Science.gov

Sample records for image-based multiscale modeling

  1. Topic Modelling for Object-Based Classification of Vhr Satellite Images Based on Multiscale Segmentations

    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.

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

    PubMed

    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 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. PMID:23794749

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

    SciTech Connect

    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.

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

    PubMed Central

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

    2012-01-01

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

  5. An automatic generation of non-uniform mesh for CFD analyses of image-based multiscale human airway models

    NASA Astrophysics Data System (ADS)

    Miyawaki, Shinjiro; Tawhai, Merryn H.; Hoffman, Eric A.; Lin, Ching-Long

    2014-11-01

    The authors have developed a method to automatically generate non-uniform CFD mesh for image-based human airway models. The sizes of generated tetrahedral elements vary in both radial and longitudinal directions to account for boundary layer and multiscale nature of pulmonary airflow. The proposed method takes advantage of our previously developed centerline-based geometry reconstruction method. In order to generate the mesh branch by branch in parallel, we used the open-source programs Gmsh and TetGen for surface and volume meshes, respectively. Both programs can specify element sizes by means of background mesh. The size of an arbitrary element in the domain is a function of wall distance, element size on the wall, and element size at the center of airway lumen. The element sizes on the wall are computed based on local flow rate and airway diameter. The total number of elements in the non-uniform mesh (10 M) was about half of that in the uniform mesh, although the computational time for the non-uniform mesh was about twice longer (170 min). The proposed method generates CFD meshes with fine elements near the wall and smooth variation of element size in longitudinal direction, which are required, e.g., for simulations with high flow rate. NIH Grants R01-HL094315, U01-HL114494, and S10-RR022421. Computer time provided by XSEDE.

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

    PubMed Central

    Tawhai, Merryn H; Hoffman, Eric A

    2013-01-01

    Improved understanding of structure and function relationships in the human lungs in individuals and sub-populations is fundamentally important to the future of pulmonary medicine. Image-based measures of the lungs can provide sensitive indicators of localized features, however to provide a better prediction of lung response to disease, treatment and environment, it is desirable to integrate quantifiable regional features from imaging with associated value-added high-level modeling. With this objective in mind, recent advances in computational fluid dynamics (CFD) of the bronchial airways - from a single bifurcation symmetric model to a multiscale image-based subject-specific lung model - will be reviewed. The interaction of CFD models with local parenchymal tissue expansion - assessed by image registration - allows new understanding of the interplay between environment, hot spots where inhaled aerosols could accumulate, and inflammation. To bridge ventilation function with image-derived central airway structure in CFD, an airway geometrical modeling method that spans from the model ‘entrance’ to the terminal bronchioles will be introduced. Finally, the effects of turbulent flows and CFD turbulence models on aerosol transport and deposition will be discussed. CFD simulation of airflow and particle transport in the human lung has been pursued by a number of research groups, whose interest has been in studying flow physics and airways resistance, improving drug delivery, or investigating which populations are most susceptible to inhaled pollutants. The three most important factors that need to be considered in airway CFD studies are lung structure, regional lung function, and flow characteristics. Their correct treatment is important because the transport of therapeutic or pollutant particles is dependent on the characteristics of the flow by which they are transported; and the airflow in the lungs is dependent on the geometry of the airways and how ventilation

  7. Multiscale Cancer Modeling

    PubMed Central

    Macklin, Paul; Cristini, Vittorio

    2013-01-01

    Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate predictions. A growing number of examples illustrate the value of this approach in providing quantitative insight on the initiation, progression, and treatment of cancer. In this review, we introduce the most recent and important multiscale cancer modeling works that have successfully established a mechanistic link between different biological scales. Biophysical, biochemical, and biomechanical factors are considered in these models. We also discuss innovative, cutting-edge modeling methods that are moving predictive multiscale cancer modeling toward clinical application. Furthermore, because the development of multiscale cancer models requires a new level of collaboration among scientists from a variety of fields such as biology, medicine, physics, mathematics, engineering, and computer science, an innovative Web-based infrastructure is needed to support this growing community. PMID:21529163

  8. Multiscale Segmentation of Polarimetric SAR Image Based on Srm Superpixels

    NASA Astrophysics Data System (ADS)

    Lang, F.; Yang, J.; Wu, L.; Li, D.

    2016-06-01

    Multi-scale segmentation of remote sensing image is more systematic and more convenient for the object-oriented image analysis compared to single-scale segmentation. However, the existing pixel-based polarimetric SAR (PolSAR) image multi-scale segmentation algorithms are usually inefficient and impractical. In this paper, we proposed a superpixel-based binary partition tree (BPT) segmentation algorithm by combining the generalized statistical region merging (GSRM) algorithm and the BPT algorithm. First, superpixels are obtained by setting a maximum region number threshold to GSRM. Then, the region merging process of the BPT algorithm is implemented based on superpixels but not pixels. The proposed algorithm inherits the advantages of both GSRM and BPT. The operation efficiency is obviously improved compared to the pixel-based BPT segmentation. Experiments using the Lband ESAR image over the Oberpfaffenhofen test site proved the effectiveness of the proposed method.

  9. Community Multiscale Air Quality Model

    EPA Science Inventory

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

  10. Multiscale modeling of chalcogenides

    NASA Astrophysics Data System (ADS)

    Mauro, John C.

    Chalcogenide glasses exhibit unique properties applicable to a wide range of fields, including electrical and optical switching and the transmission of infrared radiation. In this thesis, we adopt a hierarchical multiscale modeling approach to investigate the fundamental physics of chalcogenide systems. Our multiscale modeling begins in Part I at the quantum mechanical level, where we use the highly accurate Moller-Plesset perturbation technique to derive interaction potentials for elemental and heterogeneous chalcogenide systems. The resulting potentials consist of two-, three-, and effective four-body terms. In Part II, we use these ab initio potentials in classical Monte Carlo simulations to investigate the structure of chalcogenide glasses. We discuss our simulation results in relation to the Phillips model of topological constraints, which predicts critical behavior in chalcogenide systems as a function of average coordination number. Finally, in Part III we address the issue of glass transition range behavior. After reviewing previous models of the glass transition, we derive a new model based on nonequilibrium statistical mechanics and an energy landscape formalism. The new model requires as input a description of inherent structure energies and the transition energies between these structures. To address this issue, we derive an eigenvector-following technique for mapping a multidimensional potential energy landscape. This technique is then extended for application to enthalpy landscapes. Our model will enable the first-ever calculation of glass transition behavior based on only ab initio physics.

  11. 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.

  12. Adaptive multiscale model reduction with Generalized Multiscale Finite Element Methods

    NASA Astrophysics Data System (ADS)

    Chung, Eric; Efendiev, Yalchin; Hou, Thomas Y.

    2016-09-01

    In this paper, we discuss a general multiscale model reduction framework based on multiscale finite element methods. We give a brief overview of related multiscale methods. Due to page limitations, the overview focuses on a few related methods and is not intended to be comprehensive. We present a general adaptive multiscale model reduction framework, the Generalized Multiscale Finite Element Method. Besides the method's basic outline, we discuss some important ingredients needed for the method's success. We also discuss several applications. The proposed method allows performing local model reduction in the presence of high contrast and no scale separation.

  13. Image-Based Flow Modeling

    NASA Astrophysics Data System (ADS)

    Dillard, Seth; Mousel, John; Buchholz, James; Udaykumar, H. S.

    2009-11-01

    A preliminary method has been developed to model complex moving boundaries interacting with fluids in two dimensions using video files. Image segmentation techniques are employed to generate sharp object interfaces which are cast as level sets embedded in a Cartesian flow domain. In this way, boundary evolution is effected directly through imagery rather than by way of functional approximation. Videos of an American eel swimming in a water tunnel apparatus and a guinea pig duodenum undergoing peristaltic contractions in vitro serve as external and internal flow examples, which are evaluated for wake structure and mixing efficacy, respectively.

  14. MULTISCALE THERMOHYDROLOGIC MODEL

    SciTech Connect

    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.

  15. An improved fusion algorithm for infrared and visible images based on multi-scale transform

    NASA Astrophysics Data System (ADS)

    Li, He; Liu, Lei; Huang, Wei; Yue, Chao

    2016-01-01

    In this paper, an improved fusion algorithm for infrared and visible images based on multi-scale transform is proposed. First of all, Morphology-Hat transform is used for an infrared image and a visible image separately. Then two images were decomposed into high-frequency and low-frequency images by contourlet transform (CT). The fusion strategy of high-frequency images is based on mean gradient and the fusion strategy of low-frequency images is based on Principal Component Analysis (PCA). Finally, the final fused image is obtained by using the inverse contourlet transform (ICT). The experiments and results demonstrate that the proposed method can significantly improve image fusion performance, accomplish notable target information and high contrast and preserve rich details information at the same time.

  16. Multiscale Thermohydrologic Model

    SciTech Connect

    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

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

    NASA Astrophysics Data System (ADS)

    Arshadi, Amir

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

  18. MULTISCALE THERMOHYDROLOGIC MODEL

    SciTech Connect

    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

  19. Image-based modelling of organogenesis.

    PubMed

    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. PMID:26510443

  20. Differential Geometry Based Multiscale Models

    PubMed Central

    Wei, Guo-Wei

    2010-01-01

    Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atom-istic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier–Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson–Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson–Nernst–Planck equations that

  1. Multiscale Modeling of Recrystallization

    SciTech Connect

    Godfrey, A.W.; Holm, E.A.; Hughes, D.A.; Lesar, R.; Miodownik, M.A.

    1998-12-07

    We propose a multi length scale approach to modeling recrystallization which links a dislocation model, a cell growth model and a macroscopic model. Although this methodology and linking framework will be applied to recrystallization, it is also applicable to other types of phase transformations in bulk and layered materials. Critical processes such as the dislocation structure evolution, nucleation, the evolution of crystal orientations into a preferred texture, and grain size evolution all operate at different length scales. In this paper we focus on incorporating experimental measurements of dislocation substructures, rnisorientation measurements of dislocation boundaries, and dislocation simulations into a mesoscopic model of cell growth. In particular, we show how feeding information from the dislocation model into the cell growth model can create realistic initial microstructure.

  2. Automatic Method to Classify Images Based on Multiscale Fractal Descriptors and Paraconsistent Logic

    NASA Astrophysics Data System (ADS)

    Pavarino, E.; Neves, L. A.; Nascimento, M. Z.; Godoy, M. F.; Arruda, P. F.; Neto, D. S.

    2015-01-01

    In this study is presented an automatic method to classify images from fractal descriptors as decision rules, such as multiscale fractal dimension and lacunarity. The proposed methodology was divided in three steps: quantification of the regions of interest with fractal dimension and lacunarity, techniques under a multiscale approach; definition of reference patterns, which are the limits of each studied group; and, classification of each group, considering the combination of the reference patterns with signals maximization (an approach commonly considered in paraconsistent logic). The proposed method was used to classify histological prostatic images, aiming the diagnostic of prostate cancer. The accuracy levels were important, overcoming those obtained with Support Vector Machine (SVM) and Best- first Decicion Tree (BFTree) classifiers. The proposed approach allows recognize and classify patterns, offering the advantage of giving comprehensive results to the specialists.

  3. Towards a Multiscale Approach to Cybersecurity Modeling

    SciTech Connect

    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.

  4. Object-Oriented Change Detection for Remote Sensing Images Based on Multi-Scale Fusion

    NASA Astrophysics Data System (ADS)

    Feng, Wenqing; Sui, Haigang; Tu, Jihui

    2016-06-01

    In the process of object-oriented change detection, the determination of the optimal segmentation scale is directly related to the subsequent change information extraction and analysis. Aiming at this problem, this paper presents a novel object-level change detection method based on multi-scale segmentation and fusion. First of all, the fine to coarse segmentation is used to obtain initial objects of different sizes; then, according to the features of the objects, Change Vector Analysis is used to obtain the change detection results of various scales. Furthermore, in order to improve the accuracy of change detection, this paper introduces fuzzy fusion and two kinds of decision level fusion methods to get the results of multi-scale fusion. Based on these methods, experiments are done with SPOT5 multi-spectral remote sensing imagery. Compared with pixel-level change detection methods, the overall accuracy of our method has been improved by nearly 10%, and the experimental results prove the feasibility and effectiveness of the fusion strategies.

  5. A skull segmentation method for brain MR images based on multiscale bilateral filtering scheme

    NASA Astrophysics Data System (ADS)

    Yang, Xiaofeng; Fei, Baowei

    2010-03-01

    We present a novel automatic segmentation method for the skull on brain MR images for attenuation correction in combined PET/MRI applications. Our method transforms T1-weighted MR images to the Radon domain and then detects the feature of the skull. In the Radon domain we use a bilateral filter to construct a multiscale images series. For the repeated convolution we increase the spatial smoothing at each scale and make the cumulative width of the spatial and range Gaussian doubled at each scale. Two filters with different kernels along the vertical direction are applied along the scales from the coarse to fine levels. The results from a coarse scale give a mask for the next fine scale and supervise the segmentation in the next fine scale. The method is robust for noise MR images because of its multiscale bilateral filtering scheme. After combining the two filtered sinogram, the reciprocal binary sinogram of the skull is obtained for the reconstruction of the skull image. We use the filtered back projection method to reconstruct the segmented skull image. We define six metrics to evaluate our segmentation method. The method has been tested with brain phantom data, simulated brain data, and real MRI data. Evaluation results showed that our method is robust and accurate, which is useful for skull segmentation and subsequently for attenuation correction in combined PET/MRI applications.

  6. MULTISCALE MODELING OF POLYMER NANOCOMPOSITES

    SciTech Connect

    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.

  7. Metrics for image-based modeling of target acquisition

    NASA Astrophysics Data System (ADS)

    Fanning, Jonathan D.

    2012-06-01

    This paper presents an image-based system performance model. The image-based system model uses an image metric to compare a given degraded image of a target, as seen through the modeled system, to the set of possible targets in the target set. This is repeated for all possible targets to generate a confusion matrix. The confusion matrix is used to determine the probability of identifying a target from the target set when using a particular system in a particular set of conditions. The image metric used in the image-based model should correspond closely to human performance. The image-based model performance is compared to human perception data on Contrast Threshold Function (CTF) tests, naked eye Triangle Orientation Discrimination (TOD), and TOD including an infrared camera system. Image-based system performance modeling is useful because it allows modeling of arbitrary image processing. Modern camera systems include more complex image processing, much of which is nonlinear. Existing linear system models, such as the TTP metric model implemented in NVESD models such as NV-IPM, assume that the entire system is linear and shift invariant (LSI). The LSI assumption makes modeling nonlinear processes difficult, such as local area processing/contrast enhancement (LAP/LACE), turbulence reduction, and image fusion.

  8. Multiscale Modeling of Hematologic Disorders

    SciTech Connect

    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.

  9. Feature and Contrast Enhancement of Mammographic Image Based on Multiscale Analysis and Morphology

    PubMed Central

    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

  10. Multiscale modelling in immunology: a review.

    PubMed

    Cappuccio, Antonio; Tieri, Paolo; Castiglione, Filippo

    2016-05-01

    One of the greatest challenges in biomedicine is to get a unified view of observations made from the molecular up to the organism scale. Towards this goal, multiscale models have been highly instrumental in contexts such as the cardiovascular field, angiogenesis, neurosciences and tumour biology. More recently, such models are becoming an increasingly important resource to address immunological questions as well. Systematic mining of the literature in multiscale modelling led us to identify three main fields of immunological applications: host-virus interactions, inflammatory diseases and their treatment and development of multiscale simulation platforms for immunological research and for educational purposes. Here, we review the current developments in these directions, which illustrate that multiscale models can consistently integrate immunological data generated at several scales, and can be used to describe and optimize therapeutic treatments of complex immune diseases. PMID:25810307

  11. 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.

  12. A framework for multi-scale modelling

    PubMed Central

    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

  13. Image-based modeling of lung structure and function

    PubMed Central

    Tawhai, Merryn H.; Lin, Ching-Long

    2010-01-01

    Current state-of-the-art in image-based modeling allows derivation of patient-specific models of the lung, lobes, airways, and pulmonary vascular trees. The application of traditional engineering analyses of fluid and structural mechanics to image-based subject-specific models has the potential to provide new insight into structure-function relationships in the individual via functional interpretation that complements imaging and experimental studies. Three major issues that are encountered in studies of air flow through the bronchial airways are the representation of airway geometry, the imposition of physiological boundary conditions, and the treatment of turbulence. Here we review some efforts to resolve each of these issues, with particular focus on image-based models that have been developed to simulate air flow from the mouth to the terminal bronchiole, and subjected to physiologically meaningful boundary conditions via image registration and soft tissue mechanics models. PMID:21105146

  14. 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.

  15. Multiscale Modeling of Cortical Neural Networks

    NASA Astrophysics Data System (ADS)

    Torben-Nielsen, Benjamin; Stiefel, Klaus M.

    2009-09-01

    In this study, we describe efforts at modeling the electrophysiological dynamics of cortical networks in a multi-scale manner. Specifically, we describe the implementation of a network model composed of simple single-compartmental neuron models, in which a single complex multi-compartmental model of a pyramidal neuron is embedded. The network is capable of generating Δ (2 Hz, observed during deep sleep states) and γ (40 Hz, observed during wakefulness) oscillations, which are then imposed onto the multi-compartmental model, thus providing realistic, dynamic boundary conditions. We furthermore discuss the challenges and chances involved in multi-scale modeling of neural function.

  16. Multiscale Computational Models of Complex Biological Systems

    PubMed Central

    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

  17. A bidirectional coupling procedure applied to multiscale respiratory modeling

    NASA Astrophysics Data System (ADS)

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

    2013-07-01

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

  18. A Bidirectional Coupling Procedure Applied to Multiscale Respiratory Modeling.

    PubMed

    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

  19. A Bidirectional Coupling Procedure Applied to Multiscale Respiratory Modeling

    SciTech Connect

    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

  20. A bidirectional coupling procedure applied to multiscale respiratory modeling

    SciTech Connect

    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

  1. Multiscale Modeling of Plastic Bonded Explosives

    NASA Astrophysics Data System (ADS)

    Smith, Grant; Bedrov, Dmitry; Borodin, Oleg

    2007-06-01

    We have developed a multiscale modeling paradigm for the prediction of the viscoelastic properties, equation of state and yielding behavior of plastic bonded explosives (PBXs). In our multiscale modeling approach the components of the explosive (e.g., energetic material, metal and binder) are explicitly resolved and the material point method (MPM) is utilized to predict the response of the composite material to loading (isentropic, shock, etc.). This data are then utilized to develop equation-of-state and constitutive models for the PBX. The properties of the components are determined either from atomistic simulations or are taken from the literature. Force fields for the atomistic simulations in turn have been developed based upon high-level electronic structure calculations of model compounds and molecular complexes. Hence, our multiscale simulation approach systematically bridges length scales from atomistic to macroscopic. Applications of this approach to PBX-9501 and other PBXs will be considered.

  2. 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

  3. 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

  4. A multiscale modeling approach to adhesive contact

    NASA Astrophysics Data System (ADS)

    Fan, KangQi; Wang, WeiDong; Zhu, YingMin; Zhang, XiuYan

    2011-09-01

    In order to model the adhesive contact across different length scales, a multiscale approach is developed and used to study the adhesive contact behaviors between a rigid cylinder and an elastic face-centered cubic (FCC) substrate. The approach combines an atomistic treatment of the interfacial region with an elastic mechanics method description of the continuum region. The two regions are connected by a coupling region where nodes of the continuum region are refined to atoms of the atomistic region. Moreover, the elastic constants of FCC crystals are obtained directly from the Lennard-Jones potential to describe the elastic response characteristics of the continuum region, which ensures the consistency of material proprieties between atomistic and continuum regions. The multiscale approach is examined by comparing it with the pure MD simulation, and the results indicate that the multiscale modeling approach agrees well with the MD method in studying the adhesive contact behaviors.

  5. 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.

  6. Towards multiscale modeling of influenza infection

    PubMed Central

    Murillo, Lisa N.; Murillo, Michael S.; Perelson, Alan S.

    2013-01-01

    Aided by recent advances in computational power, algorithms, and higher fidelity data, increasingly detailed theoretical models of infection with influenza A virus are being developed. We review single scale models as they describe influenza infection from intracellular to global scales, and, in particular, we consider those models that capture details specific to influenza and can be used to link different scales. We discuss the few multiscale models of influenza infection that have been developed in this emerging field. In addition to discussing modeling approaches, we also survey biological data on influenza infection and transmission that is relevant for constructing influenza infection models. We envision that, in the future, multiscale models that capitalize on technical advances in experimental biology and high performance computing could be used to describe the large spatial scale epidemiology of influenza infection, evolution of the virus, and transmission between hosts more accurately. PMID:23608630

  7. Multiscale modeling of mucosal immune responses

    PubMed Central

    2015-01-01

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

  8. 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.

  9. Multiscale modelling of hydraulic conductivity in vuggy porous media

    PubMed Central

    Daly, K. R.; Roose, T.

    2014-01-01

    Flow in both saturated and non-saturated vuggy porous media, i.e. soil, is inherently multiscale. The complex microporous structure of the soil aggregates and the wider vugs provides a multitude of flow pathways and has received significant attention from the X-ray computed tomography (CT) community with a constant drive to image at higher resolution. Using multiscale homogenization, we derive averaged equations to study the effects of the microscale structure on the macroscopic flow. The averaged model captures the underlying geometry through a series of cell problems and is verified through direct comparison to numerical simulations of the full structure. These methods offer significant reductions in computation time and allow us to perform three-dimensional calculations with complex geometries on a desktop PC. The results show that the surface roughness of the aggregate has a significantly greater effect on the flow than the microstructure within the aggregate. Hence, this is the region in which the resolution of X-ray CT for image-based modelling has the greatest impact. PMID:24511248

  10. 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.

  11. Stochastic multiscale model for carbonate rocks.

    PubMed

    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. PMID:17677251

  12. Concurrent Multiscale Modeling of Embedded Nanomechanics

    SciTech Connect

    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.

  13. Digital marbling: a multiscale fluid model.

    PubMed

    Acar, Rüyam; Boulanger, Pierre

    2006-01-01

    This paper presents a multiscale fluid model based on mesoscale dynamics and viscous fluid equations as a generic tool for digital marbling purposes. The model uses an averaging technique on the adaptation of a stochastic mesoscale model to obtain the effect of fluctuations at different levels. It allows various user controls to simulate complex flow behaviors as in traditional marbling techniques, as well as laminar and turbulent flows. Material transport is based on an improved advection solution to be able to match the highly detailed, sharp fluid interfaces in marbling patterns. In the transport model, two reaction models are introduced to create different effects and to simulate density fluctuations. PMID:16805267

  14. The Lung Physiome: merging imaging-based measures with predictive computational models of structure and function

    PubMed Central

    Tawhai, Merryn H; Hoffman, Eric A; Lin, Ching-Long

    2009-01-01

    Global measurements of the lung provided by standard pulmonary function tests do not give insight into the regional basis of lung function and lung disease. Advances in imaging methodologies, computer technologies, and subject-specific simulations are creating new opportunities for studying structure-function relationships in the lung through multi-disciplinary research. The digital Human Lung Atlas is an imaging-based resource compiled from male and female subjects spanning several decades of age. The Atlas comprises both structural and functional measures, and includes computational models derived to match individual subjects for personalized prediction of function. The computational models in the Atlas form part of the Lung Physiome project, which is an international effort to develop integrative models of lung function at all levels of biological organization. The computational models provide mechanistic interpretation of imaging measures; the Atlas provides structural data upon which to base model geometry, and functional data against which to test hypotheses. The example of simulating air flow on a subject-specific basis is considered. Methods for deriving multi-scale models of the airway geometry for individual subjects in the Atlas are outlined, and methods for modeling turbulent flows in the airway are reviewed. PMID:20835982

  15. Quantum Mechanics Based Multiscale Modeling of Materials

    NASA Astrophysics Data System (ADS)

    Lu, Gang

    2013-03-01

    We present two quantum mechanics based multiscale approaches that can simulate extended defects in metals accurately and efficiently. The first approach (QCDFT) can treat multimillion atoms effectively via density functional theory (DFT). The method is an extension of the original quasicontinuum approach with DFT as its sole energetic formulation. The second method (QM/MM) has to do with quantum mechanics/molecular mechanics coupling based on the constrained density functional theory, which provides an exact framework for a self-consistent quantum mechanical embedding. Several important materials problems will be addressed using the multiscale modeling approaches, including hydrogen-assisted cracking in Al, magnetism-controlled dislocation properties in Fe and Si pipe diffusion along Al dislocation core. We acknowledge the support from the Office of Navel Research and the Army Research Office.

  16. 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.

  17. Image-based modeling of the human eye.

    PubMed

    François, Guillaume; Gautron, Pascal; Breton, Gaspard; Bouatouch, Kadi

    2009-01-01

    Rendering realistic organic materials is a challenging issue. The human eye is an important part of nonverbal communication which, consequently, requires specific modeling and rendering techniques to enhance the realism of virtual characters. We propose an image-based method for estimating both iris morphology and scattering features in order to generate convincing images of virtual eyes. In this regard, we develop a technique to unrefract iris photographs. We model the morphology of the human iris as an irregular multilayered tissue. We then approximate the scattering features of the captured iris. Finally, we propose a real-time rendering technique based on the subsurface texture mapping representation and introduce a precomputed refraction function as well as a caustic function, which accounts for the light interactions at the corneal interface. PMID:19590107

  18. Functional derivatives for multi-scale modeling

    NASA Astrophysics Data System (ADS)

    Reeve, Samuel; Strachan, Alejandro

    2015-03-01

    As we look beyond petascale computing and towards the exascale, effectively utilizing computational resources by using multi-fidelity and multi-scale materials simulations becomes increasingly important. Determining when and where to run high-fidelity simulations in order to have the most effect on a given quantity of interest (QoI) is a difficult problem. This work utilizes functional uncertainty quantification (UQ) for this task. While most UQ focuses on uncertainty in output from uncertainty in input parameters, we focus on uncertainty from the function itself (e.g. from using a specific functional form for an interatomic potential or constitutive law). In the case of a multi-scale simulation with a given constitutive law, calculating the functional derivative of the QoI with respect to that constitutive law can determine where a fine-scale model evaluation will maximize the increase in accuracy of the predicted QoI. Additionally, for a given computational budget the optimal set of coarse and fine-scale simulations can be determined. Numerical calculation of the functional derivative has been developed and methods of including this work within existing multi-fidelity and multi-scale orchestrators are explored.

  19. Multiscale modeling with smoothed dissipative particle dynamics.

    PubMed

    Kulkarni, Pandurang M; Fu, Chia-Chun; Shell, M Scott; Leal, L Gary

    2013-06-21

    In this work, we consider two issues related to the use of Smoothed Dissipative Particle Dynamics (SDPD) as an intermediate mesoscale model in a multiscale scheme for solution of flow problems when there are local parts of a macroscopic domain that require molecular resolution. The first is to demonstrate that SDPD with different levels of resolution can accurately represent the fluid properties from the continuum scale all the way to the molecular scale. Specifically, while the thermodynamic quantities such as temperature, pressure, and average density remain scale-invariant, we demonstrate that the dynamic properties are quantitatively consistent with an all-atom Lennard-Jones reference system when the SDPD resolution approaches the atomistic scale. This supports the idea that SDPD can serve as a natural bridge between molecular and continuum descriptions. In the second part, a simple multiscale methodology is proposed within the SDPD framework that allows several levels of resolution within a single domain. Each particle is characterized by a unique physical length scale called the smoothing length, which is inversely related to the local number density and can change on-the-fly. This multiscale methodology is shown to accurately reproduce fluid properties for the simple problem of steady and transient shear flow. PMID:23802949

  20. 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.

  1. Multiscale Gaussian network model (mGNM) and multiscale anisotropic network model (mANM).

    PubMed

    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. PMID:26627949

  2. Multiscale Modeling of Phase Transformations in Steels

    NASA Astrophysics Data System (ADS)

    Militzer, M.; Hoyt, J. J.; Provatas, N.; Rottler, J.; Sinclair, C. W.; Zurob, H. S.

    2014-05-01

    Multiscale modeling tools have great potential to aid the development of new steels and processing routes. Currently, industrial process models are at least in part based on empirical material parameters to describe microstructure evolution and the resulting material properties. Modeling across different length and time scales is a promising approach to develop next-generation process models with enhanced predictive capabilities for the role of alloying elements. The status and challenges of this multiscale modeling approach are discussed for microstructure evolution in advanced low-carbon steels. First-principle simulations of solute segregation to a grain boundary and an austenite-ferrite interface in iron confirm trends of important alloying elements (e.g., Nb, Mo, and Mn) on grain growth, recrystallization, and phase transformation in steels. In particular, the linkage among atomistic simulations, phase-field modeling, and classic diffusion models is illustrated for the effects of solute drag on the austenite-to-ferrite transformation as observed in dedicated experimental studies for iron model alloys and commercial steels.

  3. Image-Based Predictive Modeling of Heart Mechanics.

    PubMed

    Wang, V Y; Nielsen, P M F; Nash, M P

    2015-01-01

    Personalized biophysical modeling of the heart is a useful approach for noninvasively analyzing and predicting in vivo cardiac mechanics. Three main developments support this style of analysis: state-of-the-art cardiac imaging technologies, modern computational infrastructure, and advanced mathematical modeling techniques. In vivo measurements of cardiac structure and function can be integrated using sophisticated computational methods to investigate mechanisms of myocardial function and dysfunction, and can aid in clinical diagnosis and developing personalized treatment. In this article, we review the state-of-the-art in cardiac imaging modalities, model-based interpretation of 3D images of cardiac structure and function, and recent advances in modeling that allow personalized predictions of heart mechanics. We discuss how using such image-based modeling frameworks can increase the understanding of the fundamental biophysics behind cardiac mechanics, and assist with diagnosis, surgical guidance, and treatment planning. Addressing the challenges in this field will require a coordinated effort from both the clinical-imaging and modeling communities. We also discuss future directions that can be taken to bridge the gap between basic science and clinical translation. PMID:26643023

  4. Multiscale tumor spatiokinetic model for intraperitoneal therapy.

    PubMed

    Au, Jessie L-S; Guo, Peng; Gao, Yue; Lu, Ze; Wientjes, Michael G; Tsai, Max; Wientjes, M Guillaume

    2014-05-01

    This study established a multiscale computational model for intraperitoneal (IP) chemotherapy, to depict the time-dependent and spatial-dependent drug concentrations in peritoneal tumors as functions of drug properties (size, binding, diffusivity, permeability), transport mechanisms (diffusion, convection), spatial-dependent tumor heterogeneities (vessel density, cell density, pressure gradient), and physiological properties (peritoneal pressure, peritoneal fluid volume). Equations linked drug transport and clearance on three scales (tumor, IP cavity, whole organism). Paclitaxel was the test compound. The required model parameters (tumor diffusivity, tumor hydraulic conductivity, vessel permeability and surface area, microvascular hydrostatic pressure, drug association with cells) were obtained from literature reports, calculation, and/or experimental measurements. Drug concentration-time profiles in peritoneal fluid and plasma were the boundary conditions for tumor domain and blood vessels, respectively. The finite element method was used to numerically solve the nonlinear partial differential equations for fluid and solute transport. The resulting multiscale model accounted for intratumoral spatial heterogeneity, depicted diffusive and convective drug transport in tumor interstitium and across blood vessels, and provided drug flux and concentration as a function of time and spatial position in the tumor. Comparison of model-predicted tumor spatiokinetics with experimental results (autoradiographic data of 3H-paclitaxel in IP ovarian tumors in mice, 6 h posttreatment) showed good agreement (1% deviation for area under curve and 23% deviations for individual data points, which were several-fold lower compared to the experimental intertumor variations). The computational multiscale model provides a tool to quantify the effects of drug-, tumor-, and host-dependent variables on the concentrations and residence time of IP therapeutics in tumors. PMID:24570339

  5. Multiscale modeling of polymer rheology.

    PubMed

    De, Subhranil; Fish, Jacob; Shephard, Mark S; Keblinski, Pawel; Kumar, Sanat K

    2006-09-01

    We propose a simulation method which can be used to readily parallelize simulations on systems with a large spatial extent. We simulate small parts of the system with independent molecular dynamics simulations, and only occasionally pass information between them through a constitutive model free continuum approach. We illustrate the power of this method in the case of a polymeric fluid undergoing rapid one-dimensional shear flow. Since we show that this flow problem cannot be modeled by using a steady-state constitutive model, this method offers the unique capability for accessing the nonlinear viscoelasticity of complex fluids. PMID:17025582

  6. Multiscale Stochastic Simulation and Modeling

    SciTech Connect

    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.

  7. Multiscale Modeling with Carbon Nanotubes

    SciTech Connect

    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.

  8. 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

  9. Multiscale modeling of magnetospheric reconnection

    NASA Astrophysics Data System (ADS)

    Kuznetsova, M. M.; Hesse, M.; RastäTter, L.; Taktakishvili, A.; Toth, G.; de Zeeuw, D. L.; Ridley, A.; Gombosi, T. I.

    2007-10-01

    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 use the global MHD code BATS-R-US and replace an ad hoc anomalous resistivity often employed by global MHD models with a physically motivated dissipation model. The primary kinetic mechanism controlling the dissipation in the diffusion region in the vicinity of the reconnection site is incorporated into the MHD description in terms of nongyrotropic corrections to the induction equation. We developed an algorithm to search for reconnection sites in north-south symmetric magnetotail. Spatial scales of the diffusion region and magnitude of the reconnection electric field are calculated consistently using local MHD plasma and field parameters. The locations of the reconnection sites are constantly updated during the simulations. To clarify the role of nongyrotropic effects in the diffusion region on the global magnetospheric dynamics, we perform simulations with steady southward interplanetary magnetic field driving of the magnetosphere. Ideal MHD simulations with magnetic reconnection supported by numerical resistivity often produce quasi-steady configuration with almost stationary near-Earth neutral line (NENL). Simulations with nongyrotropic corrections demonstrate dynamic quasi-periodic response to the steady driving conditions. Fast magnetotail reconnection supported by nongyrotropic effects results in tailward retreat of the reconnection site with average speed of the order of 100 km/s followed by a formation of a new NENL in the near-Earth thin current sheet. This approach allowed to model for the first time loading/unloading cycle frequently observed during extended periods of steady low-mach-number solar wind with southward interplanetary magnetic field.

  10. Multiscale Modeling of Molecular Magnets

    SciTech Connect

    Ramasesha, S.; Raghunathan, Rajamani

    2007-11-29

    Here, we present an overview of methods of modeling Molecular Magnets in different length scales. First, we discuss a microscopic model to understand the nature of superexchange interaction in binuclear transition metal complexes of different geometry viz. A-B, A-B-A, B-A-B, linear A-B-A-B, and cyclic A-B-A-B systems. We obtain the quantum phase diagrams along various planes in the parameter space and identify the various model parameters which control the nature of superexchange in these systems. We also obtain contours of effective superexchange constants. In the next section we discuss the method of full symmetry adaptation in Valence Bond method to obtain the low-lying eigenstates of the Heisenberg spin Hamiltonian of large systems. The third part of this article deals with the calculation of the magnetic anisotropy parameters (D{sub M} and E{sub M}) of Single Molecule Magnets (SMMs). We use the single ion anisotropy values to obtain D{sub M} and E{sub M} values of the SMM, using a perturbative approach. We first solve the unperturbed Hamiltonian which is a simple spin Heisenberg Hamiltonian. Then we introduce the perturbing term H{sub 1} consisting of the single ion anisotropy. We then solve for the molecular anisotropy parameters by equating two different ways for computing the matrix elements of the perturbation term, from knowledge of the spin-spin correlation functions and the direction of orientation of the single ion anisotropies.

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

    SciTech Connect

    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

  12. Institute for Multiscale Modeling of Biological Interactions

    SciTech Connect

    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.

  13. Multiscale Model of Swarming Bacteria

    NASA Astrophysics Data System (ADS)

    Alber, Mark

    2011-03-01

    Many bacteria can rapidly traverse surfaces from which they are extracting nutrient for growth. They generate flat, spreading colonies, called swarms because they resemble swarms of insects. In the beginning of the talk, swarms of the M. xanthus will be described in detail. Individual M. xanthus cells are elongated; they always move in the direction of their long axis; and they are in constant motion, repeatedly touching each other. As a cell glides, the slime capsule of a cell interacts with the bare agar surface, non-oriented slime which arises from the surface contact with the slime capsule, or oriented slime trails. Remarkably, cells regularly reverse their gliding directions. In this talk a detailed cell- and behavior-based computational model of M. xanthus swarming will be used to demonstrate that reversals of gliding direction and cell bending are essential for swarming and that specific reversal frequencies result in optimal swarming rate of the whole population. This suggests that the circuit regulating reversals evolved to its current sensitivity under selection for growth achieved by swarming.

  14. Variational multiscale models for charge transport

    PubMed Central

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

    2012-01-01

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

  15. Multiscale Models in the Biomechanics of Plant Growth

    PubMed Central

    Fozard, John A.

    2015-01-01

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

  16. Multiscale Model Describing Bacterial Adhesion and Detachment.

    PubMed

    Ostvar, Sassan; Wood, Brian D

    2016-05-24

    Bacterial surfaces are complex structures with nontrivial adhesive properties. The physics of bacterial adhesion deviates from that of ideal colloids as a result of cell-surface roughness and because of the mechanical properties of the polymers covering the cell surface. In the present study, we develop a simple multiscale model for the interplay between the potential energy functions that characterize the cell surface biopolymers and their interaction with the extracellular environment. We then use the model to study a discrete network of bonds in the presence of significant length heterogeneities in cell-surface polymers. The model we present is able to generate force curves (both approach and retraction) that closely resemble those measured experimentally. Our results show that even small-length-scale heterogeneities can lead to macroscopically nonlinear behavior that is qualitatively and quantitatively different from the homogeneous case. We also report on the energetic consequences of such structural heterogeneity. PMID:27129780

  17. Multiscale measurement error models for aggregated small area health data.

    PubMed

    Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin

    2016-08-01

    Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates. PMID:27566773

  18. Multiscale agent-based consumer market modeling.

    SciTech Connect

    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.

  19. 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+.

  20. Novel Multiscale Modeling Tool Applied to Pseudomonas aeruginosa Biofilm Formation

    PubMed Central

    Biggs, Matthew B.; Papin, Jason A.

    2013-01-01

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

  1. MSCALE: A General Utility for Multiscale Modeling

    PubMed Central

    Woodcock, H. Lee; Miller, Benjamin T.; Hodoscek, Milan; Okur, Asim; Larkin, Joseph D.; Ponder, Jay W.; Brooks, Bernard R.

    2011-01-01

    The combination of theoretical models of macromolecules that exist at different spatial and temporal scales has become increasingly important for addressing complex biochemical problems. This work describes the extension of concurrent multiscale approaches, introduces a general framework for carrying out calculations, and describes its implementation into the CHARMM macromolecular modeling package. This functionality, termed MSCALE, generalizes both the additive and subtractive multiscale scheme (e.g. QM/MM ONIOM-type), and extends its support to classical force fields, coarse grained modeling (e.g. ENM, GNM, etc.), and a mixture of them all. The MSCALE scheme is completely parallelized with each subsystem running as an independent, but connected calculation. One of the most attractive features of MSCALE is the relative ease of implementation using the standard MPI communication protocol. This allows external access to the framework and facilitates the combination of functionality previously isolated in separate programs. This new facility is fully integrated with free energy perturbation methods, Hessian based methods, and the use of periodicity and symmetry, which allows the calculation of accurate pressures. We demonstrate the utility of this new technique with four examples; (1) subtractive QM/MM and QM/QM calculations; (2) multi-force field alchemical free energy perturbation; (3) integration with the SANDER module of AMBER and the TINKER package to gain access to potentials not available in CHARMM; and (4) mixed resolution (i.e. coarse grain / all-atom) normal mode analysis. The potential of this new tool is clearly established and in conclusion an interesting mathematical problem is highlighted and future improvements are proposed. PMID:21691425

  2. 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.

  3. An approach to multiscale modelling with graph grammars

    PubMed Central

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

    2014-01-01

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

  4. Multiscale modeling of integrated CCS systems

    NASA Astrophysics Data System (ADS)

    Alhajaj, Ahmed; Shah, Nilay

    2015-01-01

    The world will continue consuming fossil fuel within the coming decades to meet its growing energy demand; however, this source must be cleaner through implementation of carbon capture, transport and storage (CCTS). This process is complex and involves multiple phases, owned by different operational companies and stakeholders with different business models and regulatory framework. The objective of this work is to develop a multiscale modeling approach to link process models, post-combustion capture plant model and network design models under an optimization framework in order to design and analyse the cost optimal CO2 infrastructure that match CO2 sources and sinks in capacity and time. The network comprises a number of CO2 sources at fixed locations and a number of potential CO2 storage sites. The decisions to be determined include from which sources it is appropriate to capture CO2 and the cost-optimal degree-of-capture (DOC) for a given source and the infrastructural layout of the CO2 transmission network.

  5. Integrating Multiscale Modeling with Drug Effects for Cancer Treatment

    PubMed Central

    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

  6. Structurally governed cell mechanotransduction through multiscale modeling.

    PubMed

    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

  7. Modelling approaches for evaluating multiscale tendon mechanics.

    PubMed

    Fang, Fei; Lake, Spencer P

    2016-02-01

    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

  8. 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)

  9. A computational library for multiscale modeling of material failure

    NASA Astrophysics Data System (ADS)

    Talebi, Hossein; Silani, Mohammad; Bordas, Stéphane P. A.; Kerfriden, Pierre; Rabczuk, Timon

    2014-05-01

    We present an open-source software framework called PERMIX for multiscale modeling and simulation of fracture in solids. The framework is an object oriented open-source effort written primarily in Fortran 2003 standard with Fortran/C++ interfaces to a number of other libraries such as LAMMPS, ABAQUS, LS-DYNA and GMSH. Fracture on the continuum level is modeled by the extended finite element method (XFEM). Using several novel or state of the art methods, the piece software handles semi-concurrent multiscale methods as well as concurrent multiscale methods for fracture, coupling two continuum domains or atomistic domains to continuum domains, respectively. The efficiency of our open-source software is shown through several simulations including a 3D crack modeling in clay nanocomposites, a semi-concurrent FE-FE coupling, a 3D Arlequin multiscale example and an MD-XFEM coupling for dynamic crack propagation.

  10. Multiscale Modeling of Cardiac Cellular Energetics

    PubMed Central

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

    2010-01-01

    Multiscale modeling is essential to integrating knowledge of human physiology starting from genomics, molecular biology, and the environment through the levels of cells, tissues, and organs all the way to integrated systems behavior. The lowest levels concern biophysical and biochemical events. The higher levels of organization in tissues, organs, and organism are complex, representing the dynamically varying behavior of billions of cells interacting together. Models integrating cellular events into tissue and organ behavior are forced to resort to simplifications to minimize computational complexity, thus reducing the model’s ability to respond correctly to dynamic changes in external conditions. Adjustments at protein and gene regulatory levels shortchange the simplified higher-level representations. Our cell primitive is composed of a set of subcellular modules, each defining an intracellular function (action potential, tricarboxylic acid cycle, oxidative phosphorylation, glycolysis, calcium cycling, contraction, etc.), composing what we call the “eternal cell,” which assumes that there is neither proteolysis nor protein synthesis. Within the modules are elements describing each particular component (i.e., enzymatic reactions of assorted types, transporters, ionic channels, binding sites, etc.). Cell subregions are stirred tanks, linked by diffusional or transporter-mediated exchange. The modeling uses ordinary differential equations rather than stochastic or partial differential equations. This basic model is regarded as a primitive upon which to build models encompassing gene regulation, signaling, and long-term adaptations in structure and function. During simulation, simpler forms of the model are used, when possible, to reduce computation. However, when this results in error, the more complex and detailed modules and elements need to be employed to improve model realism. The processes of error recognition and of mapping between different levels of

  11. Multiscale Concrete Modeling of Aging Degradation

    SciTech Connect

    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].

  12. Multiscale mechanobiology modeling for surgery assessment

    NASA Astrophysics Data System (ADS)

    Garbey, M.; Bass, B. L.; Berceli, S.

    2012-08-01

    This paper discusses some of the concept of modeling surgery outcome. It is also an attempt to offer a road map for progress. This paper may serve as a common ground of discussion for both communities i.e surgeons and computational scientist in its broadest sense. Predicting surgery outcome is a very difficult task. All patients are different, and multiple factors such as genetic, or environment conditions plays a role. The difficulty is to construct models that are complex enough to address some of these significant multiscale elements and simple enough to be used in clinical conditions and calibrated on patient data. We will provide a multilevel progressive approach inspired by two applications in surgery that we have been working on. One is about vein graft adaptation after a transplantation, the other is the recovery of cosmesis outcome after a breast lumpectomy. This work, that is still very much in progress, may teach us some lessons. We are convinced that the digital revolution that is transforming the working environment of the surgeon makes closer collaboration between surgeons and computational scientist unavoidable. We believe that "computational surgery" will allow the community to develop predictive model of the surgery outcome and greatprogresses in surgery procedures that goes far beyond the operating room procedural aspect.

  13. Multiscale modeling of polyisoprene on graphite

    SciTech Connect

    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.

  14. Toward a Multiscale Approach for Geodynamo Models

    NASA Astrophysics Data System (ADS)

    Marcotte, F.; Dormy, E.

    2014-12-01

    The generation of the Earth's magnetic field by dynamo action in the liquid iron core is modeled by a large set of coupled, non-linear partial differential equations. Numerical models presently involve direct discretization of the geodynamo equations and allow to produce axial dipolar magnetic fields that are qualitatively comparable to the Earth's one, but whose dynamics remain considerably remote from the geophysical regime. Indeed, due to the extreme values of the dimensionless numbers characterizing the Earth's core dynamics, the relevant regime remains far beyond the reach of direct numerical simulation - so far that one cannot simply rely on the increase in computational power. Simplification of the governing equations is not straightforward. In particular, the importance of return flow from the thin Ekman layers located at the inner core and core-mantle boundaries into the main flow prevents one from purely suppressing the viscous dissipation term in Navier-Stokes equation even in the limiting case where inertia is neglected. Therefore more advanced models are needed, which require prior mathematical treatment of the equations of magnetohydrodynamics. The one-dimensional structure of most viscous and magnetic layers demonstrates the possibility of huge computational savings by means of multiscale techniques. In our approach, asymptotic matching is applied on simplified problems such as the Proudman-Stewartson flow to solve for the viscous shear layers while keeping the mainstream resolved on a coarse grid.

  15. Multiscale vascular surface model generation from medical imaging data using hierarchical features.

    PubMed

    Bekkers, Eric J; Taylor, Charles A

    2008-03-01

    Computational fluid dynamics (CFD) modeling of blood flow from image-based patient specific models can provide useful physiologic information for guiding clinical decision making. A novel method for the generation of image-based, 3-D, multiscale vascular surface models for CFD is presented. The method generates multiscale surfaces based on either a linear triangulated or a globally smooth nonuniform rational B-spline (NURB) representation. A robust local curvature analysis is combined with a novel global feature analysis to set mesh element size. The method is particularly useful for CFD modeling of complex vascular geometries that have a wide range of vasculature size scales, in conditions where 1) initial surface mesh density is an important consideration for balancing surface accuracy with manageable size volumetric meshes, 2) adaptive mesh refinement based on flow features makes an underlying explicit smooth surface representation desirable, and 3) semi-automated detection and trimming of a large number of inlet and outlet vessels expedites model construction. PMID:18334429

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Multiscale Modeling in the Clinic: Drug Design and Development.

    PubMed

    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

    2016-09-01

    A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multiscale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multiscale 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 multiscale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical and computational techniques employed for multiscale modeling approaches used in pharmacometric and systems pharmacology models in drug development and present several examples illustrating the current state-of-the-art models for (1) excitable systems and applications in cardiac disease; (2) stem cell driven complex biosystems; (3) nanoparticle delivery, with applications to angiogenesis and cancer therapy; (4) host-pathogen interactions and their use in metabolic disorders, inflammation and sepsis; and (5) computer-aided design of nanomedical systems. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multiscale models. PMID:26885640

  1. 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.

  2. 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

  3. Foundations for a multiscale collaborative Earth model

    NASA Astrophysics Data System (ADS)

    Afanasiev, Michael; Peter, Daniel; Sager, Korbinian; Simutė, Saulė; Ermert, Laura; Krischer, Lion; Fichtner, Andreas

    2016-01-01

    of the CSEM development, the broad global updates mostly act to remove artefacts from the assembly of the initial CSEM. During the future evolution of the CSEM, the reference data set will be used to account for the influence of small-scale refinements on large-scale global structure. The CSEM as a computational framework is intended to help bridging the gap between local, regional and global tomography, and to contribute to the development of a global multiscale Earth model. While the current construction serves as a first proof of concept, future refinements and additions will require community involvement, which is welcome at this stage already.

  4. 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

  5. A perspective on modeling the multiscale response of energetic materials

    NASA Astrophysics Data System (ADS)

    Rice, Betsy M.

    2015-06-01

    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 be done only within a multiscale framework. In this talk, I will describe our philosophy and progress in the development of a predictive, experimentally validated multiscale reactive modeling capability for energetic materials. I will also describe new opportunities and challenges that have arisen in the course of our development that will be pursued in the future.

  6. COMMUNITY MULTISCALE AIR QUALITY MODELING SYSTEM (ONE ATMOSPHERE)

    EPA Science Inventory

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

  7. 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.

  8. Image Based Validation of Dynamical Models for Cell Reorientation

    PubMed Central

    Lockley, Robert; Ladds, Graham; Bretschneider, Till

    2016-01-01

    A key feature of directed cell movement is the ability of cells to reorient quickly in response to changes in the direction of an extracellular stimulus. Mathematical models have suggested quite different regulatory mechanisms to explain reorientation, raising the question of how we can validate these models in a rigorous way. In this study, we fit three reaction—diffusion models to experimental data of Dictyostelium amoebae reorienting in response to alternating gradients of mechanical shear flow. The experimental readouts we use to fit are spatio-temporal distributions of a fluorescent reporter for cortical F-actin labeling the cell front. Experiments performed under different conditions are fitted simultaneously to challenge the models with different types of cellular dynamics. Although the model proposed by Otsuji is unable to provide a satisfactory fit, those suggested by Meinhardt and Levchenko fit equally well. Further, we show that reduction of the three-variable Meinhardt model to a two-variable model also provides an excellent fit, but has the advantage of all parameters being uniquely identifiable. Our work demonstrates that model selection and identifiability analysis, commonly applied to temporal dynamics problems in systems biology, can be a powerful tool when extended to spatio-temporal imaging data. PMID:25492625

  9. Image based validation of dynamical models for cell reorientation.

    PubMed

    Lockley, Robert; Ladds, Graham; Bretschneider, Till

    2015-06-01

    A key feature of directed cell movement is the ability of cells to reorient quickly in response to changes in the direction of an extracellular stimulus. Mathematical models have suggested quite different regulatory mechanisms to explain reorientation, raising the question of how we can validate these models in a rigorous way. In this study, we fit three reaction-diffusion models to experimental data of Dictyostelium amoebae reorienting in response to alternating gradients of mechanical shear flow. The experimental readouts we use to fit are spatio-temporal distributions of a fluorescent reporter for cortical F-actin labeling the cell front. Experiments performed under different conditions are fitted simultaneously to challenge the models with different types of cellular dynamics. Although the model proposed by Otsuji is unable to provide a satisfactory fit, those suggested by Meinhardt and Levchenko fit equally well. Further, we show that reduction of the three-variable Meinhardt model to a two-variable model also provides an excellent fit, but has the advantage of all parameters being uniquely identifiable. Our work demonstrates that model selection and identifiability analysis, commonly applied to temporal dynamics problems in systems biology, can be a powerful tool when extended to spatio-temporal imaging data. PMID:25492625

  10. 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.

  11. Image-Based Structural Modeling of the Cardiac Purkinje Network

    PubMed Central

    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

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

    NASA Astrophysics Data System (ADS)

    Macioł, Piotr; Regulski, Krzysztof

    2016-06-01

    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.

  13. SimVascular 2.0: an Integrated Open Source Pipeline for Image-Based Cardiovascular Modeling and Simulation

    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.

  14. Multiscale modeling and simulation of brain blood flow

    NASA Astrophysics Data System (ADS)

    Perdikaris, Paris; Grinberg, Leopold; Karniadakis, George Em

    2016-02-01

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

  15. 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

  16. Multi-scale modeling of hemodynamics in the cardiovascular system

    NASA Astrophysics Data System (ADS)

    Liu, Hao; Liang, Fuyou; Wong, Jasmin; Fujiwara, Takashi; Ye, Wenjing; Tsubota, Ken-iti; Sugawara, Michiko

    2015-08-01

    The human cardiovascular system is a closed-loop and complex vascular network with multi-scaled heterogeneous hemodynamic phenomena. Here, we give a selective review of recent progress in macro-hemodynamic modeling, with a focus on geometrical multi-scale modeling of the vascular network, micro-hemodynamic modeling of microcirculation, as well as blood cellular, subcellular, endothelial biomechanics, and their interaction with arterial vessel mechanics. We describe in detail the methodology of hemodynamic modeling and its potential applications in cardiovascular research and clinical practice. In addition, we present major topics for future study: recent progress of patient-specific hemodynamic modeling in clinical applications, micro-hemodynamic modeling in capillaries and blood cells, and the importance and potential of the multi-scale hemodynamic modeling.

  17. Mathematical and Numerical Analyses of Peridynamics for Multiscale Materials Modeling

    SciTech Connect

    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

  18. Modeling Crack Propagation in Polycrystalline Microstructure Using Variational Multiscale Method

    DOE PAGESBeta

    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

  19. 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.

  20. Final Report for Integrated Multiscale Modeling of Molecular Computing Devices

    SciTech Connect

    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.

  1. Image-based indoor localization system based on 3D SfM model

    NASA Astrophysics Data System (ADS)

    Lu, Guoyu; Kambhamettu, Chandra

    2013-12-01

    Indoor localization is an important research topic for both of the robot and signal processing communities. In recent years, image-based localization is also employed in indoor environment for the easy availability of the necessary equipment. After capturing an image and sending it to an image database, the best matching image is returned with the navigation information. By allowing further camera pose estimation, the image-based localization system with the use of Structure-from-Motion reconstruction model can achieve higher accuracy than the methods of searching through a 2D image database. However, this emerging technique is still only on the use of outdoor environment. In this paper, we introduce the 3D SfM model based image-based localization system into the indoor localization task. We capture images of the indoor environment and reconstruct the 3D model. On the localization task, we simply use the images captured by a mobile to match the 3D reconstructed model to localize the image. In this process, we use the visual words and the approximate nearest neighbor methods to accelerate the process of nding the query feature's correspondences. Within the visual words, we conduct linear search in detecting the correspondences. From the experiments, we nd that the image-based localization method based on 3D SfM model gives good localization result based on both accuracy and speed.

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

    SciTech Connect

    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.

  3. Multiscale geometric modeling of macromolecules II: Lagrangian representation

    PubMed Central

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

    2013-01-01

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

  4. Multiscale geometric modeling of macromolecules II: Lagrangian representation.

    PubMed

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

    2013-09-15

    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-electron microscopy, 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, whereas our coarse resolution representations highlight the compatibility of protein-ligand bindings and possibility of protein-protein interactions. PMID:23813599

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

    SciTech Connect

    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.

  6. Moist multi-scale models for the hurricane embryo

    SciTech Connect

    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.

  7. Blood Flow: Multi-scale Modeling and Visualization

    SciTech Connect

    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.

  8. Range and Image Based Modelling: a way for Frescoed Vault Texturing Optimization

    NASA Astrophysics Data System (ADS)

    Caroti, G.; Martínez-Espejo Zaragoza, I.; Piemonte, A.

    2015-02-01

    In the restoration of the frescoed vaults it is not only important to know the geometric shape of the painted surface, but it is essential to document its chromatic characterization and conservation status. The new techniques of range-based and image-based modelling, each with its limitations and advantages, offer a wide range of methods to obtain the geometric shape. In fact, several studies widely document that laser scanning enable obtaining three-dimensional models with high morphological precision. However, the quality level of the colour obtained with built-in laser scanner cameras is not comparable to that obtained for the shape. It is possible to improve the texture quality by means of a dedicated photographic campaign. This procedure, however, requires to calculate the external orientation of each image identifying the control points on it and on the model through a costly step of post processing. With image-based modelling techniques it is possible to obtain models that maintain the colour quality of the original images, but with variable geometric precision, locally lower than the laser scanning model. This paper presents a methodology that uses the camera external orientation parameters calculated by image based modelling techniques to project the same image on the model obtained from the laser scan. This methodology is tested on an Italian mirror (a schifo) frescoed vault. In the paper the different models, the analysis of precision and the efficiency evaluation of proposed methodology are presented.

  9. The Potential Vorticity Budget of Multi-Scale MJO Models

    NASA Astrophysics Data System (ADS)

    Back, A.; Biello, J. A.; Majda, A.

    2015-12-01

    Zhang and Ling (J. Atmos. Sci. 2012) performed a comprehensive analysis of the potential vorticity budget of the Madden-Julian Oscillation throughout its initiation and evolution. Biello and Majda have used the Intraseasonal Planetary Equatorial Synoptic-Scale Dynamics (IPESD) framework of Majda and Klein (J. Atmos. Sci. 2003) to create kinematic models of the MJO which distinguish MJO events forced by large-scale heating from MJO events forced by the upscale fluxes of momentum and temperature from the synoptic scales. In the present study, the results of Zhang and Ling provide a benchmark for comparing the different multi-scale MJO models. In particular, a potential vorticity budget can be obtained in the multiscale framework, and the advection, in-scale generation and upscale transfer of PV are considered.

  10. Multiscale Aspects of Modeling Gas-Phase Nanoparticle Synthesis

    PubMed Central

    Buesser, B.; Gröhn, A.J.

    2013-01-01

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

  11. 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

  12. Multiscale systems modeling of the tetralogy of Fallot.

    PubMed

    Summers, Ron; Abdulla, Tariq; Imms, Ryan; Carrault, Guy; Hernandez, Alfredo; Houyel, Lucile; Schleich, Jean-Marc

    2010-01-01

    This paper provides a first description of a multiscale systems modeling approach applied to the congenital birth defect known as the tetralogy of Fallot. The multiscale approach adopted owes a lot to the effort of the world-wide physiome consortium and the work of research groups within the European Union on the Virtual Physiological Human. Both a spatial scale and time scale are used to establish the systems boundaries of the application. The tetralogy of Fallot includes up to four simultaneously occurring anatomic abnormalities that underpin the defect. The use of finite state machines and cellular automata pave the way to understand the processes in time and space that contribute to the defect. PMID:21095902

  13. Multi-Scale Multi-Dimensional Ion Battery Performance Model

    Energy Science and Technology Software Center (ESTSC)

    2007-05-07

    The Multi-Scale Multi-Dimensional (MSMD) Lithium Ion Battery Model allows for computer prediction and engineering optimization of thermal, electrical, and electrochemical performance of lithium ion cells with realistic geometries. The model introduces separate simulation domains for different scale physics, achieving much higher computational efficiency compared to the single domain approach. It solves a one dimensional electrochemistry model in a micro sub-grid system, and captures the impacts of macro-scale battery design factors on cell performance and materialmore » usage by solving cell-level electron and heat transports in a macro grid system.« less

  14. Multi-scale modeling for sustainable chemical production.

    PubMed

    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. PMID:23520143

  15. A hybrid approach to multi-scale modelling of cancer.

    PubMed

    Osborne, J M; Walter, A; Kershaw, S K; Mirams, G R; Fletcher, A G; Pathmanathan, P; Gavaghan, D; Jensen, O E; Maini, P K; Byrne, H M

    2010-11-13

    In this paper, we review multi-scale models of solid tumour growth and discuss a middle-out framework that tracks individual cells. By focusing on the cellular dynamics of a healthy colorectal crypt and its invasion by mutant, cancerous cells, we compare a cell-centre, a cell-vertex and a continuum model of cell proliferation and movement. All models reproduce the basic features of a healthy crypt: cells proliferate near the crypt base, they migrate upwards and are sloughed off near the top. The models are used to establish conditions under which mutant cells are able to colonize the crypt either by top-down or by bottom-up invasion. While the continuum model is quicker and easier to implement, it can be difficult to relate system parameters to measurable biophysical quantities. Conversely, the greater detail inherent in the multi-scale models means that experimentally derived parameters can be incorporated and, therefore, these models offer greater scope for understanding normal and diseased crypts, for testing and identifying new therapeutic targets and for predicting their impacts. PMID:20921009

  16. 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

  17. Multiscale geometric modeling of macromolecules I: Cartesian representation

    SciTech Connect

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

    2014-01-15

    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

  18. Multiscale geometric modeling of macromolecules I: Cartesian representation

    PubMed Central

    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

  19. Multiscale geometric modeling of macromolecules I: Cartesian representation.

    PubMed

    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

  20. 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

  1. Efficient Multiscale Models of Polymer Assembly.

    PubMed

    Ruiz-Martinez, Alvaro; Bartol, Thomas M; Sejnowski, Terrence J; Tartakovsky, Daniel M

    2016-07-12

    Protein polymerization and bundling play a central role in cell physiology. Predictive modeling of these processes remains an open challenge, especially when the proteins involved become large and their concentrations high. We present an effective kinetics model of filament formation, bundling, and depolymerization after GTP hydrolysis, which involves a relatively small number of species and reactions, and remains robust over a wide range of concentrations and timescales. We apply this general model to study assembly of FtsZ protein, a basic element in the division process of prokaryotic cells such as Escherichia coli, Bacillus subtilis, or Caulobacter crescentus. This analysis demonstrates that our model outperforms its counterparts in terms of both accuracy and computational efficiency. Because our model comprises only 17 ordinary differential equations, its computational cost is orders-of-magnitude smaller than the current alternatives consisting of up to 1000 ordinary differential equations. It also provides, to our knowledge, a new insight into the characteristics and functioning of FtsZ proteins at high concentrations. The simplicity and versatility of our model render it a powerful computational tool, which can be used either as a standalone descriptor of other biopolymers' assembly or as a component in more complete kinetic models. PMID:27410746

  2. Multiscale Materials Modeling in an Industrial Environment.

    PubMed

    Weiß, Horst; Deglmann, Peter; In 't Veld, Pieter J; Cetinkaya, Murat; Schreiner, Eduard

    2016-06-01

    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. PMID:26927661

  3. Silicon EFG process development by multiscale modeling

    NASA Astrophysics Data System (ADS)

    Müller, M.; Birkmann, B.; Mosel, F.; Westram, I.; Seidl, A.

    2010-04-01

    An overview of simulation models in use for optimizing the edge-defined film-fed growth (EFG) process of thin-walled hollow silicon tubes at WACKER SCHOTT Solar is presented. The simulations span the length scales from complete furnace models over growth simulations with a mesoscopic description of the crystalline character of silicon down to solidification simulations with atomic resolution. Results gained from one model are used as input parameters or boundary conditions on other levels. Examples for the application of these models and their impact on process design are given. These include the reduction of tube thickness variations, the control of tube deformations, residual stresses and dislocation densities and the identification of twin formation processes typical for EFG silicon.

  4. Multiphysics and Multiscale Model Coupling Using Gerris

    NASA Astrophysics Data System (ADS)

    Keen, T. R.; Dykes, J. D.; Campbell, T. J.

    2012-12-01

    This work is implementing oceanographic processes encompassing multiple physics and scales using the Gerris Flow Solver (GFS) in order to examine their interdependence and sensitivity to changes in the physical environment. The processes include steady flow due to tides and the wind, phase-averaged wave-forced flow and oscillatory currents, and sediment transport. The 2D steady flow is calculated by the Ocean module contained within GFS. This model solves the Navier-Stokes (N-S) equations using the finite volume method. The model domain is represented by quad-tree adaptive mesh refinement (AMR). A stationary wave field is computed for a specified wave spectrum is uniformly distributed over the domain as a tracer with local wind input parameterized as a source, and dissipation by friction and breaking as a sink. Alongshore flow is included by a radiation stress term; this current is added to the steady flow component from tides and wind. Wave-current interaction is parameterized using a bottom boundary layer model. Sediment transport as suspended and bed load is implemented using tracers that are transported via the advection equations. A bed-conservation equation is implemented to allow changes in seafloor elevation to be used in adjusting the AMR refinement. These processes are being coupled using programming methods that are inherent to GFS and that do not require modification or recompiling of the code. These techniques include passive tracers, C functions that operate as plug-ins, and user-defined C-type macros included with GFS. Our results suggest that the AMR model coupling method is useful for problems where the dynamics are governed by several processes. This study is examining the relative influence of the steady currents, wave field, and sedimentation. Hydrodynamic and sedimentation interaction in nearshore environments is being studied for an idealized beach and for the Sandy Duck storm of Oct. 1998. The potential behavior of muddy sediments on the

  5. Multiscale numerical modeling of levee breach processes

    NASA Astrophysics Data System (ADS)

    Kees, C. E.; Farthing, M. W.; Akkerman, I.; Bazilevs, Y.

    2010-12-01

    One of the dominant failure modes of levees during flood and storm surge events is erosion-based breach formation due to high velocity flow over the back (land-side) slope. Modeling the breaching process numerically is challenging due to both physical and geometric complexity that develops and evolves during the overtopping event. The surface water flows are aerated and sediment-laden mixtures in the supercritical and turbulent regimes. The air/water free surface may undergo perturbations on the same order as the depth or even topological change (breaking). Likewise the soil/fluid interface is characterized by evolving headcuts, which are essentially moving discontinuities in the soil surface elevation. The most widely used models of levee breaching are nevertheless based on depth-integrated models of flow, sediment transport, and bed morphology. In this work our objective is to explore models with less restrictive modeling assumptions, which have become computationally tractable due to advances in both numerical methods and high-performance computing hardware. In particular, we present formulations of fully three-dimensional flow, transport, and morphological evolution for overtopping and breaching processes and apply recently developed finite element and level set methods to solve the governing equations for relevant test problems.

  6. 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).

  7. Multiscale modeling of virus replication and spread.

    PubMed

    Kumberger, Peter; Frey, Felix; Schwarz, Ulrich S; Graw, Frederik

    2016-07-01

    Replication and spread of human viruses is based on the simultaneous exploitation of many different host functions, bridging multiple scales in space and time. Mathematical modeling is essential to obtain a systems-level understanding of how human viruses manage to proceed through their life cycles. Here, we review corresponding advances for viral systems of large medical relevance, such as human immunodeficiency virus-1 (HIV-1) and hepatitis C virus (HCV). We will outline how the combination of mathematical models and experimental data has advanced our quantitative knowledge about various processes of these pathogens, and how novel quantitative approaches promise to fill remaining gaps. PMID:26878104

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

    EPA Science Inventory

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

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

    PubMed

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

    2011-01-01

    Future multiscale and multiphysics models must use the power of high performance computing (HPC) systems to enable research into human disease, translational medical science, and treatment. Previously we showed that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message passing processes (e.g. the message passing interface (MPI)) with multithreading (e.g. OpenMP, POSIX pthreads). The objective of this work is to compare the performance of such hybrid programming models when applied to the simulation of a lightweight multiscale cardiac model. Our results show that the hybrid models do not perform favourably when compared to an implementation using only MPI which is in contrast to our results using complex physiological models. Thus, with regards to lightweight multiscale cardiac models, the user may not need to increase programming complexity by using a hybrid programming approach. However, considering that model complexity will increase as well as the HPC system size in both node count and number of cores per node, it is still foreseeable that we will achieve faster than real time multiscale cardiac simulations on these systems using hybrid programming models. PMID:22254341

  10. 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.

  11. 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].

  12. 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

  13. Multiscale Modeling of Solar Coronal Magnetic Reconnection

    NASA Technical Reports Server (NTRS)

    Antiochos, Spiro K.; Karpen, Judith T.; DeVore, C. Richard

    2010-01-01

    Magnetic reconnection is widely believed to be the primary process by which the magnetic field releases energy to plasma in the Sun's corona. For example, in the breakout model for the initiation of coronal mass ejections/eruptive flares, reconnection is responsible for the catastrophic destabilizing of magnetic force balance in the corona, leading to explosive energy release. A critical requirement for the reconnection is that it have a "switch-on' nature in that the reconnection stays off until a large store of magnetic free energy has built up, and then it turn on abruptly and stay on until most of this free energy has been released. We discuss the implications of this requirement for reconnection in the context of the breakout model for CMEs/flares. We argue that it imposes stringent constraints on the properties of the flux breaking mechanism, which is expected to operate in the corona on kinetic scales. We present numerical simulations demonstrating how the reconnection and the eruption depend on the effective resistivity, i.e., the effective Lundquist number, and propose a model for incorporating kinetic flux-breaking mechanisms into MHO calculation of CMEs/flares.

  14. A multiscale approach for modeling crystalline solids

    NASA Astrophysics Data System (ADS)

    Cuitiño, Alberto M.; Stainier, Laurent; Wang, Guofeng; Strachan, Alejandro; Çağin, Tahir; Goddard, William A.; Ortiz, Michael

    2001-05-01

    In this paper we present a modeling approach to bridge the atomistic with macroscopic scales in crystalline materials. The methodology combines identification and modeling of the controlling unit processes at microscopic level with the direct atomistic determination of fundamental material properties. These properties are computed using a many body Force Field derived from ab initio quantum-mechanical calculations. This approach is exercised to describe the mechanical response of high-purity Tantalum single crystals, including the effect of temperature and strain-rate on the hardening rate. The resulting atomistically informed model is found to capture salient features of the behavior of these crystals such as: the dependence of the initial yield point on temperature and strain rate; the presence of a marked stage I of easy glide, specially at low temperatures and high strain rates; the sharp onset of stage II hardening and its tendency to shift towards lower strains, and eventually disappear, as the temperature increases or the strain rate decreases; the parabolic stage II hardening at low strain rates or high temperatures; the stage II softening at high strain rates or low temperatures; the trend towards saturation at high strains; the temperature and strain-rate dependence of the saturation stress; and the orientation dependence of the hardening rate.

  15. Multiscale analysis of compartment models with dispersal

    PubMed Central

    Kang, Yun; Castillo-Chavez, Carlos

    2014-01-01

    Dispersal, minimally defined as the movement or spatial displacement of organisms, links the dynamics of local population within and across regions. Landscape-population interactions responsible for driving co-evolutionary processes that on the long run shape communities of organisms, determine the outcomes of biological invasions, or alter the dynamics and evolution of infectious agents, are connected via dispersal. A generalized modeling framework is introduced derived from our interests in characterizing the dynamics of animal populations and trade in the presence of disease. We explore the impact of dispersal on systems that include disease, Allee effects, and host mobility. The emphasis is on disease, a selective force, that often plays a fundamental role on the life-history dynamics of a population. The models incorporate disease-driven effects on, often excluded, interactions like individual’s competitive ability to acquire resources. The framework makes use of deterministic and stochastic models that account for features often ignored or rarely included like (a) induced Allee effects; (b) disease dynamics; and (c) spatial heterogeneity. Preliminary results highlight the role of initial conditions, patch quality, and “topological” or connectivity landscape structure (the physical space where individuals move, reproduce, get sick, die, or compete for resources) on the dynamics of populations when disease is an important selective force. We dedicate this article to our grand mentor Simon Levin. PMID:22934939

  16. Multiscale Modeling of Heterogeneous Lipid Bilayers

    NASA Astrophysics Data System (ADS)

    Faller, Roland; Bennun-Serrano, Sandra; Dickey, Allison

    2005-03-01

    The first line of defense for a cell against intrusive molecules is the membrane which must be resilient to prevent unwanted molecules from passing through as a change in the intracellular ion balance could be detrimental. Experimentally, it has been shown that as chain length and concentration of alcohols near a membrane increase, the area per lipid expands, increasing the likelihood of permeation. Additionally, there is evidence for pattern formation in cell membranes due to the presence of various lipids. These patterns or rafts are believed to play important roles in cell signaling. Here, we use MD to study the interactions between alcohols and pure lipid bilayers as well as pattern formation in mixed membranes using atomistic and coarse-grained models. We characterize the effect of alcohol chain-length and concentration on the lipid bilayer through area per head group, order parameter, and density profile. We also examine the effects of lipid-alcohol interactions on membrane curvature with the CG model and find satisfactory system representation. We use a mixture of DLPC and DSPC as model system for phase separation. Different concentrations and temperatures are used to reproduce phase transitions. We obtain agreement with experiments for area per lipid head group and deuterium order parameter. At high DSPC concentrations phase separation into a gel and liquid state is found. Simulations confirm that increasing DLPC concentrations lower the transition temperature.

  17. 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.

  18. Multi-scale modelling of granular avalanches

    NASA Astrophysics Data System (ADS)

    Kumar, Krishna; Soga, Kenichi; Delenne, Jean-Yves

    2013-06-01

    Avalanches, debris flows, and landslides are geophysical hazards, which involve rapid mass movement of granular solids, water and air as a single-phase system. The dynamics of a granular flow involve at least three distinct scales: the micro-scale, meso-scale, and the macro-scale. This study aims to understand the ability of continuum models to capture the micro-mechanics of dry granular collapse. Material Point Method (MPM), a hybrid Lagrangian and Eulerian approach, with Mohr-Coulomb failure criterion is used to describe the continuum behaviour of granular column collapse, while the micromechanics is captured using Discrete Element Method (DEM) with tangential contact force model. The run-out profile predicted by the continuum simulations matches with DEM simulations for columns with small aspect ratios (`h/r' < 2), however MPM predicts larger run-out distances for columns with higher aspect ratios (`h/r' > 2). Energy evolution studies in DEM simulations reveal higher collisional dissipation in the initial free-fall regime for tall columns. The lack of a collisional energy dissipation mechanism in MPM simulations results in larger run-out distances. Micro-structural effects, such as shear band formations, were observed both in DEM and MPM simulations. A sliding flow regime is observed above the distinct passive zone at the core of the column. Velocity profiles obtained from both the scales are compared to understand the reason for a slow flow run-out mobilization in MPM simulations.

  19. Multiscale modeling for fluid transport in nanosystems.

    SciTech Connect

    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.

  20. 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.

  1. 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

  2. Multiscale modeling and computation of optically manipulated nano devices

    NASA Astrophysics Data System (ADS)

    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.

  3. Integrated Multiscale Modeling of Molecular Computing Devices

    SciTech Connect

    Weinan E

    2012-03-29

    The main bottleneck in modeling transport in molecular devices is to develop the correct formulation of the problem and efficient algorithms for analyzing the electronic structure and dynamics using, for example, the time-dependent density functional theory. We have divided this task into several steps. The first step is to developing the right mathematical formulation and numerical algorithms for analyzing the electronic structure using density functional theory. The second step is to study time-dependent density functional theory, particularly the far-field boundary conditions. The third step is to study electronic transport in molecular devices. We are now at the end of the first step. Under DOE support, we have made subtantial progress in developing linear scaling and sub-linear scaling algorithms for electronic structure analysis. Although there has been a huge amount of effort in the past on developing linear scaling algorithms, most of the algorithms developed suffer from the lack of robustness and controllable accuracy. We have made the following progress: (1) We have analyzed thoroughly the localization properties of the wave-functions. We have developed a clear understanding of the physical as well as mathematical origin of the decay properties. One important conclusion is that even for metals, one can choose wavefunctions that decay faster than any algebraic power. (2) We have developed algorithms that make use of these localization properties. Our algorithms are based on non-orthogonal formulations of the density functional theory. Our key contribution is to add a localization step into the algorithm. The addition of this localization step makes the algorithm quite robust and much more accurate. Moreover, we can control the accuracy of these algorithms by changing the numerical parameters. (3) We have considerably improved the Fermi operator expansion (FOE) approach. Through pole expansion, we have developed the optimal scaling FOE algorithm.

  4. A multiscale coupling method for the modeling of dynamics of solids with application to brittle cracks

    SciTech Connect

    Li Xiantao Yang, Jerry Z. E, Weinan

    2010-05-20

    We present a multiscale model for numerical simulations of dynamics of crystalline solids. The method combines the continuum nonlinear elasto-dynamics model, which models the stress waves and physical loading conditions, and molecular dynamics model, which provides the nonlinear constitutive relation and resolves the atomic structures near local defects. The coupling of the two models is achieved based on a general framework for multiscale modeling - the heterogeneous multiscale method (HMM). We derive an explicit coupling condition at the atomistic/continuum interface. Application to the dynamics of brittle cracks under various loading conditions is presented as test examples.

  5. Integrated Multiscale Modeling of Molecular Computing Devices

    SciTech Connect

    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.

  6. 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.

  7. A multiscale statistical model for time series forecasting

    NASA Astrophysics Data System (ADS)

    Wang, W.; Pollak, I.

    2007-02-01

    We propose a stochastic grammar model for random-walk-like time series that has features at several temporal scales. We use a tree structure to model these multiscale features. The inside-outside algorithm is used to estimate the model parameters. We develop an algorithm to forecast the sign of the first difference of a time series. We illustrate the algorithm using log-price series of several stocks and compare with linear prediction and a neural network approach. We furthermore illustrate our algorithm using synthetic data and show that it significantly outperforms both the linear predictor and the neural network. The construction of our synthetic data indicates what types of signals our algorithm is well suited for.

  8. Multiscale Modeling of Biomimetic Self-Healing Materials

    NASA Astrophysics Data System (ADS)

    Kolmakov, German; Scarbrough, Amy; Gnegy, Chet; Salib, Isaac; Matyjaszewski, Krzysztof; Balazs, Anna

    2011-03-01

    We use a hybrid computational approach to examine the self-healing behavior of polymeric materials composed of soft nanogel particles crosslinked by a network of both stable and labile bonds. The latter are highly reactive and therefore, can break and readily reform. To capture the multiscale structure of the material, we take advantage of the multi-level Hierarchical Bell Model (mHBM) where the labile crosslinks are organized into M levels of interconnected elements, each of them represents a number of bonds that lie in parallel and is described by a single-level HBM. We vary the number of hierarchical levels M and the number of labile bonds in each element to determine optimal conditions for improving strength and toughness of the material. We also compare the properties of the multiscale material with those for the gel, in which only single-level interconnections are presented. This study takes its inspiration from biological systems that show remarkable resilience in response to mechanical deformation.

  9. Adaptive registration of magnetic resonance images based on a viscous fluid model.

    PubMed

    Chang, Herng-Hua; Tsai, Chih-Yuan

    2014-11-01

    This paper develops a new viscous fluid registration algorithm that makes use of a closed incompressible viscous fluid model associated with mutual information. In our approach, we treat the image pixels as the fluid elements of a viscous fluid governed by the nonlinear Navier-Stokes partial differential equation (PDE) that varies in both temporal and spatial domains. We replace the pressure term with an image-based body force to guide the transformation that is weighted by the mutual information between the template and reference images. A computationally efficient algorithm with staggered grids is introduced to obtain stable solutions of this modified PDE for transformation. The registration process of updating the body force, the velocity and deformation fields is repeated until the mutual information reaches a prescribed threshold. We have evaluated this new algorithm in a number of synthetic and medical images. As consistent with the theory of the viscous fluid model, we found that our method faithfully transformed the template images into the reference images based on the intensity flow. Experimental results indicated that the proposed scheme achieved stable registrations and accurate transformations, which is of potential in large-scale medical image deformation applications. PMID:25176596

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

    SciTech Connect

    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

  11. A Coupled Multiscale Model of Texture Evolution and Plastic Anisotropy

    NASA Astrophysics Data System (ADS)

    Gawad, J.; Van Bael, A.; Yerra, S. K.; Samaey, G.; Van Houtte, P.; Roose, D.

    2010-06-01

    In this paper we present a multiscale model of a plastic deformation process in which the anisotropy of plastic properties is related to the evolution of the crystallographic texture. The model spans several length scales from the macroscopic deformation of the workpiece to the microscale interactions between individual grains in a polycrystalline material. The macroscopic behaviour of the material is described by means of a Finite Element (FE) model. Plastic anisotropy is taken into account in a constitutive law, based on the concept of a plastic potential in strain rate space. The coefficients of a sixth-order Facet equation are determined using the Taylor theory, provided that the current crystallographic texture at a given FE integration point is known. Texture evolution in the FE integration points is predicted by an ALAMEL micromechanical model. Mutual interactions between coarse and fine scale are inherent in the physics of the deformation process. These dependencies are taken into account by full bidirectional coupling in the model. Therefore, the plastic deformation influences the crystallographic texture and the evolution of the texture induces anisotropy of the macroscopic deformation. The presented approach enables an adaptive texture and yield surface update scheme with respect to the local plastic deformation in the FE integration points. Additionally, the computational cost related to the updates of the constitutive law is reduced by application of parallel computing techniques. Suitability of on-demand computing for this computational problem is discussed. The parallelisation strategy addresses both distributed memory and shared memory architectures. The cup drawing process has been simulated using the multiscale model outlined above. The discussion of results includes the analysis of the planar anisotropy in the cup and the influence of complex deformation path on texture development. Evolution of texture at selected material points is assessed as

  12. 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

  13. Multi-scale, multi-resolution brain cancer modeling.

    PubMed

    Zhang, Le; Chen, L Leon; Deisboeck, Thomas S

    2009-03-01

    In advancing discrete-based computational cancer models towards clinical applications, one faces the dilemma of how to deal with an ever growing amount of biomedical data that ought to be incorporated eventually in one form or another. Model scalability becomes of paramount interest. In an effort to start addressing this critical issue, here, we present a novel multi-scale and multi-resolution agent-based in silico glioma model. While 'multi-scale' refers to employing an epidermal growth factor receptor (EGFR)-driven molecular network to process cellular phenotypic decisions within the micro-macroscopic environment, 'multi-resolution' is achieved through algorithms that classify cells to either active or inactive spatial clusters, which determine the resolution they are simulated at. The aim is to assign computational resources where and when they matter most for maintaining or improving the predictive power of the algorithm, onto specific tumor areas and at particular times. Using a previously described 2D brain tumor model, we have developed four different computational methods for achieving the multi-resolution scheme, three of which are designed to dynamically train on the high-resolution simulation that serves as control. To quantify the algorithms' performance, we rank them by weighing the distinct computational time savings of the simulation runs versus the methods' ability to accurately reproduce the high-resolution results of the control. Finally, to demonstrate the flexibility of the underlying concept, we show the added value of combining the two highest-ranked methods. The main finding of this work is that by pursuing a multi-resolution approach, one can reduce the computation time of a discrete-based model substantially while still maintaining a comparably high predictive power. This hints at even more computational savings in the more realistic 3D setting over time, and thus appears to outline a possible path to achieve scalability for the all

  14. 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

  15. 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

  16. Breakdown parameter for kinetic modeling of multiscale gas flows.

    PubMed

    Meng, Jianping; Dongari, Nishanth; Reese, Jason M; Zhang, Yonghao

    2014-06-01

    Multiscale methods built purely on the kinetic theory of gases provide information about the molecular velocity distribution function. It is therefore both important and feasible to establish new breakdown parameters for assessing the appropriateness of a fluid description at the continuum level by utilizing kinetic information rather than macroscopic flow quantities alone. We propose a new kinetic criterion to indirectly assess the errors introduced by a continuum-level description of the gas flow. The analysis, which includes numerical demonstrations, focuses on the validity of the Navier-Stokes-Fourier equations and corresponding kinetic models and reveals that the new criterion can consistently indicate the validity of continuum-level modeling in both low-speed and high-speed flows at different Knudsen numbers. PMID:25019910

  17. Image-based Tissue Distribution Modeling for Skeletal Muscle Quality Characterization

    PubMed Central

    Fishbein, K. W.; Moore, A. Z.; Spencer, R. G.; Ferrucci, L.

    2016-01-01

    The identification and characterization of regional body tissues is essential to understand changes that occur with aging and age-related metabolic diseases such as diabetes and obesity and how these diseases affect trajectories of health and functional status. Imaging technologies are frequently used to derive volumetric, area, and density measurements of different tissues. Despite the significance and direct applicability of automated tissue quantification and characterization techniques, these topics have remained relatively under-explored in the medical image analysis literature. We present a method for identification and characterization of muscle and adipose tissue in the mid-thigh region using MRI. We propose an image-based muscle quality prediction technique that estimates tissue-specific probability density models and their eigenstructures in the joint domain of water- and fat-suppressed voxel signal intensities along with volumetric and intensity-based tissue characteristics computed during the quantification stage. We evaluated the predictive capability of our approach against reference biomechanical muscle quality measurements using statistical tests and classification performance experiments. The reference standard for muscle quality is defined as the ratio of muscle strength to muscle mass. The results show promise for the development of non-invasive image-based muscle quality descriptors. PMID:26336111

  18. Multiscale modeling for clinical translation in neuropsychiatric disease

    PubMed Central

    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

  19. ONE-ATMOSPHERE DYNAMICS DESCRIPTION IN THE MODELS-3 COMMUNITY MULTI-SCALE QUALITY (CMAQ) MODELING SYSTEM

    EPA Science Inventory

    This paper proposes a general procedure to link meteorological data with air quality models, such as U.S. EPA's Models-3 Community Multi-scale Air Quality (CMAQ) modeling system. CMAQ is intended to be used for studying multi-scale (urban and regional) and multi-pollutant (ozon...

  20. 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.

  1. Integrating multiple scales of hydraulic conductivity measurements in training image-based stochastic models

    NASA Astrophysics Data System (ADS)

    Mahmud, K.; Mariethoz, G.; Baker, A.; Sharma, A.

    2015-01-01

    Hydraulic conductivity is one of the most critical and at the same time one of the most uncertain parameters in many groundwater models. One problem commonly faced is that the data are usually not collected at the same scale as the discretized elements used in a numerical model. Moreover, it is common that different types of hydraulic conductivity measurements, corresponding to different spatial scales, coexist in a studied domain, which have to be integrated simultaneously. Here we address this issue in the context of Image Quilting, one of the recently developed multiple-point geostatistics methods. Based on a training image that represents fine-scale spatial variability, we use the simplified renormalization upscaling method to obtain a series of upscaled training images that correspond to the different scales at which measurements are available. We then apply Image Quilting with such a multiscale training image to be able to incorporate simultaneously conditioning data at several spatial scales of heterogeneity. The realizations obtained satisfy the conditioning data exactly across all scales, but it can come at the expense of a small approximation in the representation of the physical scale relationships. In order to mitigate this approximation, we iteratively apply a kriging-based correction to the finest scale that ensures local conditioning at the coarsest scales. The method is tested on a series of synthetic examples where it gives good results and shows potential for the integration of different measurement methods in real-case hydrogeological models.

  2. Multiscale modelling of the feto–placental vasculature

    PubMed Central

    Clark, A. R.; Lin, M.; Tawhai, M.; Saghian, R.; James, J. L.

    2015-01-01

    The placenta provides all the nutrients required for the fetus through pregnancy. It develops dynamically, and, to avoid rejection of the fetus, there is no mixing of fetal and maternal blood; rather, the branched placental villi ‘bathe’ in blood supplied from the uterine arteries. Within the villi, the feto–placental vasculature also develops a complex branching structure in order to maximize exchange between the placental and maternal circulations. To understand the development of the placenta, we must translate functional information across spatial scales including the interaction between macro- and micro-scale haemodynamics and account for the effects of a dynamically and rapidly changing structure through the time course of pregnancy. Here, we present steps towards an anatomically based and multiscale approach to modelling the feto–placental circulation. We assess the effect of the location of cord insertion on feto–placental blood flow resistance and flow heterogeneity and show that, although cord insertion does not appear to directly influence feto–placental resistance, the heterogeneity of flow in the placenta is predicted to increase from a 19.4% coefficient of variation with central cord insertion to 23.3% when the cord is inserted 2 cm from the edge of the placenta. Model geometries with spheroidal and ellipsoidal shapes, but the same volume, showed no significant differences in flow resistance or heterogeneity, implying that normal asymmetry in shape does not affect placental efficiency. However, the size and number of small capillary vessels is predicted to have a large effect on feto–placental resistance and flow heterogeneity. Using this new model as an example, we highlight the importance of taking an integrated multi-disciplinary and multiscale approach to understand development of the placenta. PMID:25844150

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  5. Multi-Scale Coupling in Ocean and Climate Modeling

    SciTech Connect

    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.

  6. Multiscale approach to modeling intrinsic dissipation in solids

    NASA Astrophysics Data System (ADS)

    Kunal, K.; Aluru, N. R.

    2016-08-01

    In this paper, we develop a multiscale approach to model intrinsic dissipation under high frequency of vibrations in solids. For vibrations with a timescale comparable to the phonon relaxation time, the local phonon distribution deviates from the equilibrium distribution. We extend the quasiharmonic (QHM) method to describe the dynamics under such a condition. The local deviation from the equilibrium state is characterized using a nonequilibrium stress tensor. A constitutive relation for the time evolution of the stress component is obtained. We then parametrize the evolution equation using the QHM method and a stochastic sampling approach. The stress relaxation dynamics is obtained using mode Langevin dynamics. Methods to obtain the input variables for the Langevin dynamics are discussed. The proposed methodology is used to obtain the dissipation rate Edissip for different cases. Frequency and size effect on Edissip are studied. The results are compared with those obtained using nonequilibrium molecular dynamics (MD).

  7. 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.

  8. Concurrent multiscale modelling of atomistic and hydrodynamic processes in liquids

    PubMed Central

    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

  9. Diagnosis of pulmonary hypertension from magnetic resonance imaging-based computational models and decision tree analysis.

    PubMed

    Lungu, Angela; Swift, Andrew J; Capener, David; Kiely, David; Hose, Rod; Wild, Jim M

    2016-06-01

    Accurately identifying patients with pulmonary hypertension (PH) using noninvasive methods is challenging, and right heart catheterization (RHC) is the gold standard. Magnetic resonance imaging (MRI) has been proposed as an alternative to echocardiography and RHC in the assessment of cardiac function and pulmonary hemodynamics in patients with suspected PH. The aim of this study was to assess whether machine learning using computational modeling techniques and image-based metrics of PH can improve the diagnostic accuracy of MRI in PH. Seventy-two patients with suspected PH attending a referral center underwent RHC and MRI within 48 hours. Fifty-seven patients were diagnosed with PH, and 15 had no PH. A number of functional and structural cardiac and cardiovascular markers derived from 2 mathematical models and also solely from MRI of the main pulmonary artery and heart were integrated into a classification algorithm to investigate the diagnostic utility of the combination of the individual markers. A physiological marker based on the quantification of wave reflection in the pulmonary artery was shown to perform best individually, but optimal diagnostic performance was found by the combination of several image-based markers. Classifier results, validated using leave-one-out cross validation, demonstrated that combining computation-derived metrics reflecting hemodynamic changes in the pulmonary vasculature with measurement of right ventricular morphology and function, in a decision support algorithm, provides a method to noninvasively diagnose PH with high accuracy (92%). The high diagnostic accuracy of these MRI-based model parameters may reduce the need for RHC in patients with suspected PH. PMID:27252844

  10. 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

  11. Multiscale Modeling of Gastrointestinal Electrophysiology and Experimental Validation

    PubMed Central

    Du, Peng; O'Grady, Greg; Davidson, John B.; Cheng, Leo K.; Pullan, Andrew J.

    2011-01-01

    Normal gastrointestinal (GI) motility results from the coordinated interplay of multiple cooperating mechanisms, both intrinsic and extrinsic to the GI tract. A fundamental component of this activity is an omnipresent electrical activity termed slow waves, which is generated and propagated by the interstitial cells of Cajal (ICCs). The role of ICC loss and network degradation in GI motility disorders is a significant area of ongoing research. This review examines recent progress in the multiscale modeling framework for effectively integrating a vast range of experimental data in GI electrophysiology, and outlines the prospect of how modeling can provide new insights into GI function in health and disease. The review begins with an overview of the GI tract and its electrophysiology, and then focuses on recent work on modeling GI electrical activity, spanning from cell to body biophysical scales. Mathematical cell models of the ICCs and smooth muscle cell are presented. The continuum framework of monodomain and bidomain models for tissue and organ models are then considered, and the forward techniques used to model the resultant body surface potential and magnetic field are discussed. The review then outlines recent progress in experimental support and validation of modeling, and concludes with a discussion on potential future research directions in this field. PMID:21133835

  12. A MULTISCALE, CELL-BASED FRAMEWORK FOR MODELING CANCER DEVELOPMENT

    SciTech Connect

    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.

  13. A Multiscale Dynamo Model Driven by Quasi-geostrophic Convection

    NASA Astrophysics Data System (ADS)

    Julien, Keith; Calkins, Michael; Tobias, Steve; Aurnou, Jonathan

    2015-11-01

    A convection-driven multiscale dynamo model is discussed for the plane layer geometry in the limit of low Rossby number. The small-scale fluctuating dynamics are described by a magnetically-modified quasi-geostrophic equation set, and the large-scale mean dynamics are governed by a diagnostic thermal wind balance. The model utilizes three timescales that respectively characterize the convective timescale, the large-scale magnetic diffusion timescale, and the large-scale thermal diffusion timescale. It is shown that in limit of low magnetic Prandtl number the model is characterized by a magnetic to kinetic energy ratio that is asymptotically large, with ohmic dissipation dominating viscous dissipation on the large-scales. For the order one magnetic Prandtl number model the magnetic and kinetic energies are equipartitioned and both ohmic and viscous dissipation are weak on the large-scales. For both cases the Elsasser number is small. The new models can be considered fully nonlinear, generalized versions of the dynamo model originally developed by Childress and Soward. These models may be useful for understanding the dynamics of convection-driven dynamos in regimes that are only just becoming accessible to simulations of the full set of governing equations. NSF EAR #1320991, NSF EAR CSEDI 1067944.

  14. 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.

  15. 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

  16. 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

  17. Multiscale Model of Colorectal Cancer Using the Cellular Potts Framework

    PubMed Central

    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

  18. 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.

  19. 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.

  20. A universal and efficient method to compute maps from image-based prediction models.

    PubMed

    Sabuncu, Mert R

    2014-01-01

    Discriminative supervised learning algorithms, such as Support Vector Machines, are becoming increasingly popular in biomedical image computing. One of their main uses is to construct image-based prediction models, e.g., for computer aided diagnosis or "mind reading." A major challenge in these applications is the biological interpretation of the machine learning models, which can be arbitrarily complex functions of the input features (e.g., as induced by kernel-based methods). Recent work has proposed several strategies for deriving maps that highlight regions relevant for accurate prediction. Yet most of these methods o n strong assumptions about t he prediction model (e.g., linearity, sparsity) and/or data (e.g., Gaussianity), or fail to exploit the covariance structure in the data. In this work, we propose a computationally efficient and universal framework for quantifying associations captured by black box machine learning models. Furthermore, our theoretical perspective reveals that examining associations with predictions, in the absence of ground truth labels, can be very informative. We apply the proposed method to machine learning models trained to predict cognitive impairment from structural neuroimaging data. We demonstrate that our approach yields biologically meaningful maps of association. PMID:25320819

  1. Image-Based Personalization of Cardiac Anatomy for Coupled Electromechanical Modeling.

    PubMed

    Crozier, A; Augustin, C M; Neic, A; Prassl, A J; Holler, M; Fastl, T E; Hennemuth, A; Bredies, K; Kuehne, T; Bishop, M J; Niederer, S A; Plank, G

    2016-01-01

    Computational models of cardiac electromechanics (EM) are increasingly being applied to clinical problems, with patient-specific models being generated from high fidelity imaging and used to simulate patient physiology, pathophysiology and response to treatment. Current structured meshes are limited in their ability to fully represent the detailed anatomical data available from clinical images and capture complex and varied anatomy with limited geometric accuracy. In this paper, we review the state of the art in image-based personalization of cardiac anatomy for biophysically detailed, strongly coupled EM modeling, and present our own tools for the automatic building of anatomically and structurally accurate patient-specific models. Our method relies on using high resolution unstructured meshes for discretizing both physics, electrophysiology and mechanics, in combination with efficient, strongly scalable solvers necessary to deal with the computational load imposed by the large number of degrees of freedom of these meshes. These tools permit automated anatomical model generation and strongly coupled EM simulations at an unprecedented level of anatomical and biophysical detail. PMID:26424476

  2. An Image-Based Model of Fluid Flow Through Lymph Nodes.

    PubMed

    Cooper, Laura J; Heppell, James P; Clough, Geraldine F; Ganapathisubramani, Bharathram; Roose, Tiina

    2016-01-01

    The lymphatic system returns fluid to the bloodstream from the tissues to maintain tissue fluid homeostasis. Lymph nodes distributed throughout the system filter the lymphatic fluid. The afferent and efferent lymph flow conditions of lymph nodes can be measured in experiments; however, it is difficult to measure the flow within the nodes. In this paper, we present an image-based modelling approach to investigating how the internal structure of the node affects the fluid flow pathways within the node. Selective plane illumination microscopy images of murine lymph nodes are used to identify the geometry and structure of the tissue within the node and to determine the permeability of the lymph node interstitium to lymphatic fluid. Experimental data are used to determine boundary conditions and optimise the parameters for the model. The numerical simulations conducted within the model are implemented in COMSOL Multiphysics, a commercial finite element analysis software. The parameter fitting resulted in the estimate that the average permeability for lymph node tissue is of the order of magnitude of [Formula: see text]. Our modelling shows that the flow predominantly takes a direct path between the afferent and efferent lymphatics and that fluid is both filtered and absorbed across the blood vessel boundaries. The amount that is absorbed or extravasated in the model is dependent on the efferent lymphatic lumen fluid pressure. PMID:26690921

  3. Final technical report for DOE Computational Nanoscience Project: Integrated Multiscale Modeling of Molecular Computing Devices

    SciTech Connect

    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.

  4. Multiscale modeling of droplet interface bilayer membrane networks.

    PubMed

    Freeman, Eric C; Farimani, Amir B; Aluru, Narayana R; Philen, Michael K

    2015-11-01

    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

  5. Bayesian Multiscale Modeling of Closed Curves in Point Clouds

    PubMed Central

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

    2014-01-01

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

  6. Multiscale mechanistic modeling in pharmaceutical research and development.

    PubMed

    Kuepfer, Lars; Lippert, Jörg; Eissing, Thomas

    2012-01-01

    Discontinuation of drug development projects due to lack of efficacy or adverse events is one of the main cost drivers in pharmaceutical research and development (R&D). Investments have to be written-off and contribute to the total costs of a successful drug candidate receiving marketing authorization and allowing return on invest. A vital risk for pharmaceutical innovator companies is late stage clinical failure since costs for individual clinical trials may exceed the one billion Euro threshold. To guide investment decisions and to safeguard maximum medical benefit and safety for patients recruited in clinical trials, it is therefore essential to understand the clinical consequences of all information and data generated. The complexity of the physiological and pathophysiological processes and the sheer amount of information available overcharge the mental capacity of any human being and prevent a prediction of the success in clinical development. A rigorous integration of knowledge, assumption, and experimental data into computational models promises a significant improvement of the rationalization of decision making in pharmaceutical industry. We here give an overview of the current status of modeling and simulation in pharmaceutical R&D and outline the perspectives of more recent developments in mechanistic modeling. Specific modeling approaches for different biological scales ranging from intracellular processes to whole organism physiology are introduced and an example for integrative multiscale modeling of therapeutic efficiency in clinical oncology trials is showcased. PMID:22161351

  7. Multiscale modeling of the trihexyltetradecylphosphonium chloride ionic liquid.

    PubMed

    Wang, Yong-Lei; Sarman, Sten; Li, Bin; Laaksonen, Aatto

    2015-09-14

    A multiscale modeling protocol was sketched for the trihexyltetradecylphosphonium chloride ([P6,6,6,14]Cl) ionic liquid (IL). The optimized molecular geometries of an isolated [P6,6,6,14] cation and a tightly bound [P6,6,6,14]Cl ion pair structure were obtained from quantum chemistry ab initio calculations. A cost-effective united-atom model was proposed for the [P6,6,6,14] cation based on the corresponding atomistic model. Atomistic and coarse-grained molecular dynamics simulations were performed over a wide temperature range to validate the proposed united-atom [P6,6,6,14] model against the available experimental data. Through a systemic analysis of volumetric quantities, microscopic structures, and transport properties of the bulk [P6,6,6,14]Cl IL under varied thermodynamic conditions, it was identified that the proposed united-atom [P6,6,6,14] cationic model could essentially capture the local intermolecular structures and the nonlocal experimental thermodynamics, including liquid density, volume expansivity and isothermal compressibility, and transport properties, such as zero-shear viscosity, of the bulk [P6,6,6,14]Cl IL within a wide temperature range. PMID:26256677

  8. 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 t 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.

  9. A multi-scale strength model with phase transformation

    NASA Astrophysics Data System (ADS)

    Barton, Nathan; Arsenlis, Athanasios; Rhee, Moono; Marian, Jaime; Bernier, Joel V.; Tang, Meijie; Yang, Lin

    2012-03-01

    We present a multi-scale strength model that includes phase transformation. In each phase, strength depends on pressure, strain rate, temperature, and evolving dislocation density descriptors. A donor cell type of approach is used for the transfer of dislocation density between phases. While the shear modulus can be modeled as smooth through the BCC to rhombohedral transformation in vanadium, the multi-phase strength model predicts abrupt changes in the material strength due to changes in dislocation kinetics. In the rhombohedral phase, the dislocation density is decomposed into populations associated with short and long Burgers vectors. Strength 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. We demonstrate the behavior of the model through simulations of Rayleigh Taylor instability growth experiments of the type used to assess material strength at high pressure and strain rate.

  10. A multi-scale strength model with phase transformation

    NASA Astrophysics Data System (ADS)

    Barton, N.; Arsenlis, A.; Rhee, M.; Marian, J.; Bernier, J.; Tang, M.; Yang, L.

    2011-06-01

    We present a multi-scale strength model that includes phase transformation. In each phase, strength depends on pressure, strain rate, temperature, and evolving dislocation density descriptors. A donor cell type of approach is used for the transfer of dislocation density between phases. While the shear modulus can be modeled as smooth through the BCC to rhombohedral transformation in vanadium, the multi-phase strength model predicts abrupt changes in the material strength due to changes in dislocation kinetics. In the rhombohedral phase, the dislocation density is decomposed into populations associated with short and long Burgers vectors. Strength 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. We demonstrate the behavior of the model through simulations of Rayleigh Taylor instability growth experiments of the type used to assess material strength at high pressure and strain rate. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 (LLNL-ABS-464695).

  11. The multi-scale modelling of coronary blood flow.

    PubMed

    Lee, Jack; Smith, Nicolas P

    2012-11-01

    Coronary flow is governed by a number of determinants including network anatomy, systemic afterload and the mechanical interaction with the myocardium throughout the cardiac cycle. The range of spatial scales and multi-physics nature of coronary perfusion highlights a need for a multiscale framework that captures the relevant details at each level of the network. The goal of this review is to provide a compact and accessible introduction to the methodology and current state of the art application of the modelling frameworks that have been used to study the coronary circulation. We begin with a brief description of the seminal experimental observations that have motivated the development of mechanistic frameworks for understanding how myocardial mechanics influences coronary flow. These concepts are then linked to an overview of the lumped parameter models employed to test these hypotheses. We then outline the full and reduced-order (3D and 1D) continuum mechanics models based on the Navier-Stokes equations and highlight, with examples, their application regimes. At the smaller spatial scales the case for the importance of addressing the microcirculation is presented, with an emphasis on the poroelastic approach that is well-suited to bridge an existing gap in the development of an integrated whole heart model. Finally, the recent accomplishments of the wave intensity analysis and related approaches are presented and the clinical outlook for coronary flow modelling discussed. PMID:22565815

  12. Relational grounding facilitates development of scientifically useful multiscale models

    PubMed Central

    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

  13. Strategy for analysis of flow diverting devices based on multi-modality image-based modeling

    PubMed Central

    Cebral, Juan R.; Mut, Fernando; Raschi, Marcelo; Ding, Yong-Hong; Kadirvel, Ramanathan; Kallmes, David

    2014-01-01

    Quantification and characterization of the hemodynamic environment created after flow diversion treatment of cerebral aneurysms is important to understand the effects of flow diverters and their interactions with the biology of the aneurysm wall and the thrombosis process that takes place subsequently. This paper describes the construction of multi-modality image-based subject-specific CFD models of experimentally created aneurysms in rabbits and subsequently treated with flow diverters. Briefly, anatomical models were constructed from 3D rotational angiography images, flow conditions were derived from Doppler ultrasound measurements, stent models were created and virtually deployed, and the results were compared to in vivo digital subtraction angiography and Doppler ultrasound images. The models were capable of reproducing in vivo observations, including velocity waveforms measured in the parent artery, peak velocity values measured in the aneurysm, and flow structures observed with digital subtraction angiography before and after deployment of flow diverters. The results indicate that regions of aneurysm occlusion after flow diversion coincide with slow and smooth flow patterns, while regions still permeable at the time of animal sacrifice were observed in parts of the aneurysm exposed to larger flow activity, i.e. higher velocities, more swirling and more complex flow structures. PMID:24719392

  14. Strategy for analysis of flow diverting devices based on multi-modality image-based modeling.

    PubMed

    Cebral, Juan R; Mut, Fernando; Raschi, Marcelo; Ding, Yong-Hong; Kadirvel, Ramanathan; Kallmes, David

    2014-10-01

    Quantification and characterization of the hemodynamic environment created after flow diversion treatment of cerebral aneurysms is important to understand the effects of flow diverters and their interactions with the biology of the aneurysm wall and the thrombosis process that takes place subsequently. This paper describes the construction of multi-modality image-based subject-specific CFD models of experimentally created aneurysms in rabbits and subsequently treated with flow diverters. Briefly, anatomical models were constructed from 3D rotational angiography images, flow conditions were derived from Doppler ultrasound measurements, stent models were created and virtually deployed, and the results were compared with in vivo digital subtraction angiography and Doppler ultrasound images. The models were capable of reproducing in vivo observations, including velocity waveforms measured in the parent artery, peak velocity values measured in the aneurysm, and flow structures observed with digital subtraction angiography before and after deployment of flow diverters. The results indicate that regions of aneurysm occlusion after flow diversion coincide with slow and smooth flow patterns, whereas regions still permeable at the time of animal sacrifice were observed in parts of the aneurysm exposed to larger flow activity, that is, higher velocities, more swirling, and more complex flow structures. PMID:24719392

  15. 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.

  16. Integrating Cellular Metabolism into a Multiscale Whole-Body Model

    PubMed Central

    Krauss, Markus; Schaller, Stephan; Borchers, Steffen; Findeisen, Rolf; Lippert, Jörg; Kuepfer, Lars

    2012-01-01

    Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development. PMID:23133351

  17. 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.

  18. 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.

  19. 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

  20. MIDA: A Multimodal Imaging-Based Detailed Anatomical Model of the Human Head and Neck

    PubMed Central

    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

  1. 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.

  2. Modeling multiscale evolution of numerous voids in shocked brittle material

    NASA Astrophysics Data System (ADS)

    Yu, Yin; Wang, Wenqiang; He, Hongliang; Lu, Tiecheng

    2014-04-01

    The influence of the evolution of numerous voids on macroscopic properties of materials is a multiscale problem that challenges computational research. A shock-wave compression model for brittle material, which can obtain both microscopic evolution and macroscopic shock properties, was developed using discrete element methods (lattice model). Using a model interaction-parameter-mapping procedure, qualitative features, as well as trends in the calculated shock-wave profiles, are shown to agree with experimental results. The shock wave splits into an elastic wave and a deformation wave in porous brittle materials, indicating significant shock plasticity. Void collapses in the deformation wave were the natural reason for volume shrinkage and deformation. However, media slippage and rotation deformations indicated by complex vortex patterns composed of relative velocity vectors were also confirmed as an important source of shock plasticity. With increasing pressure, the contribution from slippage deformation to the final plastic strain increased. Porosity was found to determine the amplitude of the elastic wave; porosity and shock stress together determine propagation speed of the deformation wave, as well as stress and strain on the final equilibrium state. Thus, shock behaviors of porous brittle material can be systematically designed for specific applications.

  3. 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.

  4. Multiscale mathematical modeling of the hypothalamo-pituitary-gonadal axis.

    PubMed

    Clément, Frédérique

    2016-07-01

    Although the fields of systems and integrative biology are in full expansion, few teams are involved worldwide into the study of reproductive function from the mathematical modeling viewpoint. This may be due to the fact that the reproductive function is not compulsory for individual organism survival, even if it is for species survival. Alternatively, the complexity of reproductive physiology may be discouraging. Indeed, the hypothalamo-pituitary-gonadal (HPG) axis involves not only several organs and tissues but also intricate time (from the neuronal millisecond timescale to circannual rhythmicity) and space (from molecules to organs) scales. Yet, mathematical modeling, and especially multiscale modeling, can renew our approaches of the molecular, cellular, and physiological processes underlying the control of reproductive functions. In turn, the remarkable dynamic features exhibited by the HPG axis raise intriguing and challenging questions to modelers and applied mathematicians. In this article, we draw a panoramic review of some mathematical models designed in the framework of the female HPG, with a special focus on the gonadal and central control of follicular development. On the gonadal side, the modeling of follicular development calls to the generic formalism of structured cell populations, that allows one to make mechanistic links between the control of cell fate (proliferation, differentiation, or apoptosis) and that of the follicle fate (ovulation or degeneration) or to investigate how the functional interactions between the oocyte and its surrounding cells shape the follicle morphogenesis. On the central, mainly hypothalamic side, models based on dynamical systems with multiple timescales allow one to represent within a single framework both the pulsatile and surge patterns of the neurohormone GnRH. Beyond their interest in basic research investigations, mathematical models can also be at the source of useful tools to study the encoding and decoding of

  5. Multi-scale Modeling of Plasticity in Tantalum.

    SciTech Connect

    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

  6. Multiscale Modeling of the Orthotropic Behaviour of PA6-6 overmoulded Composites using MMI Approach

    SciTech Connect

    Bikard, Jerome; Robert, Gilles; Moulinjeune, Olivier

    2011-05-04

    In this study the MMI ConfidentDesign multiscale approach (consisting in a non-linear multiscale simulation based on DIGIMAT registered including the injection modeling of the filled polymer and a multiscale mechanical model using the fiber orientation tensor resulting from the injection) has been combined with an orthotropic damageable elastic simulation. The anisotropic properties (including rupture criterion) are estimated and a multiscale simulation including the heterogeneous material properties issued from injection process is done. The impact of fiber ratios is then investigated. The structural simulation predicts stresses localized close to the punch, as well in injected PA66 than in composite part. Greater the fiber volume ratio, greater the modulus and more brittle the composite.

  7. Multiscale Modeling of Shock-Induced Phase Transitions in Iron

    NASA Astrophysics Data System (ADS)

    Carter, Emily; Caspersen, Kyle; Lew, Adrian; Ortiz, Michael

    2004-03-01

    Multiscale Modeling of Shock-Induced Phase Transitions in Iron Emily Carter, Kyle Caspersen, Adrian Lew and Michael Ortiz We investigate the bcc to hcp phase transition in iron under both pressure and shear. We use DFT to map out the energy landscape of uniformly deformed iron, including its equation of state and its elastic moduli as a function of volume. >From these data we construct a nonlinear-elastic energy density which gives the energy density for arbitrary - not necessarily small - deformations. The energy density contains two wells corresponding to the bcc and hcp phases. We take this multi-well energy density as a basis for the investigation of the effect of shear on the phase diagram of iron. We allow for mixed states consisting alternating lamellae of bcc and hcp phases, and, for each macroscopic deformation, we determine the optimal microstructure of the mixed state by energy minimization using a sequential-lamination algorithm. We find that the superposition of shearing deformation on a volume change has the effect of inducing mixed states of varying spatial complexity, and of markedly lowering the critical transformation pressure. Indeed, we find that shear must be taken into consideration in order to obtain agreement with measured transformation pressures. Finally, we demonstrate how the microstructure model can be integrated into large-scale finite element calculations of shocked iron.

  8. 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.

  9. 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.

  10. Full field spatially-variant image-based resolution modelling reconstruction for the HRRT.

    PubMed

    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. PMID:25596999

  11. 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

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

    PubMed Central

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

    2010-01-01

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

  13. Multi-scale Modelling of the Ocean Beneath Ice Shelves

    NASA Astrophysics Data System (ADS)

    Candy, A. S.; Kimura, S.; Holland, P.; Kramer, S. C.; Piggott, M. D.; Jenkins, A.; Pain, C. C.

    2011-12-01

    Quantitative prediction of future sea-level is currently limited because we lack an understanding of how the mass balance of the Earth's great ice sheets respond to and influence the climate. Understanding the behaviour of the ocean beneath an ice shelf and its interaction with the sheet above presents a great scientific challenge. A solid ice cover, in many places kilometres thick, bars access to the water column, so that observational data can only be obtained by drilling holes through, or launching autonomous vehicles beneath, the ice. In the absence of a comprehensive observational database, numerical modelling can be a key tool to advancing our understanding of the sub-ice-shelf regime. While we have a reasonable understanding of the overall ocean circulation and basic sensitivities, there remain critical processes that are difficult or impossible to represent in current operational models. Resolving these features adequately within a domain that includes the entire ice shelf and continental shelf to the north can be difficult with a structured horizontal resolution. It is currently impossible to adequately represent the key grounding line region, where the water column thickness reduces to zero, with a structured vertical grid. In addition, fronts and pycnoclines, the ice front geometry, shelf basal irregularities and modelling surface pressure all prove difficult in current approaches. The Fluidity-ICOM model (Piggott et al. 2008, doi:10.1002/fld.1663) simulates non-hydrostatic dynamics on meshes that can be unstructured in all three dimensions and uses anisotropic adaptive resolution which optimises the mesh and calculation in response to evolving solution dynamics. These features give it the flexibility required to tackle the challenges outlined above and the opportunity to develop a model that can improve understanding of the physical processes occurring under ice shelves. The approaches taken to develop a multi-scale model of ice shelf ocean cavity

  14. Beta test of models-3 with Community Multiscale Air Quality (CMAQ) model

    SciTech Connect

    LeDuc, S.

    1997-12-31

    The Models-3 framework for advanced air quality modeling, developed by the Environmental Protection Agency, Office of Research and Development (EPA/ORD), was provided to a limited number of beta test sites during the summer of 1997. Tutorial datasets and the Community Multiscale Air Quality (CMAQ) model were also provided. Valuable feedback on framework installation, performance, functionality, intuitiveness, user friendliness resulted from the beta test. This information will be used to guide framework improvements preparatory to public release in June 1998.

  15. A neotropical Miocene pollen database employing image-based search and semantic modeling1

    PubMed Central

    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

  16. Modeling and simulations of three-dimensional laser imaging based on space-variant structure

    NASA Astrophysics Data System (ADS)

    Cao, Jie; Hao, Qun; Peng, Yuxin; Cheng, Yang; Mu, Jiaxing; Wang, Peng; Yu, Haoyong

    2016-04-01

    A three-dimensional (3D) laser imaging system based on time of flight is proposed, based on the human retina structure. The system obtains 3D images with space-variant resolution, and we further establish mathematical models of the system and carried out simulative comparison between space-variant structure (SVS) and space-invariant structure (SIS). The system based on SVS produces significant improvements over traditional system based on SIS in the following aspects: (1) The system based on SVS uses less pixels than that based on SIS under the same field of view (FOV) and resolution. Therefore, this property is more suitable for uses in situations that require high speed and large volume data processing. (2) The system based on SVS has higher efficiency of utilization of photodiode array than that based on SIS. (3) 3D image based on SVS has the properties of rotation and scaling invariance. (4) The system based on SVS has higher echo power in outside ring of large photodiode array, which is more effective in detecting targets with low reflectance.

  17. 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.

  18. Mechanism of the Exchange Reaction in HRAS from Multiscale Modeling

    PubMed Central

    Kapoor, Abhijeet; Travesset, Alex

    2014-01-01

    HRAS regulates cell growth promoting signaling processes by cycling between active (GTP-bound) and inactive (GDP-bound) states. Understanding the transition mechanism is central for the design of small molecules to inhibit the formation of RAS-driven tumors. Using a multiscale approach involving coarse-grained (CG) simulations, all-atom classical molecular dynamics (CMD; total of 3.02 µs), and steered molecular dynamics (SMD) in combination with Principal Component Analysis (PCA), we identified the structural features that determine the nucleotide (GDP) exchange reaction. We show that weakening the coupling between the SwitchI (residues 25–40) and SwitchII (residues 59–75) accelerates the opening of SwitchI; however, an open conformation of SwitchI is unstable in the absence of guanine nucleotide exchange factors (GEFs) and rises up towards the bound nucleotide to close the nucleotide pocket. Both I21 and Y32, play a crucial role in SwitchI transition. We show that an open SwitchI conformation is not necessary for GDP destabilization but is required for GDP/Mg escape from the HRAS. Further, we present the first simulation study showing displacement of GDP/Mg away from the nucleotide pocket. Both SwitchI and SwitchII, delays the escape of displaced GDP/Mg in the absence of GEF. Based on these results, a model for the mechanism of GEF in accelerating the exchange process is hypothesized. PMID:25272152

  19. Full-hexahedral structured meshing for image-based computational vascular modeling.

    PubMed

    De Santis, Gianluca; De Beule, Matthieu; Van Canneyt, Koen; Segers, Patrick; Verdonck, Pascal; Verhegghe, Benedict

    2011-12-01

    Image-based computational modeling offers a virtual access to spatially and temporally high resolution flow and structural mechanical data in vivo. Due to inter-subject morphological variability, mesh generation represents a critical step in modeling the patient-specific geometry and is usually performed using unstructured tetrahedral meshing algorithms. Although hexahedral structured meshes are known to provide higher accuracy and reduce the computational costs both for Finite Element Analysis and Computational Fluid Dynamics, their application in computational cardiovascular studies is challenging due to the complex 3D and branching topology of vascular territories. In this study, we propose a robust procedure for structured mesh generation, tailoring the mesh structure to the subject-specific vessel topology. The proposed methodology is based on centerline-based synthetic descriptors (i.e. centerlines, radii and centerlines' normals) which are used to solve the meshing problem following a bottom-up approach. First, topologically equivalent block-structures are placed inside and outside the lumen domain. Then, a projection operation is performed, returning a parametric volume mesh which fits the original triangulated model with sub-micrometric accuracy. Additionally, a three-layered arterial wall (resembling the intima, media and adventitia) is artificially generated, with the possibility of setting variable thickness (e.g. proximal-to-distal tapering) and material anisotropy (e.g. position-dependent collagen-fibers' orientation). This new meshing procedure, implemented using open-source software packages only, is demonstrated on two challenging human cases, being an aortic arch and an abdominal aortic aneurysm. High-quality meshes are generated in both cases, according to shape-quality metrics. By increasing the computation accuracy, the developed meshing tool has the potential to further add "confidence" to the use of computational methods in vascular

  20. Image-based finite element modeling of alveolar epithelial cell injury during airway reopening.

    PubMed

    Dailey, H L; Ricles, L M; Yalcin, H C; Ghadiali, S N

    2009-01-01

    The acute respiratory distress syndrome (ARDS) is characterized by fluid accumulation in small pulmonary airways. The reopening of these fluid-filled airways involves the propagation of an air-liquid interface that exerts injurious hydrodynamic stresses on the epithelial cells (EpC) lining the airway walls. Previous experimental studies have demonstrated that these hydrodynamic stresses may cause rupture of the plasma membrane (i.e., cell necrosis) and have postulated that cell morphology plays a role in cell death. However, direct experimental measurement of stress and strain within the cell is intractable, and limited data are available on the mechanical response (i.e., deformation) of the epithelium during airway reopening. The goal of this study is to use image-based finite element models of cell deformation during airway reopening to investigate how cell morphology and mechanics influence the risk of cell injury/necrosis. Confocal microscopy images of EpC in subconfluent and confluent monolayers were used to generate morphologically accurate three-dimensional finite element models. Hydrodynamic stresses on the cells were calculated from boundary element solutions of bubble propagation in a fluid-filled parallel-plate flow channel. Results indicate that for equivalent cell mechanical properties and hydrodynamic load conditions, subconfluent cells develop higher membrane strains than confluent cells. Strain magnitudes were also found to decrease with increasing stiffness of the cell and membrane/cortex region but were most sensitive to changes in the cell's interior stiffness. These models may be useful in identifying pharmacological treatments that mitigate cell injury during airway reopening by altering specific biomechanical properties of the EpC. PMID:19008489

  1. Application of Finite Element Modeling Methods in Magnetic Resonance Imaging-Based Research and Clinical Management

    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

  2. Consideration of shear modulus in biomechanical analysis of peri-implant jaw bone: accuracy verification using image-based multi-scale simulation.

    PubMed

    Matsunaga, Satoru; Naito, Hiroyoshi; Tamatsu, Yuichi; Takano, Naoki; Abe, Shinichi; Ide, Yoshinobu

    2013-01-01

    The aim of this study was to clarify the influence of shear modulus on the analytical accuracy in peri-implant jaw bone simulation. A 3D finite element (FE) model was prepared based on micro-CT data obtained from images of a jawbone containing implants. A precise model that closely reproduced the trabecular architecture, and equivalent models that gave shear modulus values taking the trabecular architecture into account, were prepared. Displacement norms during loading were calculated, and the displacement error was evaluated. The model that gave shear modulus values taking the trabecular architecture into account showed an analytical error of around 10-20% in the cancellous bone region, while in the model that used incorrect shear modulus, the analytical error exceeded 40% in certain regions. The shear modulus should be evaluated precisely in addition to the Young modulus when considering the mechanics of peri-implant trabecular bone structure. PMID:23719004

  3. a Fractal Permeability Model for Shale Matrix with Multi-Scale Porous Structure

    NASA Astrophysics Data System (ADS)

    Sheng, Mao; Li, Gensheng; Tian, Shouceng; Huang, Zhongwei; Chen, Liqiang

    2016-01-01

    Nanopore structure and its multiscale feature significantly affect the shale-gas permeability. This paper employs fractal theory to build a shale-gas permeability model, particularly considering the effects of multiscale flow within a multiscale pore space. Contrary to previous studies which assume a bundle of capillary tubes with equal size, in this research, this model reflects various flow regimes that occur in multiscale pores and takes the measured pore-size distribution into account. The flow regime within different scales is individually determined by the Knudsen number. The gas permeability is an integral value of individual permeabilities contributed from pores of different scales. Through comparing the results of five shale samples, it is confirmed that the gas permeability varies with the pore-size distribution of the samples, even though their intrinsic permeabilities are the same. Due to consideration of multiscale flow, the change of gas permeability with pore pressure becomes more complex. Consequently, it is necessary to cover the effects of multiscale flow while determining shale-gas permeability.

  4. 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.

  5. A Combined In Vitro Imaging and Multi-Scale Modeling System for Studying the Role of Cell Matrix Interactions in Cutaneous Wound Healing.

    PubMed

    De Jesus, Aribet M; Aghvami, Maziar; Sander, Edward A

    2016-01-01

    Many cell types remodel the extracellular matrix of the tissues they inhabit in response to a wide range of environmental stimuli, including mechanical cues. Such is the case in dermal wound healing, where fibroblast migrate into and remodel the provisional fibrin matrix in a complex manner that depends in part on the local mechanical environment and the evolving multi-scale mechanical interactions of the system. In this study, we report on the development of an image-based multi-scale mechanical model that predicts the short-term (24 hours), structural reorganization of a fibrin gel by fibroblasts. These predictive models are based on an in vitro experimental system where clusters of fibroblasts (i.e., explants) were spatially arranged into a triangular geometry onto the surface of fibrin gels that were subjected to either Fixed or Free in-plane mechanical constraints. Experimentally, regional differences in short-term structural remodeling and cell migration were observed for the two gel boundary conditions. A pilot experiment indicated that these small differences in the short-term remodeling of the fibrin gel translate into substantial differences in long-term (4 weeks) remodeling, particularly in terms of collagen production. The multi-scale models were able to predict some regional differences in remodeling and qualitatively similar reorganization patterns for the two boundary conditions. However, other aspects of the model, such as the magnitudes and rates of deformation of gel, did not match the experiments. These discrepancies between model and experiment provide fertile ground for challenging model assumptions and devising new experiments to enhance our understanding of how this multi-scale system functions. These efforts will ultimately improve the predictions of the remodeling process, particularly as it relates to dermal wound healing and the reduction of patient scarring. Such models could be used to recommend patient-specific mechanical

  6. A Combined In Vitro Imaging and Multi-Scale Modeling System for Studying the Role of Cell Matrix Interactions in Cutaneous Wound Healing

    PubMed Central

    2016-01-01

    Many cell types remodel the extracellular matrix of the tissues they inhabit in response to a wide range of environmental stimuli, including mechanical cues. Such is the case in dermal wound healing, where fibroblast migrate into and remodel the provisional fibrin matrix in a complex manner that depends in part on the local mechanical environment and the evolving multi-scale mechanical interactions of the system. In this study, we report on the development of an image-based multi-scale mechanical model that predicts the short-term (24 hours), structural reorganization of a fibrin gel by fibroblasts. These predictive models are based on an in vitro experimental system where clusters of fibroblasts (i.e., explants) were spatially arranged into a triangular geometry onto the surface of fibrin gels that were subjected to either Fixed or Free in-plane mechanical constraints. Experimentally, regional differences in short-term structural remodeling and cell migration were observed for the two gel boundary conditions. A pilot experiment indicated that these small differences in the short-term remodeling of the fibrin gel translate into substantial differences in long-term (4 weeks) remodeling, particularly in terms of collagen production. The multi-scale models were able to predict some regional differences in remodeling and qualitatively similar reorganization patterns for the two boundary conditions. However, other aspects of the model, such as the magnitudes and rates of deformation of gel, did not match the experiments. These discrepancies between model and experiment provide fertile ground for challenging model assumptions and devising new experiments to enhance our understanding of how this multi-scale system functions. These efforts will ultimately improve the predictions of the remodeling process, particularly as it relates to dermal wound healing and the reduction of patient scarring. Such models could be used to recommend patient-specific mechanical

  7. Multiscale Model for the Assembly Kinetics of Protein Complexes.

    PubMed

    Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

    2016-02-01

    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. PMID:26738810

  8. WE-E-17A-01: Characterization of An Imaging-Based Model of Tumor Angiogenesis

    SciTech Connect

    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

  9. Multiscale air quality modeling of the Northeastern United States

    NASA Astrophysics Data System (ADS)

    Kumar, Naresh; Russell, Armistead G.

    The Urban and Regional Multiscale (URM) model has been used to study the ozone problem in the northeastern United States. The model was applied to a multiday ozone episode extending from 2 July 1988 to 8 July 1988. The URM model is particularly suitable for application to the Northeast as there is a dense network of urban centers along with large rural areas, and the model allows the use of variable grid sizes to effectively capture the pollutant dynamics while being computationally efficient. This study particularly concentrates on how spatial grid resolution affects results, particularly in the Northeast Corridor, a string of urban centers extending from Washington D.C. to Boston. Three different grid systems are employed in the model simulations to examine this issue. The most dynamic grid system uses grid sizes varying from 4.625 to 74 km, with the finest grids concentrated in the Northeast Corridor. The uniform grid system uses a uniform grid size of 18.5 km similar to that used in the regional oxidant model (ROM). The intermediate grid system uses grid sizes varying from 4.625 to 18.5 km. When finer grids are used over the urban areas, as in the intermediate and the most dynamic grid systems, the model predicted higher peak ozone concentrations with greater detail. Sensitivity calculations were performed to quantify the effect of various inputs on the predicted ozone. Effects of zeroing the initial conditions persisted until 7 July 1988. When using background levels of species concentrations as initial conditions, the effect lasted only for two days of simulation. Boundary conditions impacted the ozone concentrations near the boundary cells only. Emission inputs were the major factor in producing the large concentrations of ozone predicted in the Northeast Corridor. The URM model was also used to study ozone control strategy issues in the Northeast Corridor. A suite of simulations was performed where anthropogenic NO x and VOC emission levels were reducd

  10. Multi-Scale Continuum Modeling of Biological Processes

    PubMed Central

    Cheng, Y; Kekenes-Huskey, P; Hake, JE; Holst, MJ; McCammon, JA; Michailova, AP

    2012-01-01

    This article provides a brief review of multi-scale modeling at the molecular to cellular scale, with new results for heart muscle cells. A finite element-based simulation package (SMOL) was used to investigate the signaling transduction at molecular and sub-cellular scales (http://mccammon.ucsd.edu/smol/, http://FETK.org) by numerical solution of time-dependent Smoluchowski equations and a reaction-diffusion system. At the molecular scale, SMOL has yielded experimentally-validated estimates of the diffusion-limited association rates for the binding of acetylcholine to mouse acetylcholinesterase using crystallographic structural data. The predicted rate constants exhibit increasingly delayed steady-state times with increasing ionic strength and demonstrate the role of an enzyme’s electrostatic potential in influencing ligand binding. At the sub-cellular scale, an extension of SMOL solves a non-linear, reaction-diffusion system describing Ca2+ ligand buffering and diffusion in experimentally-derived rodent ventricular myocyte geometries. Results reveal the important role for mobile and stationary Ca2+ buffers, including Ca2+ indicator dye. We found that the alterations in Ca2+-binding and dissociation rates of troponin C (TnC) and total TnC concentration modulate subcellular Ca2+ signals. Model predicts that reduced off-rate in whole troponin complex (TnC, TnI, TnT) versus reconstructed thin filaments (Tn, Tm, actin) alters cytosolic Ca2+ dynamics under control conditions or in disease-linked TnC mutations. The ultimate goal of these studies is to develop scalable methods and theories for integration of molecular-scale information into simulations of cellular-scale systems. PMID:23505398

  11. 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.

  12. Multiscale modeling of the dynamics of multicellular systems

    NASA Astrophysics Data System (ADS)

    Kosztin, Ioan

    2011-03-01

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

  13. Multiscale Multiphysics and Multidomain Models I: Basic Theory

    PubMed Central

    Wei, Guo-Wei

    2013-01-01

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

  14. A nonlinear manifold-based reduced order model for multiscale analysis of heterogeneous hyperelastic materials

    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.

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

    PubMed Central

    Puglisi, G.

    2016-01-01

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

  16. 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

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

    SciTech Connect

    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

  18. Sparse Representation and Multiscale Methods - Application to Digital Elevation Models

    NASA Astrophysics Data System (ADS)

    Stefanescu, R. E. R.; Patra, A. K.; Bursik, M. I.

    2014-12-01

    In general, a Digital Elevation Model (DEM) is produced either digitizing existing maps and elevation values are interpolated from the contours, or elevation information is collected from stereo imagery on digital photogrammetric workstations. Both methods produce a DEM to the required specification, but each method contains a variety of possible production scenarios, and each method results in DEM cells with totally different character. Common artifacts found in DEM are missing-values at different location which can influence the output of the application that uses this particular DEM. In this work we introduce a numerically-stable multiscale scheme to evaluate the missing-value DEM's quantity of interest (elevation, slope, etc.). This method is very efficient for the case when dealing with large high resolution DEMs that cover large area, resulting in O(106-1010) data points. Our scheme relies on graph-based algorithms and low-rank approximations of the entire adjacency matrix of the DEM's graph. When dealing with large data sets such as DEMs, the Laplacian or kernel matrix resulted from the interaction of the data points is stupendously big. One needs to identify a subspace that capture most of the action of the kernel matrix. By the application of a randomized projection on the graph affinity matrix, a well-conditioned basis is identified for it numerical range. This basis is later used in out-of-sample extension at missing-value location. In many cases, this method beats its classical competitors in terms of accuracy, speed, and robustness.

  19. 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.

  20. Hybrid continuum–molecular modelling of multiscale internal gas flows

    SciTech Connect

    Patronis, Alexander; Lockerby, Duncan A.; Borg, Matthew K.; Reese, Jason M.

    2013-12-15

    We develop and apply an efficient multiscale method for simulating a large class of low-speed internal rarefied gas flows. The method is an extension of the hybrid atomistic–continuum approach proposed by Borg et al. (2013) [28] for the simulation of micro/nano flows of high-aspect ratio. The major new extensions are: (1) incorporation of fluid compressibility; (2) implementation using the direct simulation Monte Carlo (DSMC) method for dilute rarefied gas flows, and (3) application to a broader range of geometries, including periodic, non-periodic, pressure-driven, gravity-driven and shear-driven internal flows. The multiscale method is applied to micro-scale gas flows through a periodic converging–diverging channel (driven by an external acceleration) and a non-periodic channel with a bend (driven by a pressure difference), as well as the flow between two eccentric cylinders (with the inner rotating relative to the outer). In all these cases there exists a wide variation of Knudsen number within the geometries, as well as substantial compressibility despite the Mach number being very low. For validation purposes, our multiscale simulation results are compared to those obtained from full-scale DSMC simulations: very close agreement is obtained in all cases for all flow variables considered. Our multiscale simulation is an order of magnitude more computationally efficient than the full-scale DSMC for the first and second test cases, and two orders of magnitude more efficient for the third case.

  1. Hybrid continuum-molecular modelling of multiscale internal gas flows

    NASA Astrophysics Data System (ADS)

    Patronis, Alexander; Lockerby, Duncan A.; Borg, Matthew K.; Reese, Jason M.

    2013-12-01

    We develop and apply an efficient multiscale method for simulating a large class of low-speed internal rarefied gas flows. The method is an extension of the hybrid atomistic-continuum approach proposed by Borg et al. (2013) [28] for the simulation of micro/nano flows of high-aspect ratio. The major new extensions are: (1) incorporation of fluid compressibility; (2) implementation using the direct simulation Monte Carlo (DSMC) method for dilute rarefied gas flows, and (3) application to a broader range of geometries, including periodic, non-periodic, pressure-driven, gravity-driven and shear-driven internal flows. The multiscale method is applied to micro-scale gas flows through a periodic converging-diverging channel (driven by an external acceleration) and a non-periodic channel with a bend (driven by a pressure difference), as well as the flow between two eccentric cylinders (with the inner rotating relative to the outer). In all these cases there exists a wide variation of Knudsen number within the geometries, as well as substantial compressibility despite the Mach number being very low. For validation purposes, our multiscale simulation results are compared to those obtained from full-scale DSMC simulations: very close agreement is obtained in all cases for all flow variables considered. Our multiscale simulation is an order of magnitude more computationally efficient than the full-scale DSMC for the first and second test cases, and two orders of magnitude more efficient for the third case.

  2. Atmospheric Correction Comparison of SPOT-5 Image Based on Model Flaash and Model Quac

    NASA Astrophysics Data System (ADS)

    Guo, Y.; ZENG, F.

    2012-07-01

    tmospheric correction of satellite remote sensing image is the precondition of quantitative remote sensing study, and also among the difficulties of it. There are various methods and models for atmospheric correction. The author makes the atmospheric correction of SPOT-5 multi-spectrum remote sensing image covering Changsha, Zhuzhou and Xiangtan by adopting Model FLAASH and Model QUAC in the trail, and then makes a contrastive analysis of the image before and after the correction from the point of sight, surface features spectral curve and RVI result. The results show that both models with their specific scope of application can both basically eliminate the atmospheric effects and can restore the typical characteristics of various surface features spectral better, emphasis the vegetation information; the one using Model FLASSH has higher accuracy than the one using Model QUAC; it is more convenient to use Model QUAL than Model FLASSH, because it has little dependence on input parameters and calibration accuracy of instruments.

  3. A multiscale modeling study for the convective mass transfer in a subsurface aquifer

    NASA Astrophysics Data System (ADS)

    Alam, Jahrul M.

    2015-09-01

    Quantitative and realistic computer simulations of mass transfer associated with disposal in subsurface aquifers is a challenging endeavor. This article has proposed a novel and efficient multiscale modeling framework, and has examined its potential to study the penetrative mass transfer in a plume that migrates in an aquifer. Numerical simulations indicate that the migration of the injected enhances the vorticity generation, and the dissolution of has a strong effect on the natural convection mass transfer. The vorticity decays with the increase of the porosity. The time scale of the vertical migration of a plume is strongly dependent on the rate of dissolution. Comparisons confirm the near optimal performance of the proposed multiscale model. These primary results with an idealized computational model of the migration in an aquifer brings the potential of the proposed multiscale model to the field of heat and mass transfer in the geoscience.

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

    NASA Technical Reports Server (NTRS)

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

    2015-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2015-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2015-01-01

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

  7. 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.

  8. 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.

  9. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2006-01-01

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

  11. Using Multi-scale Modeling Systems to Study the Precipitation Processes

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2007-01-01

    Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (CRM), (2) a regional scale model, (3) a coupled CRM and global model, and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer processes and the explicit cloud-radiation, and cloudland surface interactive processes are applied in this multi-scale modeling system. 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.

  12. Evaluation of the Community Multiscale Air Quality model version 5.1

    EPA Science Inventory

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

  13. Multiscale models of colloidal dispersion of particles in nematic liquid crystals.

    PubMed

    Bennett, T P; D'Alessandro, G; Daly, K R

    2014-12-01

    We use homogenization theory to develop a multiscale model of colloidal dispersion of particles in nematic liquid crystals under weak-anchoring conditions. We validate the model by comparing it with simulations by using the Landau-de Gennes free energy and show that the agreement is excellent. We then use the multiscale model to study the effect that particle anisotropy has on the liquid crystal: spherically symmetric particles always reduce the effective elastic constant. Asymmetric particles introduce an effective alignment field that can increase the Fredericks threshold and decrease the switch-off time. PMID:25615117

  14. A stochastic multiscale framework for modeling flow through random heterogeneous porous media

    SciTech Connect

    Ganapathysubramanian, B.; Zabaras, N.

    2009-02-01

    Flow through porous media is ubiquitous, occurring from large geological scales down to the microscopic scales. Several critical engineering phenomena like contaminant spread, nuclear waste disposal and oil recovery rely on accurate analysis and prediction of these multiscale phenomena. Such analysis is complicated by inherent uncertainties as well as the limited information available to characterize the system. Any realistic modeling of these transport phenomena has to resolve two key issues: (i) the multi-length scale variations in permeability that these systems exhibit, and (ii) the inherently limited information available to quantify these property variations that necessitates posing these phenomena as stochastic processes. A stochastic variational multiscale formulation is developed to incorporate uncertain multiscale features. A stochastic analogue to a mixed multiscale finite element framework is used to formulate the physical stochastic multiscale process. Recent developments in linear and non-linear model reduction techniques are used to convert the limited information available about the permeability variation into a viable stochastic input model. An adaptive sparse grid collocation strategy is used to efficiently solve the resulting stochastic partial differential equations (SPDEs). The framework is applied to analyze flow through random heterogeneous media when only limited statistics about the permeability variation are given.

  15. 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.

  16. Image-based flow modeling in a two-chamber model of the left heart

    NASA Astrophysics Data System (ADS)

    Vedula, Vijay; Seo, Jung-Hee; Shoele, Kourosh; George, Richard; Younes, Laurent; Mittal, Rajat

    2014-11-01

    Computational modeling of cardiac flows has been an active topic of discussion over the past decade. Modeling approaches have been consistently improved by inclusion of additional complexities and these continue to provide new insights into the dynamics of blood flow in health and disease. The vast majority of cardiac models have been single-chamber models, which have typically focused on the left or right ventricles, and in these models, the atria are modeled in highly simplistic ways. However, the left atrium acts as a mixing chamber and works with the left ventricle in a highly coordinated fashion to move the blood from the pulmonary veins to the aorta. The flow dynamics associated with this two-chamber interaction is not well understood. In addition, the flow in the left atrium has by itself significant clinical implications and our understanding of this is far less than that of the left ventricle. In the current study, we use 4D CT to create a physiological heart model that is functionally normal and use an experimentally validated sharp-interface immersed boundary flow solver to explore the atrio-ventricular interaction and develop insights into some of the questions addressed above. This research is supported by the U.S. National Science Foundation through NSF Grants IOS-1124804 and IIS-1344772. Computational resources are provided in part through the NSF XSEDE grants TG-CTS100002 and TG-CTS130064.

  17. 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

  18. 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

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  20. The potential vorticity budget of the multi-scale models of the MJO

    NASA Astrophysics Data System (ADS)

    Remmel, M.; Biello, J. A.; Majda, A.

    2012-12-01

    Zhang and Ling (J.Atmos Sci. 2012) performed a comprehensive analysis of the potential vorticity budget of the MJO, distinguishing it from Rossby and Kelvin waves. Biello and Majda have used the IPESD multi-scale framework of tropical dynamics to create kinematic models of the MJO which distinguish an MJO forced by in-scale heating with ones forced by fluxes of momentum and temperature from synoptic to MJO scales. In this study we use the results of Zhang and Ling as a benchmark for comparing the different multi-scale models. In particular, a PV budget can be obtained in the multi-scale framework, and PV advection, in-scale generation, and upscale generation terms are compared.

  1. 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

  2. Ensuring Congruency in Multiscale Modeling: Towards Linking Agent Based and Continuum Biomechanical Models of Arterial Adaptation

    PubMed Central

    Hayenga, Heather N.; Thorne, Bryan C.; Peirce, Shayn M.; Humphrey, Jay D.

    2011-01-01

    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. PMID:21809144

  3. 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

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

    PubMed

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

    2011-10-01

    Future multiscale and multiphysics models that support research into human disease, translational medical science, and treatment can utilize the power of high-performance computing (HPC) systems. We anticipate that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message-passing processes [e.g., the message-passing interface (MPI)] with multithreading (e.g., OpenMP, Pthreads). The objective of this study is to compare the performance of such hybrid programming models when applied to the simulation of a realistic physiological multiscale model of the heart. Our results show that the hybrid models perform favorably when compared to an implementation using only the MPI and, furthermore, that OpenMP in combination with the MPI provides a satisfactory compromise between performance and code complexity. Having the ability to use threads within MPI processes enables the sophisticated use of all processor cores for both computation and communication phases. Considering that HPC systems in 2012 will have two orders of magnitude more cores than what was used in this study, we believe that faster than real-time multiscale cardiac simulations can be achieved on these systems. PMID:21768044

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

    PubMed

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

    2016-09-01

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

  6. A second gradient theoretical framework for hierarchical multiscale modeling of materials

    SciTech Connect

    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.

  7. A hierarchical framework for the multiscale modeling of microstructure evolution in heterogeneous materials.

    SciTech Connect

    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.

  8. Multiscale musculoskeletal modelling, data-model fusion and electromyography-informed modelling.

    PubMed

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

    2016-04-01

    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

  9. Multiscale model for pulmonary oxygen uptake and its application to quantify hypoxemia in hepatopulmonary syndrome.

    PubMed

    Chakraborty, Saikat; Balakotaiah, Vemuri; Bidani, Akhil

    2007-01-21

    This paper presents a novel multiscale methodology for quantitative analysis of pulmonary gas exchange. The process of oxygen uptake in the lungs is a complex multiscale process, characterized by multiple time and length scales which are coupled nonlinearly through the processes of diffusion, convection and reaction, and the overall oxygen uptake is significantly influenced by the transport and reaction rate processes at the small-scales. Based on the separation of length scales, we characterize these disparate scales by three representative ones, namely micro (red blood cell), meso (capillary and alveolus) and macro (lung). We start with the fundamental convection-diffusion-reaction (CDR) equation that quantifies transport and reaction rates at each scale and apply spatial averaging techniques to reduce the dimensionality of these models. The resultant low-dimensional models embed each scale hierarchically within the other while retaining the important parameters of the small-scales in the averaged equations, and drastically reduce the computational efforts involved in solving them. We use our multiscale model for pulmonary gas exchange to quantify the oxygen uptake abnormalities in patients with hepatopulmonary syndrome (HPS), a disease which is characterized by coupled abnormalities in multiple length scales. Based on our multiscale modeling, we suggest a strategy to stratify patients with HPS into two categories--those who are oxygen-responsive and those who are oxygen non-responsive with intractable hypoxemia. PMID:16973178

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

    EPA Science Inventory

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

  11. Multiscale Modeling for Linking Growth, Microstructure, and Properties of Inorganic Microporous Films

    NASA Technical Reports Server (NTRS)

    Vlachos, Dion G.

    2002-01-01

    The focus of this presentation is on multiscale modeling in order to link processing, microstructure, and properties of materials. Overview of problems we study includes: Growth mechanisms in chemical and physical vapor epitaxy; thin films of zeolites for separation and sensing; thin Pd films for hydrogen separation and pattern formation by self-regulation routes.

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

    EPA Science Inventory

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

  13. 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.

  14. Multi-class and multi-scale models of complex biological phenomena.

    PubMed

    Yu, Jessica S; Bagheri, Neda

    2016-06-01

    Computational modeling has significantly impacted our ability to analyze vast (and exponentially increasing) quantities of experimental data for a variety of applications, such as drug discovery and disease forecasting. Single-scale, single-class models persist as the most common group of models, but biological complexity often demands more sophisticated approaches. This review surveys modeling approaches that are multi-class (incorporating multiple model types) and/or multi-scale (accounting for multiple spatial or temporal scales) and describes how these models, and combinations thereof, should be used within the context of the problem statement. We end by highlighting agent-based models as an intuitive, modular, and flexible framework within which multi-scale and multi-class models can be implemented. PMID:27115496

  15. Urban air quality simulation with community multi-scale air quality (CMAQ) modeling system

    SciTech Connect

    Byun, D.; Young, J.; Gipson, G.; Schere, K.; Godowitch, J.

    1998-11-01

    In an effort to provide a state-of-the-science air quality modeling capability, US EPA has developed a new comprehensive and flexible Models-3 Community Multi-scale Air Quality (CMAQ) modeling system. The authors demonstrate CMAQ simulations for a high ozone episode in the northeastern US during 12-15 July 1995 and discuss meteorological issues important for modeling of urban air quality.

  16. A multiphysics and multiscale software environment for modeling astrophysical systems

    NASA Astrophysics Data System (ADS)

    Portegies Zwart, Simon; McMillan, Steve; Harfst, Stefan; Groen, Derek; Fujii, Michiko; Nualláin, Breanndán Ó.; Glebbeek, Evert; Heggie, Douglas; Lombardi, James; Hut, Piet; Angelou, Vangelis; Banerjee, Sambaran; Belkus, Houria; Fragos, Tassos; Fregeau, John; Gaburov, Evghenii; Izzard, Rob; Jurić, Mario; Justham, Stephen; Sottoriva, Andrea; Teuben, Peter; van Bever, Joris; Yaron, Ofer; Zemp, Marcel

    2009-05-01

    We present MUSE, a software framework for combining existing computational tools for different astrophysical domains into a single multiphysics, multiscale application. MUSE facilitates the coupling of existing codes written in different languages by providing inter-language tools and by specifying an interface between each module and the framework that represents a balance between generality and computational efficiency. This approach allows scientists to use combinations of codes to solve highly coupled problems without the need to write new codes for other domains or significantly alter their existing codes. MUSE currently incorporates the domains of stellar dynamics, stellar evolution and stellar hydrodynamics for studying generalized stellar systems. We have now reached a "Noah's Ark" milestone, with (at least) two available numerical solvers for each domain. MUSE can treat multiscale and multiphysics systems in which the time- and size-scales are well separated, like simulating the evolution of planetary systems, small stellar associations, dense stellar clusters, galaxies and galactic nuclei. In this paper we describe three examples calculated using MUSE: the merger of two galaxies, the merger of two evolving stars, and a hybrid N-body simulation. In addition, we demonstrate an implementation of MUSE on a distributed computer which may also include special-purpose hardware, such as GRAPEs or GPUs, to accelerate computations. The current MUSE code base is publicly available as open source at http://muse.li.

  17. A multiscale approach to model hydrogen bonding: The case of polyamide

    NASA Astrophysics Data System (ADS)

    Gowers, Richard J.; Carbone, Paola

    2015-06-01

    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.

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

    PubMed Central

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

    2012-01-01

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

  19. A multiscale approach to model hydrogen bonding: The case of polyamide

    SciTech Connect

    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.

  20. 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

  1. Stochastic multiscale modelling of cortical bone elasticity based on high-resolution imaging.

    PubMed

    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

  2. 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.

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

    PubMed Central

    2013-01-01

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

  4. An imaging-based tumour growth and treatment response model: investigating the effect of tumour oxygenation on radiation therapy response

    NASA Astrophysics Data System (ADS)

    Titz, Benjamin; Jeraj, Robert

    2008-09-01

    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.

  5. A Global and Regional Multi-scale Advanced Prediction Model System(graps) Part I: A Scientific Design of A Nh/h Multi-scale Dynamic Model

    NASA Astrophysics Data System (ADS)

    Chen, Dehui; Xue Xuesheng Yang, Jishan; Zhang, Hongliang; Hu, Jianglin; Jin, Zhiyan; Huang, Liping; Wu, Xiangjun

    With social progress and economic development, the requirement for providing much longer, more detailed and more accurate meteorological forecasting services with higher resolution, including climate, synoptic and meso-scale weather forecasts, and air pollution as well as forest fire warning is increased significantly. On the other hand, to meet all needs of services, the numerical weather prediction models will become more and more complicated, and more and more "huge". The costs for improvement and maintenance will be expensive if several NWP systems are to be developed, improved and maintained at the same time and at the same center! In this paper, a Global and Regional multi-scale Advanced Prediction model System (GRAPS) was designed to meet all needs of short, medium and long range weather forecasts as well as environmental predictions. The main features of the GRAPS model include (1) full latitude-longitude grid points; (2) multi-scale in an unified model; (3) hydrostatic or non hydrostatic hypotheses optionally; (4) variable or uniform resolution in option; (5) possibility to run in regional or global mode; (6) finite difference in the vertical discretization in option; (7) semi-implicit and semi - Lagrangian scheme; (8) height terrain-following coordinate; (9) Arakawa-C variable staggering; (10) Cascade-interpolation; (11) quasi-conservation of semi-Lagrangian advection scheme combined Staniforth (1992) and Preistley (1993). Key Words: numerical weather prediction, grid point model, non-hydrostatic, variable resolution, vertical spectral formulation

  6. A Multiscale Computational Model of the Heart: Exploring Space Medicine and Terrestrial Applications

    NASA Technical Reports Server (NTRS)

    Gladding, Patrick; Orr, Martin; Kazuaki, Negishi; Borowski, Alan; Hussan, Jagir R.; Hunter, Peter; Kassemi, Mohammed; Martin, David; Levine, Benjamin; Schlegel, Todd T.; Thomas, James D.

    2016-01-01

    The impact of long-term spaceflight on cardiac electromechanical function is unknown. Integrating heterogeneous biophysical data from sources such as echocardiography (Echo), electrocardiography (ECG), and genomics into a mathematical model could be used to predict cardiac dysfunction in space. We have developed a multiscale heart model, onto which astronaut-specific ultrasound data can be imposed, with the aim of integrating advanced ECG (A-ECG) and genomic data.

  7. 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.

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

  11. Multiscale Modeling of Gene-Behavior Associations in an Artificial Neural Network Model of Cognitive Development.

    PubMed

    Thomas, Michael S C; Forrester, Neil A; Ronald, Angelica

    2016-01-01

    In the multidisciplinary field of developmental cognitive neuroscience, statistical associations between levels of description play an increasingly important role. One example of such associations is the observation of correlations between relatively common gene variants and individual differences in behavior. It is perhaps surprising that such associations can be detected despite the remoteness of these levels of description, and the fact that behavior is the outcome of an extended developmental process involving interaction of the whole organism with a variable environment. Given that they have been detected, how do such associations inform cognitive-level theories? To investigate this question, we employed a multiscale computational model of development, using a sample domain drawn from the field of language acquisition. The model comprised an artificial neural network model of past-tense acquisition trained using the backpropagation learning algorithm, extended to incorporate population modeling and genetic algorithms. It included five levels of description-four internal: genetic, network, neurocomputation, behavior; and one external: environment. Since the mechanistic assumptions of the model were known and its operation was relatively transparent, we could evaluate whether cross-level associations gave an accurate picture of causal processes. We established that associations could be detected between artificial genes and behavioral variation, even under polygenic assumptions of a many-to-one relationship between genes and neurocomputational parameters, and when an experience-dependent developmental process interceded between the action of genes and the emergence of behavior. We evaluated these associations with respect to their specificity (to different behaviors, to function vs. structure), to their developmental stability, and to their replicability, as well as considering issues of missing heritability and gene-environment interactions. We argue that gene

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

    EPA Science Inventory

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

  13. A multi-scale urban atmospheric dispersion model for emergency management

    NASA Astrophysics Data System (ADS)

    Miao, Yucong; Liu, Shuhua; Zheng, Hui; Zheng, Yijia; Chen, Bicheng; Wang, Shu

    2014-11-01

    To assist emergency management planning and prevention in case of hazardous chemical release into the atmosphere, especially in densely built-up regions with large populations, a multi-scale urban atmospheric dispersion model was established. Three numerical dispersion experiments, at horizontal resolutions of 10 m, 50 m and 3000 m, were performed to estimate the adverse effects of toxic chemical release in densely built-up areas. The multi-scale atmospheric dispersion model is composed of the Weather Forecasting and Research (WRF) model, the Open Source Field Operation and Manipulation software package, and a Lagrangian dispersion model. Quantification of the adverse health effects of these chemical release events are given by referring to the U.S. Environmental Protection Agency's Acute Exposure Guideline Levels. The wind fields of the urban-scale case, with 3 km horizontal resolution, were simulated by the Beijing Rapid Update Cycle system, which were utilized by the WRF model. The sub-domain-scale cases took advantage of the computational fluid dynamics method to explicitly consider the effects of buildings. It was found that the multi-scale atmospheric dispersion model is capable of simulating the flow pattern and concentration distribution on different scales, ranging from several meters to kilometers, and can therefore be used to improve the planning of prevention and response programs.

  14. Multiscale modeling of ultrafast element-specific magnetization dynamics of ferromagnetic alloys

    NASA Astrophysics Data System (ADS)

    Hinzke, D.; Atxitia, U.; Carva, K.; Nieves, P.; Chubykalo-Fesenko, O.; Oppeneer, P. M.; Nowak, U.

    2015-08-01

    A hierarchical multiscale approach to model the magnetization dynamics of ferromagnetic random alloys is presented. First-principles calculations of the Heisenberg exchange integrals are linked to atomistic spin models based upon the stochastic Landau-Lifshitz-Gilbert (LLG) equation to calculate temperature-dependent parameters (e.g., effective exchange interactions, damping parameters). These parameters are subsequently used in the Landau-Lifshitz-Bloch (LLB) model for multisublattice magnets to calculate numerically and analytically the ultrafast demagnetization times. The developed multiscale method is applied here to FeNi (permalloy) as well as to copper-doped FeNi alloys. We find that after an ultrafast heat pulse the Ni sublattice demagnetizes faster than the Fe sublattice for the here-studied FeNi-based alloys.

  15. 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.

  16. A semi-automatic image-based close range 3D modeling pipeline using a multi-camera configuration.

    PubMed

    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

  17. A Semi-Automatic Image-Based Close Range 3D Modeling Pipeline Using a Multi-Camera Configuration

    PubMed Central

    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

  18. A Multiphysics and Multiscale Software Environment for Modeling Astrophysical Systems

    NASA Astrophysics Data System (ADS)

    Portegies Zwart, Simon; McMillan, Steve; O'Nualláin, Breanndán; Heggie, Douglas; Lombardi, James; Hut, Piet; Banerjee, Sambaran; Belkus, Houria; Fragos, Tassos; Fregeau, John; Fuji, Michiko; Gaburov, Evghenii; Glebbeek, Evert; Groen, Derek; Harfst, Stefan; Izzard, Rob; Jurić, Mario; Justham, Stephen; Teuben, Peter; van Bever, Joris; Yaron, Ofer; Zemp, Marcel

    We present MUSE, a software framework for tying together existing computational tools for different astrophysical domains into a single multiphysics, multiscale workload. MUSE facilitates the coupling of existing codes written in different languages by providing inter-language tools and by specifying an interface between each module and the framework that represents a balance between generality and computational efficiency. This approach allows scientists to use combinations of codes to solve highly-coupled problems without the need to write new codes for other domains or significantly alter their existing codes. MUSE currently incorporates the domains of stellar dynamics, stellar evolution and stellar hydrodynamics for a generalized stellar systems workload. MUSE has now reached a "Noah's Ark" milestone, with two available numerical solvers for each domain. MUSE can treat small stellar associations, galaxies and everything in between, including planetary systems, dense stellar clusters and galactic nuclei. Here we demonstrate an examples calculated with MUSE: the merger of two galaxies. In addition we demonstrate the working of MUSE on a distributed computer. The current MUSE code base is publicly available as open source at http://muse.li.

  19. Multi-scale modelling of uranyl chloride solutions

    SciTech Connect

    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.

  20. A systematic multiscale modeling and experimental approach to protect grain boundaries in magnesium alloys from corrosion

    SciTech Connect

    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.

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

    PubMed

    Hamdi, Mustapha

    2009-12-01

    Developments in the field of nanobiodevices coupling nanostructures and biological components are of great interest in medical nanorobotics. As the fundamentals of bio/non-bio interaction processes are still poorly understood in the design of these devices, design tools and multiscale dynamics modeling approaches are necessary at the fabrication pre-project stage. This paper proposes a new concept of optimized carbon nanotube based servomotor design for drug delivery and biomolecular transport applications. The design of an encapsulated DNA-multi-walled carbon nanotube actuator is prototyped using multiscale modeling. The system is parametrized by using a quantum level approach and characterized by using a molecular dynamics simulation. Based on the analysis of the simulation results, a servo nanoactuator using ionic current feedback is simulated and analyzed for application as a drug delivery carrier. PMID:19880974

  2. Multiscale Model Predicts Tissue-Level Failure From Collagen Fiber-Level Damage

    PubMed Central

    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

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

  4. Multiscale Modeling of the Deformation of Advanced Ferritic Steels for Generation IV Nuclear Energy

    SciTech Connect

    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.

  5. A Multiscale Model Based On Intragranular Microstructure — Prediction Of Dislocation Patterns At The Microscopic Scale

    NASA Astrophysics Data System (ADS)

    Franz, Gérald; Abed-Meraim, Farid; Zineb, Tarak Ben; Lemoine, Xavier; Berveiller, Marcel

    2007-04-01

    A large strain elastic-plastic single crystal constitutive law, based on dislocation annihilation and storage, is implemented in a new self-consistent scheme, leading to a multiscale model which achieves, for each grain, the calculation of plastic slip activity, with help of regularized formulation drawn from visco-plasticity, and dislocation microstructure evolution. This paper focuses on the relationship between the deformation history of a BCC grain and induced microstructure during monotonic and two-stage strain paths.

  6. Evaluating and Improving Cloud Processes in the Multi-Scale Modeling Framework

    SciTech Connect

    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

  7. A multiscale modeling technique for bridging molecular dynamics with finite element method

    SciTech Connect

    Lee, Yongchang Basaran, Cemal

    2013-11-15

    In computational mechanics, molecular dynamics (MD) and finite element (FE) analysis are well developed and most popular on nanoscale and macroscale analysis, respectively. MD can very well simulate the atomistic behavior, but cannot simulate macroscale length and time due to computational limits. FE can very well simulate continuum mechanics (CM) problems, but has the limitation of the lack of atomistic level degrees of freedom. Multiscale modeling is an expedient methodology with a potential to connect different levels of modeling such as quantum mechanics, molecular dynamics, and continuum mechanics. This study proposes a new multiscale modeling technique to couple MD with FE. The proposed method relies on weighted average momentum principle. A wave propagation example has been used to illustrate the challenges in coupling MD with FE and to verify the proposed technique. Furthermore, 2-Dimensional problem has also been used to demonstrate how this method would translate into real world applications. -- Highlights: •A weighted averaging momentum method is introduced for bridging molecular dynamics (MD) with finite element (FE) method. •The proposed method shows excellent coupling results in 1-D and 2-D examples. •The proposed method successfully reduces the spurious wave reflection at the border of MD and FE regions. •Big advantages of the proposed method are simplicity and inexpensive computational cost of multiscale analysis.

  8. Multiscale Enaction Model (MEM): the case of complexity and "context-sensitivity" in vision.

    PubMed

    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

  9. Multiscale Enaction Model (MEM): the case of complexity and “context-sensitivity” in vision

    PubMed Central

    Laurent, Éric

    2014-01-01

    I review the data on human visual perception that reveal the critical role played by non-visual contextual factors influencing visual activity. The global perspective that progressively emerges reveals that vision is sensitive to multiple couplings with other systems whose nature and levels of abstraction in science are highly variable. Contrary to some views where vision is immersed in modular hard-wired modules, rather independent from higher-level or other non-cognitive processes, converging data gathered in this article suggest that visual perception can be theorized in the larger context of biological, physical, and social systems with which it is coupled, and through which it is enacted. Therefore, any attempt to model complexity and multiscale couplings, or to develop a complex synthesis in the fields of mind, brain, and behavior, shall involve a systematic empirical study of both connectedness between systems or subsystems, and the embodied, multiscale and flexible teleology of subsystems. The conceptual model (Multiscale Enaction Model [MEM]) that is introduced in this paper finally relates empirical evidence gathered from psychology to biocomputational data concerning the human brain. Both psychological and biocomputational descriptions of MEM are proposed in order to help fill in the gap between scales of scientific analysis and to provide an account for both the autopoiesis-driven search for information, and emerging perception. PMID:25566115

  10. 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

  11. Use of QM/DMD as a Multiscale Approach to Modeling Metalloenzymes.

    PubMed

    Gallup, N M; Alexandrova, A N

    2016-01-01

    Enzymes are complex biomolecules capable of performing unique catalysis under physiological conditions at neutral temperature and pH. However, the architecture of enzymatic catalysis is often a combination of the quantum influence of the immediate active site, as well as the electrostatic and configurational influences of amino acids surrounding the active site. As a result of this cooperation between baseline chemical reactivity and electrostatic assistance, it has become important to model enzymes using multiscale methods that take advantage of treating the active site with quantum mechanical methods, while approximately treating the surrounding protein using cheaper, classically driven force-field molecular mechanics methods. Here we describe the use of a multiscale engine which utilizes a combination of density functional theory with discrete molecular dynamics (dubbed QM/DMD) to aid in the characterization of metalloenzymes. PMID:27498643

  12. 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.

  13. Multiscale Modeling of Carbon/Phenolic Composite Thermal Protection Materials: Atomistic to Effective Properties

    NASA Technical Reports Server (NTRS)

    Arnold, Steven M.; Murthy, Pappu L.; Bednarcyk, Brett A.; Lawson, John W.; Monk, Joshua D.; Bauschlicher, Charles W., Jr.

    2016-01-01

    Next generation ablative thermal protection systems are expected to consist of 3D woven composite architectures. It is well known that composites can be tailored to achieve desired mechanical and thermal properties in various directions and thus can be made fit-for-purpose if the proper combination of constituent materials and microstructures can be realized. In the present work, the first, multiscale, atomistically-informed, computational analysis of mechanical and thermal properties of a present day - Carbon/Phenolic composite Thermal Protection System (TPS) material is conducted. Model results are compared to measured in-plane and out-of-plane mechanical and thermal properties to validate the computational approach. Results indicate that given sufficient microstructural fidelity, along with lowerscale, constituent properties derived from molecular dynamics simulations, accurate composite level (effective) thermo-elastic properties can be obtained. This suggests that next generation TPS properties can be accurately estimated via atomistically informed multiscale analysis.

  14. The role of continuity in residual-based variational multiscale modeling of turbulence

    NASA Astrophysics Data System (ADS)

    Akkerman, I.; Bazilevs, Y.; Calo, V. M.; Hughes, T. J. R.; Hulshoff, S.

    2008-02-01

    This paper examines the role of continuity of the basis in the computation of turbulent flows. We compare standard finite elements and non-uniform rational B-splines (NURBS) discretizations that are employed in Isogeometric Analysis (Hughes et al. in Comput Methods Appl Mech Eng, 194:4135 4195, 2005). We make use of quadratic discretizations that are C 0-continuous across element boundaries in standard finite elements, and C 1-continuous in the case of NURBS. The variational multiscale residual-based method (Bazilevs in Isogeometric analysis of turbulence and fluid-structure interaction, PhD thesis, ICES, UT Austin, 2006; Bazilevs et al. in Comput Methods Appl Mech Eng, submitted, 2007; Calo in Residual-based multiscale turbulence modeling: finite volume simulation of bypass transition. PhD thesis, Department of Civil and Environmental Engineering, Stanford University, 2004; Hughes et al. in proceedings of the XXI international congress of theoretical and applied mechanics (IUTAM), Kluwer, 2004; Scovazzi in Multiscale methods in science and engineering, PhD thesis, Department of Mechanical Engineering, Stanford Universty, 2004) is employed as a turbulence modeling technique. We find that C 1-continuous discretizations outperform their C 0-continuous counterparts on a per-degree-of-freedom basis. We also find that the effect of continuity is greater for higher Reynolds number flows.

  15. An imaging-based stochastic model for simulation of tumour vasculature

    PubMed Central

    Adhikarla, Vikram; Jeraj, Robert

    2013-01-01

    A mathematical model which reconstructs the structure of existing vasculature using patient-specific anatomical, functional and molecular imaging as input was developed. The vessel structure is modelled according to empirical vascular parameters, such as the mean vessel branching angle. The model is calibrated such that the resultant oxygen map modelled from the simulated microvasculature stochastically matches the input oxygen map to a high degree of accuracy (R2 ≈ 1). The calibrated model was successfully applied to preclinical imaging data. Starting from the anatomical vasculature image (obtained from contrast-enhanced computed tomography), a representative map of the complete vasculature was stochastically simulated as determined by the oxygen map (obtained from hypoxia [64Cu]Cu-ATSM positron emission tomography). The simulated microscopic vasculature and the calculated oxygenation map successfully represent the imaged hypoxia distribution (R2 = 0.94). The model elicits the parameters required to simulate vasculature consistent with imaging and provides a key mathematical relationship relating the vessel volume to the tissue oxygen tension. Apart from providing an excellent framework for visualizing the imaging gap between the microscopic and macroscopic imagings, the model has the potential to be extended as a tool to study the dynamics between the tumour and the vasculature in a patient-specific manner and has an application in the simulation of anti-angiogenic therapies. PMID:22971525

  16. Continuum Level Formulation and Implementation of a Multi-scale Model for Vanadium

    SciTech Connect

    Lawrence Livermore National Laboratory

    2009-08-17

    A multi-scale approach is used to construct a continuum strength model for vanadium. The model is formulated assuming plastic deformation by dislocation motion and strain hardening due to dislocation interactions. Dislocation density is adopted as the state variable in the model. Information from molecular statics, molecular dynamics and dislocation dynamics simulations is combined to create kinetic relations for dislocation motion, strain hardening relations and evolution equations for the dislocation density. Implicit time integration of the constitutive equations is described in the context of implementation in a finite element code. Results are provided illustrating the strain, strain rate, temperature and pressure dependence of the constitutive model.

  17. 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

  18. 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.

  19. 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

  20. Prediction of water loss and viscoelastic deformation of apple tissue using a multiscale model.

    PubMed

    Aregawi, Wondwosen A; Abera, Metadel K; Fanta, Solomon W; Verboven, Pieter; Nicolai, Bart

    2014-11-19

    A two-dimensional multiscale water transport and mechanical model was developed to predict the water loss and deformation of apple tissue (Malus × domestica Borkh. cv. 'Jonagold') during dehydration. At the macroscopic level, a continuum approach was used to construct a coupled water transport and mechanical model. Water transport in the tissue was simulated using a phenomenological approach using Fick's second law of diffusion. Mechanical deformation due to shrinkage was based on a structural mechanics model consisting of two parts: Yeoh strain energy functions to account for non-linearity and Maxwell's rheological model of visco-elasticity. Apparent parameters of the macroscale model were computed from a microscale model. The latter accounted for water exchange between different microscopic structures of the tissue (intercellular space, the cell wall network and cytoplasm) using transport laws with the water potential as the driving force for water exchange between different compartments of tissue. The microscale deformation mechanics were computed using a model where the cells were represented as a closed thin walled structure. The predicted apparent water transport properties of apple cortex tissue from the microscale model showed good agreement with the experimentally measured values. Deviations between calculated and measured mechanical properties of apple tissue were observed at strains larger than 3%, and were attributed to differences in water transport behavior between the experimental compression tests and the simulated dehydration-deformation behavior. Tissue dehydration and deformation in the high relative humidity range ( > 97% RH) could, however, be accurately predicted by the multiscale model. The multiscale model helped to understand the dynamics of the dehydration process and the importance of the different microstructural compartments (intercellular space, cell wall, membrane and cytoplasm) for water transport and mechanical deformation

  1. Multi-Scale Modeling in Morphogenesis: A Critical Analysis of the Cellular Potts Model

    PubMed Central

    Voss-Böhme, Anja

    2012-01-01

    Cellular Potts models (CPMs) are used as a modeling framework to elucidate mechanisms of biological development. They allow a spatial resolution below the cellular scale and are applied particularly when problems are studied where multiple spatial and temporal scales are involved. Despite the increasing usage of CPMs in theoretical biology, this model class has received little attention from mathematical theory. To narrow this gap, the CPMs are subjected to a theoretical study here. It is asked to which extent the updating rules establish an appropriate dynamical model of intercellular interactions and what the principal behavior at different time scales characterizes. It is shown that the longtime behavior of a CPM is degenerate in the sense that the cells consecutively die out, independent of the specific interdependence structure that characterizes the model. While CPMs are naturally defined on finite, spatially bounded lattices, possible extensions to spatially unbounded systems are explored to assess to which extent spatio-temporal limit procedures can be applied to describe the emergent behavior at the tissue scale. To elucidate the mechanistic structure of CPMs, the model class is integrated into a general multiscale framework. It is shown that the central role of the surface fluctuations, which subsume several cellular and intercellular factors, entails substantial limitations for a CPM's exploitation both as a mechanistic and as a phenomenological model. PMID:22984409

  2. 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.

  3. Block adjustment of Chang'E-1 images based on rational function model

    NASA Astrophysics Data System (ADS)

    Liu, Bin; Liu, Yiliang; Di, Kaichang; Sun, Xiliang

    2014-05-01

    Chang'E-1(CE-1) is the first lunar orbiter of China's lunar exploration program. The CCD camera carried by CE-1 has acquired stereo images covering the entire lunar surface. Block adjustment and 3D mapping using CE-1 images are of great importance for morphological and other scientific research of the Moon. Traditional block adjustment based on rigorous sensor model is complicated due to a large number of parameters and possible correlations among them. To tackle this problem, this paper presents a block adjustment method using Rational Function Model (RFM). The RFM parameters are generated based on rigorous sensor model using virtual grid of control points. Afterwards, the RFM based block adjustment solves the refinement parameters through a least squares solution. Experimental results using CE-1 images located in Sinus Irdium show that the RFM can fit the rigorous sensor model with a high precision of 1% pixel level. Through the RFM-based block adjustment, the back-projection residuals in image space can be reduced from around 1.5 pixels to sub-pixel., indicating that RFM can replace rigorous sensor model for geometric processing of lunar images.

  4. 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

  5. Mammalian models of chemically induced primary malignancies exploitable for imaging-based preclinical theragnostic research

    PubMed Central

    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

  6. A hierarchical framework for the multiscale modeling of microstructure evolution in heterogeneous materials

    NASA Astrophysics Data System (ADS)

    Luscher, Darby J.

    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. This research developed a hierarchical multiscale approach for modeling microstructure evolution. A theoretical framework for the hierarchical homogenization of inelastic response of heterogeneous materials was developed with a special focus on scale invariance principles needed to assure physical consistency across scales. Within this multiscale framework, the second gradient is used as a nonlocal 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 two scales results in specific requirements for constraints on the fluctuation field. A multiscale internal state variable (ISV) constitutive theory is developed that is couched in the coarse scale intermediate configuration and from which an important new concept in scale transitions emerges, namely scale invariance of dissipation. At the fine scale, the material is treated using finite element models of statistical volume elements of microstructure. Fine scale boundary conditions are developed that satisfy kinematic consistency requirements and methods for numerical implementation of such boundary conditions are developed and evaluated in the context of fine scale response. The coarse scale is

  7. 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

  8. Model-based measurement of food portion size for image-based dietary assessment using 3D/2D registration

    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.

  9. Historic Building Information Modelling - Adding intelligence to laser and image based surveys of European classical architecture

    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.

  10. 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).

  11. Detecting Gait Phases from RGB-D Images Based on Hidden Markov Model

    PubMed Central

    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

  12. 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.

  13. Detecting Gait Phases from RGB-D Images Based on Hidden Markov Model.

    PubMed

    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

  14. 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

  15. Minimal camera networks for 3D image based modeling of cultural heritage objects.

    PubMed

    Alsadik, Bashar; Gerke, Markus; Vosselman, George; Daham, Afrah; Jasim, Luma

    2014-01-01

    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. PMID:24670718

  16. Minimal Camera Networks for 3D Image Based Modeling of Cultural Heritage Objects

    PubMed Central

    Alsadik, Bashar; Gerke, Markus; Vosselman, George; Daham, Afrah; Jasim, Luma

    2014-01-01

    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. PMID:24670718

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

    PubMed

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

    2013-11-01

    Integrated assessment modelling has evolved to support policy development in relation to air pollutants and greenhouse gases by providing integrated simulation tools able to produce quick and realistic representations of emission scenarios and their environmental impacts without the need to re-run complex atmospheric dispersion models. The UK Integrated Assessment Model (UKIAM) has been developed to investigate strategies for reducing UK emissions by bringing together information on projected UK emissions of SO2, NOx, NH3, PM10 and PM2.5, atmospheric dispersion, criteria for protection of ecosystems, urban air quality and human health, and data on potential abatement measures to reduce emissions, which may subsequently be linked to associated analyses of costs and benefits. We describe the multi-scale model structure ranging from continental to roadside, UK emission sources, atmospheric dispersion of emissions, implementation of abatement measures, integration with European-scale modelling, and environmental impacts. The model generates outputs from a national perspective which are used to evaluate alternative strategies in relation to emissions, deposition patterns, air quality metrics and ecosystem critical load exceedance. We present a selection of scenarios in relation to the 2020 Business-As-Usual projections and identify potential further reductions beyond those currently being planned. PMID:24096039

  18. Correlation modeling between process condition of sandblasting and surface texture: A multi-scale approach.

    PubMed

    Ho, Hsin Shen; Bigerelle, Maxence; Vincent, Renald; Deltomb, Raphael

    2016-05-01

    In the present study, the influence of sandblasting condition (working pressure) on surface texture is modeled, relying on a multi-scale approach and statistical analysis. To improve the correlation modeling between the process condition and surface texture, special effort is made to identification of an optimal parameter set, including 3D roughness parameters, cut-off lengths, filter types and model types. A power law relationship is identified between the pressure and Sdq computed with a cut-off length of 120 µm using a low-pass filter. Experimental and theoretical arguments are provided for justification. SCANNING 38:191-201, 2016. © 2015 Wiley Periodicals, Inc. PMID:26249107

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

    PubMed Central

    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

  20. An Automatic Image-Based Modelling Method Applied to Forensic Infography

    PubMed Central

    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

  1. New deconvolution method for microscopic images based on the continuous Gaussian radial basis function interpolation model

    NASA Astrophysics Data System (ADS)

    Chen, Zhaoxue; Chen, Hao

    2014-07-01

    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.

  2. Optimizing Global Coronal Magnetic Field Models Using Image-based Constraints

    NASA Astrophysics Data System (ADS)

    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.

  3. Image-based modelling of nutrient movement in and around the rhizosphere

    PubMed Central

    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

  4. Image-based modelling of nutrient movement in and around the rhizosphere.

    PubMed

    Daly, Keith R; Keyes, Samuel D; Masum, Shakil; Roose, Tiina

    2016-02-01

    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

  5. Segmentation of vertebral bodies in CT and MR images based on 3D deterministic models

    NASA Astrophysics Data System (ADS)

    Štern, Darko; Vrtovec, Tomaž; Pernuš, Franjo; Likar, Boštjan

    2011-03-01

    The evaluation of vertebral deformations is of great importance in clinical diagnostics and therapy of pathological conditions affecting the spine. Although modern clinical practice is oriented towards the computed tomography (CT) and magnetic resonance (MR) imaging techniques, as they can provide a detailed 3D representation of vertebrae, the established methods for the evaluation of vertebral deformations still provide only a two-dimensional (2D) geometrical description. Segmentation of vertebrae in 3D may therefore not only improve their visualization, but also provide reliable and accurate 3D measurements of vertebral deformations. In this paper we propose a method for 3D segmentation of individual vertebral bodies that can be performed in CT and MR images. Initialized with a single point inside the vertebral body, the segmentation is performed by optimizing the parameters of a 3D deterministic model of the vertebral body to achieve the best match of the model to the vertebral body in the image. The performance of the proposed method was evaluated on five CT (40 vertebrae) and five T2-weighted MR (40 vertebrae) spine images, among them five are normal and five are pathological. The results show that the proposed method can be used for 3D segmentation of vertebral bodies in CT and MR images and that the proposed model can describe a variety of vertebral body shapes. The method may be therefore used for initializing whole vertebra segmentation or reliably describing vertebral body deformations.

  6. 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.

  7. [A Method to Reconstruct Surface Reflectance Spectrum from Multispectral Image Based on Canopy Radiation Transfer Model].

    PubMed

    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. PMID:26717721

  8. Pulmonary nodule detection in CT images based on shape constraint CV model

    SciTech Connect

    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.

  9. An image-based skeletal dosimetry model for the ICRP reference newborn—internal electron sources

    NASA Astrophysics Data System (ADS)

    Pafundi, Deanna; Rajon, Didier; Jokisch, Derek; Lee, Choonsik; Bolch, Wesley

    2010-04-01

    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.

  10. Hybrid 3D reconstruction and image-based rendering techniques for reality modeling

    NASA Astrophysics Data System (ADS)

    Sequeira, Vitor; Wolfart, Erik; Bovisio, Emanuele; Biotti, Ester; Goncalves, Joao G. M.

    2000-12-01

    This paper presents a component approach that combines in a seamless way the strong features of laser range acquisition with the visual quality of purely photographic approaches. The relevant components of the system are: (i) Panoramic images for distant background scenery where parallax is insignificant; (ii) Photogrammetry for background buildings and (iii) High detailed laser based models for the primary environment, structure of exteriors of buildings and interiors of rooms. These techniques have a wide range of applications in visualization, virtual reality, cost effective as-built analysis of architectural and industrial environments, building facilities management, real-estate, E-commerce, remote inspection of hazardous environments, TV production and many others.

  11. 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

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

    SciTech Connect

    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.

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

    DOE PAGESBeta

    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 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

  14. Review of Advances in Cobb Angle Calculation and Image-Based Modelling Techniques for Spinal Deformities

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  16. 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

  17. Landmark detection from 3D mesh facial models for image-based analysis of dysmorphology.

    PubMed

    Chendeb, Marwa; Tortorici, Claudio; Al Muhairi, Hassan; Al Safar, Habiba; Linguraru, Marius; Werghi, Naoufel

    2015-01-01

    Facial landmark detection is a task of interest for facial dysmorphology, an important factor in the diagnosis of genetic conditions. In this paper, we propose a framework for feature points detection from 3D face images. The method is based on 3D Constrained Local Model (CLM) which learns both global variations in the 3D facial scan and local changes around every vertex landmark. Compared to state of the art methods our framework is distinguished by the following novel aspects: 1) It operates on facial surfaces, 2) It allows fusion of shape and color information on the mesh surface, 3) It introduces the use of LBP descriptors on the mesh. We showcase our landmarks detection framework on a set of scans including down syndrome and control cases. We also validate our method through a series of quantitative experiments conducted with the publicly available Bosphorus database. PMID:26736227

  18. Image based hemodynamic modeling of cerebral aneurysms and the determination of the risk of rupture

    NASA Astrophysics Data System (ADS)

    Kroon, D. J.; Slump, C. H.; Sluzewski, M.; van Rooij, W. J. J.

    2006-03-01

    This paper is about the quantitative prediction of the long term outcome of the endovascular coiling treatment of a patient's cerebral aneurysm. It is generally believed that the local hemodynamic properties of the patient's cerebral arteries are strongly influencing the origin and growth of aneurysms. We describe our approach: modelling the flow in a 3D Rotational Angiography (3DRA) reconstruction of the aneurysms including supplying and draining blood vessels, in combination with simulations and experiments of artificial blood vessel phantom constructs and measurements. The goal is to obtain insight in the observed phenomena to support the diagnostic decision process in order to predict the outcome of the intervention with possible simulation of the flow alternation due to the pertinent intervention.

  19. Color single-pixel imaging based on multiple measurement vectors model

    NASA Astrophysics Data System (ADS)

    Zhao, Ming; Kang, Chen; Tian, Pin; Xu, Wenhai

    2016-03-01

    Single-pixel imaging (SPI) represents a promising approach to multispectral imaging. We investigated the interband similarity of color images among red, green, and blue bands and found that it is highly possible for their wavelet coefficients to be at the same locations due to edges and transactions. Accordingly, we constructed a multiple measurement vectors model that includes a constraint under which the sparse coefficients of different bands have the same sparse structure, and then joint reconstruction is performed for all bands. We ran both simulated and actual experiments to validate the feasibility and effectiveness of the proposed method and found that compared with similar methods, it significantly improves the reconstruction quality of color SPI.

  20. Numerical Study of Cerebroarterial Hemodynamic Changes Following Carotid Artery Operation: A Comparison Between Multiscale Modeling and Stand-Alone Three-Dimensional Modeling.

    PubMed

    Liang, Fuyou; Oshima, Marie; Huang, Huaxiong; Liu, Hao; Takagi, Shu

    2015-10-01

    Free outflow boundary conditions have been widely adopted in hemodynamic model studies, they, however, intrinsically lack the ability to account for the regulatory mechanisms of systemic hemodynamics and hence carry a risk of producing incorrect results when applied to vascular segments with multiple outlets. In the present study, we developed a multiscale model capable of incorporating global cardiovascular properties into the simulation of blood flows in local vascular segments. The multiscale model was constructed by coupling a three-dimensional (3D) model of local arterial segments with a zero-one-dimensional (0-1-D) model of the cardiovascular system. Numerical validation based on an idealized model demonstrated the ability of the multiscale model to preserve reasonable pressure/flow wave transmission among different models. The multiscale model was further calibrated with clinical data to simulate cerebroarterial hemodynamics in a patient undergoing carotid artery operation. The results showed pronounced hemodynamic changes in the cerebral circulation following the operation. Additional numerical experiments revealed that a stand-alone 3D model with free outflow conditions failed to reproduce the results obtained by the multiscale model. These results demonstrated the potential advantage of multiscale modeling over single-scale modeling in patient-specific hemodynamic studies. Due to the fact that the present study was limited to a single patient, studies on more patients would be required to further confirm the findings. PMID:26343584

  1. Modelling catchment non-stationarity - multi-scale modelling and data assimilation

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    Modelling environmental change is in many senses a 'Grand Challenge' for hydrology, but poses major methodological challenges for hydrological models. Conceptual models represent complex processes in a simplified and spatially aggregated manner; typically parameters have no direct relationship to measurable physical properties. Calibration using observed data results in parameter equifinality, unless highly parsimonious model structures are employed. Use of such models to simulate effects of catchment non-stationarity is essentially speculative, unless attention is given to the analysis of parameter temporal variability in a non-stationary observation record. Black-box models are similarly constrained by the information content of the observational data. In contrast, distributed physics-based models provide a stronger theoretical basis for the prediction of change. However, while such models have parameters that are in principle measurable, in practice, for catchment-scale application, the measurement scale is inconsistent with the scale of model representation, the costs associated with such an exercise are high, and key properties are spatially variable, often strongly non-linear, and highly uncertain. In this paper we present a framework for modelling catchment non-stationarity that integrates information (with uncertainty) from multiple models and data sources. The context is the need to model the effects of agricultural land use change at multiple scales. A detailed UK multi-scale and multi-site experimental programme has provided data to support high resolution physics-based models of runoff processes that can, for example, represent the effects of soil structural change (due to grazing densities or trafficking), localised tree planting and drainage. Such models necessarily have high spatial resolution (1m in the horizontal plane, 1 cm in the vertical in this case), and hence can be applied at the scale of a field or hillslope element, but would be

  2. Inversion of Three Layers Multi-Scale SPM Model Based on Neural Network Technique for the Retrieval of Soil Multi-Scale Roughness and Moisture Parameters

    NASA Astrophysics Data System (ADS)

    Hosni, I.; JaafriGhamki, M.; Bennaceur Farah, L.; Naceur, M. S.

    2015-04-01

    In this paper, a multi-layered multi-scale backscattering model for a lossy medium and a neural network inversion procedure has been presented. We have used a bi-dimensional multi-scale (2D MLS) roughness description where the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each one having a spatial scale using the wavelet transform and the Mallat algorithm to describe natural surface roughness. An adapted three layers 2D MLS small perturbations (SPM) model has been used to describe radar backscattering response of semiarid sub-surfaces. The total reflection coefficients of the natural soil are computed using the multilayer model, and volumetric scattering is approximated by the internal reflections between layers. The original multi-scale SPM model includes only the surface scattering of the natural bare soil, while the multilayer soil modified 2D MLS SPM model includes both the surface scattering and the volumetric scattering within the soil. This multi-layered model has been used to calculate the total surface reflection coefficients of a natural soil surface for both horizontal and vertical co-polarizations. A parametric analysis presents the dependence of the backscattering coefficient on multi scale roughness and soil. The overall objective of this work is to retrieve soil surfaces parameters namely roughness and soil moisture related to the dielectric constant by inverting the radar backscattered signal from natural soil surfaces. To perform the inversion of the modified three layers 2D MLS SPM model, we used a multilayer neural network (NN) architecture trained by a back-propagation learning rule.

  3. An Improved Multi-Scale Modeling Framework for WRF over Complex Terrain

    NASA Astrophysics Data System (ADS)

    Wiersema, D. J.; Lundquist, K. A.; Chow, F. K.

    2014-12-01

    Atmospheric modelers continue to push towards higher resolution simulations of the planetary boundary layer. As resolution is refined, the resolved terrain slopes increase. Atmospheric models using terrain-following coordinates, such as the Weather Research and Forecasting (WRF) model, suffer from numerical errors since steep terrain slopes lead to grid skewness, resulting in model failure. One solution to this problem is the use of an immersed boundary method, which uses a non-conforming grid, for simulations over complex terrain. Our implementation of an immersed boundary method in WRF, known as WRF-IBM, was developed for use at the micro-scale and has been shown to accurately simulate flow around complex topography, such as urban environments or mountainous terrain. The research presented here describes our newly developed framework to enable concurrently run multi-scale simulations using the WRF model at the meso-scale and the WRF-IBM model at the micro-scale. WRF and WRF-IBM use different vertical coordinates therefore it is not possible to use the existing nesting framework to pass lateral boundary conditions from a WRF parent domain to a WRF-IBM nested domain. Nesting between WRF and WRF-IBM requires "vertical grid nesting", meaning the ability to pass information between domains with different vertical levels. Our newly implemented method for vertical grid nesting, available in the public release of WRFv3.6.1, allows nested domains to utilize different vertical levels. Using our vertical grid nesting code, we are currently developing the ability to nest a domain using IBM within a domain using terrain-following coordinates. Here we present results from idealized cases displaying the functionality of the multi-scale nesting framework and the advancement towards multi-scale meteorological simulations over complex terrain.

  4. Mathematical and Numerical Analyses of Peridynamics for Multiscale Materials Modeling

    SciTech Connect

    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.

  5. Finite element implementation of a multiscale model of the human lens capsule.

    PubMed

    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. PMID:25957261

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

    PubMed Central

    Pan, Keyao; Deem, Michael W

    2015-01-01

    The zebrafish (Danio rerio) is one of the model animals for 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-principles 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. PMID:21832808

  7. 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.

  8. Advances in Semantic Representation for Multiscale Biosimulation: A Case Study in Merging Models

    PubMed Central

    Neal, Maxwell Lewis; Gennari, John H.; Arts, Theo; Cook, Daniel L.

    2009-01-01

    As a case-study of biosimulation model integration, we describe our experiences applying the SemSim methodology to integrate independently-developed, multiscale models of cardiac circulation. In particular, we have integrated the CircAdapt model (written by T. Arts for MATLAB) of an adapting vascular segment with a cardiovascular system model (written by M. Neal for JSim). We report on three results from the model integration experience. First, models should be explicit about simulations that occur on different time scales. Second, data structures and naming conventions used to represent model variables may not translate across simulation languages. Finally, identifying the dependencies among model variables is a non-trivial task. We claim that these challenges will appear whenever researchers attempt to integrate models from others, especially when those models are written in a procedural style (using MATLAB, Fortran, etc.) rather than a declarative format (as supported by languages like SBML, CellML or JSim's MML). PMID:19209710

  9. Evaluation of Hydrometeor Occurrence Profiles in the Multiscale Modeling Framework Climate Model using Atmospheric Classification

    SciTech Connect

    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.

  10. Image-based estimation of ventricular fiber orientations for personalized modeling of cardiac electrophysiology.

    PubMed

    Vadakkumpadan, Fijoy; Arevalo, Hermenegild; Ceritoglu, Can; Miller, Michael; Trayanova, Natalia

    2012-05-01

    Technological limitations pose a major challenge to acquisition of myocardial fiber orientations for patient-specific modeling of cardiac (dys)function and assessment of therapy. The objective of this project was to develop a methodology to estimate cardiac fiber orientations from in vivo images of patient heart geometries. An accurate representation of ventricular geometry and fiber orientations was reconstructed, respectively, from high-resolution ex vivo structural magnetic resonance (MR) and diffusion tensor (DT) MR images of a normal human heart, referred to as the atlas. Ventricular geometry of a patient heart was extracted, via semiautomatic segmentation, from an in vivo computed tomography (CT) image. Using image transformation algorithms, the atlas ventricular geometry was deformed to match that of the patient. Finally, the deformation field was applied to the atlas fiber orientations to obtain an estimate of patient fiber orientations. The accuracy of the fiber estimates was assessed using six normal and three failing canine hearts. The mean absolute difference between inclination angles of acquired and estimated fiber orientations was 15.4°. Computational simulations of ventricular activation maps and pseudo-ECGs in sinus rhythm and ventricular tachycardia indicated that there are no significant differences between estimated and acquired fiber orientations at a clinically observable level. PMID:22271833

  11. 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.

  12. Image-Based Estimation of Ventricular Fiber Orientations for Personalized Modeling of Cardiac Electrophysiology

    PubMed Central

    Arevalo, Hermenegild; Ceritoglu, Can; Miller, Michael; Trayanova, Natalia

    2012-01-01

    Technological limitations pose a major challenge to acquisition of myocardial fiber orientations for patient-specific modeling of cardiac (dys)function and assessment of therapy. The objective of this project was to develop a methodology to estimate cardiac fiber orientations from in vivo images of patient heart geometries. An accurate representation of ventricular geometry and fiber orientations was reconstructed, respectively, from high-resolution ex vivo structural magnetic resonance (MR) and diffusion tensor (DT) MR images of a normal human heart, referred to as the atlas. Ventricular geometry of a patient heart was extracted, via semiautomatic segmentation, from an in vivo computed tomography (CT) image. Using image transformation algorithms, the atlas ventricular geometry was deformed to match that of the patient. Finally, the deformation field was applied to the atlas fiber orientations to obtain an estimate of patient fiber orientations. The accuracy of the fiber estimates was assessed using six normal and three failing canine hearts. The mean absolute difference between inclination angles of acquired and estimated fiber orientations was 15.4°. Computational simulations of ventricular activation maps and pseudo-ECGs in sinus rhythm and ventricular tachycardia indicated that there are no significant differences between estimated and acquired fiber orientations at a clinically observable level. PMID:22271833

  13. A ``partitioned leaping'' approach for multiscale modeling of chemical reaction dynamics

    NASA Astrophysics Data System (ADS)

    Harris, Leonard A.; Clancy, Paulette

    2006-10-01

    We present a novel multiscale simulation approach for modeling stochasticity in chemical reaction networks. The approach seamlessly integrates exact-stochastic and "leaping" methodologies into a single partitioned leaping algorithmic framework. The technique correctly accounts for stochastic noise at significantly reduced computational cost, requires the definition of only three model-independent parameters, and is particularly well suited for simulating systems containing widely disparate species populations. We present the theoretical foundations of partitioned leaping, discuss various options for its practical implementation, and demonstrate the utility of the method via illustrative examples.

  14. The process e+e- → barb s in the topcolour-assisted multiscale technicolour model

    NASA Astrophysics Data System (ADS)

    Lu, Gongru; Yue, Chongxing; Li, Weibin; Sun, Junfeng

    2000-03-01

    We calculated the contribution of pseudo-Goldstone bosons (technipions, top pions) to the cross-section icons/Journals/Common/sigma" ALT="sigma" ALIGN="TOP"/> of the process e+ e → barb s in the topcolour-assisted multiscale technicolour model at LEPII. Our results show that the cross-section σ is of the order of 10-2 fb, for reasonable values of the parameter. This is larger than that predicted by the standard model by about one order of magnitude. Such enhancement might provide an opportunity to detect the new physics at future colliders.

  15. Carbon Capture Simulation Initiative: A Case Study in Multi-Scale Modeling and New Challenges

    SciTech Connect

    Miller, David; Syamlal, Madhava; Mebane, David; Storlie, Curtis; Bhattacharyya, Debangsu; Sahinidis, Nikolaos V.; Agarwal, Deborah A.; Tong, Charles; Zitney, Stephen E.; Sarkar, Avik; Sun, Xin; Sundaresan, Sankaran; Ryan, Emily M.; Engel, David W.; Dale, Crystal

    2014-04-01

    Advanced multi-scale modeling and simulation has the potential to dramatically reduce development time, resulting in considerable cost savings. The Carbon Capture Simulation Initiative is a partnership among national laboratories, industry and universities that is developing and deploying a suite of multi-scale modeling and simulation tools including basic data submodels, steady-state and dynamic process models, process optimization and uncertainty quantification tools, an advanced dynamic process control framework, high-resolution filtered computational-fluid-dynamic (CFD) submodels, validated high-fidelity device-scale CFD models with quantified uncertainty, and a risk analysis framework. These tools and models enable basic data submodels, including thermodynamics and kinetics, to be used within detailed process models to synthesize and optimize a process. The resulting process informs the development of process control systems and more detailed simulations of potential equipment to improve the design and reduce scale-up risk. Quantification and propagation of uncertainty across scales is an essential part of these tools and models.

  16. Carbon Capture Simulation Initiative: A Case Study in Multi-Scale Modeling and New Challenges

    SciTech Connect

    Miller, David C; Syamlal, Madhava; Zitney, Stephen E.

    2014-06-07

    Abstract: Advanced multi-scale modeling and simulation has the potential to dramatically reduce development time, resulting in considerable cost savings. The Carbon Capture Simulation Initiative is a partnership among national laboratories, industry and universities that is developing and deploying a suite of multi-scale modeling and simulation tools including basic data submodels, steady-state and dynamic process models, process optimization and uncertainty quantification tools, an advanced dynamic process control framework, high-resolution filtered computational-fluid-dynamic (CFD) submodels, validated high-fidelity device-scale CFD models with quantified uncertainty, and a risk analysis framework. These tools and models enable basic data submodels, including thermodynamics and kinetics, to be used within detailed process models to synthesize and optimize a process. The resulting process informs the development of process control systems and more detailed simulations of potential equipment to improve the design and reduce scale-up risk. Quantification and propagation of uncertainty across scales is an essential part of these tools and models.

  17. Improved convergence of gradient-based reconstruction using multi-scale models

    SciTech Connect

    Cunningham, G.S.; Hanson, K.M.; Koyfman, I.

    1996-05-01

    Geometric models have received increasing attention in medical imaging for tasks such as segmentation, reconstruction, restoration, and registration. In order to determine the best configuration of the geometric model in the context of any of these tasks, one needs to perform a difficult global optimization of an energy function that may have many local minima. Explicit models of geometry, also called deformable models, snakes, or active contours, have been used extensively to solve image segmentation problems in a non-Bayesian framework. Researchers have seen empirically that multi-scale analysis is useful for convergence to a configuration that is near the global minimum. In this type of analysis, the image data are convolved with blur functions of increasing resolution, and an optimal configuration of the snake is found for each blurred image. The configuration obtained using the highest resolution blur is used as the solution to the global optimization problem. In this article, the authors use explicit models of geometry for a variety of Bayesian estimation problems, including image segmentation, reconstruction and restoration. The authors introduce a multi-scale approach that blurs the geometric model, rather than the image data, and show that this approach turns a global, highly nonquadratic optimization into a sequence of local, approximately quadratic problems that converge to the global minimum. The result is a deterministic, robust, and efficient optimization strategy applicable to a wide variety of Bayesian estimation problems in which geometric models of images are an important component.

  18. Multiscale methods for gore curvature calculations from FSI modeling of spacecraft parachutes

    NASA Astrophysics Data System (ADS)

    Takizawa, Kenji; Tezduyar, Tayfun E.; Kolesar, Ryan; Boswell, Cody; Kanai, Taro; Montel, Kenneth

    2014-12-01

    There are now some sophisticated and powerful methods for computer modeling of parachutes. These methods are capable of addressing some of the most formidable computational challenges encountered in parachute modeling, including fluid-structure interaction (FSI) between the parachute and air flow, design complexities such as those seen in spacecraft parachutes, and operational complexities such as use in clusters and disreefing. One should be able to extract from a reliable full-scale parachute modeling any data or analysis needed. In some cases, however, the parachute engineers may want to perform quickly an extended or repetitive analysis with methods based on simplified models. Some of the data needed by a simplified model can very effectively be extracted from a full-scale computer modeling that serves as a pilot. A good example of such data is the circumferential curvature of a parachute gore, where a gore is the slice of the parachute canopy between two radial reinforcement cables running from the parachute vent to the skirt. We present the multiscale methods we devised for gore curvature calculation from FSI modeling of spacecraft parachutes. The methods include those based on the multiscale sequentially-coupled FSI technique and using NURBS meshes. We show how the methods work for the fully-open and two reefed stages of the Orion spacecraft main and drogue parachutes.

  19. 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 -ɛ linear eddy-viscosity model, k - ɛ 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

  20. NEW DEVELOPMENTS IN THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL

    EPA Science Inventory

    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...

  1. Spectral imaging based in vivo model system for characterization of tumor microvessel response to vascular targeting agents

    NASA Astrophysics Data System (ADS)

    Wankhede, Mamta

    Functional vasculature is vital for tumor growth, proliferation, and metastasis. Many tumor-specific vascular targeting agents (VTAs) aim to destroy this essential tumor vasculature to induce indirect tumor cell death via oxygen and nutrition deprivation. The tumor angiogenesis-inhibiting anti-angiogenics (AIs) and the established tumor vessel targeting vascular disrupting agents (VDAs) are the two major players in the vascular targeting field. Combination of VTAs with conventional therapies or with each other, have been shown to have additive or supra-additive effects on tumor control and treatment. Pathophysiological changes post-VTA treatment in terms of structural and vessel function changes are important parameters to characterize the treatment efficacy. Despite the abundance of information regarding these parameters acquired using various techniques, there remains a need for a quantitative, real-time, and direct observation of these phenomenon in live animals. Through this research we aspired to develop a spectral imaging based mouse tumor system for real-time in vivo microvessel structure and functional measurements for VTA characterization. A model tumor system for window chamber studies was identified, and then combinatorial effects of VDA and AI were characterized in model tumor system. (Full text of this dissertation may be available via the University of Florida Libraries web site. Please check http://www.uflib.ufl.edu/etd.html)

  2. 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.

  3. Multi-scale Modeling of the Cardiovascular System: Disease Development, Progression, and Clinical Intervention.

    PubMed

    Zhang, Yanhang; Barocas, Victor H; Berceli, Scott A; Clancy, Colleen E; Eckmann, David M; Garbey, Marc; Kassab, Ghassan S; Lochner, Donna R; McCulloch, Andrew D; Tran-Son-Tay, Roger; Trayanova, Natalia A

    2016-09-01

    Cardiovascular diseases (CVDs) are the leading cause of death in the western world. With the current development of clinical diagnostics to more accurately measure the extent and specifics of CVDs, a laudable goal is a better understanding of the structure-function relation in the cardiovascular system. Much of this fundamental understanding comes from the development and study of models that integrate biology, medicine, imaging, and biomechanics. Information from these models provides guidance for developing diagnostics, and implementation of these diagnostics to the clinical setting, in turn, provides data for refining the models. In this review, we introduce multi-scale and multi-physical models for understanding disease development, progression, and designing clinical interventions. We begin with multi-scale models of cardiac electrophysiology and mechanics for diagnosis, clinical decision support, personalized and precision medicine in cardiology with examples in arrhythmia and heart failure. We then introduce computational models of vasculature mechanics and associated mechanical forces for understanding vascular disease progression, designing clinical interventions, and elucidating mechanisms that underlie diverse vascular conditions. We conclude with a discussion of barriers that must be overcome to provide enhanced insights, predictions, and decisions in pre-clinical and clinical applications. PMID:27138523

  4. A Multi-Scale Modeling System with Unified Physics

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2008-01-01

    Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. In recent years, exponentially increasing computer power has extended cloud-resolving-mode1 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.

  5. A multiscale strength model for tantalum over an extended range of strain rates

    NASA Astrophysics Data System (ADS)

    Barton, N. R.; Rhee, M.

    2013-09-01

    A strength model for tantalum is developed and exercised across a range of conditions relevant to various types of experimental observations. The model is based on previous multiscale modeling work combined with experimental observations. As such, the model's parameterization includes a hybrid of quantities that arise directly from predictive sub-scale physics models and quantities that are adjusted to align the model with experimental observations. Given current computing and experimental limitations, the response regions for sub-scale physics simulations and detailed experimental observations have been largely disjoint. In formulating the new model and presenting results here, attention is paid to integrated experimental observations that probe strength response at the elevated strain rates where a previous version of the model has generally been successful in predicting experimental data [Barton et al., J. Appl. Phys. 109(7), 073501 (2011)].

  6. On multiscale approaches to three-dimensional modelling of morphogenesis

    PubMed Central

    Chaturvedi, R; Huang, C; Kazmierczak, B; Schneider, T; Izaguirre, J.A; Glimm, T; Hentschel, H.G.E; Glazier, J.A; Newman, S.A; Alber, M.S

    2005-01-01

    In this paper we present the foundation of a unified, object-oriented, three-dimensional biomodelling environment, which allows us to integrate multiple submodels at scales from subcellular to those of tissues and organs. Our current implementation combines a modified discrete model from statistical mechanics, the Cellular Potts Model, with a continuum reaction–diffusion model and a state automaton with well-defined conditions for cell differentiation transitions to model genetic regulation. This environment allows us to rapidly and compactly create computational models of a class of complex-developmental phenomena. To illustrate model development, we simulate a simplified version of the formation of the skeletal pattern in a growing embryonic vertebrate limb. PMID:16849182

  7. Development of land surface reflectance models based on multiscale simulation

    NASA Astrophysics Data System (ADS)

    Goodenough, Adam A.; Brown, Scott D.

    2015-05-01

    Modeling and simulation of Earth imaging sensors with large spatial coverage necessitates an understanding of how photons interact with individual land surface processes at an aggregate level. For example, the leaf angle distribution of a deciduous forest canopy has a significant impact on the path of a single photon as it is scattered among the leaves and, consequently, a significant impact on the observed bidirectional reflectance distribution function (BRDF) of the canopy as a whole. In particular, simulation of imagery of heterogeneous scenes for many multispectral/hyperspectral applications requires detailed modeling of regions of the spectrum where many orders of scattering are required due to both high reflectance and transmittance. Radiative transfer modeling based on ray tracing, hybrid Monte Carlo techniques and detailed geometric and optical models of land cover means that it is possible to build effective, aggregate optical models with parameters such as species, spatial distribution, and underlying terrain variation. This paper examines the capability of the Digital Image and Remote Sensing Image Generation (DIRSIG) model to generate BRDF data representing land surfaces at large scale from modeling at a much smaller scale. We describe robust methods for generating optical property models effectively in DIRSIG and present new tools for facilitating the process. The methods and results for forest canopies are described relative to the RAdiation transfer Model Intercomparison (RAMI) benchmark scenes, which also forms the basis for an evaluation of the approach. Additional applications and examples are presented, representing different types of land cover.

  8. Image-Based Rendering of LOD1 3D City Models for traffic-augmented Immersive Street-view Navigation

    NASA Astrophysics Data System (ADS)

    Brédif, M.

    2013-10-01

    It may be argued that urban areas may now be modeled with sufficient details for realistic fly-through over the cities at a reasonable price point. Modeling cities at the street level for immersive street-view navigation is however still a very expensive (or even impossible) operation if one tries to match the level of detail acquired by street-view mobile mapping imagery. This paper proposes to leverage the richness of these street-view images with the common availability of nation-wide LOD1 3D city models, using an image-based rendering technique : projective multi-texturing. Such a coarse 3D city model may be used as a lightweight scene proxy of approximate coarse geometry. The images neighboring the interpolated viewpoint are projected onto this scene proxy using their estimated poses and calibrations and blended together according to their relative distance. This enables an immersive navigation within the image dataset that is perfectly equal to - and thus as rich as - original images when viewed from their viewpoint location, and which degrades gracefully in between viewpoint locations. Beyond proving the applicability of this preprocessing-free computer graphics technique to mobile mapping images and LOD1 3D city models, our contributions are three-fold. Firstly, image distortion is corrected online in the GPU, preventing an extra image resampling step. Secondly, externally-computed binary masks may be used to discard pixels corresponding to moving objects. Thirdly, we propose a shadowmap-inspired technique that prevents, at marginal cost, the projective texturing of surfaces beyond the first, as seen from the projected image viewpoint location. Finally, an augmented visualization application is introduced to showcase the proposed immersive navigation: images are unpopulated from vehicles using externally-computed binary masks and repopulated using a 3D visualization of a 2D traffic simulation.

  9. 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.

  10. In Vitro Validation of a Multiscale Patient-Specific Norwood Palliation Model.

    PubMed

    Hang, Tianqi; Giardini, Alessandro; Biglino, Giovanni; Conover, Timothy; Figliola, Richard S

    2016-01-01

    In Norwood physiology, shunt size and the occurrence of coarctation can affect hemodynamics significantly. The aim of the study was to validate an in vitro model of the Norwood circulation against clinical measurements for patients presenting differing aortic morphologies. The mock circulatory system used coupled a lumped parameter network of the neonatal Norwood circulation with modified Blalock-Taussig (mBT) shunt with a three-dimensional aorta model. Five postoperative aortic arch anatomies of differing morphologies were reconstructed from imaging data, and the system was tuned to patient-specific clinical values. Experimentally measured flow rates and pressures were compared with clinical measurements. Time-based experimental and clinical pressure and flow signals within the aorta and pulmonary circulation branches agreed closely (0.72 < R < 0.95) for the five patients, whereas mean values within the systemic and pulmonary branches showed no significant differences (95% confidence interval). We validated an experimental multiscale model of the Norwood circulation with mBT shunt by showing it capable of reproducing clinical pressure and flow rates at various positions of the circulation with very good fidelity across a range of patient physiologies and morphologies. The multiscale aspect of the model provides a means to study variables in isolation with their effects both locally and at the system level. The model serves as a tool to further the understanding of the complex physiology of single-ventricle circulation. PMID:26771396

  11. 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.

  12. 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

  13. Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

    PubMed Central

    Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.

    2015-01-01

    Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

  14. 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.

  15. A multiscale model to evaluate the efficacy of anticancer therapies based on chimeric polypeptide nanoparticles

    NASA Astrophysics Data System (ADS)

    Paiva, L. R.; Martins, M. L.

    2011-01-01

    A multiscale model for tumor growth and its chemotherapy using conjugate nanoparticles is presented, and the corresponding therapeutic outcomes are evaluated. It is found that doxorubicin assembled into chimeric polypeptide nanoparticles cannot eradicate either vascularized primary tumors or avascular micrometastasis even administrated at loads close to their maximum tolerated doses. Furthermore, an effective and safety treatment demands for conjugate nanoparticles targeted to the malignant cells with much higher specificity and affinity than those currently observed in order to leave most of the normal tissues unaffected and to ensure a fast intracellular drug accumulation.

  16. Multi-scale modeling for dynamics of structure-soil-structure interactions

    NASA Astrophysics Data System (ADS)

    Boutin, Claude; Soubestre, Jean; Schwan, Logan; Dietz, Matt

    2014-10-01

    This paper presents two cases of multi-scale modeling in the context of dynamic structure soil-structure interaction. The first case concerns the behaviour of reinforced soils. It is shown that such system may involve both shear and bending effect at the leading order, which corresponds to a second gradient material. The second case addresses the seismic response of soils in presence of a densely urbanized city. It appears that the effect of resonance of the whole buildings in interaction actually modify the seismic response. In both cases the theoretical approach is completed by a validation through analogous samples tested on a shaking table.

  17. A Multiscale Survival Process for Modeling Human Activity Patterns

    PubMed Central

    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

  18. Parameterized locally invariant manifolds: A tool for multiscale modeling

    NASA Astrophysics Data System (ADS)

    Sawant, Aarti

    In this thesis two methods for coarse graining in nonlinear ODE systems are demonstrated through analysis of model problems. The basic ideas of a method for model reduction and a method for non-asymptotic time-averaging are presented, using the idea of the Parameterized locally invariant manifolds. New approximation techniques for carrying out this methodology are developed. The work is divided in four categories based on the type of coarse-graining used: reduction of degrees of freedom, spatial averaging, time averaging and a combination of space and time averaging. Model problems showing complex dynamics are selected and various features of the PLIM method are elaborated. The quality and efficiency of the different coarse-graining approaches are evaluated. From the computational standpoint, it is shown that the method has the potential of serving as a subgrid modeling tool for problems in engineering. The developed ideas are evaluated on the following model problems: Lorenz System, a 4D Hamiltonian System due to Hald, 1D Elastodynamics in a strongly heterogeneous medium, kinetics of a phase transforming material with wiggly energy due to Abeyaratne, Chu and James, 2D gradient system with wiggly energy due to Menon, and macroscopic stress-strain behavior of an atomic chain based on the Frenkel-Kontorova model.

  19. 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.

  20. Multiscale modeling of carbon nanotube materials with distinct element method

    NASA Astrophysics Data System (ADS)

    Ostanin, Igor Aleksandrovich

    Mesoscale simulation techniques are becoming increasingly important due to the interest in complex mechanical problems involving nanoscale structures and materials. This work is devoted to the development of a novel mesoscopic modeling technique based on an extension of the distinct element method and its application to the problem of mechanical modeling of carbon nanotube materials. Starting from an atomistic description, the important interactions between segments of the tubes are encapsulated into two types of contact models. The nanomechanics of intratube bonds is characterized by the parallel bond contact model. Intertube interactions are accounted for by an anisotropic vdW contact model. Energy dissipation is formulated in a top-down manner, based on the macroscopic mechanical properties of carbon nanotube materials. The developed model is applied to the analysis of various mesoscopic structures and materials - self-folded nanotube configurations, nanotube bundles and ropes, nanotube papers and films. The results of mesoscopic simulations not only are in good agreement with experimental observations, but they also provide interesting insights on the roles of effects of morphology, vdW adhesion and registry, cross-linking and energy dissipation on the nanomechanics of carbon nanotube based materials.

  1. Integration of Biochemical and Electrical Signaling-Multiscale Model of the Medium Spiny Neuron of the Striatum

    PubMed Central

    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

  2. Multiscale sagebrush rangeland habitat modeling in southwest Wyoming

    USGS Publications Warehouse

    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

  3. A multiscale model for glioma spread including cell-tissue interactions and proliferation.

    PubMed

    Engwer, Christian; Knappitsch, Markus; Surulescu, Christina

    2016-04-01

    Glioma is a broad class of brain and spinal cord tumors arising from glia cells, which are the main brain cells that can develop into neoplasms. They are highly invasive and lead to irregular tumor margins which are not precisely identifiable by medical imaging, thus rendering a precise enough resection very difficult. The understanding of glioma spread patterns is hence essential for both radiological therapy as well as surgical treatment. In this paper we propose a multiscale model for glioma growth including interactions of the cells with the underlying tissue network, along with proliferative effects. Our current accounting for two subpopulations of cells to accomodate proliferation according to the go-or-grow dichtomoty is an extension of the setting in [16]. As in that paper, we assume that cancer cells use neuronal fiber tracts as invasive pathways. Hence, the individual structure of brain tissue seems to be decisive for the tumor spread. Diffusion tensor imaging (DTI) is able to provide such information, thus opening the way for patient specific modeling of glioma invasion. Starting from a multiscale model involving subcellular (microscopic) and individual (mesoscale) cell dynamics, we perform a parabolic scaling to obtain an approximating reaction-diffusion-transport equation on the macroscale of the tumor cell population. Numerical simulations based on DTI data are carried out in order to assess the performance of our modeling approach. PMID:27105989

  4. 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.

  5. Multiscale and multiresolution modeling of shales and their flow and morphological properties

    PubMed Central

    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

  6. 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.

  7. Safer Batteries through Coupled Multiscale Modeling (ICCS 2015)

    SciTech Connect

    Turner, John A; Allu, Srikanth; Berrill, Mark A; Elwasif, Wael R; Kalnaus, Sergiy; Kumar, Abhishek; Lebrun-Grandie, Damien T; Pannala, Dr. Sreekanth; Simunovic, Srdjan

    2015-01-01

    Batteries are highly complex electrochemical systems, with performance and safety governed by coupled nonlinear electrochemical-electrical-thermal-mechanical processes over a range of spatiotemporal scales. We describe a new, open source computational environment for battery simulation known as VIBE - the Virtual Integrated Battery Environment. VIBE includes homogenized and pseudo-2D electrochemistry models such as those by Newman-Tiedemann-Gu (NTG) and Doyle- Fuller-Newman (DFN, a.k.a. DualFoil) as well as a new advanced capability known as AMPERES (Advanced MultiPhysics for Electrochemical and Renewable Energy Storage). AMPERES provides a 3D model for electrochemistry and full coupling with 3D electrical and thermal models on the same grid. VIBE/AMPERES has been used to create three-dimensional battery cell and pack models that explicitly simulate all the battery components (current collectors, electrodes, and separator). The models are used to predict battery performance under normal operations and to study thermal and mechanical response under adverse conditions.

  8. Sparsity: a ubiquitous but unexplored property of geophysical signals for multi-scale modeling and reconstruction

    NASA Astrophysics Data System (ADS)

    Fouofula-Georgiou, E.; Ebtehaj, A. M.

    2012-04-01

    Sparsity: a ubiquitous but unexplored property of geophysical signals for multi-scale modeling and reconstruction Efi Foufoula-Georgiou and Ardeshir Mohammad Ebtehaj Department of Civil Engineering and National Center for Earth-surface Dynamics University of Minnesota, Minneapolis, MN 55414 Many geophysical processes exhibit variability over a wide range of scales. Yet, in numerical modeling or remote sensing observations not all of this variability is explicitly resolved due to limitations in computational resources or sensor configurations. As a result, sub-grid scale parameterizations and downscaling/upscaling representations are essential. Such representations take advantage of scale invariance which has been theoretically or empirically documented in a wide range of geophysical processes, including precipitation, soil moisture, and topography. Here we present a new direction in the field of multi-scale analysis and reconstruction. It capitalizes on the fact that most geophysical signals are naturally redundant, due to spatial dependence and coherence over a range of scales, and thus when projected onto an appropriate space (e.g, Fourier or wavelet) only a few representation coefficients are non-zero -- this property is called sparsity. The sparsity can serve as a priori knowledge to properly regularize the otherwise ill-posed inverse problem of creating information at scales smaller than resolved, which is at the heart of sub-grid scale and downscaling parameterizations. The same property of sparsity is also shown to play a revolutionary role in revisiting the problem of optimal estimation of non-Gaussian processes. Theoretical concepts are borrowed from the new field of compressive sampling and super-resolution and the merits of the methodology are demonstrated using examples from precipitation downscaling, multi-scale data fusion and data assimilation.

  9. A multiscale modelling of bone ultrastructure elastic proprieties using finite elements simulation and neural network method.

    PubMed

    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 different repetitive structural units or building blocks are found: at the first level, collagen molecules are arranged in a pentameric structure where mineral crystals grow in specific sites. This primary bone structure constitutes the mineralized collagen microfibril. A structural organization of inter-digitating microfibrils forms the mineralized collagen fibril which represents the second scale level. The third scale level corresponds to the mineralized collagen fibre which is composed by the binding of fibrils. The hierarchical nature of the bone tissue is largely responsible of their significant mechanical properties; consequently, this is a current outstanding research topic. Scarce works in literature correlates the elastic properties in the three scale levels at the bone nanoscale. The main goal of this work is to estimate the elastic properties of the bone tissue in a multiscale approach including a sensitivity analysis of the elastic behaviour at each length scale. This proposal is achieved by means of a novel hybrid multiscale modelling that involves neural network (NN) computations and finite elements method (FEM) analysis. The elastic properties are estimated using a neural network simulation that previously has been trained with the database results of the finite element models. In the results of this work, parametric analysis and averaged elastic constants for each length scale are provided. Likewise, the influence of the elastic constants of the tissue constituents is also depicted. Results highlight

  10. A multiple time stepping algorithm for efficient multiscale modeling of platelets flowing in blood plasma

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

    We developed a multiple time-stepping (MTS) algorithm for multiscale modeling of the dynamics of platelets flowing in viscous blood plasma. This MTS algorithm improves considerably the computational efficiency without significant loss of accuracy. This study of the dynamic properties of flowing platelets employs a combination of the dissipative particle dynamics (DPD) and the coarse-grained molecular dynamics (CGMD) methods to describe the dynamic microstructures of deformable platelets in response to extracellular flow-induced stresses. The disparate spatial scales between the two methods are handled by a hybrid force field interface. However, the disparity in temporal scales between the DPD and CGMD that requires time stepping at microseconds and nanoseconds respectively, represents a computational challenge that may become prohibitive. Classical MTS algorithms manage to improve computing efficiency by multi-stepping within DPD or CGMD for up to one order of magnitude of scale differential. In order to handle 3-4 orders of magnitude disparity in the temporal scales between DPD and CGMD, we introduce a new MTS scheme hybridizing DPD and CGMD by utilizing four different time stepping sizes. We advance the fluid system at the largest time step, the fluid-platelet interface at a middle timestep size, and the nonbonded and bonded potentials of the platelet structural system at two smallest timestep sizes. Additionally, we introduce parameters to study the relationship of accuracy versus computational complexities. The numerical experiments demonstrated 3000x reduction in computing time over standard MTS methods for solving the multiscale model. This MTS algorithm establishes a computationally feasible approach for solving a particle-based system at multiple scales for performing efficient multiscale simulations.

  11. A Multiple Time Stepping Algorithm for Efficient Multiscale Modeling of Platelets Flowing in Blood Plasma

    PubMed Central

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

    2015-01-01

    We developed a multiple time-stepping (MTS) algorithm for multiscale modeling of the dynamics of platelets flowing in viscous blood plasma. This MTS algorithm improves considerably the computational efficiency without significant loss of accuracy. This study of the dynamic properties of flowing platelets employs a combination of the dissipative particle dynamics (DPD) and the coarse-grained molecular dynamics (CGMD) methods to describe the dynamic microstructures of deformable platelets in response to extracellular flow-induced stresses. The disparate spatial scales between the two methods are handled by a hybrid force field interface. However, the disparity in temporal scales between the DPD and CGMD that requires time stepping at microseconds and nanoseconds respectively, represents a computational challenge that may become prohibitive. Classical MTS algorithms manage to improve computing efficiency by multi-stepping within DPD or CGMD for up to one order of magnitude of scale differential. In order to handle 3–4 orders of magnitude disparity in the temporal scales between DPD and CGMD, we introduce a new MTS scheme hybridizing DPD and CGMD by utilizing four different time stepping sizes. We advance the fluid system at the largest time step, the fluid-platelet interface at a middle timestep size, and the nonbonded and bonded potentials of the platelet structural system at two smallest timestep sizes. Additionally, we introduce parameters to study the relationship of accuracy versus computational complexities. The numerical experiments demonstrated 3000x reduction in computing time over standard MTS methods for solving the multiscale model. This MTS algorithm establishes a computationally feasible approach for solving a particle-based system at multiple scales for performing efficient multiscale simulations. PMID:25641983

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

    PubMed Central

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

    2012-01-01

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

  13. Time analysis of aneurysm wall shear stress for both Newtonian and Casson flows from image-based CFD models

    NASA Astrophysics Data System (ADS)

    Castro, Marcelo A.; Ahumada Olivares, María. C.; Putman, Christopher M.; Cebral, Juan R.

    2014-03-01

    The optimal management of unruptured aneurysms is controversial, and current decision making is mainly based on aneurysm size and location. Incidentally detected unruptured aneurysms less than 5mm in diameter should be treated conservatively. However, small unruptured aneurysms also bleed. Risk factors based on the hemodynamic forces exerted over the arterial wall have been investigated using image-based computational fluid dynamic (CFD) methodologies during the last decade. Accurate estimation of wall shear stress (WSS) is required to properly study associations between flow features and aneurysm processes. Previous works showed that Newtonian and non-Newtonian (Casson) models produce similar WSS distributions and characterization, with no significant differences. Other authors showed that the WSS distribution computed from time-averaged velocity fields is significantly higher for the Newtonian model where WSS is low. In this work we reconstructed ten patient-specific CFD models from angiography images to investigate the time evolution of WSS at selected locations such as aneurysm blebs (low WSS), and the parent artery close to the aneurysm neck (high WSS). When averaging all cases it is seen that the estimation of the time-averaged WSS, the peak WSS and the minimum WSS value before the systolic peak were all higher when the Casson rheology was considered. However, none of them showed statistically significant differences. At the afferent artery Casson rheology systematically predicted higher WSS values. On the other hand, at the selected blebs either Newtonian or Casson WSS estimations are higher in some phases of the cardiac cycle. Those observations differ among individual cases.

  14. A Multiscale Modeling System: Developments, Applications, and Critical Issues

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Lau, William; Simpson, Joanne; Chern, Jiun-Dar; Atlas, Robert; Khairoutdinov, David Randall Marat; Li, Jui-Lin; Waliser, Duane E.; Jiang, Jonathan; Hou, Arthur; Lin, Xin; Peters-Lidard, Christa

    2009-01-01

    The foremost challenge in parameterizing convective clouds and cloud systems in large-scale models are the many coupled dynamical and physical processes that interact over a wide range of scales, from microphysical scales to the synoptic and planetary scales. This makes the comprehension and representation of convective clouds and cloud systems one of the most complex scientific problems in Earth science. During the past decade, the Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) has pioneered the use of single-column models (SCMs) and cloud-resolving models (CRMs) for the evaluation of the cloud and radiation parameterizations in general circulation models (GCMs; e.g., GEWEX Cloud System Science Team 1993). These activities have uncovered many systematic biases in the radiation, cloud and convection parameterizations of GCMs and have led to the development of new schemes (e.g., Zhang 2002; Pincus et al, 2003; Zhang and Wu 2003; Wu et al. 2003; Liang and Wu 2005; Wu and Liang 2005, and others). Comparisons between SCMs and CRMs using the same large-scale forcing derived from field campaigns have demonstrated that CRMs are superior to SCMs in the prediction of temperature and moisture tendencies (e.g., Das et al. 1999; Randall et al 2003b; Xie et al. 2005).

  15. Multi-Scale Multi-Species Modeling for Plasma Devices

    NASA Astrophysics Data System (ADS)

    Araki, Samuel Jun

    This dissertation describes three computational models developed to simulate important aspects of low-temperature plasma devices, most notably ring-cusp ion discharges and thrusters. The main findings of this dissertation are related to (1) the mechanisms of cusp confinement for micro-scale plasmas, (2) the implementation and merits of magnetic field aligned meshes, and (3) an improved method for describing heavy species interactions. The Single Cusp (SC) model focuses on the near-cusp region of the discharge chamber to investigate the near surface cusp confinement of a micro-scale plasma. The model employs the multi-species iterative Monte Carlo method and uses various advanced methods such as electric field calculation and particle weighting algorithm that are compatible with a non-uniform mesh in cylindrical coordinates. Three different plasma conditions are simulated with the SC model, including an electron plasma, a sparse plasma, and a weakly ionized plasma. It is found that the scaling of plasma loss to the cusp for a sparse plasma can be similar to that for a weakly ionized plasma, while the loss mechanism is significantly different; the primary electrons strongly influence the loss structure of the sparse plasma. The model is also used, along with experimental results, to describe the importance of the local magnetic field on the primary electron loss behavior at the cusp. Many components of the 2D/3D hybrid fluid/particle model (DC-ION) are improved from the original version. The DC-ION code looks at the macroscopic structure of the discharge plasma and can be used to address the design and optimization challenges of miniature to micro discharges on the order of 3 cm to 1 cm in diameter. Among the work done for DC-ION, detailed steps for the magnetic field aligned (MFA) mesh are provided. Solving the plasma diffusion equation in the ring-cusp configuration, the benefit of the MFA mesh has been fully investigated by comparing the solution with a uniform

  16. Integration of multiscale dendritic spine structure and function data into systems biology models

    PubMed Central

    Mancuso, James J.; Cheng, Jie; Yin, Zheng; Gilliam, Jared C.; Xia, Xiaofeng; Li, Xuping; Wong, Stephen T. C.

    2014-01-01

    Comprising 1011 neurons with 1014 synaptic connections the human brain is the ultimate systems biology puzzle. An increasing body of evidence highlights the observation that changes in brain function, both normal and pathological, consistently correlate with dynamic changes in neuronal anatomy. Anatomical changes occur on a full range of scales from the trafficking of individual proteins, to alterations in synaptic morphology both individually and on a systems level, to reductions in long distance connectivity and brain volume. The major sites of contact for synapsing neurons are dendritic spines, which provide an excellent metric for the number and strength of signaling connections between elements of functional neuronal circuits. A comprehensive model of anatomical changes and their functional consequences would be a holy grail for the field of systems neuroscience but its realization appears far on the horizon. Various imaging technologies have advanced to allow for multi-scale visualization of brain plasticity and pathology, but computational analysis of the big data sets involved forms the bottleneck toward the creation of multiscale models of brain structure and function. While a full accounting of techniques and progress toward a comprehensive model of brain anatomy and function is beyond the scope of this or any other single paper, this review serves to highlight the opportunities for analysis of neuronal spine anatomy and function provided by new imaging technologies and the high-throughput application of older technologies while surveying the strengths and weaknesses of currently available computational analytical tools and room for future improvement. PMID:25429262

  17. A Multiscale Dynamic Model of DNA Supercoil Relaxation by Topoisomerase IB

    PubMed Central

    Lillian, Todd D.; Taranova, Maryna; Wereszczynski, Jeff; Andricioaei, Ioan; Perkins, N.C.

    2011-01-01

    In this study, we report what we believe to be the first multiscale simulation of the dynamic relaxation of DNA supercoils by human topoisomerase IB (topo IB). We leverage our previous molecular dynamics calculations of the free energy landscape describing the interaction between a short DNA fragment and topo IB. Herein, this landscape is used to prescribe boundary conditions for a computational, elastodynamic continuum rod model of a long length of supercoiled DNA. The rod model, which accounts for the nonlinear bending, twisting, and electrostatic interaction of the (negatively charged) DNA backbone, is extended to include the hydrodynamic drag induced by the surrounding physiological buffer. Simulations for a 200-bp-long DNA supercoil in complex with topo IB reveal a relaxation timescale of ∼0.1–1.0 μs. The relaxation follows a sequence of cascading reductions in the supercoil linking number (Lk), twist (Tw), and writhe (Wr) that follow companion cascading reductions in the supercoil elastic and electrostatic energies. The novel (to our knowledge) multiscale modeling method may enable simulations of the entire experimental setup that measures DNA supercoiling and relaxation via single molecule magnetic trapping. PMID:21504738

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

    NASA Astrophysics Data System (ADS)

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

    2013-07-01

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

  19. Information Management Workflow and Tools Enabling Multiscale Modeling Within ICME Paradigm

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

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

  20. Multiscale model for the assessment of autonomic dysfunction in human endotoxemia

    PubMed Central

    Foteinou, Panagiota T.; Calvano, Steve E.; Lowry, Stephen F.

    2010-01-01

    Severe injury and infection are associated with autonomic dysfunction. The realization that a dysregulation in autonomic function may predispose a host to excessive inflammatory processes has renewed interest in understanding the role of central nervous system (CNS) in modulating systemic inflammatory processes. Assessment of heart rate variability (HRV) has been used to evaluate systemic abnormalities and as a predictor of the severity of illness. Dissecting the relevance of neuroimmunomodulation in controlling inflammatory processes requires an understanding of the multiscale interplay between CNS and the immune response. A vital enabler in that respect is the development of a systems-based approach that integrates data across multiple scales, and models the emerging host response as the outcome of interactions of critical modules. Thus, a multiscale model of human endotoxemia, as a prototype model of systemic inflammation in humans, is proposed that integrates processes across the host from the cellular to the systemic host response level. At the cellular level interacting components are associated with elementary signaling pathways that propagate extracellular signals to the transcriptional response level. Further, essential modules associated with the neuroendocrine immune crosstalk are considered. Finally, at the systemic level, phenotypic expressions such as HRV are incorporated to assess systemic decomplexification indicative of the severity of the host response. Thus, the proposed work intends to associate acquired endocrine dysfunction with diminished HRV as a critical enabler for clarifying how cellular inflammatory processes and neural-based pathways mediate the links between patterns of autonomic control (HRV) and clinical outcomes. PMID:20233835

  1. Improvements in the Scalability of the NASA Goddard Multiscale Modeling Framework for Hurricane Climate Studies

    NASA Technical Reports Server (NTRS)

    Shen, Bo-Wen; Tao, Wei-Kuo; Chern, Jiun-Dar

    2007-01-01

    Improving our understanding of hurricane inter-annual variability and the impact of climate change (e.g., doubling CO2 and/or global warming) on hurricanes brings both scientific and computational challenges to researchers. As hurricane dynamics involves multiscale interactions among synoptic-scale flows, mesoscale vortices, and small-scale cloud motions, an ideal numerical model suitable for hurricane studies should demonstrate its capabilities in simulating these interactions. The newly-developed multiscale modeling framework (MMF, Tao et al., 2007) and the substantial computing power by the NASA Columbia supercomputer show promise in pursuing the related studies, as the MMF inherits the advantages of two NASA state-of-the-art modeling components: the GEOS4/fvGCM and 2D GCEs. This article focuses on the computational issues and proposes a revised methodology to improve the MMF's performance and scalability. It is shown that this prototype implementation enables 12-fold performance improvements with 364 CPUs, thereby making it more feasible to study hurricane climate.

  2. Identification of crucial parameters in a mathematical multiscale model of glioblastoma growth.

    PubMed

    Schuetz, Tina A; Mang, Andreas; Becker, Stefan; Toma, Alina; Buzug, Thorsten M

    2014-01-01

    Glioblastomas are highly malignant brain tumours. Mathematical models and their analysis provide a tool to support the understanding of the development of these tumours as well as the design of more effective treatment strategies. We have previously developed a multiscale model of glioblastoma progression that covers processes on the cellular and molecular scale. Here, we present a novel nutrient-dependent multiscale sensitivity analysis of this model that helps to identify those reaction parameters of the molecular interaction network that influence the tumour progression on the cellular scale the most. In particular, those parameters are identified that essentially determine tumour expansion and could be therefore used as potential therapy targets. As indicators for the success of a potential therapy target, a deceleration of the tumour expansion and a reduction of the tumour volume are employed. From the results, it can be concluded that no single parameter variation results in a less aggressive tumour. However, it can be shown that a few combined perturbations of two systematically selected parameters cause a slow-down of the tumour expansion velocity accompanied with a decrease of the tumour volume. Those parameters are primarily linked to the reactions that involve the microRNA-451 and the thereof regulated protein MO25. PMID:24899919

  3. Multi-core CPU or GPU-accelerated Multiscale Modeling for Biomolecular Complexes

    PubMed Central

    Liao, Tao; Zhang, Yongjie; Kekenes-Huskey, Peter M.; Cheng, Yuhui; Michailova, Anushka; McCulloch, Andrew D.; Holst, Michael; McCammon, J. Andrew

    2013-01-01

    Multi-scale modeling plays an important role in understanding the structure and biological functionalities of large biomolecular complexes. In this paper, we present an efficient computational framework to construct multi-scale models from atomic resolution data in the Protein Data Bank (PDB), which is accelerated by multi-core CPU and programmable Graphics Processing Units (GPU). A multi-level summation of Gaus-sian kernel functions is employed to generate implicit models for biomolecules. The coefficients in the summation are designed as functions of the structure indices, which specify the structures at a certain level and enable a local resolution control on the biomolecular surface. A method called neighboring search is adopted to locate the grid points close to the expected biomolecular surface, and reduce the number of grids to be analyzed. For a specific grid point, a KD-tree or bounding volume hierarchy is applied to search for the atoms contributing to its density computation, and faraway atoms are ignored due to the decay of Gaussian kernel functions. In addition to density map construction, three modes are also employed and compared during mesh generation and quality improvement to generate high quality tetrahedral meshes: CPU sequential, multi-core CPU parallel and GPU parallel. We have applied our algorithm to several large proteins and obtained good results. PMID:24352481

  4. Multiscale modeling of cell shape from the actin cytoskeleton.

    PubMed

    Rangamani, Padmini; Xiong, Granville Yuguang; Iyengar, Ravi

    2014-01-01

    The actin cytoskeleton is a dynamic structure that constantly undergoes complex reorganization events during many cellular processes. Mathematical models and simulations are powerful tools that can provide insight into the physical mechanisms underlying these processes and make predictions that can be experimentally tested. Representation of the interactions of the actin filaments with the plasma membrane and the movement of the plasma membrane for computation remains a challenge. Here, we provide an overview of the different modeling approaches used to study cytoskeletal dynamics and highlight the differential geometry approach that we have used to implement the interactions between the plasma membrane and the cytoskeleton. Using cell spreading as an example, we demonstrate how this approach is able to successfully capture in simulations, experimentally observed behavior. We provide a perspective on how the differential geometry approach can be used for other biological processes. PMID:24560144

  5. Multiscale Modeling of Powder Bed–Based Additive Manufacturing

    NASA Astrophysics Data System (ADS)

    Markl, Matthias; Körner, Carolin

    2016-07-01

    Powder bed fusion processes are additive manufacturing technologies that are expected to induce the third industrial revolution. Components are built up layer by layer in a powder bed by selectively melting confined areas, according to sliced 3D model data. This technique allows for manufacturing of highly complex geometries hardly machinable with conventional technologies. However, the underlying physical phenomena are sparsely understood and difficult to observe during processing. Therefore, an intensive and expensive trial-and-error principle is applied to produce components with the desired dimensional accuracy, material characteristics, and mechanical properties. This review presents numerical modeling approaches on multiple length scales and timescales to describe different aspects of powder bed fusion processes. In combination with tailored experiments, the numerical results enlarge the process understanding of the underlying physical mechanisms and support the development of suitable process strategies and component topologies.

  6. Multiscale mechanobiology: computational models for integrating molecules to multicellular systems

    PubMed Central

    Mak, Michael; Kim, Taeyoon

    2015-01-01

    Mechanical signals exist throughout the biological landscape. Across all scales, these signals, in the form of force, stiffness, and deformations, are generated and processed, resulting in an active mechanobiological circuit that controls many fundamental aspects of life, from protein unfolding and cytoskeletal remodeling to collective cell motions. The multiple scales and complex feedback involved present a challenge for fully understanding the nature of this circuit, particularly in development and disease in which it has been implicated. Computational models that accurately predict and are based on experimental data enable a means to integrate basic principles and explore fine details of mechanosensing and mechanotransduction in and across all levels of biological systems. Here we review recent advances in these models along with supporting and emerging experimental findings. PMID:26019013

  7. Multiscale modeling of lithium ion batteries: thermal aspects

    PubMed Central

    Zausch, Jochen

    2015-01-01

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

  8. Nonlinear Compliance Modulates Dynamic Bronchoconstriction in a Multiscale Airway Model

    PubMed Central

    Hiorns, Jonathan E.; Jensen, Oliver E.; Brook, Bindi S.

    2014-01-01

    The role of breathing and deep inspirations (DI) in modulating airway hyperresponsiveness remains poorly understood. In particular, DIs are potent bronchodilators of constricted airways in nonasthmatic subjects but not in asthmatic subjects. Additionally, length fluctuations (mimicking DIs) have been shown to reduce mean contractile force when applied to airway smooth muscle (ASM) cells and tissue strips. However, these observations are not recapitulated on application of transmural pressure (PTM) oscillations (that mimic tidal breathing and DIs) in isolated intact airways. To shed light on this paradox, we have developed a biomechanical model of the intact airway, accounting for strain-stiffening due to collagen recruitment (a large component of the extracellular matrix (ECM)), and dynamic actomyosin-driven force generation by ASM cells. In agreement with intact airway studies, our model shows that PTM fluctuations at particular mean transmural pressures can lead to only limited bronchodilation. However, our model predicts that moving the airway to a more compliant point on the static pressure-radius relationship (which may involve reducing mean PTM), before applying pressure fluctuations, can generate greater bronchodilation. This difference arises from competition between passive strain-stiffening of ECM and force generation by ASM yielding a highly nonlinear relationship between effective airway stiffness and PTM, which is modified by the presence of contractile agonist. Effectively, the airway at its most compliant may allow for greater strain to be transmitted to subcellular contractile machinery. The model predictions lead us to hypothesize that the maximum possible bronchodilation of an airway depends on its static compliance at the PTM about which the fluctuations are applied. We suggest the design of additional experimental protocols to test this hypothesis. PMID:25517167

  9. Multi-scale modeling of ternary-component lipid bilayers

    NASA Astrophysics Data System (ADS)

    Tumaneng, Paul

    The connection between membrane inhomogeneity and the structural basis of lipid rafts has sparked interest in the lateral organization of model lipid bilayers of two and three components. In an effort to investigate lateral organization in mixed bilayers, a self-consistent mean-field theoretical model is presented and applied to two important three-component bilayer mixtures. The model utilizes molecular dynamics simulations to estimate interaction parameters and to construct chain conformation libraries for utilization in a statistical mechanical treatment. The first application is to dipalmitoylphosphatidylcholine (DOPC) - stearoyl sphingomyelin (SSM) - cholesterol mixtures. The compositional dependence of lateral organization in these mixtures is mapped onto a ternary plot. It is found that at some concentration ratios the bilayers separate spatially into regions of higher and lower chain order coinciding with areas enriched with SSM and DOPC respectively. In the second application, ternary mixtures of palmitoyloleoylphosphatidylcholine (POPC) - palmitoyl sphingomyelin (PSM) - cholesterol are investigated. Again, results are organized onto a ternary plot. To examine the effect of the asymmetric chain structure of POPC on bilayer lateral inhomogeneity, POPC-POPC interactions with and without angular dependence are considered. Results are compared with experimental data and with results from the DOPC - SSM - cholesterol mixtures.

  10. A Multiscale Model Evaluates Screening for Neoplasia in Barrett's Esophagus.

    PubMed

    Curtius, Kit; Hazelton, William D; Jeon, Jihyoun; Luebeck, E Georg

    2015-05-01

    Barrett's esophagus (BE) patients are routinely screened for high grade dysplasia (HGD) and esophageal adenocarcinoma (EAC) through endoscopic screening, during which multiple esophageal tissue samples are removed for histological analysis. We propose a computational method called the multistage clonal expansion for EAC (MSCE-EAC) screening model that is used for screening BE patients in silico to evaluate the effects of biopsy sampling, diagnostic sensitivity, and treatment on disease burden. Our framework seamlessly integrates relevant cell-level processes during EAC development with a spatial screening process to provide a clinically relevant model for detecting dysplastic and malignant clones within the crypt-structured BE tissue. With this computational approach, we retain spatio-temporal information about small, unobserved tissue lesions in BE that may remain undetected during biopsy-based screening but could be detected with high-resolution imaging. This allows evaluation of the efficacy and sensitivity of current screening protocols to detect neoplasia (dysplasia and early preclinical EAC) in the esophageal lining. We demonstrate the clinical utility of this model by predicting three important clinical outcomes: (1) the probability that small cancers are missed during biopsy-based screening, (2) the potential gains in neoplasia detection probabilities if screening occurred via high-resolution tomographic imaging, and (3) the efficacy of ablative treatments that result in the curative depletion of metaplastic and neoplastic cell populations in BE in terms of the long-term impact on reducing EAC incidence. PMID:26001209

  11. Multiscale modeling of metabolism, flows, and exchanges in heterogeneous organs

    PubMed Central

    Bassingthwaighte, James B.; Raymond, Gary M.; Butterworth, Erik; Alessio, Adam; Caldwell, James H.

    2010-01-01

    Large-scale models accounting for the processes supporting metabolism and function in an organ or tissue with a marked heterogeneity of flows and metabolic rates are computationally complex and tedious to compute. Their use in the analysis of data from positron emission tomography (PET) and magnetic resonance imaging (MRI) requires model reduction since the data are composed of concentration–time curves from hundreds of regions of interest (ROI) within the organ. Within each ROI, one must account for blood flow, intracapillary gradients in concentrations, transmembrane transport, and intracellular reactions. Using modular design, we configured a whole organ model, GENTEX, to allow adaptive usage for multiple reacting molecular species while omitting computation of unused components. The temporal and spatial resolution and the number of species are adaptable and the numerical accuracy and computational speed is adjustable during optimization runs, which increases accuracy and spatial resolution as convergence approaches. An application to the interpretation of PET image sequences after intravenous injection of 13NH3 provides functional image maps of regional myocardial blood flows. PMID:20201893

  12. Automatic Multi-Scale Calibration Procedure for Nested Hydrological-Hydrogeological Regional Models

    NASA Astrophysics Data System (ADS)

    Labarthe, B.; Abasq, L.; Flipo, N.; de Fouquet, C. D.

    2014-12-01

    Large hydrosystem modelling and understanding is a complex process depending on regional and local processes. A nested interface concept has been implemented in the hydrosystem modelling platform for a large alluvial plain model (300 km2) part of a 11000 km2 multi-layer aquifer system, included in the Seine basin (65000 km2, France). The platform couples hydrological and hydrogeological processes through four spatially distributed modules (Mass balance, Unsaturated Zone, River and Groundwater). An automatic multi-scale calibration procedure is proposed. Using different data sets from regional scale (117 gauging stations and 183 piezometers over the 65000 km2) to the intermediate scale(dense past piezometric snapshot), it permits the calibration and homogenization of model parameters over scales.The stepwise procedure starts with the optimisation of the water mass balance parameters at regional scale using a conceptual 7 parameters bucket model coupled with the inverse modelling tool PEST. The multi-objective function is derived from river discharges and their de-composition by hydrograph separation. The separation is performed at each gauging station using an automatic procedure based one Chapman filter. Then, the model is run at the regional scale to provide recharge estimate and regional fluxes to the groundwater local model. Another inversion method is then used to determine the local hydrodynamic parameters. This procedure used an initial kriged transmissivity field which is successively updated until the simulated hydraulic head distribution equals a reference one obtained by krigging. Then, the local parameters are upscaled to the regional model by renormalisation procedure.This multi-scale automatic calibration procedure enhances both the local and regional processes representation. Indeed, it permits a better description of local heterogeneities and of the associated processes which are transposed into the regional model, improving the overall performances

  13. Evaluation of a Cloud Resolving Model Using TRMM Observations for Multiscale Modeling Applications

    NASA Technical Reports Server (NTRS)

    Posselt, Derek J.; L'Ecuyer, Tristan; Tao, Wei-Kuo; Hou, Arthur Y.; Stephens, Graeme L.

    2007-01-01

    The climate change simulation community is moving toward use of global cloud resolving models (CRMs), however, current computational resources are not sufficient to run global CRMs over the hundreds of years necessary to produce climate change estimates. As an intermediate step between conventional general circulation models (GCMs) and global CRMs, many climate analysis centers are embedding a CRM in each grid cell of a conventional GCM. These Multiscale Modeling Frameworks (MMFs) represent a theoretical advance over the use of conventional GCM cloud and convection parameterizations, but have been shown to exhibit an overproduction of precipitation in the tropics during the northern hemisphere summer. In this study, simulations of clouds, precipitation, and radiation over the South China Sea using the CRM component of the NASA Goddard MMF are evaluated using retrievals derived from the instruments aboard the Tropical Rainfall Measuring Mission (TRMM) satellite platform for a 46-day time period that spans 5 May - 20 June 1998. The NASA Goddard Cumulus Ensemble (GCE) model is forced with observed largescale forcing derived from soundings taken during the intensive observing period of the South China Sea Monsoon Experiment. It is found that the GCE configuration used in the NASA Goddard MMF responds too vigorously to the imposed large-scale forcing, accumulating too much moisture and producing too much cloud cover during convective phases, and overdrying the atmosphere and suppressing clouds during monsoon break periods. Sensitivity experiments reveal that changes to ice cloud microphysical parameters have a relatively large effect on simulated clouds, precipitation, and radiation, while changes to grid spacing and domain length have little effect on simulation results. The results motivate a more detailed and quantitative exploration of the sources and magnitude of the uncertainty associated with specified cloud microphysical parameters in the CRM components of MMFs.

  14. Multiscale modeling of photon detectors from the infrared to the ultraviolet

    NASA Astrophysics Data System (ADS)

    Bellotti, Enrico; Schuster, Jonathan; Pinkie, Benjamin; Bertazzi, Francesco

    2013-09-01

    Due to the ever increasing complexity of novel semiconductor systems, it is essential to possess design tools and simulation strategies that include in the macroscopic device models the details of the microscopic physics and their dependence on the macroscopic (continuum) variables. Towards this end, we have developed robust multi-scale modeling capabilities that begin with modeling the intrinsic semiconductor properties. The models are fully capable of incorporating effects of substrate driven stress/strain and the material quality (dislocations and defects) on microscopic quantities such as the local transport coefficients and non-radiative recombination rate. Using this modeling approach we have extensively studied UV APD detectors and infrared focal plane arrays. Particular emphasis was placed on HgCdTe and InAsSb arrays incorporating photon trapping structures as well as two-color HgCdTe detectors arrays.

  15. Multiscale modeling of liquid crystalline/nanotube composites

    NASA Astrophysics Data System (ADS)

    Patrale, Sharil

    The objective of this research is to synthesize structural composites designed with particular areas defined with custom modulus, strength and toughness values in order to improve the overall mechanical behavior of the composite. Such composites are defined and referred to as 3D-designer composites. These composites will be formed from liquid crystalline polymers and carbon nanotubes. The fabrication process is a variation of rapid prototyping process, which is a layered, additive-manufacturing approach. Composites formed using this process can be custom designed by apt modeling methods for superior performance in advanced applications. The focus of this research is on enhancement of Young's modulus in order to make the final composite stiffer. Strength and toughness of the final composite with respect to various applications is also discussed. We have taken into consideration the mechanical properties of final composite at different fiber volume content as well as at different orientations and lengths of the fibers. The orientation of the LC monomers is supposed to be carried out using electric or magnetic fields. A computer program is modeled incorporating the Mori-Tanaka modeling scheme to generate the stiffness matrix of the final composite. The final properties are then deduced from the stiffness matrix using composite micromechanics. Eshelby's tensor, required to calculate the stiffness tensor using Mori-Tanaka method, is calculated using a numerical scheme that determines the components of the Eshelby's tensor (Gavazzi and Lagoudas 1990). The numerical integration is solved using Gaussian Quadrature scheme and is worked out using MATLAB as well. MATLAB provides a good deal of commands and algorithms that can be used efficiently to elaborate the continuum of the formula to its extents. Graphs are plotted using different combinations of results and parameters involved in finding these results.

  16. Multi-scale modeling and synthesis of polyester ionomers.

    PubMed

    Nikolić, Dragan; Moffat, Karen A; Farrugia, Valerie M; Kobryn, Alexander E; Gusarov, Sergey; Wosnick, Jordan H; Kovalenko, Andriy

    2013-04-28

    Simulations of microphase separation are carried out using the dissipative particle dynamics (DPD). By varying the concentration and temperature of resin solutions we explore mesomorphologies supported by the all-atom models. We found that for a low degree of functionalization the homogeneously distributed ionomers self-assemble into spherical micelles at solid loads below 31 wt%, subject to the activation energy barrier for the gradual growth of pre-micellar aggregates. Computed optimum aggregation numbers exhibit sensitivity to both the temperature-dependent interfacial tension and the ionic content and compare well with the experimental observations. PMID:23507929

  17. Towards enhancing Sandia's capabilities in multiscale materials modeling and simulation.

    SciTech Connect

    Aidun, John Bahram; Fang, Huei Eliot; Barbour, John Charles; Westrich, Henry Roger; Chen, Er-Ping

    2004-01-01

    We report our conclusions in support of the FY 2003 Science and Technology Milestone ST03-3.5. The goal of the milestone was to develop a research plan for expanding Sandia's capabilities in materials modeling and simulation. From inquiries and discussion with technical staff during FY 2003 we conclude that it is premature to formulate the envisioned coordinated research plan. The more appropriate goal is to develop a set of computational tools for making scale transitions and accumulate experience with applying these tools to real test cases so as to enable us to attack each new problem with higher confidence of success.

  18. multi-scale approaches for full waveform difference inversion and tomographic model analysis

    NASA Astrophysics Data System (ADS)

    Yuan, Y.; Simons, F. J.; Luo, Y.

    2012-12-01

    Tomographic Earth models are solutions to mixed-determined inverse problems, which are formulated to minimize some measure of difference between synthetics and observed data. Typically, the measurement takes the form of a cross-correlation travel-time difference, or it might be the norm of the difference between the entire waveforms, in which case every wiggle is being used to extract information from the data. Full-waveform difference tomography suffers from a slow convergence rate and a danger of converging to local minima. In this presentation, we explore several routes to improving full-waveform inversion strategies for global and regional seismic tomography. First, we will discuss a wavelet-based multi-scale approach that works progressively from low to higher scales, step-by-step involving more details of the waveform. Second, we will discuss a hybrid misfit strategy that combines cross-correlation traveltime and waveform-difference measurements. We will discuss the making of multiscale sensitivity kernels using wavelet decompositions of the seismogram. Lastly, we move to the model space to conduct a multi-scale analysis of global tomographic models using a class of 3-D spherical wavelet bases that are implemented on the ``cubed ball'', the 3-D extension of the ``cubed sphere''. Using this novel transform we study the sparsity of global seismic tomographic models via thresholded reconstruction, and characterize the relative importance and patterns of features in the Earth models via individual and cumulative reconstructions of their wavelet coefficients. Whether on the side of the data, the sensitivity kernels, or in the model space, tomographic inverse problems have much to gain from the flexibility of the wavelet decomposition in one, two and three dimensions, and this on a global, regional or exploration scale, as we show by example. Full waveform difference inversion. The first figure shows our target model with two anomalous regions. The red stars

  19. On-line coupling of volcanic ash and aerosols transport with multiscale meteorological models

    NASA Astrophysics Data System (ADS)

    Marti, Alejandro; Folch, Arnau; Jorba, Oriol

    2014-05-01

    Large explosive volcanic eruptions can inject significant amounts of tephra and aerosols (e.g. SO2) into the atmosphere inducing a multi-scale array of physical, chemical and biological feedbacks within the environment. Effective coupled Numerical Weather Prediction (NWP) models capable to forecast on-line the spatial and temporal distribution of volcanic ash and aerosols are necessary to assess the magnitude of these feedback effects. However, due to several limitations (users from different communities, operational constrains, computational power, etc.), tephra transport models and NWP models have evolved independently. Within the framework of NEMOH(an Initial Training Network of the European Commission FP7 Program), we aim to quantify the feedback effects of volcanic ash clouds and aerosols emitted during large-magnitude eruptions on regional meteorology. As a first step, we have focused on the differences between the off-line hypothesis, currently assumed by tephra transport models (e.g. FALL3D), and the on-line approach, where transport and sedimentation of volcanic ash is coupled on-line to the NMMB (Non-hydrostatic Multiscale Meteorological model on a B grid) meteorological model; the evolution of the WRF-NMME meteorological model. We compared the spatiotemporal transport of volcanic ash particles simulated with the on-line coupled FALL3D-NMMB/BSC-CTM model with those from the off-line FALL3D model, by using the 2011 Cordón-Caulle eruption as a test-case and validating results against satellite data. Additionally, this presentation introduces the forthcoming steps to implement a sulfate aerosol module within the chemical transport module of the FALL3D-NMMB/BSC-CTM model, in order to quantify the feedback effects on the atmospheric radiative budget, particularly during large-magnitude explosive volcanic eruptions. Keywords: volcanic ash, SO2, FALL3D, NMMB, meteorology, on-line coupling, NEMOH.

  20. A MULTISCALE MODEL OF THE ORGAN OF CORTI

    PubMed Central

    Steele, Charles R.; Boutet de Monvel, Jacques; Puria, Sunil

    2010-01-01

    The organ of Corti is the sensory epithelium in the cochlea of the inner ear. It is modeled as a shell-of-revolution structure with continuous and discrete components. Our recent work has been on the inclusion of the viscous fluid. Measurements from various laboratories provide the opportunity to refocus on the elastic properties. The current detailed model for the organ of Corti is reasonably consistent with diverse measurements. Most components have little stiffness in the propagation direction. However, the isotropic stiffness of the pillar heads is found to offer an explanation for the difference in point load and pressure measurements. The individual rows of inner hair cell stereocilia with tip links and the Hensen stripe are included, since these details are important for the determination of the neural excitation. The results for low frequency show a phase of tip link tension similar to auditory nerve measurements. The nonlinearity of fluid in the small gaps is considered. A result is that as amplitude increases, because of the near contact with the Hensen stripe, the excitation changes polarity, similar to the peak-splitting neural behavior sometimes observed. PMID:20485573

  1. Multi-scale modelling for HEDP experiments on Orion

    NASA Astrophysics Data System (ADS)

    Sircombe, N. J.; Ramsay, M. G.; Hughes, S. J.; Hoarty, D. J.

    2016-05-01

    The Orion laser at AWE couples high energy long-pulse lasers with high intensity short-pulses, allowing material to be compressed beyond solid density and heated isochorically. This experimental capability has been demonstrated as a platform for conducting High Energy Density