an ATOS-I 2M active scanner. The best result has an absolute accuracy of 0.26 mm and a relative accuracy of 1:17,333. It demonstrates the feasibility of the proposed low-cost image-based 3D modeling pipeline and its applicability to a large quantity of antiques stored in a museum. PMID:23112656
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.
NASA Technical Reports Server (NTRS)
Arnold, Steven M.; Murthy, Pappu L.; Bednarcyk, Brett A.; Lawson, John W.; Monk, Joshua D.; Bauschlicher, Charles W., Jr.
2016-01-01
Next generation ablative thermal protection systems are expected to consist of 3D woven composite architectures. It is well known that composites can be tailored to achieve desired mechanical and thermal properties in various directions and thus can be made fit-for-purpose if the proper combination of constituent materials and microstructures can be realized. In the present work, the first, multiscale, atomistically-informed, computational analysis of mechanical and thermal properties of a present day - Carbon/Phenolic composite Thermal Protection System (TPS) material is conducted. Model results are compared to measured in-plane and out-of-plane mechanical and thermal properties to validate the computational approach. Results indicate that given sufficient microstructural fidelity, along with lowerscale, constituent properties derived from molecular dynamics simulations, accurate composite level (effective) thermo-elastic properties can be obtained. This suggests that next generation TPS properties can be accurately estimated via atomistically informed multiscale analysis.
Multiscale description of avian migration: from chemical compass to behaviour modeling
Pedersen, J. Boiden; Nielsen, Claus; Solov’yov, Ilia A.
2016-01-01
Despite decades of research the puzzle of the magnetic sense of migratory songbirds has still not been unveiled. Although the problem really needs a multiscale description, most of the individual research efforts were focused on single scale investigations. Here we seek to establish a multiscale link between some of the scales involved, and in particular construct a bridge between electron spin dynamics and migratory bird behaviour. In order to do that, we first consider a model cyclic reaction scheme that could form the basis of the avian magnetic compass. This reaction features a fast spin-dependent process which leads to an unusually precise compass. We then propose how the reaction could be realized in a realistic molecular environment, and argue that it is consistent with the known facts about avian magnetoreception. Finally we show how the microscopic dynamics of spins could possibly be interpreted by a migrating bird and used for the navigational purpose. PMID:27830725
Multiscale description of avian migration: from chemical compass to behaviour modeling
NASA Astrophysics Data System (ADS)
Pedersen, J. Boiden; Nielsen, Claus; Solov’Yov, Ilia A.
2016-11-01
Despite decades of research the puzzle of the magnetic sense of migratory songbirds has still not been unveiled. Although the problem really needs a multiscale description, most of the individual research efforts were focused on single scale investigations. Here we seek to establish a multiscale link between some of the scales involved, and in particular construct a bridge between electron spin dynamics and migratory bird behaviour. In order to do that, we first consider a model cyclic reaction scheme that could form the basis of the avian magnetic compass. This reaction features a fast spin-dependent process which leads to an unusually precise compass. We then propose how the reaction could be realized in a realistic molecular environment, and argue that it is consistent with the known facts about avian magnetoreception. Finally we show how the microscopic dynamics of spins could possibly be interpreted by a migrating bird and used for the navigational purpose.
Training Systems Modelers through the Development of a Multi-scale Chagas Disease Risk Model
NASA Astrophysics Data System (ADS)
Hanley, J.; Stevens-Goodnight, S.; Kulkarni, S.; Bustamante, D.; Fytilis, N.; Goff, P.; Monroy, C.; Morrissey, L. A.; Orantes, L.; Stevens, L.; Dorn, P.; Lucero, D.; Rios, J.; Rizzo, D. M.
2012-12-01
The goal of our NSF-sponsored Division of Behavioral and Cognitive Sciences grant is to create a multidisciplinary approach to develop spatially explicit models of vector-borne disease risk using Chagas disease as our model. Chagas disease is a parasitic disease endemic to Latin America that afflicts an estimated 10 million people. The causative agent (Trypanosoma cruzi) is most commonly transmitted to humans by blood feeding triatomine insect vectors. Our objectives are: (1) advance knowledge on the multiple interacting factors affecting the transmission of Chagas disease, and (2) provide next generation genomic and spatial analysis tools applicable to the study of other vector-borne diseases worldwide. This funding is a collaborative effort between the RSENR (UVM), the School of Engineering (UVM), the Department of Biology (UVM), the Department of Biological Sciences (Loyola (New Orleans)) and the Laboratory of Applied Entomology and Parasitology (Universidad de San Carlos). Throughout this five-year study, multi-educational groups (i.e., high school, undergraduate, graduate, and postdoctoral) will be trained in systems modeling. This systems approach challenges students to incorporate environmental, social, and economic as well as technical aspects and enables modelers to simulate and visualize topics that would either be too expensive, complex or difficult to study directly (Yasar and Landau 2003). We launch this research by developing a set of multi-scale, epidemiological models of Chagas disease risk using STELLA® software v.9.1.3 (isee systems, inc., Lebanon, NH). We use this particular system dynamics software as a starting point because of its simple graphical user interface (e.g., behavior-over-time graphs, stock/flow diagrams, and causal loops). To date, high school and undergraduate students have created a set of multi-scale (i.e., homestead, village, and regional) disease models. Modeling the system at multiple spatial scales forces recognition that
Prediction of water loss and viscoelastic deformation of apple tissue using a multiscale model
NASA Astrophysics Data System (ADS)
Aregawi, Wondwosen A.; Abera, Metadel K.; Fanta, Solomon W.; Verboven, Pieter; Nicolai, Bart
2014-11-01
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
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'.
NASA Astrophysics Data System (ADS)
Hoekstra, Alfons G.; Alowayyed, Saad; Lorenz, Eric; Melnikova, Natalia; Mountrakis, Lampros; van Rooij, Britt; Svitenkov, Andrew; Závodszky, Gábor; Zun, Pavel
2016-11-01
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'.
Alowayyed, Saad; Lorenz, Eric; Melnikova, Natalia; Mountrakis, Lampros; van Rooij, Britt; Svitenkov, Andrew; Závodszky, Gábor; Zun, Pavel
2016-01-01
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’. PMID:27698036
Chen, X; Hickling, T P; Vicini, P
2014-09-03
A mechanistic, multiscale mathematical model of immunogenicity for therapeutic proteins was built by recapitulating key underlying known biological processes for immunogenicity. The model is able to simulate immune responses based on protein-specific antigenic properties (e.g., number of T-epitopes and their major histocompatibility complex (MHC)-II binding affinities) and host-specific immunological/physiological characteristics (e.g., MHC-II allele genotype, drug clearance rate). Preliminary validation was performed using mouse studies with antigens such as ovalbumin (OVA) or OVA-derived peptide. Further, using adalimumab as an example therapeutic protein, the model is able to simulate immune responses against adalimumab in individual subjects and in a population, and also provides estimations of immunogenicity incidence and drug exposure reduction that can be validated experimentally. This is a first attempt at modeling immunogenicity of biologics, so the model simulations should be used to help understand the immunogenicity mechanisms and impacting factors, rather than making direct predictions. This prototype model needs to be subjected to extensive experimental validation and refinement before fulfilling its ultimate mission of predicting immunogenicity. Nevertheless, the current model could potentially set up the starting framework to integrate various in silico, in vitro, in vivo, and clinical immunogenicity assessment results to help meet the challenge of immunogenicity prediction.
NASA Astrophysics Data System (ADS)
O'Reilly, Shannon E.; DeWeese, Lindsay S.; Maynard, Matthew R.; Rajon, Didier A.; Wayson, Michael B.; Marshall, Emily L.; Bolch, Wesley E.
2016-12-01
An image-based skeletal dosimetry model for internal electron sources was created for the ICRP-defined reference adult female. Many previous skeletal dosimetry models, which are still employed in commonly used internal dosimetry software, do not properly account for electron escape from trabecular spongiosa, electron cross-fire from cortical bone, and the impact of marrow cellularity on active marrow self-irradiation. Furthermore, these existing models do not employ the current ICRP definition of a 50 µm bone endosteum (or shallow marrow). Each of these limitations was addressed in the present study. Electron transport was completed to determine specific absorbed fractions to both active and shallow marrow of the skeletal regions of the University of Florida reference adult female. The skeletal macrostructure and microstructure were modeled separately. The bone macrostructure was based on the whole-body hybrid computational phantom of the UF series of reference models, while the bone microstructure was derived from microCT images of skeletal region samples taken from a 45 years-old female cadaver. The active and shallow marrow are typically adopted as surrogate tissue regions for the hematopoietic stem cells and osteoprogenitor cells, respectively. Source tissues included active marrow, inactive marrow, trabecular bone volume, trabecular bone surfaces, cortical bone volume, and cortical bone surfaces. Marrow cellularity was varied from 10 to 100 percent for active marrow self-irradiation. All other sources were run at the defined ICRP Publication 70 cellularity for each bone site. A total of 33 discrete electron energies, ranging from 1 keV to 10 MeV, were either simulated or analytically modeled. The method of combining skeletal macrostructure and microstructure absorbed fractions assessed using MCNPX electron transport was found to yield results similar to those determined with the PIRT model applied to the UF adult male skeletal dosimetry model. Calculated
O'Reilly, Shannon E; DeWeese, Lindsay S; Maynard, Matthew R; Rajon, Didier A; Wayson, Michael B; Marshall, Emily L; Bolch, Wesley E
2016-12-21
An image-based skeletal dosimetry model for internal electron sources was created for the ICRP-defined reference adult female. Many previous skeletal dosimetry models, which are still employed in commonly used internal dosimetry software, do not properly account for electron escape from trabecular spongiosa, electron cross-fire from cortical bone, and the impact of marrow cellularity on active marrow self-irradiation. Furthermore, these existing models do not employ the current ICRP definition of a 50 µm bone endosteum (or shallow marrow). Each of these limitations was addressed in the present study. Electron transport was completed to determine specific absorbed fractions to both active and shallow marrow of the skeletal regions of the University of Florida reference adult female. The skeletal macrostructure and microstructure were modeled separately. The bone macrostructure was based on the whole-body hybrid computational phantom of the UF series of reference models, while the bone microstructure was derived from microCT images of skeletal region samples taken from a 45 years-old female cadaver. The active and shallow marrow are typically adopted as surrogate tissue regions for the hematopoietic stem cells and osteoprogenitor cells, respectively. Source tissues included active marrow, inactive marrow, trabecular bone volume, trabecular bone surfaces, cortical bone volume, and cortical bone surfaces. Marrow cellularity was varied from 10 to 100 percent for active marrow self-irradiation. All other sources were run at the defined ICRP Publication 70 cellularity for each bone site. A total of 33 discrete electron energies, ranging from 1 keV to 10 MeV, were either simulated or analytically modeled. The method of combining skeletal macrostructure and microstructure absorbed fractions assessed using MCNPX electron transport was found to yield results similar to those determined with the PIRT model applied to the UF adult male skeletal dosimetry model. Calculated
The Multi-Scale Model Approach to Thermohydrology at Yucca Mountain
Glascoe, L; Buscheck, T A; Gansemer, J; Sun, Y
2002-03-27
The Multi-Scale Thermo-Hydrologic (MSTH) process model is a modeling abstraction of them1 hydrology (TH) of the potential Yucca Mountain repository at multiple spatial scales. The MSTH model as described herein was used for the Supplemental Science and Performance Analyses (BSC, 2001) and is documented in detail in CRWMS M&O (2000) and Glascoe et al. (2002). The model has been validated to a nested grid model in Buscheck et al. (In Review). The MSTH approach is necessary for modeling thermal hydrology at Yucca Mountain for two reasons: (1) varying levels of detail are necessary at different spatial scales to capture important TH processes and (2) a fully-coupled TH model of the repository which includes the necessary spatial detail is computationally prohibitive. The MSTH model consists of six ''submodels'' which are combined in a manner to reduce the complexity of modeling where appropriate. The coupling of these models allows for appropriate consideration of mountain-scale thermal hydrology along with the thermal hydrology of drift-scale discrete waste packages of varying heat load. Two stages are involved in the MSTH approach, first, the execution of submodels, and second, the assembly of submodels using the Multi-scale Thermohydrology Abstraction Code (MSTHAC). MSTHAC assembles the submodels in a five-step process culminating in the TH model output of discrete waste packages including a mountain-scale influence.
Multiscale modeling of the moist-convective atmosphere — A review
NASA Astrophysics Data System (ADS)
Arakawa, A.; Jung, J.-H.
2011-11-01
Multiscale modeling of the moist-convective atmosphere is reviewed with an emphasis on the recently proposed approaches of unified parameterization and Quasi-3D (Q3D) Multiscale Modeling Framework (MMF). The cumulus parameterization problem, which was introduced to represent the multiscale effects of moist convection, has been one of the central issues in atmospheric modeling. After a review of the history of cumulus parameterization, it is pointed out that currently there are two families of atmospheric models with quite different formulations of model physics, one represented by the general circulation models (GCMs) and the other by the cloud-resolving models (CRMs). Ideally, these two families of models should be unified so that a continuous transition of model physics from one kind to the other takes place as the resolution changes. This paper discusses two possible routes to achieve the unification. ROUTE I unifies the cumulus parameterization in conventional GCMs and the cloud microphysics parameterization in CRMs. A key to construct such a unified parameterization is to reformulate the vertical eddy transport due to subgrid-scale moist convection in such a way that it vanishes when the resolution is sufficiently high. A preliminary design of the unified parameterization is presented with supporting evidence for its validity. ROUTE II for the unification follows the MMF approach based on a coupled GCM/CRM, originally known as the “super-parameterization”. The Q3D MMF is an attempt to broaden the applicability of the super-parameterization without necessarily using a fully three-dimensional CRM. This is accomplished using a network of cloud-resolving grids with gaps. The basic Q3D algorithm and highlights of preliminary results are reviewed. It is suggested that the hierarchy of future global models should form a “Multiscale Modeling Network (MMN)”, which combines these two routes. With this network, the horizontal resolution of the dynamics core and
Multi-scale groundwater modelling for the assessment of sustainable borehole yields under drought
NASA Astrophysics Data System (ADS)
Upton, Kirsty; Butler, Adrian; Jackson, Chris; Jones, Mike
2014-05-01
A new multi-scale groundwater modelling methodology is presented for simulating abstraction boreholes in regional groundwater models. This provides a robust tool for assessing the sustainable yield of supply boreholes, thus improving our understanding of groundwater availability during droughts. The yield of an abstraction well is dependent on a number of factors. These include antecedent recharge and groundwater conditions; the properties of a regional aquifer system; requirements on a groundwater system to maintain river flows or sites of ecological significance; the properties of an individual abstraction borehole; small-scale aquifer heterogeneity around a borehole; the rate of abstraction; and the way in which neighboring abstraction boreholes interact. These factors can all be represented in the multi-scale model, which couples a small-scale radial flow model of an abstraction borehole with a regional-scale groundwater model. The regional groundwater model, ZOOMQ3D, represents the large-scale groundwater system, including lateral and vertical aquifer heterogeneity, rivers, and spatially varying recharge. The 3D radial flow model, SPIDERR, represents linear and non-linear flow to a borehole, local vertical heterogeneity, well storage and pump location. The multi-scale model is applied to a supply borehole (operated by Thames Water) located in the Chalk aquifer within the catchment of the River Thames in southern England. Groundwater abstraction from the Chalk aquifer accounts for 40-70% of the total public water supply in this region. Drought is a recurring feature of the UK climate, and in particular the south and east of England. Since 1850, nine major groundwater droughts have occurred, all of which lasted longer than one year. The most recent occurred in 2010-2012, during which seven water supply companies introduced water usage restrictions, affecting over 20 million people. The radial flow model is initially calibrated against pumping test data from the
Applying an animal model to quantify the uncertainties of an image-based 4D-CT algorithm
NASA Astrophysics Data System (ADS)
Pierce, Greg; Wang, Kevin; Battista, Jerry; Lee, Ting-Yim
2012-06-01
The purpose of this paper is to use an animal model to quantify the spatial displacement uncertainties and test the fundamental assumptions of an image-based 4D-CT algorithm in vivo. Six female Landrace cross pigs were ventilated and imaged using a 64-slice CT scanner (GE Healthcare) operating in axial cine mode. The breathing amplitude pattern of the pigs was varied by periodically crimping the ventilator gas return tube during the image acquisition. The image data were used to determine the displacement uncertainties that result from matching CT images at the same respiratory phase using normalized cross correlation (NCC) as the matching criteria. Additionally, the ability to match the respiratory phase of a 4.0 cm subvolume of the thorax to a reference subvolume using only a single overlapping 2D slice from the two subvolumes was tested by varying the location of the overlapping matching image within the subvolume and examining the effect this had on the displacement relative to the reference volume. The displacement uncertainty resulting from matching two respiratory images using NCC ranged from 0.54 ± 0.10 mm per match to 0.32 ± 0.16 mm per match in the lung of the animal. The uncertainty was found to propagate in quadrature, increasing with number of NCC matches performed. In comparison, the minimum displacement achievable if two respiratory images were matched perfectly in phase ranged from 0.77 ± 0.06 to 0.93 ± 0.06 mm in the lung. The assumption that subvolumes from separate cine scan could be matched by matching a single overlapping 2D image between to subvolumes was validated. An in vivo animal model was developed to test an image-based 4D-CT algorithm. The uncertainties associated with using NCC to match the respiratory phase of two images were quantified and the assumption that a 4.0 cm 3D subvolume can by matched in respiratory phase by matching a single 2D image from the 3D subvolume was validated. The work in this paper shows the image-based 4D
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.
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
2017-01-01
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.
Multiscale model for phonon-assisted band-to-band tunneling in semiconductors
NASA Astrophysics Data System (ADS)
Ajoy, Arvind; Laux, S. E.; Murali, Kota V. R. M.; Karmalkar, Shreepad
2013-02-01
We present a TCAD (Technology Computer Aided Design) compatible multiscale model of phonon-assisted band-to-band tunneling in semiconductors, which incorporates the non-parabolic nature of complex bands within the bandgap of the material. This model is shown capture the measured current-voltage data in silicon, for current transport along the [100], [110], and [111] directions. Our model will be useful to predict band-to-band tunneling phenomena to quantify on and off currents in tunnel FETs and in small geometry MOSFETs and FINFETs.
Bridging scales through multiscale modeling: a case study on protein kinase A
Boras, Britton W.; Hirakis, Sophia P.; Votapka, Lane W.; Malmstrom, Robert D.; Amaro, Rommie E.; McCulloch, Andrew D.
2015-01-01
The goal of multiscale modeling in biology is to use structurally based physico-chemical models to integrate across temporal and spatial scales of biology and thereby improve mechanistic understanding of, for example, how a single mutation can alter organism-scale phenotypes. This approach may also inform therapeutic strategies or identify candidate drug targets that might otherwise have been overlooked. However, in many cases, it remains unclear how best to synthesize information obtained from various scales and analysis approaches, such as atomistic molecular models, Markov state models (MSM), subcellular network models, and whole cell models. In this paper, we use protein kinase A (PKA) activation as a case study to explore how computational methods that model different physical scales can complement each other and integrate into an improved multiscale representation of the biological mechanisms. Using measured crystal structures, we show how molecular dynamics (MD) simulations coupled with atomic-scale MSMs can provide conformations for Brownian dynamics (BD) simulations to feed transitional states and kinetic parameters into protein-scale MSMs. We discuss how milestoning can give reaction probabilities and forward-rate constants of cAMP association events by seamlessly integrating MD and BD simulation scales. These rate constants coupled with MSMs provide a robust representation of the free energy landscape, enabling access to kinetic, and thermodynamic parameters unavailable from current experimental data. These approaches have helped to illuminate the cooperative nature of PKA activation in response to distinct cAMP binding events. Collectively, this approach exemplifies a general strategy for multiscale model development that is applicable to a wide range of biological problems. PMID:26441670
Multiscale Modeling of Advanced Materials for Damage Prediction and Structural Health Monitoring
NASA Astrophysics Data System (ADS)
Borkowski, Luke
Advanced aerospace materials, including fiber reinforced polymer and ceramic matrix composites, are increasingly being used in critical and demanding applications, challenging the current damage prediction, detection, and quantification methodologies. Multiscale computational models offer key advantages over traditional analysis techniques and can provide the necessary capabilities for the development of a comprehensive virtual structural health monitoring (SHM) framework. Virtual SHM has the potential to drastically improve the design and analysis of aerospace components through coupling the complementary capabilities of models able to predict the initiation and propagation of damage under a wide range of loading and environmental scenarios, simulate interrogation methods for damage detection and quantification, and assess the health of a structure. A major component of the virtual SHM framework involves having micromechanics-based multiscale composite models that can provide the elastic, inelastic, and damage behavior of composite material systems under mechanical and thermal loading conditions and in the presence of microstructural complexity and variability. Quantification of the role geometric and architectural variability in the composite microstructure plays in the local and global composite behavior is essential to the development of appropriate scale-dependent unit cells and boundary conditions for the multiscale model. Once the composite behavior is predicted and variability effects assessed, wave-based SHM simulation models serve to provide knowledge on the probability of detection and characterization accuracy of damage present in the composite. The research presented in this dissertation provides the foundation for a comprehensive SHM framework for advanced aerospace materials. The developed models enhance the prediction of damage formation as a result of ceramic matrix composite processing, improve the understanding of the effects of architectural and
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
Sondak, D.; Shadid, J. N.; Oberai, A. A.; Pawlowski, R. P.; Cyr, E. C.; Smith, T. M.
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 high 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.
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
Gao, Shenshen; Ren, Li; Qiu, Rui; Wu, Zhen; Li, Chunyan; Li, Junli
2017-01-10
Based on the Chinese reference adult male voxel model, a set of microscopic skeletal models of Chinese adult male is constructed through the processes of computed tomography (CT) imaging, bone coring, micro-CT imaging, image segmentation, merging into macroscopic bone model and implementation in Geant4. At the step of image segmentation, a new bone endosteum (BE) segmentation method is realized by sampling. The set of model contains 32 spongiosa samples with voxel size of 19 μm cubes. The microscopic spongiosa bone data for Chinese adult male are provided. Electron absorbed fractions in red bone marrow (RBM) and BE are calculated. Source tissues include the bone marrow (red and yellow), trabecular bone (surfaces and volumes) and cortical bone (surfaces and volumes). Target tissues include RBM and BE. Electron energies range from 10 keV to 10 MeV. Additionally, comparison of the result with other investigations is provided.
Image-based Modeling and Characterization of RF Ablation Lesions in Cardiac Arrhythmia Therapy.
Linte, Cristian A; Camp, Jon J; Rettmann, Maryam E; Holmes, David R; Robb, Richard A
2013-02-09
In spite of significant efforts to enhance guidance for catheter navigation, limited research has been conducted to consider the changes that occur in the tissue during ablation as means to provide useful feedback on the progression of therapy delivery. We propose a technique to visualize lesion progression and monitor the effects of the RF energy delivery using a surrogate thermal ablation model. The model incorporates both physical and physiological tissue parameters, and uses heat transfer principles to estimate temperature distribution in the tissue and geometry of the generated lesion in near real time. The ablation model has been calibrated and evaluated using ex vivo beef muscle tissue in a clinically relevant ablation protocol. To validate the model, the predicted temperature distribution was assessed against that measured directly using fiberoptic temperature probes inserted in the tissue. Moreover, the model-predicted lesions were compared to the lesions observed in the post-ablation digital images. Results showed an agreement within 5°C between the model-predicted and experimentally measured tissue temperatures, as well as comparable predicted and observed lesion characteristics and geometry. These results suggest that the proposed technique is capable of providing reasonably accurate and sufficiently fast representations of the created RF ablation lesions, to generate lesion maps in near real time. These maps can be used to guide the placement of successive lesions to ensure continuous and enduring suppression of the arrhythmic pathway.
Image-based modeling of normal tissue complication probability for radiation therapy.
Deasy, Joseph O; El Naqa, Issam
2008-01-01
We therefore conclude that NTCP models, at least in some cases, are definitely tools not toys. However, like any good tool, they can be abused and in fact could lead to injury with misuse. In particular, we have pointed out that it is risky indeed to apply NTCP models to dose distributions which are very dissimilar to the dose distributions for which the NTCP model has been validated. While this warning is somewhat fuzzy, it is clear that more research needs to be done in this area. We believe that ultimately for NTCP models to be used routinely in treatment planning in a safe and effective way, the actual application will need to be closely related to the characteristics of the data sets and the uncertainties of the treatment parameters in the models under consideration. Another sign that NTCP models are becoming tools rather than toys is that there is often good agreement as to what constitutes a correct direction of improving the reduced risk for that particular complication endpoint. Thus, for example, mean dose to normal lung almost always comes out as being the most predictive or nearly most predictive factor in the analysis of radiation pneumonitis.
Image-based modeling and characterization of RF ablation lesions in cardiac arrhythmia therapy
NASA Astrophysics Data System (ADS)
Linte, Cristian A.; Camp, Jon J.; Rettmann, Maryam E.; Holmes, David R.; Robb, Richard A.
2013-03-01
In spite of significant efforts to enhance guidance for catheter navigation, limited research has been conducted to consider the changes that occur in the tissue during ablation as means to provide useful feedback on the progression of therapy delivery. We propose a technique to visualize lesion progression and monitor the effects of the RF energy delivery using a surrogate thermal ablation model. The model incorporates both physical and physiological tissue parameters, and uses heat transfer principles to estimate temperature distribution in the tissue and geometry of the generated lesion in near real time. The ablation model has been calibrated and evaluated using ex vivo beef muscle tissue in a clinically relevant ablation protocol. To validate the model, the predicted temperature distribution was assessed against that measured directly using fiberoptic temperature probes inserted in the tissue. Moreover, the model-predicted lesions were compared to the lesions observed in the post-ablation digital images. Results showed an agreement within 5°C between the model-predicted and experimentally measured tissue temperatures, as well as comparable predicted and observed lesion characteristics and geometry. These results suggest that the proposed technique is capable of providing reasonably accurate and sufficiently fast representations of the created RF ablation lesions, to generate lesion maps in near real time. These maps can be used to guide the placement of successive lesions to ensure continuous and enduring suppression of the arrhythmic pathway.
Multirate method for co-simulation of electrical-chemical systems in multiscale modeling.
Brocke, Ekaterina; Djurfeldt, Mikael; Bhalla, Upinder S; Kotaleski, Jeanette Hellgren; Hanke, Michael
2017-04-07
Multiscale modeling by means of co-simulation is a powerful tool to address many vital questions in neuroscience. It can for example be applied in the study of the process of learning and memory formation in the brain. At the same time the co-simulation technique makes it possible to take advantage of interoperability between existing tools and multi-physics models as well as distributed computing. However, the theoretical basis for multiscale modeling is not sufficiently understood. There is, for example, a need of efficient and accurate numerical methods for time integration. When time constants of model components are different by several orders of magnitude, individual dynamics and mathematical definitions of each component all together impose stability, accuracy and efficiency challenges for the time integrator. Following our numerical investigations in Brocke et al. (Frontiers in Computational Neuroscience, 10, 97, 2016), we present a new multirate algorithm that allows us to handle each component of a large system with a step size appropriate to its time scale. We take care of error estimates in a recursive manner allowing individual components to follow their discretization time course while keeping numerical error within acceptable bounds. The method is developed with an ultimate goal of minimizing the communication between the components. Thus it is especially suitable for co-simulations. Our preliminary results support our confidence that the multirate approach can be used in the class of problems we are interested in. We show that the dynamics ofa communication signal as well as an appropriate choice of the discretization order between system components may have a significant impact on the accuracy of the coupled simulation. Although, the ideas presented in the paper have only been tested on a single model, it is likely that they can be applied to other problems without loss of generality. We believe that this work may significantly contribute to the
A multi-scale model for correlation in B cell VDJ usage of zebrafish
NASA Astrophysics Data System (ADS)
Pan, Keyao; Deem, Michael W.
2011-10-01
The zebrafish (Danio rerio) is one of the model animals used for the study of immunology because the dynamics in the adaptive immune system of zebrafish are similar to that in higher animals. In this work, we built a multi-scale model to simulate the dynamics of B cells in the primary and secondary immune responses of zebrafish. We use this model to explain the reported correlation between VDJ usage of B cell repertoires in individual zebrafish. We use a delay ordinary differential equation (ODE) system to model the immune responses in the 6-month lifespan of a zebrafish. This mean field theory gives the number of high-affinity B cells as a function of time during an infection. The sequences of those B cells are then taken from a distribution calculated by a 'microscopic' random energy model. This generalized NK model shows that mature B cells specific to one antigen largely possess a single VDJ recombination. The model allows first-principle calculation of the probability, p, that two zebrafish responding to the same antigen will select the same VDJ recombination. This probability p increases with the B cell population size and the B cell selection intensity. The probability p decreases with the B cell hypermutation rate. The multi-scale model predicts correlations in the immune system of the zebrafish that are highly similar to that from experiment.
Finite element implementation of a multiscale model of the human lens capsule.
Burd, H J; Regueiro, R A
2015-11-01
An axisymmetric finite element implementation of a previously described structural constitutive model for the human lens capsule (Burd in Biomech Model Mechanobiol 8(3):217-231, 2009) is presented. This constitutive model is based on a hyperelastic approach in which the network of collagen IV within the capsule is represented by an irregular hexagonal planar network of hyperelastic bars, embedded in a hyperelastic matrix. The paper gives a detailed specification of the model and the periodic boundary conditions adopted for the network component. Momentum balance equations for the network are derived in variational form. These balance equations are used to develop a nonlinear solution scheme to enable the equilibrium configuration of the network to be computed. The constitutive model is implemented within a macroscopic finite element framework to give a multiscale model of the lens capsule. The possibility of capsule wrinkling is included in the formulation. To achieve this implementation, values of the first and second derivatives of the strain energy density with respect to the in-plane stretch ratios need to be computed at the local, constitutive model, level. Procedures to determine these strain energy derivatives at equilibrium configurations of the network are described. The multiscale model is calibrated against previously published experimental data on isolated inflation and uniaxial stretching of ex vivo human capsule samples. Two independent example lens capsule inflation analyses are presented.
Multi-scale modeling of composites subjected to high speed impact
NASA Astrophysics Data System (ADS)
Lee, Minhyung; Cha, Myung S.; Kim, Nam H.
2017-01-01
In this paper, multi-scale modeling methodology has been applied to simulate the relatively thick composite panels subjected to high speed local impact loading. Instead of massive parallel processing, we propose to use surrogate modeling to bridge micro-scale and macro-scale. Multi-scale modeling of fracture phenomena of composite materials will consist of (1) micro-scale modeling of fiber-matrix structure using the unit-volume-element technique, which can incorporate the boundary effect, and the level set method for crack modeling, which can model the crack propagation independent of finite element mesh; (2) macro-scale simulation of composite panels under high strain-rate impact using material response calculated from micro-scale modeling; and (3) surrogate modeling to integrate the two scales. In order to validate the predictions, first we did the material level lab experiment such as tensile test. We also did the field test of bullet impact into composite panels made of 4 plies fiber. The impact velocity ranges from 300 ˜ 600 m/s.
Du, Peng; O'Grady, Gregory; Gao, Jerry; Sathar, Shameer; Cheng, Leo K
2013-01-01
Experimental progress in investigating normal and disordered gastric motility is increasingly being complimented by sophisticated multiscale modeling studies. Mathematical modeling has become a valuable tool in this effort, as there is an ever-increasing need to gain an integrative and quantitative understanding of how physiological mechanisms achieve coordinated functions across multiple biophysical scales. These interdisciplinary efforts have been particularly notable in the area of gastric electrophysiology, where they are beginning to yield a comprehensive and integrated in silico organ modeling framework, or 'virtual stomach'. At the cellular level, a number of biophysically based mathematical cell models have been developed, and these are now being applied in areas including investigations of gastric electrical pacemaker mechanisms, smooth muscle electrophysiology, and electromechanical coupling. At the tissue level, micro-structural models are being creatively developed and employed to investigate clinically significant questions, such as the functional effects of ICC degradation on gastrointestinal (GI) electrical activation. At the organ level, high-resolution electrical mapping and modeling studies are combined to provide improved insights into normal and dysrhythmic gastric electrical activation. These efforts are also enabling detailed forward and inverse modeling studies at the 'whole body' level, with implications for diagnostic techniques for gastric dysrhythmias. These recent advances, together with several others highlighted in this review, collectively demonstrate a powerful trend toward applying mathematical models to effectively investigate structure-function relationships and overcome multiscale challenges in basic and clinical GI research.
NASA Astrophysics Data System (ADS)
Abghary, Mohammad Javad; Nedoushan, Reza Jafari; Hasani, Hossein
2016-11-01
In this paper a multi-scale numerical model for simulating the mechanical behavior of biaxial weft knitted fabrics produced based on 1×1 rib structure is presented. Fabrics were produced on a modern flat knitting machine using polyester as stitch yarns and nylon as straight yarns. A macro constitutive equation was presented to model the fabric mechanical behavior as a continuum material. User defined material subroutines were provided to implement the constitutive behavior in Abaqus software. The constitutive equation needs remarkable tensile tests on the fabric as the inputs. To solve this drawbacks meso scale modeling of the fabric was used to predict stress-strain curves of the fabric in three different directions (course, wale and 45°). In these simulations only the yarn properties are needed. To evaluate the accuracy of the proposed macro and meso models, fabric tensile behavior in 22.5 and 67.5° directions were simulated by the calibrated macro model and compared with experimental results. Spherical deformation was also simulated by the multi scale model and compared with experimental results. The results showed that the multi-scale modeling can successfully predict the tensile and spherical deformation of the biaxial weft knitted fabric with least required experiments. This model will be useful for composite applications.
Mathematical and Numerical Analyses of Peridynamics for Multiscale Materials Modeling
Gunzburger, Max
2015-02-17
We have treated the modeling, analysis, numerical analysis, and algorithmic development for nonlocal models of diffusion and mechanics. Variational formulations were developed and finite element methods were developed based on those formulations for both steady state and time dependent problems. Obstacle problems and optimization problems for the nonlocal models were also treated and connections made with fractional derivative models.
Marchand, Roger T.; Beagley, Nathaniel; Ackerman, Thomas P.
2009-09-01
Vertical profiles of hydrometeor occurrence from the Multiscale Modeling Framework (MMF) climate model are compared with profiles observed by a vertically pointing millimeter wavelength cloud-radar (located in the U.S. Southern Great Plains) as a function of the largescale atmospheric state. The atmospheric state is determined by classifying (or clustering) the large-scale (synoptic) fields produced by the MMF and a numerical weather prediction model using a neural network approach. The comparison shows that for cold frontal and post-cold frontal conditions the MMF produces profiles of hydrometeor occurrence that compare favorably with radar observations, while for warm frontal conditions the model tends to produce hydrometeor fractions that are too large with too much cloud (non-precipitating hydrometeors) above 7 km and too much precipitating hydrometeor coverage below 7 km. We also find that the MMF has difficulty capturing the formation of low clouds and that for all atmospheric states that occur during June, July, and August, the MMF produces too much high and thin cloud, especially above 10 km.
NASA Astrophysics Data System (ADS)
Chen, Hsin-Chen; Jia, Wenyan; Yue, Yaofeng; Li, Zhaoxin; Sun, Yung-Nien; Fernstrom, John D.; Sun, Mingui
2013-10-01
Dietary assessment is important in health maintenance and intervention in many chronic conditions, such as obesity, diabetes and cardiovascular disease. However, there is currently a lack of convenient methods for measuring the volume of food (portion size) in real-life settings. We present a computational method to estimate food volume from a single photographic image of food contained on a typical dining plate. First, we calculate the food location with respect to a 3D camera coordinate system using the plate as a scale reference. Then, the food is segmented automatically from the background in the image. Adaptive thresholding and snake modeling are implemented based on several image features, such as color contrast, regional color homogeneity and curve bending degree. Next, a 3D model representing the general shape of the food (e.g., a cylinder, a sphere, etc) is selected from a pre-constructed shape model library. The position, orientation and scale of the selected shape model are determined by registering the projected 3D model and the food contour in the image, where the properties of the reference are used as constraints. Experimental results using various realistically shaped foods with known volumes demonstrated satisfactory performance of our image-based food volume measurement method even if the 3D geometric surface of the food is not completely represented in the input image.
Chen, Hsin-Chen; Jia, Wenyan; Yue, Yaofeng; Li, Zhaoxin; Sun, Yung-Nien; Fernstrom, John D.; Sun, Mingui
2013-01-01
Dietary assessment is important in health maintenance and intervention in many chronic conditions, such as obesity, diabetes, and cardiovascular disease. However, there is currently a lack of convenient methods for measuring the volume of food (portion size) in real-life settings. We present a computational method to estimate food volume from a single photographical image of food contained in a typical dining plate. First, we calculate the food location with respect to a 3D camera coordinate system using the plate as a scale reference. Then, the food is segmented automatically from the background in the image. Adaptive thresholding and snake modeling are implemented based on several image features, such as color contrast, regional color homogeneity and curve bending degree. Next, a 3D model representing the general shape of the food (e.g., a cylinder, a sphere, etc.) is selected from a pre-constructed shape model library. The position, orientation and scale of the selected shape model are determined by registering the projected 3D model and the food contour in the image, where the properties of the reference are used as constraints. Experimental results using various realistically shaped foods with known volumes demonstrated satisfactory performance of our image based food volume measurement method even if the 3D geometric surface of the food is not completely represented in the input image. PMID:24223474
Chen, Hsin-Chen; Jia, Wenyan; Yue, Yaofeng; Li, Zhaoxin; Sun, Yung-Nien; Fernstrom, John D; Sun, Mingui
2013-10-01
Dietary assessment is important in health maintenance and intervention in many chronic conditions, such as obesity, diabetes, and cardiovascular disease. However, there is currently a lack of convenient methods for measuring the volume of food (portion size) in real-life settings. We present a computational method to estimate food volume from a single photographical image of food contained in a typical dining plate. First, we calculate the food location with respect to a 3D camera coordinate system using the plate as a scale reference. Then, the food is segmented automatically from the background in the image. Adaptive thresholding and snake modeling are implemented based on several image features, such as color contrast, regional color homogeneity and curve bending degree. Next, a 3D model representing the general shape of the food (e.g., a cylinder, a sphere, etc.) is selected from a pre-constructed shape model library. The position, orientation and scale of the selected shape model are determined by registering the projected 3D model and the food contour in the image, where the properties of the reference are used as constraints. Experimental results using various realistically shaped foods with known volumes demonstrated satisfactory performance of our image based food volume measurement method even if the 3D geometric surface of the food is not completely represented in the input image.
A 4DCT imaging-based breathing lung model with relative hysteresis
NASA Astrophysics Data System (ADS)
Miyawaki, Shinjiro; Choi, Sanghun; Hoffman, Eric A.; Lin, Ching-Long
2016-12-01
To reproduce realistic airway motion and airflow, the authors developed a deforming lung computational fluid dynamics (CFD) model based on four-dimensional (4D, space and time) dynamic computed tomography (CT) images. A total of 13 time points within controlled tidal volume respiration were used to account for realistic and irregular lung motion in human volunteers. Because of the irregular motion of 4DCT-based airways, we identified an optimal interpolation method for airway surface deformation during respiration, and implemented a computational solid mechanics-based moving mesh algorithm to produce smooth deforming airway mesh. In addition, we developed physiologically realistic airflow boundary conditions for both models based on multiple images and a single image. Furthermore, we examined simplified models based on one or two dynamic or static images. By comparing these simplified models with the model based on 13 dynamic images, we investigated the effects of relative hysteresis of lung structure with respect to lung volume, lung deformation, and imaging methods, i.e., dynamic vs. static scans, on CFD-predicted pressure drop. The effect of imaging method on pressure drop was 24 percentage points due to the differences in airflow distribution and airway geometry.
Image-based mass-spring model of mitral valve closure for surgical planning
NASA Astrophysics Data System (ADS)
Hammer, Peter E.; Perrin, Douglas P.; del Nido, Pedro J.; Howe, Robert D.
2008-03-01
Surgical repair of the mitral valve is preferred in most cases over valve replacement, but replacement is often performed instead due to the technical difficulty of repair. A surgical planning system based on patient-specific medical images that allows surgeons to simulate and compare potential repair strategies could greatly improve surgical outcomes. In such a surgical simulator, the mathematical model of mechanics used to close the valve must be able to compute the closed state quickly and to handle the complex boundary conditions imposed by the chords that tether the valve leaflets. We have developed a system for generating a triangulated mesh of the valve surface from volumetric image data of the opened valve. We then compute the closed position of the mesh using a mass-spring model of dynamics. The triangulated mesh is produced by fitting an isosurface to the volumetric image data, and boundary conditions, including the valve annulus and chord endpoints, are identified in the image data using a graphical user interface. In the mass-spring model, triangle sides are treated as linear springs, and sides shared by two triangles are treated as bending springs. Chords are treated as nonlinear springs, and self-collisions are detected and resolved. Equations of motion are solved using implicit numerical integration. Accuracy was assessed by comparison of model results with an image of the same valve taken in the closed state. The model exhibited rapid valve closure and was able to reproduce important features of the closed valve.
Variational multiscale turbulence modelling in a high order spectral element method
Wasberg, Carl Erik Gjesdal, Thor Reif, Bjorn Anders Pettersson Andreassen, Oyvind
2009-10-20
In the variational multiscale (VMS) approach to large eddy simulation (LES), the governing equations are projected onto an a priori scale partitioning of the solution space. This gives an alternative framework for designing and analyzing turbulence models. We describe the implementation of the VMS LES methodology in a high order spectral element method with a nodal basis, and discuss the properties of the proposed scale partitioning. The spectral element code is first validated by doing a direct numerical simulation of fully developed plane channel flow. The performance of the turbulence model is then assessed by several coarse grid simulations of channel flow at different Reynolds numbers.
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.
On Limits of Embedding in 3D Images Based on 2D Watson's Model
NASA Astrophysics Data System (ADS)
Kavehvash, Zahra; Ghaemmaghami, Shahrokh
We extend the Watson image quality metric to 3D images through the concept of integral imaging. In the Watson's model, perceptual thresholds for changes to the DCT coefficients of a 2D image are given for information hiding. These thresholds are estimated in a way that the resulting distortion in the 2D image remains undetectable by the human eyes. In this paper, the same perceptual thresholds are estimated for a 3D scene in the integral imaging method. These thresholds are obtained based on the Watson's model using the relation between 2D elemental images and resulting 3D image. The proposed model is evaluated through subjective tests in a typical image steganography scheme.
An imaging-based computational model for simulating angiogenesis and tumour oxygenation dynamics
NASA Astrophysics Data System (ADS)
Adhikarla, Vikram; Jeraj, Robert
2016-05-01
Tumour growth, angiogenesis and oxygenation vary substantially among tumours and significantly impact their treatment outcome. Imaging provides a unique means of investigating these tumour-specific characteristics. Here we propose a computational model to simulate tumour-specific oxygenation changes based on the molecular imaging data. Tumour oxygenation in the model is reflected by the perfused vessel density. Tumour growth depends on its doubling time (T d) and the imaged proliferation. Perfused vessel density recruitment rate depends on the perfused vessel density around the tumour (sMVDtissue) and the maximum VEGF concentration for complete vessel dysfunctionality (VEGFmax). The model parameters were benchmarked to reproduce the dynamics of tumour oxygenation over its entire lifecycle, which is the most challenging test. Tumour oxygenation dynamics were quantified using the peak pO2 (pO2peak) and the time to peak pO2 (t peak). Sensitivity of tumour oxygenation to model parameters was assessed by changing each parameter by 20%. t peak was found to be more sensitive to tumour cell line related doubling time (~30%) as compared to tissue vasculature density (~10%). On the other hand, pO2peak was found to be similarly influenced by the above tumour- and vasculature-associated parameters (~30-40%). Interestingly, both pO2peak and t peak were only marginally affected by VEGFmax (~5%). The development of a poorly oxygenated (hypoxic) core with tumour growth increased VEGF accumulation, thus disrupting the vessel perfusion as well as further increasing hypoxia with time. The model with its benchmarked parameters, is applied to hypoxia imaging data obtained using a [64Cu]Cu-ATSM PET scan of a mouse tumour and the temporal development of the vasculature and hypoxia maps are shown. The work underscores the importance of using tumour-specific input for analysing tumour evolution. An extended model incorporating therapeutic effects can serve as a powerful tool for analysing
Liu, Yewei; Yin, Ting; Feng, Yuanbo; Cona, Marlein Miranda; Huang, Gang; Liu, Jianjun; Song, Shaoli; Jiang, Yansheng; Xia, Qian; Swinnen, Johannes V.; Bormans, Guy; Himmelreich, Uwe; Oyen, Raymond
2015-01-01
Compared with transplanted tumor models or genetically engineered cancer models, chemically induced primary malignancies in experimental animals can mimic the clinical cancer progress from the early stage on. Cancer caused by chemical carcinogens generally develops through three phases namely initiation, promotion and progression. Based on different mechanisms, chemical carcinogens can be divided into genotoxic and non-genotoxic ones, or complete and incomplete ones, usually with an organ-specific property. Chemical carcinogens can be classified upon their origins such as environmental pollutants, cooked meat derived carcinogens, N-nitroso compounds, food additives, antineoplastic agents, naturally occurring substances and synthetic carcinogens, etc. Carcinogen-induced models of primary cancers can be used to evaluate the diagnostic/therapeutic effects of candidate drugs, investigate the biological influential factors, explore preventive measures for carcinogenicity, and better understand molecular mechanisms involved in tumor initiation, promotion and progression. Among commonly adopted cancer models, chemically induced primary malignancies in mammals have several advantages including the easy procedures, fruitful tumor generation and high analogy to clinical human primary cancers. However, in addition to the time-consuming process, the major drawback of chemical carcinogenesis for translational research is the difficulty in noninvasive tumor burden assessment in small animals. Like human cancers, tumors occur unpredictably also among animals in terms of timing, location and the number of lesions. Thanks to the availability of magnetic resonance imaging (MRI) with various advantages such as ionizing-free scanning, superb soft tissue contrast, multi-parametric information, and utility of diverse contrast agents, now a workable solution to this bottleneck problem is to apply MRI for noninvasive detection, diagnosis and therapeutic monitoring on those otherwise
Tachycardia in post-infarction hearts: insights from 3D image-based ventricular models.
Arevalo, Hermenegild; Plank, Gernot; Helm, Patrick; Halperin, Henry; Trayanova, Natalia
2013-01-01
Ventricular tachycardia, a life-threatening regular and repetitive fast heart rhythm, frequently occurs in the setting of myocardial infarction. Recently, the peri-infarct zones surrounding the necrotic scar (termed gray zones) have been shown to correlate with ventricular tachycardia inducibility. However, it remains unknown how the latter is determined by gray zone distribution and size. The goal of this study is to examine how tachycardia circuits are maintained in the infarcted heart and to explore the relationship between the tachycardia organizing centers and the infarct gray zone size and degree of heterogeneity. To achieve the goals of the study, we employ a sophisticated high-resolution electrophysiological model of the infarcted canine ventricles reconstructed from imaging data, representing both scar and gray zone. The baseline canine ventricular model was also used to generate additional ventricular models with different gray zone sizes, as well as models in which the gray zone was represented as different heterogeneous combinations of viable tissue and necrotic scar. The results of the tachycardia induction simulations with a number of high-resolution canine ventricular models (22 altogether) demonstrated that the gray zone was the critical factor resulting in arrhythmia induction and maintenance. In all models with inducible arrhythmia, the scroll-wave filaments were contained entirely within the gray zone, regardless of its size or the level of heterogeneity of its composition. The gray zone was thus found to be the arrhythmogenic substrate that promoted wavebreak and reentry formation. We found that the scroll-wave filament locations were insensitive to the structural composition of the gray zone and were determined predominantly by the gray zone morphology and size. The findings of this study have important implications for the advancement of improved criteria for stratifying arrhythmia risk in post-infarction patients and for the development of
Photographer-Friendly Work-Flows for Image-Based Modelling of Heritage Artefacts
NASA Astrophysics Data System (ADS)
Martin-Beaumont, N.; Nony, N.; Deshayes, B.; Pierrot-Deseilligny, M.; De Luca, L.
2013-07-01
Because of its low-cost and ease in use, 3D reconstruction from sets of images has an great potential for enhancing cultural heritage documentation, conservation and valuation. However, these technologies, from image acquisition to final 3D model obtaining, are often difficult to master for non-expert people. Our work consists in developing a series of acquisition protocols for the museum's photographs. The end-goal being to enable those professionals to generate efficiently and easily 3D models of heritage artefact.
Optimizing Global Coronal Magnetic Field Models Using Image-Based Constraints
NASA Technical Reports Server (NTRS)
Jones-Mecholsky, Shaela I.; Davila, Joseph M.; Uritskiy, Vadim
2016-01-01
The coronal magnetic field directly or indirectly affects a majority of the phenomena studied in the heliosphere. It provides energy for coronal heating, controls the release of coronal mass ejections, and drives heliospheric and magnetospheric activity, yet the coronal magnetic field itself has proven difficult to measure. This difficulty has prompted a decades-long effort to develop accurate, timely, models of the field, an effort that continues today. We have developed a method for improving global coronal magnetic field models by incorporating the type of morphological constraints that could be derived from coronal images. Here we report promising initial tests of this approach on two theoretical problems, and discuss opportunities for application.
Singharoy, A; Joshi, H; Cheluvaraja, S; Miao, Y; Brown, D; Ortoleva, P
2012-01-01
Most systems of interest in the natural and engineering sciences are multiscale in character. Typically available models are incomplete or uncertain. Thus, a probabilistic approach is required. We present a deductive multiscale approach to address such problems, focusing on virus and cell systems to demonstrate the ideas. There is usually an underlying physical model, all factors in which (e.g., particle masses, charges, and force constants) are known. For example, the underlying model can be cast in terms of a collection of N-atoms evolving via Newton's equations. When the number of atoms is 10(6) or more, these physical models cannot be simulated directly. However, one may only be interested in a coarse-grained description, e.g., in terms of molecular populations or overall system size, shape, position, and orientation. The premise of this chapter is that the coarse-grained equations should be derived from the underlying model so that a deductive calibration-free methodology is achieved. We consider a reduction in resolution from a description for the state of N-atoms to one in terms of coarse-grained variables. This implies a degree of uncertainty in the underlying microstates. We present a methodology for modeling microbial systems that integrates equations for coarse-grained variables with a probabilistic description of the underlying fine-scale ones. The implementation of our strategy as a general computational platform (SimEntropics™) for microbial modeling and prospects for developments and applications are discussed.
Detecting Gait Phases from RGB-D Images Based on Hidden Markov Model
Heravi, Hamed; Ebrahimi, Afshin; Olyaee, Ehsan
2016-01-01
Gait contains important information about the status of the human body and physiological signs. In many medical applications, it is important to monitor and accurately analyze the gait of the patient. Since walking shows the reproducibility signs in several phases, separating these phases can be used for the gait analysis. In this study, a method based on image processing for extracting phases of human gait from RGB-Depth images is presented. The sequence of depth images from the front view has been processed to extract the lower body depth profile and distance features. Feature vector extracted from image is the same as observation vector of hidden Markov model, and the phases of gait are considered as hidden states of the model. After training the model using the images which are randomly selected as training samples, the phase estimation of gait becomes possible using the model. The results confirm the rate of 60–40% of two major phases of the gait and also the mid-stance phase is recognized with 85% precision. PMID:27563572
Detecting Gait Phases from RGB-D Images Based on Hidden Markov Model.
Heravi, Hamed; Ebrahimi, Afshin; Olyaee, Ehsan
2016-01-01
Gait contains important information about the status of the human body and physiological signs. In many medical applications, it is important to monitor and accurately analyze the gait of the patient. Since walking shows the reproducibility signs in several phases, separating these phases can be used for the gait analysis. In this study, a method based on image processing for extracting phases of human gait from RGB-Depth images is presented. The sequence of depth images from the front view has been processed to extract the lower body depth profile and distance features. Feature vector extracted from image is the same as observation vector of hidden Markov model, and the phases of gait are considered as hidden states of the model. After training the model using the images which are randomly selected as training samples, the phase estimation of gait becomes possible using the model. The results confirm the rate of 60-40% of two major phases of the gait and also the mid-stance phase is recognized with 85% precision.
Model-based coding of facial images based on facial muscle motion through isodensity maps
NASA Astrophysics Data System (ADS)
So, Ikken; Nakamura, Osamu; Minami, Toshi
1991-11-01
A model-based coding system has come under serious consideration for the next generation of image coding schemes, aimed at greater efficiency in TV telephone and TV conference systems. In this model-based coding system, the sender's model image is transmitted and stored at the receiving side before the start of the conversation. During the conversation, feature points are extracted from the facial image of the sender and are transmitted to the receiver. The facial expression of the sender facial is reconstructed from the feature points received and a wireframed model constructed at the receiving side. However, the conventional methods have the following problems: (1) Extreme changes of the gray level, such as in wrinkles caused by change of expression, cannot be reconstructed at the receiving side. (2) Extraction of stable feature points from facial images with irregular features such as spectacles or facial hair is very difficult. To cope with the first problem, a new algorithm based on isodensity lines which can represent detailed changes in expression by density correction has already been proposed and good results obtained. As for the second problem, we propose in this paper a new algorithm to reconstruct facial images by transmitting other feature points extracted from isodensity maps.
Simulation of seagrass bed mapping by satellite images based on the radiative transfer model
NASA Astrophysics Data System (ADS)
Sagawa, Tatsuyuki; Komatsu, Teruhisa
2015-06-01
Seagrass and seaweed beds play important roles in coastal marine ecosystems. They are food sources and habitats for many marine organisms, and influence the physical, chemical, and biological environment. They are sensitive to human impacts such as reclamation and pollution. Therefore, their management and preservation are necessary for a healthy coastal environment. Satellite remote sensing is a useful tool for mapping and monitoring seagrass beds. The efficiency of seagrass mapping, seagrass bed classification in particular, has been evaluated by mapping accuracy using an error matrix. However, mapping accuracies are influenced by coastal environments such as seawater transparency, bathymetry, and substrate type. Coastal management requires sufficient accuracy and an understanding of mapping limitations for monitoring coastal habitats including seagrass beds. Previous studies are mainly based on case studies in specific regions and seasons. Extensive data are required to generalise assessments of classification accuracy from case studies, which has proven difficult. This study aims to build a simulator based on a radiative transfer model to produce modelled satellite images and assess the visual detectability of seagrass beds under different transparencies and seagrass coverages, as well as to examine mapping limitations and classification accuracy. Our simulations led to the development of a model of water transparency and the mapping of depth limits and indicated the possibility for seagrass density mapping under certain ideal conditions. The results show that modelling satellite images is useful in evaluating the accuracy of classification and that establishing seagrass bed monitoring by remote sensing is a reliable tool.
NASA Astrophysics Data System (ADS)
Santagati, C.; Inzerillo, L.; Di Paola, F.
2013-07-01
3D reconstruction from images has undergone a revolution in the last few years. Computer vision techniques use photographs from data set collection to rapidly build detailed 3D models. The simultaneous applications of different algorithms (MVS), the different techniques of image matching, feature extracting and mesh optimization are inside an active field of research in computer vision. The results are promising: the obtained models are beginning to challenge the precision of laser-based reconstructions. Among all the possibilities we can mainly distinguish desktop and web-based packages. Those last ones offer the opportunity to exploit the power of cloud computing in order to carry out a semi-automatic data processing, thus allowing the user to fulfill other tasks on its computer; whereas desktop systems employ too much processing time and hard heavy approaches. Computer vision researchers have explored many applications to verify the visual accuracy of 3D model but the approaches to verify metric accuracy are few and no one is on Autodesk 123D Catch applied on Architectural Heritage Documentation. Our approach to this challenging problem is to compare the 3Dmodels by Autodesk 123D Catch and 3D models by terrestrial LIDAR considering different object size, from the detail (capitals, moldings, bases) to large scale buildings for practitioner purpose.
NASA Astrophysics Data System (ADS)
Murphy, Maurice; McGovern, Eugene; Pavia, Sara
2013-02-01
Historic Building Information Modelling (HBIM) is a novel prototype library of parametric objects, based on historic architectural data and a system of cross platform programmes for mapping parametric objects onto point cloud and image survey data. The HBIM process begins with remote collection of survey data using a terrestrial laser scanner combined with digital photo modelling. The next stage involves the design and construction of a parametric library of objects, which are based on the manuscripts ranging from Vitruvius to 18th century architectural pattern books. In building parametric objects, the problem of file format and exchange of data has been overcome within the BIM ArchiCAD software platform by using geometric descriptive language (GDL). The plotting of parametric objects onto the laser scan surveys as building components to create or form the entire building is the final stage in the reverse engineering process. The final HBIM product is the creation of full 3D models including detail behind the object's surface concerning its methods of construction and material make-up. The resultant HBIM can automatically create cut sections, details and schedules in addition to the orthographic projections and 3D models (wire frame or textured) for both the analysis and conservation of historic objects, structures and environments.
Historic Building Information Modelling - Adding Intelligence to Laser and Image Based Surveys
NASA Astrophysics Data System (ADS)
Murphy, M.; McGovern, E.; Pavia, S.
2011-09-01
Historic Building Information Modelling (HBIM) is a novel prototype library of parametric objects based on historic data and a system of cross platform programmes for mapping parametric objects onto a point cloud and image survey data. The HBIM process begins with remote collection of survey data using a terrestrial laser scanner combined with digital photo modelling. The next stage involves the design and construction of a parametric library of objects, which are based on the manuscripts ranging from Vitruvius to 18th century architectural pattern books. In building parametric objects, the problem of file format and exchange of data has been overcome within the BIM ArchiCAD software platform by using geometric descriptive language (GDL). The plotting of parametric objects onto the laser scan surveys as building components to create or form the entire building is the final stage in the reverse engin- eering process. The final HBIM product is the creation of full 3D models including detail behind the object's surface concerning its methods of construction and material make-up. The resultant HBIM can automatically create cut sections, details and schedules in addition to the orthographic projections and 3D models (wire frame or textured).
An image-based skeletal tissue model for the ICRP reference newborn
NASA Astrophysics Data System (ADS)
Pafundi, Deanna; Lee, Choonsik; Watchman, Christopher; Bourke, Vincent; Aris, John; Shagina, Natalia; Harrison, John; Fell, Tim; Bolch, Wesley
2009-07-01
Hybrid phantoms represent a third generation of computational models of human anatomy needed for dose assessment in both external and internal radiation exposures. Recently, we presented the first whole-body hybrid phantom of the ICRP reference newborn with a skeleton constructed from both non-uniform rational B-spline and polygon-mesh surfaces (Lee et al 2007 Phys. Med. Biol. 52 3309-33). The skeleton in that model included regions of cartilage and fibrous connective tissue, with the remainder given as a homogenous mixture of cortical and trabecular bone, active marrow and miscellaneous skeletal tissues. In the present study, we present a comprehensive skeletal tissue model of the ICRP reference newborn to permit a heterogeneous representation of the skeleton in that hybrid phantom set—both male and female—that explicitly includes a delineation of cortical bone so that marrow shielding effects are correctly modeled for low-energy photons incident upon the newborn skeleton. Data sources for the tissue model were threefold. First, skeletal site-dependent volumes of homogeneous bone were obtained from whole-cadaver CT image analyses. Second, selected newborn bone specimens were acquired at autopsy and subjected to micro-CT image analysis to derive model parameters of the marrow cavity and bone trabecular 3D microarchitecture. Third, data given in ICRP Publications 70 and 89 were selected to match reference values on total skeletal tissue mass. Active marrow distributions were found to be in reasonable agreement with those given previously by the ICRP. However, significant differences were seen in total skeletal and site-specific masses of trabecular and cortical bone between the current and ICRP newborn skeletal tissue models. The latter utilizes an age-independent ratio of 80%/20% cortical and trabecular bone for the reference newborn. In the current study, a ratio closer to 40%/60% is used based upon newborn CT and micro-CT skeletal image analyses. These
Minimal camera networks for 3D image based modeling of cultural heritage objects.
Alsadik, Bashar; Gerke, Markus; Vosselman, George; Daham, Afrah; Jasim, Luma
2014-03-25
3D modeling of cultural heritage objects like artifacts, statues and buildings is nowadays an important tool for virtual museums, preservation and restoration. In this paper, we introduce a method to automatically design a minimal imaging network for the 3D modeling of cultural heritage objects. This becomes important for reducing the image capture time and processing when documenting large and complex sites. Moreover, such a minimal camera network design is desirable for imaging non-digitally documented artifacts in museums and other archeological sites to avoid disturbing the visitors for a long time and/or moving delicate precious objects to complete the documentation task. The developed method is tested on the Iraqi famous statue "Lamassu". Lamassu is a human-headed winged bull of over 4.25 m in height from the era of Ashurnasirpal II (883-859 BC). Close-range photogrammetry is used for the 3D modeling task where a dense ordered imaging network of 45 high resolution images were captured around Lamassu with an object sample distance of 1 mm. These images constitute a dense network and the aim of our study was to apply our method to reduce the number of images for the 3D modeling and at the same time preserve pre-defined point accuracy. Temporary control points were fixed evenly on the body of Lamassu and measured by using a total station for the external validation and scaling purpose. Two network filtering methods are implemented and three different software packages are used to investigate the efficiency of the image orientation and modeling of the statue in the filtered (reduced) image networks. Internal and external validation results prove that minimal image networks can provide highly accurate records and efficiency in terms of visualization, completeness, processing time (>60% reduction) and the final accuracy of 1 mm.
An image-based model of calcium waves in differentiated neuroblastoma cells.
Fink, C C; Slepchenko, B; Moraru, I I; Watras, J; Schaff, J C; Loew, L M
2000-01-01
Calcium waves produced by bradykinin-induced inositol-1,4, 5-trisphosphate (InsP(3))-mediated release from endoplasmic reticulum (ER) have been imaged in N1E-115 neuroblastoma cells. A model of this process was built using the "virtual cell," a general computational system for integrating experimental image, biochemical, and electrophysiological data. The model geometry was based on a cell for which the calcium wave had been experimentally recorded. The distributions of the relevant cellular components [InsP(3) receptor (InsP(3)R)], sarcoplasmic/endoplasmic reticulum calcium ATPase (SERCA) pumps, bradykinin receptors, and ER] were based on 3D confocal immunofluorescence images. Wherever possible, known biochemical and electrophysiological data were used to constrain the model. The simulation closely matched the spatial and temporal characteristics of the experimental calcium wave. Predictions on different patterns of calcium signals after InsP(3) uncaging or for different cell geometries were confirmed experimentally, thus helping to validate the model. Models in which the spatial distributions of key components are altered suggest that initiation of the wave in the center of the neurite derives from an interplay of soma-biased ER distribution and InsP(3) generation biased toward the neurite. Simulations demonstrate that mobile buffers (like the indicator fura-2) significantly delay initiation and lower the amplitude of the wave. Analysis of the role played by calcium diffusion indicated that the speed of the wave is only slightly dependent on the ability of calcium to diffuse to and activate neighboring InsP(3) receptor sites. PMID:10866945
Image-based modeling of hemodynamics in coronary artery aneurysms caused by Kawasaki disease.
Sengupta, Dibyendu; Kahn, Andrew M; Burns, Jane C; Sankaran, Sethuraman; Shadden, Shawn C; Marsden, Alison L
2012-07-01
Kawasaki Disease (KD) is the leading cause of acquired pediatric heart disease. A subset of KD patients develops aneurysms in the coronary arteries, leading to increased risk of thrombosis and myocardial infarction. Currently, there are limited clinical data to guide the management of these patients, and the hemodynamic effects of these aneurysms are unknown. We applied patient-specific modeling to systematically quantify hemodynamics and wall shear stress in coronary arteries with aneurysms caused by KD. We modeled the hemodynamics in the aneurysms using anatomic data obtained by multi-detector computed tomography (CT) in a 10-year-old male subject who suffered KD at age 3 years. The altered hemodynamics were compared to that of a reconstructed normal coronary anatomy using our subject as the model. Computer simulations using a robust finite element framework were used to quantify time-varying shear stresses and particle trajectories in the coronary arteries. We accounted for the cardiac contractility and the microcirculation using physiologic downstream boundary conditions. The presence of aneurysms in the proximal coronary artery leads to flow recirculation, reduced wall shear stress within the aneurysm, and high wall shear stress gradients at the neck of the aneurysm. The wall shear stress in the KD subject (2.95-3.81 dynes/sq cm) was an order of magnitude lower than the normal control model (17.10-27.15 dynes/sq cm). Particle residence times were significantly higher, taking 5 cardiac cycles to fully clear from the aneurysmal regions in the KD subject compared to only 1.3 cardiac cycles from the corresponding regions of the normal model. In this novel quantitative study of hemodynamics in coronary aneurysms caused by KD, we documented markedly abnormal flow patterns that are associated with increased risk of thrombosis. This methodology has the potential to provide further insights into the effects of aneurysms in KD and to help risk stratify patients for
Downscaling modelling system for multi-scale air quality forecasting
NASA Astrophysics Data System (ADS)
Nuterman, R.; Baklanov, A.; Mahura, A.; Amstrup, B.; Weismann, J.
2010-09-01
Urban modelling for real meteorological situations, in general, considers only a small part of the urban area in a micro-meteorological model, and urban heterogeneities outside a modelling domain affect micro-scale processes. Therefore, it is important to build a chain of models of different scales with nesting of higher resolution models into larger scale lower resolution models. Usually, the up-scaled city- or meso-scale models consider parameterisations of urban effects or statistical descriptions of the urban morphology, whereas the micro-scale (street canyon) models are obstacle-resolved and they consider a detailed geometry of the buildings and the urban canopy. The developed system consists of the meso-, urban- and street-scale models. First, it is the Numerical Weather Prediction (HIgh Resolution Limited Area Model) model combined with Atmospheric Chemistry Transport (the Comprehensive Air quality Model with extensions) model. Several levels of urban parameterisation are considered. They are chosen depending on selected scales and resolutions. For regional scale, the urban parameterisation is based on the roughness and flux corrections approach; for urban scale - building effects parameterisation. Modern methods of computational fluid dynamics allow solving environmental problems connected with atmospheric transport of pollutants within urban canopy in a presence of penetrable (vegetation) and impenetrable (buildings) obstacles. For local- and micro-scales nesting the Micro-scale Model for Urban Environment is applied. This is a comprehensive obstacle-resolved urban wind-flow and dispersion model based on the Reynolds averaged Navier-Stokes approach and several turbulent closures, i.e. k -É linear eddy-viscosity model, k - É non-linear eddy-viscosity model and Reynolds stress model. Boundary and initial conditions for the micro-scale model are used from the up-scaled models with corresponding interpolation conserving the mass. For the boundaries a
Recent Enhancements to the Community Multiscale Air Quality Model (CMAQ)
This presentation overviews recent updates to the CMAQ modeling system. The presentation will be given as part of the information exchange session on Regional Air Pollution Modeling at the UK-US Collaboration Meeting on Air Pollution Exposure Science.
NEW DEVELOPMENTS IN THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL
CMAQ model research and development is currently following two tracks at the Atmospheric Modeling Division of the USEPA. Public releases of the community model system for research and policy analysis is continuing on an annual interval with the latest release scheduled for Augus...
OPTIMIZING GLOBAL CORONAL MAGNETIC FIELD MODELS USING IMAGE-BASED CONSTRAINTS
Jones, Shaela I.; Davila, Joseph M.; Uritsky, Vadim
2016-04-01
The coronal magnetic field directly or indirectly affects a majority of the phenomena studied in the heliosphere. It provides energy for coronal heating, controls the release of coronal mass ejections, and drives heliospheric and magnetospheric activity, yet the coronal magnetic field itself has proven difficult to measure. This difficulty has prompted a decades-long effort to develop accurate, timely, models of the field—an effort that continues today. We have developed a method for improving global coronal magnetic field models by incorporating the type of morphological constraints that could be derived from coronal images. Here we report promising initial tests of this approach on two theoretical problems, and discuss opportunities for application.
An automatic image-based modelling method applied to forensic infography.
Zancajo-Blazquez, Sandra; Gonzalez-Aguilera, Diego; Gonzalez-Jorge, Higinio; Hernandez-Lopez, David
2015-01-01
This paper presents a new method based on 3D reconstruction from images that demonstrates the utility and integration of close-range photogrammetry and computer vision as an efficient alternative to modelling complex objects and scenarios of forensic infography. The results obtained confirm the validity of the method compared to other existing alternatives as it guarantees the following: (i) flexibility, permitting work with any type of camera (calibrated and non-calibrated, smartphone or tablet) and image (visible, infrared, thermal, etc.); (ii) automation, allowing the reconstruction of three-dimensional scenarios in the absence of manual intervention, and (iii) high quality results, sometimes providing higher resolution than modern laser scanning systems. As a result, each ocular inspection of a crime scene with any camera performed by the scientific police can be transformed into a scaled 3d model.
An Automatic Image-Based Modelling Method Applied to Forensic Infography
Zancajo-Blazquez, Sandra; Gonzalez-Aguilera, Diego; Gonzalez-Jorge, Higinio; Hernandez-Lopez, David
2015-01-01
This paper presents a new method based on 3D reconstruction from images that demonstrates the utility and integration of close-range photogrammetry and computer vision as an efficient alternative to modelling complex objects and scenarios of forensic infography. The results obtained confirm the validity of the method compared to other existing alternatives as it guarantees the following: (i) flexibility, permitting work with any type of camera (calibrated and non-calibrated, smartphone or tablet) and image (visible, infrared, thermal, etc.); (ii) automation, allowing the reconstruction of three-dimensional scenarios in the absence of manual intervention, and (iii) high quality results, sometimes providing higher resolution than modern laser scanning systems. As a result, each ocular inspection of a crime scene with any camera performed by the scientific police can be transformed into a scaled 3d model. PMID:25793628
Chen, Zhaoxue; Chen, Hao
2014-01-01
A deconvolution method based on the Gaussian radial basis function (GRBF) interpolation is proposed. Both the original image and Gaussian point spread function are expressed as the same continuous GRBF model, thus image degradation is simplified as convolution of two continuous Gaussian functions, and image deconvolution is converted to calculate the weighted coefficients of two-dimensional control points. Compared with Wiener filter and Lucy-Richardson algorithm, the GRBF method has an obvious advantage in the quality of restored images. In order to overcome such a defect of long-time computing, the method of graphic processing unit multithreading or increasing space interval of control points is adopted, respectively, to speed up the implementation of GRBF method. The experiments show that based on the continuous GRBF model, the image deconvolution can be efficiently implemented by the method, which also has a considerable reference value for the study of three-dimensional microscopic image deconvolution.
Image-based modelling of nutrient movement in and around the rhizosphere
Daly, Keith R.; Keyes, Samuel D.; Masum, Shakil; Roose, Tiina
2016-01-01
In this study, we developed a spatially explicit model for nutrient uptake by root hairs based on X-ray computed tomography images of the rhizosphere soil structure. This work extends our previous work to larger domains and hence is valid for longer times. Unlike the model used previously, which considered only a small region of soil about the root, we considered an effectively infinite volume of bulk soil about the rhizosphere. We asked the question: At what distance away from root surfaces do the specific structural features of root-hair and soil aggregate morphology not matter because average properties start dominating the nutrient transport? The resulting model was used to capture bulk and rhizosphere soil properties by considering representative volumes of soil far from the root and adjacent to the root, respectively. By increasing the size of the volumes that we considered, the diffusive impedance of the bulk soil and root uptake were seen to converge. We did this for two different values of water content. We found that the size of region for which the nutrient uptake properties converged to a fixed value was dependent on the water saturation. In the fully saturated case, the region of soil we needed to consider was only of radius 1.1mm for poorly soil-mobile species such as phosphate. However, in the case of a partially saturated medium (relative saturation 0.3), we found that a radius of 1.4mm was necessary. This suggests that, in addition to the geometrical properties of the rhizosphere, there is an additional effect of soil moisture properties, which extends further from the root and may relate to other chemical changes in the rhizosphere. The latter were not explicitly included in our model. PMID:26739861
Development of an Open Source Image-Based Flow Modeling Software - SimVascular
NASA Astrophysics Data System (ADS)
Updegrove, Adam; Merkow, Jameson; Schiavazzi, Daniele; Wilson, Nathan; Marsden, Alison; Shadden, Shawn
2014-11-01
SimVascular (www.simvascular.org) is currently the only comprehensive software package that provides a complete pipeline from medical image data segmentation to patient specific blood flow simulation. This software and its derivatives have been used in hundreds of conference abstracts and peer-reviewed journal articles, as well as the foundation of medical startups. SimVascular was initially released in August 2007, yet major challenges and deterrents for new adopters were the requirement of licensing three expensive commercial libraries utilized by the software, a complicated build process, and a lack of documentation, support and organized maintenance. In the past year, the SimVascular team has made significant progress to integrate open source alternatives for the linear solver, solid modeling, and mesh generation commercial libraries required by the original public release. In addition, the build system, available distributions, and graphical user interface have been significantly enhanced. Finally, the software has been updated to enable users to directly run simulations using models and boundary condition values, included in the Vascular Model Repository (vascularmodel.org). In this presentation we will briefly overview the capabilities of the new SimVascular 2.0 release. National Science Foundation.
Catchup: a mouse model for imaging-based tracking and modulation of neutrophil granulocytes.
Hasenberg, Anja; Hasenberg, Mike; Männ, Linda; Neumann, Franziska; Borkenstein, Lars; Stecher, Manuel; Kraus, Andreas; Engel, Daniel R; Klingberg, Anika; Seddigh, Pegah; Abdullah, Zeinab; Klebow, Sabrina; Engelmann, Swen; Reinhold, Annegret; Brandau, Sven; Seeling, Michaela; Waisman, Ari; Schraven, Burkhart; Göthert, Joachim R; Nimmerjahn, Falk; Gunzer, Matthias
2015-05-01
Neutrophil granulocyte biology is a central issue of immunological research, but the lack of animal models that allow for neutrophil-selective genetic manipulation has delayed progress. By modulating the neutrophil-specific locus Ly6G with a knock-in allele expressing Cre recombinase and the fluorescent protein tdTomato, we generated a mouse model termed Catchup that exhibits strong neutrophil specificity. Transgene activity was found only in very few eosinophils and basophils and was undetectable in bone marrow precursors, including granulomonocytic progenitors (GMPs). Cre-mediated reporter-gene activation allowed for intravital two-photon microscopy of neutrophils without adoptive transfer. Homozygous animals were Ly6G deficient but showed normal leukocyte cellularity in all measured organs. Ly6G-deficient neutrophils were functionally normal in vitro and in multiple models of sterile or infectious inflammation in vivo. However, Cre-mediated deletion of FcγRIV in neutrophils reduced the cells' recruitment to immune-complex-mediated peritonitis, suggesting a cell-intrinsic role for activating Fc receptors in neutrophil trafficking.
Image-Based Modeling of Blood Flow and Oxygen Transfer in Feto-Placental Capillaries
Brownbill, Paul; Janáček, Jiří; Jirkovská, Marie; Kubínová, Lucie; Chernyavsky, Igor L.; Jensen, Oliver E.
2016-01-01
During pregnancy, oxygen diffuses from maternal to fetal blood through villous trees in the placenta. In this paper, we simulate blood flow and oxygen transfer in feto-placental capillaries by converting three-dimensional representations of villous and capillary surfaces, reconstructed from confocal laser scanning microscopy, to finite-element meshes, and calculating values of vascular flow resistance and total oxygen transfer. The relationship between the total oxygen transfer rate and the pressure drop through the capillary is shown to be captured across a wide range of pressure drops by physical scaling laws and an upper bound on the oxygen transfer rate. A regression equation is introduced that can be used to estimate the oxygen transfer in a capillary using the vascular resistance. Two techniques for quantifying the effects of statistical variability, experimental uncertainty and pathological placental structure on the calculated properties are then introduced. First, scaling arguments are used to quantify the sensitivity of the model to uncertainties in the geometry and the parameters. Second, the effects of localized dilations in fetal capillaries are investigated using an idealized axisymmetric model, to quantify the possible effect of pathological placental structure on oxygen transfer. The model predicts how, for a fixed pressure drop through a capillary, oxygen transfer is maximized by an optimal width of the dilation. The results could explain the prevalence of fetal hypoxia in cases of delayed villous maturation, a pathology characterized by a lack of the vasculo-syncytial membranes often seen in conjunction with localized capillary dilations. PMID:27788214
Time series modeling of live-cell shape dynamics for image-based phenotypic profiling.
Gordonov, Simon; Hwang, Mun Kyung; Wells, Alan; Gertler, Frank B; Lauffenburger, Douglas A; Bathe, Mark
2016-01-01
Live-cell imaging can be used to capture spatio-temporal aspects of cellular responses that are not accessible to fixed-cell imaging. As the use of live-cell imaging continues to increase, new computational procedures are needed to characterize and classify the temporal dynamics of individual cells. For this purpose, here we present the general experimental-computational framework SAPHIRE (Stochastic Annotation of Phenotypic Individual-cell Responses) to characterize phenotypic cellular responses from time series imaging datasets. Hidden Markov modeling is used to infer and annotate morphological state and state-switching properties from image-derived cell shape measurements. Time series modeling is performed on each cell individually, making the approach broadly useful for analyzing asynchronous cell populations. Two-color fluorescent cells simultaneously expressing actin and nuclear reporters enabled us to profile temporal changes in cell shape following pharmacological inhibition of cytoskeleton-regulatory signaling pathways. Results are compared with existing approaches conventionally applied to fixed-cell imaging datasets, and indicate that time series modeling captures heterogeneous dynamic cellular responses that can improve drug classification and offer additional important insight into mechanisms of drug action. The software is available at http://saphire-hcs.org.
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.
Multiscale strength (MS) models: their foundation, their successes, and their challenges
NASA Astrophysics Data System (ADS)
Rudd, Robert
2013-06-01
Multiscale strength (MS) models are constructed to capture a natural hierarchy in the deformation of metals such as V and Ta starting with atomic bonding and extending up through the mobility of individual dislocations, the evolution of dislocation networks and so on until the ultimate material response at the scale of an experiment. In practice, the hierarchy is described by quantum mechanics, molecular dynamics, dislocation dynamics, and so on, ultimately informing a continuum constitutive model. We review the basic models and describe their extension to plastic flow in shocked metals and the response of polycrystalline materials. In experimental systems that match the assumptions of the multiscale strength models, they work surprisingly well, both for fundamental experiments like in-situ single crystal diffraction, and for more integral experiments like Rayleigh-Taylor plastic flow experiments. There are also clear challenges, however. The current MS models do not include failure, and they are expensive to create, due to the large amounts of computer time needed. Still, MS models provide compelling insight into metals under extreme pressures and strain rates. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
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.
An image-based skeletal dosimetry model for the ICRP reference newborn--internal electron sources.
Pafundi, Deanna; Rajon, Didier; Jokisch, Derek; Lee, Choonsik; Bolch, Wesley
2010-04-07
In this study, a comprehensive electron dosimetry model of newborn skeletal tissues is presented. The model is constructed using the University of Florida newborn hybrid phantom of Lee et al (2007 Phys. Med. Biol. 52 3309-33), the newborn skeletal tissue model of Pafundi et al (2009 Phys. Med. Biol. 54 4497-531) and the EGSnrc-based Paired Image Radiation Transport code of Shah et al (2005 J. Nucl. Med. 46 344-53). Target tissues include the active bone marrow (surrogate tissue for hematopoietic stem cells), shallow marrow (surrogate tissue for osteoprogenitor cells) and unossified cartilage (surrogate tissue for chondrocytes). Monoenergetic electron emissions are considered over the energy range 1 keV to 10 MeV for the following source tissues: active marrow, trabecular bone (surfaces and volumes), cortical bone (surfaces and volumes) and cartilage. Transport results are reported as specific absorbed fractions according to the MIRD schema and are given as skeletal-averaged values in the paper with bone-specific values reported in both tabular and graphic format as electronic annexes (supplementary data). The method utilized in this work uniquely includes (1) explicit accounting for the finite size and shape of newborn ossification centers (spongiosa regions), (2) explicit accounting for active and shallow marrow dose from electron emissions in cortical bone as well as sites of unossified cartilage, (3) proper accounting of the distribution of trabecular and cortical volumes and surfaces in the newborn skeleton when considering mineral bone sources and (4) explicit consideration of the marrow cellularity changes for active marrow self-irradiation as applicable to radionuclide therapy of diseased marrow in the newborn child.
Zhao, Yong-guang; Ma, Ling-ling; Li, Chuan-rong; Zhu, Xiao-hua; Tang, Ling-li
2015-07-01
Due to the lack of enough spectral bands for multi-spectral sensor, it is difficult to reconstruct surface retlectance spectrum from finite spectral information acquired by multi-spectral instrument. Here, taking into full account of the heterogeneity of pixel from remote sensing image, a method is proposed to simulate hyperspectral data from multispectral data based on canopy radiation transfer model. This method first assumes the mixed pixels contain two types of land cover, i.e., vegetation and soil. The sensitive parameters of Soil-Leaf-Canopy (SLC) model and a soil ratio factor were retrieved from multi-spectral data based on Look-Up Table (LUT) technology. Then, by combined with a soil ratio factor, all the parameters were input into the SLC model to simulate the surface reflectance spectrum from 400 to 2 400 nm. Taking Landsat Enhanced Thematic Mapper Plus (ETM+) image as reference image, the surface reflectance spectrum was simulated. The simulated reflectance spectrum revealed different feature information of different surface types. To test the performance of this method, the simulated reflectance spectrum was convolved with the Landsat ETM + spectral response curves and Moderate Resolution Imaging Spectrometer (MODIS) spectral response curves to obtain the simulated Landsat ETM+ and MODIS image. Finally, the simulated Landsat ETM+ and MODIS images were compared with the observed Landsat ETM+ and MODIS images. The results generally showed high correction coefficients (Landsat: 0.90-0.99, MODIS: 0.74-0.85) between most simulated bands and observed bands and indicated that the simulated reflectance spectrum was well simulated and reliable.
Pulmonary nodule detection in CT images based on shape constraint CV model
Wang, Bing; Tian, Xuedong; Wang, Qian; Yang, Ying; Xie, Hongzhi E-mail: xiehongzhi@medmail.com.cn; Zhang, Shuyang; Gu, Lixu E-mail: xiehongzhi@medmail.com.cn
2015-03-15
Purpose: Accurate detection of pulmonary nodules remains a technical challenge in computer-aided diagnosis systems because some nodules may adhere to the blood vessels or the lung wall, which have low contrast compared to the surrounding tissues. In this paper, the analysis of typical shape features of candidate nodules based on a shape constraint Chan–Vese (CV) model combined with calculation of the number of blood branches adhered to nodule candidates is proposed to reduce false positive (FP) nodules from candidate nodules. Methods: The proposed scheme consists of three major stages: (1) Segmentation of lung parenchyma from computed tomography images. (2) Extraction of candidate nodules. (3) Reduction of FP nodules. A gray level enhancement combined with a spherical shape enhancement filter is introduced to extract the candidate nodules and their sphere-like contour regions. FPs are removed by analysis of the typical shape features of nodule candidates based on the CV model using spherical constraint and by investigating the number of blood branches adhered to the candidate nodules. The constrained shapes of CV model are automatically achieved from the extracted candidate nodules. Results: The detection performance was evaluated on 127 nodules of 103 cases including three types of challenging nodules, which are juxta-pleural nodules, juxta-vascular nodules, and ground glass opacity nodules. The free-receiver operating characteristic (FROC) curve shows that the proposed method is able to detect 88% of all the nodules in the data set with 4 FPs per case. Conclusions: Evaluation shows that the authors’ method is feasible and effective for detection of three types of nodules in this study.
3D image-based characterization and flow modeling of quartz-filled microfractures
NASA Astrophysics Data System (ADS)
Prodanovic, M.; Eichhubl, P.; Bryant, S. L.; Davis, J. S.; Wanat, E. C.
2011-12-01
Accurate representation of geometry has first order influence on multiphase fluid flow in porous media on all relevant scales. 3D X-Ray computed microtomography (XCMT) has proved crucial in providing geometry information of many porous and fractured media of interest. Here we characterize 3D XCMT images of natural, quartz-filled fractures in tight gas sandstone from Piceance Basin, Colorado, and then build a representative flow model. While many rough-walled fractures have been analyzed/modeled using XCMT, this is to our knowledge the first 3D characterization and flow modeling of quartz-filled fractures. Natural quartz-filled fractures in samples analyzed are found to be very constricted, with many crystals bridging across the fracture but keeping large portions open to flow. In addition, this causes extreme local aperture variation. The affiliated pore space can be divided into fracture pores connected via very tight channels: a characterization typical for sandstones rather than microfractures, but with aspect ratios much higher than those found in sandstones. Single phase flow simulation in these network shows that the absolute permeability is about 100 times larger than in a conventional sandstone. We further simulate two phase fluid displacement directly in the pore space (using level-set based progressive quasi-static algorithm): both drainage and imbibition are characterized by discrete jumps in capillary-pressure vs. saturation relationships, as well as large residual saturations. Future work will include connecting the fracture network that represents both inter-granular and intra-granular porosity in the neighboring matrix.
Image-based modeling of blood flow and oxygen transfer in feto-placental capillaries
NASA Astrophysics Data System (ADS)
Pearce, Philip; Jensen, Oliver
2016-11-01
During pregnancy, oxygen diffuses from maternal to fetal blood through the placenta. At the smallest scale of the feto-placental vasculature are the "terminal villi", bulbous structures that are thought to be the main sites for oxygen transfer in the final trimester of pregnancy. The objective of this study is to investigate blood flow and oxygen transfer in the terminal villi of the placenta. Three-dimensional representations of villous and capillary surfaces, obtained from confocal laser scanning microscopy, are converted to finite-element meshes. Simulations of blood flow and oxygen transfer are performed to calculate the vascular flow resistance of the capillaries and the total oxygen transfer rate from the maternal blood. Scaling arguments, which predict the oxygen transfer across a range of Peclet numbers, are shown to be an efficient tool for quantifying the effect of statistical variability and experimental uncertainty. The effect of commonly observed localised dilations in the fetal vasculature on oxygen transfer is quantified using an idealised model in a simplified geometry. The model predicts how, for a fixed pressure drop through a capillary, oxygen transfer is maximised by an optimal shape of the dilation, leading to an increase in oxygen transfer of up to 15%.
NASA Astrophysics Data System (ADS)
Giannoglou, V.; Stylianidis, E.
2016-06-01
Scoliosis is a 3D deformity of the human spinal column that is caused from the bending of the latter, causing pain, aesthetic and respiratory problems. This internal deformation is reflected in the outer shape of the human back. The golden standard for diagnosis and monitoring of scoliosis is the Cobb angle, which refers to the internal curvature of the trunk. This work is the first part of a post-doctoral research, presenting the most important researches that have been done in the field of scoliosis, concerning its digital visualisation, in order to provide a more precise and robust identification and monitoring of scoliosis. The research is divided in four fields, namely, the X-ray processing, the automatic Cobb angle(s) calculation, the 3D modelling of the spine that provides a more accurate representation of the trunk and the reduction of X-ray radiation exposure throughout the monitoring of scoliosis. Despite the fact that many researchers have been working on the field for the last decade at least, there is no reliable and universal tool to automatically calculate the Cobb angle(s) and successfully perform proper 3D modelling of the spinal column that would assist a more accurate detection and monitoring of scoliosis.
NASA Astrophysics Data System (ADS)
Yu, Wangyang; Chen, Xiangguang; Wu, Lei
2015-04-01
Passive millimeter wave (PMMW) imaging has become one of the most effective means to detect the objects concealed under clothing. Due to the limitations of the available hardware and the inherent physical properties of PMMW imaging systems, images often exhibit poor contrast and low signal-to-noise ratios. Thus, it is difficult to achieve ideal results by using a general segmentation algorithm. In this paper, an advanced Gaussian Mixture Model (GMM) algorithm for the segmentation of concealed objects in PMMW images is presented. Our work is concerned with the fact that the GMM is a parametric statistical model, which is often used to characterize the statistical behavior of images. Our approach is three-fold: First, we remove the noise from the image using both a notch reject filter and a total variation filter. Next, we use an adaptive parameter initialization GMM algorithm (APIGMM) for simulating the histogram of images. The APIGMM provides an initial number of Gaussian components and start with more appropriate parameter. Bayesian decision is employed to separate the pixels of concealed objects from other areas. At last, the confidence interval (CI) method, alongside local gradient information, is used to extract the concealed objects. The proposed hybrid segmentation approach detects the concealed objects more accurately, even compared to two other state-of-the-art segmentation methods.
Image-based Modeling of Biofilm-induced Calcium Carbonate Precipitation
NASA Astrophysics Data System (ADS)
Connolly, J. M.; Rothman, A.; Jackson, B.; Klapper, I.; Cunningham, A. B.; Gerlach, R.
2013-12-01
Pore scale biological processes in the subsurface environment are important to understand in relation to many engineering applications including environmental contaminant remediation, geologic carbon sequestration, and petroleum production. Specifically, biofilm induced calcium carbonate precipitation has been identified as an attractive option to reduce permeability in a lasting way in the subsurface. This technology may be able to replace typical cement-based grouting in some circumstances; however, pore-scale processes must be better understood for it to be applied in a controlled manor. The work presented will focus on efforts to observe biofilm growth and ureolysis-induced mineral precipitation in micro-fabricated flow cells combined with finite element modelling as a tool to predict local chemical gradients of interest (see figure). We have been able to observe this phenomenon over time using a novel model organism that is able to hydrolyse urea and express a fluorescent protein allowing for non-invasive observation over time with confocal microscopy. The results of this study show the likely existence of a wide range of local saturation indices even in a small (1 cm length scale) experimental system. Interestingly, the locations of high predicted index do not correspond to the locations of higher precipitation density, highlighting the need for further understanding. Figure 1 - A micro-fabricated flow cell containing biofilm-induced calcium carbonate precipitation. (A) Experimental results: Active biofilm is in green and dark circles are calcium carbonate crystals. Note the channeling behavior in the top of the image, leaving a large hydraulically inactive area in the biofilm mass. (B) Finite element model: The prediction of relative saturation of calcium carbonate (as calcite). Fluid enters the system at a low saturation state (blue) but areas of high supersaturation (red) are predicted within the hydraulically inactive area in the biofilm. If only effluent
Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.
2015-01-01
Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228
Multi-scale model analysis and hindcast of the 2013 Colorado Flood
NASA Astrophysics Data System (ADS)
Gochis, David; Yu, Wei; Sampson, Kevin; Dugger, Aubrey; McCreight, James; Zhang, Yongxin; Ikeda, Kyoko
2015-04-01
While the generation of most flood and flash flood events is fundamentally linked to the occurrence of heavy rainfall, the physical mechanisms responsible for translating rainfall into floods are complex and manifold. These runoff generation processes evolve over many spatial and temporal scales during the course of flooding events. As such robust flood and flash flood prediction systems need to account for multitude of terrestrial processes occurring over a wide range of space and time scales. One such extreme multiscale flood event was the 2013 Colorado Flood in which over 400 mm of rainfall fell along the Rock Mountain mountain front region over the course of a few days. The flooding impacts from this heavy rainfall event included not only high, fast flows in steep mountain streams but also included large areas of inundation on the adjacent plains and numerous soil saturation excess impacts such as hillslope failures and groundwater intrusions into domestic structures. A multi-scale and multi-process evaluation of this flood event is performed using the community WRF-Hydro modeling system. We incorporate several operational quantitative precipitation estimate and quantitative precipitation forecast products in the analysis and document the skill of multiple configurations of WRF-Hydro physics options across a range of contributing area length scales. Emphasis is placed on assessing how well the different model configurations capture the multi-scale streamflow response from small headwater catchments out to the entire South Platte River basin whose total contributing area exceeds 25,000 sq km. In addition to streamflow we also present evaluations of event simulations and hindcasts of soil saturation fraction, groundwater levels and inundated areas as a means of assessing different runoff generation mechanisms. Finally, results from a U.S. national-scale, fully-coupled hydrometeorological hindcast of the 2013 Colorado flood event using the combined WRF atmospheric
Multi-Scale Modeling of Cementitious Materials (Briefing Chart)
2014-08-31
FEA approach. Voxels are generated for a heterogeneous cementitious material (Type-I cement ) consisting of typical volume fractions of various...for public release; distribution is unlimited. Micromechanics Based Representative Volume Element Modeling of Heterogeneous Cement Paste The views...P.O. Box 12211 Research Triangle Park, NC 27709-2211 cement paste, microstructure, RVE modeling, micromechanics REPORT DOCUMENTATION PAGE 11. SPONSOR
A Multi-Scale Modeling of Laser Cladding Process (Preprint)
2006-04-01
possibilities to alter a component at its surface. Despite immense potentials and advancements, the process model of microstructure evolution and its coupling...with macro parameter of laser cladding process has not been fully developed. To address this issue, a process model of microstructure evolution has
A multiscale gradient-dependent plasticity model for size effects
NASA Astrophysics Data System (ADS)
Lyu, Hao; Taheri-Nassaj, Nasrin; Zbib, Hussein M.
2016-06-01
The mechanical behaviour of polycrystalline material is closely correlated to grain size. In this study, we investigate the size-dependent phenomenon in multi-phase steels using a continuum dislocation dynamic model coupled with viscoplastic self-consistent model. We developed a dislocation-based strain gradient plasticity model and a stress gradient plasticity model, as well as a combined model, resulting in a theory that can predict size effect over a wide range of length scales. Results show that strain gradient plasticity and stress gradient plasticity are complementary rather than competing theories. The stress gradient model is dominant at the initial strain stage, and is much more effective for predicting yield strength than the strain gradient model. For larger deformations, the strain gradient model is dominant and more effective for predicting size-dependent hardening. The numerical results are compared with experimental data and it is found that they have the same trend for the yield stress. Furthermore, the effect of dislocation density at different strain stages is investigated, and the findings show that the Hall-Petch relation holds for the initial strain stage and breaks down for higher strain levels. Finally, a power law to describe the size effect and the transition zone between the strain gradient and stress gradient dominated regions is developed.
Lateral organization of complex lipid mixtures from multiscale modeling
NASA Astrophysics Data System (ADS)
Tumaneng, Paul W.; Pandit, Sagar A.; Zhao, Guijun; Scott, H. L.
2010-02-01
The organizational properties of complex lipid mixtures can give rise to functionally important structures in cell membranes. In model membranes, ternary lipid-cholesterol (CHOL) mixtures are often used as representative systems to investigate the formation and stabilization of localized structural domains ("rafts"). In this work, we describe a self-consistent mean-field model that builds on molecular dynamics simulations to incorporate multiple lipid components and to investigate the lateral organization of such mixtures. The model predictions reveal regions of bimodal order on ternary plots that are in good agreement with experiment. Specifically, we have applied the model to ternary mixtures composed of dioleoylphosphatidylcholine:18:0 sphingomyelin:CHOL. This work provides insight into the specific intermolecular interactions that drive the formation of localized domains in these mixtures. The model makes use of molecular dynamics simulations to extract interaction parameters and to provide chain configuration order parameter libraries.
[Automatic detection of exudates in retinal images based on threshold moving average models].
Wisaeng, K; Hiransakolwong, N; Pothiruk, E
2015-01-01
Since exudate diagnostic procedures require the attention of an expert ophthalmologist as well as regular monitoring of the disease, the workload of expert ophthalmologists will eventually exceed the current screening capabilities. Retinal imaging technology is a current practice screening capability providing a great potential solution. In this paper, a fast and robust automatic detection of exudates based on moving average histogram models of the fuzzy image was applied, and then the better histogram was derived. After segmentation of the exudate candidates, the true exudates were pruned based on Sobel edge detector and automatic Otsu's thresholding algorithm that resulted in the accurate location of the exudates in digital retinal images. To compare the performance of exudate detection methods we have constructed a large database of digital retinal images. The method was trained on a set of 200 retinal images, and tested on a completely independent set of 1220 retinal images. Results show that the exudate detection method performs overall best sensitivity, specificity, and accuracy of 90.42%, 94.60%, and 93.69%, respectively.
Sharpening method of satellite thermal image based on the geographical statistical model
NASA Astrophysics Data System (ADS)
Qi, Pengcheng; Hu, Shixiong; Zhang, Haijun; Guo, Guangmeng
2016-04-01
To improve the effectiveness of thermal sharpening in mountainous regions, paying more attention to the laws of land surface energy balance, a thermal sharpening method based on the geographical statistical model (GSM) is proposed. Explanatory variables were selected from the processes of land surface energy budget and thermal infrared electromagnetic radiation transmission, then high spatial resolution (57 m) raster layers were generated for these variables through spatially simulating or using other raster data as proxies. Based on this, the local adaptation statistical relationship between brightness temperature (BT) and the explanatory variables, i.e., the GSM, was built at 1026-m resolution using the method of multivariate adaptive regression splines. Finally, the GSM was applied to the high-resolution (57-m) explanatory variables; thus, the high-resolution (57-m) BT image was obtained. This method produced a sharpening result with low error and good visual effect. The method can avoid the blind choice of explanatory variables and remove the dependence on synchronous imagery at visible and near-infrared bands. The influences of the explanatory variable combination, sampling method, and the residual error correction on sharpening results were analyzed deliberately, and their influence mechanisms are reported herein.
Argenti, Fabrizio; Bianchi, Tiziano; Alparone, Luciano
2006-11-01
In this paper, a new despeckling method based on undecimated wavelet decomposition and maximum a posteriori MIAP) estimation is proposed. Such a method relies on the assumption that the probability density function (pdf) of each wavelet coefficient is generalized Gaussian (GG). The major novelty of the proposed approach is that the parameters of the GG pdf are taken to be space-varying within each wavelet frame. Thus, they may be adjusted to spatial image context, not only to scale and orientation. Since the MAP equation to be solved is a function of the parameters of the assumed pdf model, the variance and shape factor of the GG function are derived from the theoretical moments, which depend on the moments and joint moments of the observed noisy signal and on the statistics of speckle. The solution of the MAP equation yields the MAP estimate of the wavelet coefficients of the noise-free image. The restored SAR image is synthesized from such coefficients. Experimental results, carried out on both synthetic speckled images and true SAR images, demonstrate that MAP filtering can be successfully applied to SAR images represented in the shift-invariant wavelet domain, without resorting to a logarithmic transformation.
Multi-scale gravity field modeling in space and time
NASA Astrophysics Data System (ADS)
Wang, Shuo; Panet, Isabelle; Ramillien, Guillaume; Guilloux, Frédéric
2016-04-01
The Earth constantly deforms as it undergoes dynamic phenomena, such as earthquakes, post-glacial rebound and water displacement in its fluid envelopes. These processes have different spatial and temporal scales and are accompanied by mass displacements, which create temporal variations of the gravity field. Since 2002, the GRACE satellite missions provide an unprecedented view of the gravity field spatial and temporal variations. Gravity models built from these satellite data are essential to study the Earth's dynamic processes (Tapley et al., 2004). Up to present, time variations of the gravity field are often modelled using spatial spherical harmonics functions averaged over a fixed period, as 10 days or 1 month. This approach is well suited for modeling global phenomena. To better estimate gravity related to local and/or transient processes, such as earthquakes or floods, and adapt the temporal resolution of the model to its spatial resolution, we propose to model the gravity field using localized functions in space and time. For that, we build a model of the gravity field in space and time with a four-dimensional wavelet basis, well localized in space and time. First we design the 4D basis, then, we study the inverse problem to model the gravity field from the potential differences between the twin GRACE satellites, and its regularization using prior knowledge on the water cycle. Our demonstration of surface water mass signals decomposition in time and space is based on the use of synthetic along-track gravitational potential data. We test the developed approach on one year of 4D gravity modeling and compare the reconstructed water heights to those of the input hydrological model. Perspectives of this work is to apply the approach on real GRACE data, addressing the challenge of a realistic noise, to better describe and understand physical processus with high temporal resolution/low spatial resolution or the contrary.
Mattioni, Michele; Le Novère, Nicolas
2013-01-01
Neuron behavior results from the interplay between networks of biochemical processes and electrical signaling. Synaptic plasticity is one of the neuronal properties emerging from such an interaction. One of the current approaches to study plasticity is to model either its electrical aspects or its biochemical components. Among the chief reasons are the different time scales involved, electrical events happening in milliseconds while biochemical cascades respond in minutes or hours. In order to create multiscale models taking in consideration both aspects simultaneously, one needs to synchronize the two models, and exchange relevant variable values. We present a new event-driven algorithm to synchronize different neuronal models, which decreases computational time and avoids superfluous synchronizations. The algorithm is implemented in the TimeScales framework. We demonstrate its use by simulating a new multiscale model of the Medium Spiny Neuron of the Neostriatum. The model comprises over a thousand dendritic spines, where the electrical model interacts with the respective instances of a biochemical model. Our results show that a multiscale model is able to exhibit changes of synaptic plasticity as a result of the interaction between electrical and biochemical signaling. Our synchronization strategy is general enough to be used in simulations of other models with similar synchronization issues, such as networks of neurons. Moreover, the integration between the electrical and the biochemical models opens up the possibility to investigate multiscale process, like synaptic plasticity, in a more global manner, while taking into account a more realistic description of the underlying mechanisms. PMID:23843966
mRM - multiscale Routing Model for Scale-Independent Streamflow Simulations
NASA Astrophysics Data System (ADS)
Thober, Stephan; Kumar, Rohini; Samaniego, Luis; Mai, Juliane; Rakovec, Oldrich; Cuntz, Matthias
2016-04-01
Routing streamflow through a river network is a basic step within any distributed hydrologic model. It integrates the generated runoff and allows comparison with observed discharge at the outlet of a catchment. The Muskingum routing is a textbook river routing scheme that has been implemented in Earth System Models (e.g., WRF-HYDRO), stand-alone routing schemes (e.g., RAPID) , and hydrologic models (e.g., the mesoscale Hydrologic Model - mHM). Two types of implementations are mostly used. In the first one, the spatial routing resolution is fixed to that of the elevation model irrespective of the hydrologic modeling resolution. This implementation suffers from a high computational demand. In the second one, the spatial resolution is always applied at the hydrologic modelling resolution. This approach requires a scale-independent model behaviour which is often not evaluated. Here, we present the multiscale Routing Model (mRM) that provides a flexible choice of the routing resolution independent of the hydrologic modelling resolution. It incorporates a triangular unit hydrograph for overland flow routing and a Muskingum routing scheme for river routing. mRM provides a scale-independent model behaviour by exploiting the Multiscale Parameter Regionalisation (MPR) included in the open-source mHM (www.ufz.de/mhm). MPR reflects the structure of the landscape within the parametrisation of hydrologic processes. Effective model parameters are derived by upscaling of high-resolution (i.e., landscape resolution) parameters to the hydrologic modelling/routing resolution as proposed in Samaniego et al. 2010 and Kumar et al. 2013. mRM is coupled in this work to the state-of-the-art land surface model Noah-MP. Simulated streamflow is derived for the Ohio River (≈~525 000 km^2) during the period 1990-2000 at resolutions of 0.0625
A Multiscale Survival Process for Modeling Human Activity Patterns
Zhang, Tianyang; Cui, Peng; Song, Chaoming; Zhu, Wenwu; Yang, Shiqiang
2016-01-01
Human activity plays a central role in understanding large-scale social dynamics. It is well documented that individual activity pattern follows bursty dynamics characterized by heavy-tailed interevent time distributions. Here we study a large-scale online chatting dataset consisting of 5,549,570 users, finding that individual activity pattern varies with timescales whereas existing models only approximate empirical observations within a limited timescale. We propose a novel approach that models the intensity rate of an individual triggering an activity. We demonstrate that the model precisely captures corresponding human dynamics across multiple timescales over five orders of magnitudes. Our model also allows extracting the population heterogeneity of activity patterns, characterized by a set of individual-specific ingredients. Integrating our approach with social interactions leads to a wide range of implications. PMID:27023682
Multiscale analysis for a vector-borne epidemic model.
Souza, Max O
2014-04-01
Traditional studies about disease dynamics have focused on global stability issues, due to their epidemiological importance. We study a classical SIR-SI model for arboviruses in two different directions: we begin by describing an alternative proof of previously known global stability results by using only a Lyapunov approach. In the sequel, we take a different view and we argue that vectors and hosts can have very distinctive intrinsic time-scales, and that such distinctiveness extends to the disease dynamics. Under these hypothesis, we show that two asymptotic regimes naturally appear: the fast host dynamics and the fast vector dynamics. The former regime yields, at leading order, a SIR model for the hosts, but with a rational incidence rate. In this case, the vector disappears from the model, and the dynamics is similar to a directly contagious disease. The latter yields a SI model for the vectors, with the hosts disappearing from the model. Numerical results show the performance of the approximation, and a rigorous proof validates the reduced models.
Multiscale modelling of pharmaceutical powders: Macroscopic behaviour prediction
NASA Astrophysics Data System (ADS)
Loh, Jonathan; Ketterhagen, William; Elliott, James
2013-06-01
The pharmaceutical industry uses computer models at many stages during drug development. Quantum and molecular models are used to predict the crystal structures of potential active pharmaceutical ingredients (APIs), whereas discrete element models are used to optimise the mechanical properties of mixtures of APIs and excipient powders. The present work combines the strengths of modelling from all of the mentioned length scales to predict the behaviour of macroscopic powder granules from first principles using the molecular and crystal structures of acetazolamide as an example API. Starting with a single molecule of acetazolamide, ab initio self-consistent field calculations were used to calculate the equilibrium gas phase structure, vibrational spectra, interaction energy with water molecules and perform potential energy scans. By using these results and following the CHARMM General Force Field parameterisation process, all of the parameters required to perform a molecular dynamics simulation were iteratively determined using the CHARMM program. Next, by using crystallographic data from literature, the monoclinic and triclinic forms of the acetazolamide crystal were simulated. Material properties like the Young's modulus and Poisson ratio, and surface energies have been calculated. These material properties are then used as input parameters in a discrete element model containing Thornton's plastic model and the JKR cohesive force to predict the behaviour of macroscopic acetazolamide powder in angle of repose tests and tabletting simulations. Similar methodologies can be employed in the future to evaluate at an early stage the performance of novel APIs and excipients for tabletting applications.
Multiscale and multiresolution modeling of shales and their flow and morphological properties
Tahmasebi, Pejman; Javadpour, Farzam; Sahimi, Muhammad
2015-01-01
The need for more accessible energy resources makes shale formations increasingly important. Characterization of such low-permeability formations is complicated, due to the presence of multiscale features, and defies conventional methods. High-quality 3D imaging may be an ultimate solution for revealing the complexities of such porous media, but acquiring them is costly and time consuming. High-quality 2D images, on the other hand, are widely available. A novel three-step, multiscale, multiresolution reconstruction method is presented that directly uses 2D images in order to develop 3D models of shales. It uses a high-resolution 2D image representing the small-scale features to reproduce the nanopores and their network, a large scale, low-resolution 2D image to create the larger-scale characteristics, and generates stochastic realizations of the porous formation. The method is used to develop a model for a shale system for which the full 3D image is available and its properties can be computed. The predictions of the reconstructed models are in excellent agreement with the data. The method is, however, quite general and can be used for reconstructing models of other important heterogeneous materials and media. Two biological examples and from materials science are also reconstructed to demonstrate the generality of the method. PMID:26560178
Ghanbari, J; Naghdabadi, R
2009-07-22
We have used a hierarchical multiscale modeling scheme for the analysis of cortical bone considering it as a nanocomposite. This scheme consists of definition of two boundary value problems, one for macroscale, and another for microscale. The coupling between these scales is done by using the homogenization technique. At every material point in which the constitutive model is needed, a microscale boundary value problem is defined using a macroscopic kinematical quantity and solved. Using the described scheme, we have studied elastic properties of cortical bone considering its nanoscale microstructural constituents with various mineral volume fractions. Since the microstructure of bone consists of mineral platelet with nanometer size embedded in a protein matrix, it is similar to the microstructure of soft matrix nanocomposites reinforced with hard nanostructures. Considering a representative volume element (RVE) of the microstructure of bone as the microscale problem in our hierarchical multiscale modeling scheme, the global behavior of bone is obtained under various macroscopic loading conditions. This scheme may be suitable for modeling arbitrary bone geometries subjected to a variety of loading conditions. Using the presented method, mechanical properties of cortical bone including elastic moduli and Poisson's ratios in two major directions and shear modulus is obtained for different mineral volume fractions.
A multiscale approach to modeling formability of dual-phase steels
NASA Astrophysics Data System (ADS)
Srivastava, A.; Bower, A. F.; Hector, L. G., Jr.; Carsley, J. E.; Zhang, L.; Abu-Farha, F.
2016-02-01
A multiscale modeling approach is used to predict how the formability of dual-phase (DP) steels depend on the properties of their constituent phases and microstructure. First, the flow behavior of the steels is predicted using microstructure-based finite element simulations of their 3D representative volume elements, wherein the two phases (ferrite and martensite) are discretely modeled using crystal plasticity constitutive models. These results are then used to calibrate homogenized constitutive models which are then used in large-scale finite element simulations to compute the forming limit diagrams (FLDs). The multiscale approach is validated by predicting the FLDs of two commercial DP steels and comparing the predictions with experimental measurements. Subsequently, the approach is used to compute flow behavior and FLDs of a series of ‘virtual’ DP steels, constructed by varying the microstructural parameters in the commercial DP steels. The results of these computations suggest that combining the ferrite from one of the two commercial steels with the martensite of the other and optimizing the phase volume fractions can yield ‘virtual’ steels with substantially improved properties. These include a material with an FLD0 (plane strain) that exceeds those of the commercial steels by 75% without a degradation in strength; and a material with a flow strength (0.2% offset) that exceeds those of the commercial steels by ~30% without degradation of formability.
Multiscale modelling of solid tumour growth: the effect of collagen micromechanics
Wijeratne, Peter A.; Vavourakis, Vasileios; Hipwell, John H.; Voutouri, Chrysovalantis; Papageorgis, Panagiotis; Stylianopoulos, Triantafyllos; Evans, Andrew; Hawkes, David J.
2015-01-01
Here we introduce a model of solid tumour growth coupled with a multiscale biomechanical description of the tumour microenvironment, which facilitates the explicit simulation of fibre-fibre and tumour-fibre interactions. We hypothesise that such a model, which provides a purely mechanical description of tumour-host interactions, can be used to explain experimental observations of the effect of collagen micromechanics on solid tumour growth. The model was specified to mouse tumour data and numerical simulations were performed. The multiscale model produced lower stresses than an equivalent continuum-like approach, due to a more realistic remodelling of the collagen microstructure. Furthermore, solid tumour growth was found to cause a passive mechanical realignment of fibres at the tumour boundary from a random to a circumferential orientation. This is in accordance with experimental observations, thus demonstrating that such a response can be explained as purely mechanical. Finally, peritumoural fibre network anisotropy was found to produce anisotropic tumour morphology. The dependency of tumour morphology on the peritumoural microstructure was reduced by adding a load-bearing non-collagenous component to the fibre network constitutive equation. PMID:26564173
Multiscale and multiresolution modeling of shales and their flow and morphological properties.
Tahmasebi, Pejman; Javadpour, Farzam; Sahimi, Muhammad
2015-11-12
The need for more accessible energy resources makes shale formations increasingly important. Characterization of such low-permeability formations is complicated, due to the presence of multiscale features, and defies conventional methods. High-quality 3D imaging may be an ultimate solution for revealing the complexities of such porous media, but acquiring them is costly and time consuming. High-quality 2D images, on the other hand, are widely available. A novel three-step, multiscale, multiresolution reconstruction method is presented that directly uses 2D images in order to develop 3D models of shales. It uses a high-resolution 2D image representing the small-scale features to reproduce the nanopores and their network, a large scale, low-resolution 2D image to create the larger-scale characteristics, and generates stochastic realizations of the porous formation. The method is used to develop a model for a shale system for which the full 3D image is available and its properties can be computed. The predictions of the reconstructed models are in excellent agreement with the data. The method is, however, quite general and can be used for reconstructing models of other important heterogeneous materials and media. Two biological examples and from materials science are also reconstructed to demonstrate the generality of the method.
Multiscale sagebrush rangeland habitat modeling in southwest Wyoming
Homer, Collin G.; Aldridge, Cameron L.; Meyer, Debra K.; Coan, Michael J.; Bowen, Zachary H.
2009-01-01
Sagebrush-steppe ecosystems in North America have experienced dramatic elimination and degradation since European settlement. As a result, sagebrush-steppe dependent species have experienced drastic range contractions and population declines. Coordinated ecosystem-wide research, integrated with monitoring and management activities, would improve the ability to maintain existing sagebrush habitats. However, current data only identify resource availability locally, with rigorous spatial tools and models that accurately model and map sagebrush habitats over large areas still unavailable. Here we report on an effort to produce a rigorous large-area sagebrush-habitat classification and inventory with statistically validated products and estimates of precision in the State of Wyoming. This research employs a combination of significant new tools, including (1) modeling sagebrush rangeland as a series of independent continuous field components that can be combined and customized by any user at multiple spatial scales; (2) collecting ground-measured plot data on 2.4-meter imagery in the same season the satellite imagery is acquired; (3) effective modeling of ground-measured data on 2.4-meter imagery to maximize subsequent extrapolation; (4) acquiring multiple seasons (spring, summer, and fall) of an additional two spatial scales of imagery (30 meter and 56 meter) for optimal large-area modeling; (5) using regression tree classification technology that optimizes data mining of multiple image dates, ratios, and bands with ancillary data to extrapolate ground training data to coarser resolution sensors; and (6) employing rigorous accuracy assessment of model predictions to enable users to understand the inherent uncertainties. First-phase results modeled eight rangeland components (four primary targets and four secondary targets) as continuous field predictions. The primary targets included percent bare ground, percent herbaceousness, percent shrub, and percent litter. The
Probabilistic multi-scale modeling of pathogen dynamics in rivers
NASA Astrophysics Data System (ADS)
Packman, A. I.; Drummond, J. D.; Aubeneau, A. F.
2014-12-01
Most parameterizations of microbial dynamics and pathogen transport in surface waters rely on classic assumptions of advection-diffusion behavior in the water column and limited interactions between the water column and sediments. However, recent studies have shown that strong surface-subsurface interactions produce a wide range of transport timescales in rivers, and greatly the opportunity for long-term retention of pathogens in sediment beds and benthic biofilms. We present a stochastic model for pathogen dynamics, based on continuous-time random walk theory, that properly accounts for such diverse transport timescales, along with the remobilization and inactivation of pathogens in storage reservoirs. By representing pathogen dynamics probabilistically, the model framework enables diverse local-scale processes to be incorporated in system-scale models. We illustrate the application of the model to microbial dynamics in rivers based on the results of a tracer injection experiment. In-stream transport and surface-subsurface interactions are parameterized based on observations of conservative tracer transport, while E. coli retention and inactivation in sediments is parameterized based on direct local-scale experiments. The results indicate that sediments are an important reservoir of enteric organisms in rivers, and slow remobilization from sediments represents a long-term source of bacteria to streams. Current capability, potential advances, and limitations of this model framework for assessing pathogen transmission risks will be discussed. Because the transport model is probabilistic, it is amenable to incorporation into risk models, but a lack of characterization of key microbial processes in sediments and benthic biofilms hinders current application.
Barkaoui, Abdelwahed; Tlili, Brahim; Vercher-Martínez, Ana; Hambli, Ridha
2016-10-01
Bone is a living material with a complex hierarchical structure which entails exceptional mechanical properties, including high fracture toughness, specific stiffness and strength. Bone tissue is essentially composed by two phases distributed in approximately 30-70%: an organic phase (mainly type I collagen and cells) and an inorganic phase (hydroxyapatite-HA-and water). The nanostructure of bone can be represented throughout three scale levels where