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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

    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.

  3. 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.

  4. Stochastic multi-scale prediction on the apparent elastic moduli of trabecular bone considering uncertainties of biological apatite (BAp) crystallite orientation and image-based modelling.

    PubMed

    Basaruddin, Khairul Salleh; Takano, Naoki; Nakano, Takayoshi

    2015-01-01

    An assessment of the mechanical properties of trabecular bone is important in determining the fracture risk of human bones. Many uncertainty factors contribute to the dispersion of the estimated mechanical properties of trabecular bone. This study was undertaken in order to propose a computational scheme that will be able to predict the effective apparent elastic moduli of trabecular bone considering the uncertainties that are primarily caused by image-based modelling and trabecular stiffness orientation. The effect of image-based modelling which focused on the connectivity was also investigated. A stochastic multi-scale method using a first-order perturbation-based and asymptotic homogenisation theory was applied to formulate the stochastically apparent elastic properties of trabecular bone. The effective apparent elastic modulus was predicted with the introduction of a coefficient factor to represent the variation of bone characteristics due to inter-individual differences. The mean value of the predicted effective apparent Young's modulus in principal axis was found at approximately 460 MPa for respective 15.24% of bone volume fraction, and this is in good agreement with other experimental results. The proposed method may provide a reference for the reliable evaluation of the prediction of the apparent elastic properties of trabecular bone.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. Novel framework for producing multi-scale and multi-viewpoint images based on remote sensing stereopair

    NASA Astrophysics Data System (ADS)

    Tan, Ying; Cao, Zhiguo; Li, Yukun

    2007-11-01

    Automatic target recognition(ATR) is the key of the image guidance technology, yet it is difficult to recognize the target by merely depending on the real-time image acquired by flying vehicle cameras, moreover, the task of recognizing the target from the real-time images by the vehicle-carrying image processing system is a hard work itself. The main trend of the ATR nowadays is to make utilization of the images produced by high-resolution remote sensing satellite to retrieve the front elevation of the interested region before hand. These front elevations are loaded upon the flying vehicles and are matched with the real-time images acquired by vehicle-carrying cameras to recognize the interested target. Obviously, the key step of this method is to recover the 3D information from 2D images. This paper proposed a framework to produce multi-scale and multi-viewpoint projection images based on remote sensing satellite stereopair by means of photogrammetry and computer vision. First we proposed a algorithm for reconstructing the 3D structure of the target by digital photogrammetric techniques and establishing the 3D model of the target using the OpenGL visualization toolkit. Then the conversion relationship between the world coordinate system and the simulation space coordinate system is provided to produce the front elevation in the simulation space.

  14. 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

  15. Differential geometry based multiscale models.

    PubMed

    Wei, Guo-Wei

    2010-08-01

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

  16. Differential geometry based multiscale models.

    PubMed

    Wei, Guo-Wei

    2010-08-01

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

  17. Multiscale modelling of DNA mechanics

    NASA Astrophysics Data System (ADS)

    Dršata, Tomáš; Lankaš, Filip

    2015-08-01

    Mechanical properties of DNA are important not only in a wide range of biological processes but also in the emerging field of DNA nanotechnology. We review some of the recent developments in modeling these properties, emphasizing the multiscale nature of the problem. Modern atomic resolution, explicit solvent molecular dynamics simulations have contributed to our understanding of DNA fine structure and conformational polymorphism. These simulations may serve as data sources to parameterize rigid base models which themselves have undergone major development. A consistent buildup of larger entities involving multiple rigid bases enables us to describe DNA at more global scales. Free energy methods to impose large strains on DNA, as well as bead models and other approaches, are also briefly discussed.

  18. 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.

  19. Multiscale modelling of saliva secretion.

    PubMed

    Sneyd, James; Crampin, Edmund; Yule, David

    2014-11-01

    We review a multiscale model of saliva secretion, describing in brief how the model is constructed and what we have so far learned from it. The model begins at the level of inositol trisphosphate receptors (IPR), and proceeds through the cellular level (with a model of acinar cell calcium dynamics) to the multicellular level (with a model of the acinus), finally to a model of a saliva production unit that includes an acinus and associated duct. The model at the level of the entire salivary gland is not yet completed. Particular results from the model so far include (i) the importance of modal behaviour of IPR, (ii) the relative unimportance of Ca(2+) oscillation frequency as a controller of saliva secretion, (iii) the need for the periodic Ca(2+) waves to be as fast as possible in order to maximise water transport, (iv) the presence of functional K(+) channels in the apical membrane increases saliva secretion, (v) the relative unimportance of acinar spatial structure for isotonic water transport, (vi) the prediction that duct cells are highly depolarised, (vii) the prediction that the secondary saliva takes at least 1mm (from the acinus) to reach ionic equilibrium. We end with a brief discussion of future directions for the model, both in construction and in the study of scientific questions.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. Image based modeling of tumor growth.

    PubMed

    Meghdadi, N; Soltani, M; Niroomand-Oscuii, H; Ghalichi, F

    2016-09-01

    Tumors are a main cause of morbidity and mortality worldwide. Despite the efforts of the clinical and research communities, little has been achieved in the past decades in terms of improving the treatment of aggressive tumors. Understanding the underlying mechanism of tumor growth and evaluating the effects of different therapies are valuable steps in predicting the survival time and improving the patients' quality of life. Several studies have been devoted to tumor growth modeling at different levels to improve the clinical outcome by predicting the results of specific treatments. Recent studies have proposed patient-specific models using clinical data usually obtained from clinical images and evaluating the effects of various therapies. The aim of this review is to highlight the imaging role in tumor growth modeling and provide a worthwhile reference for biomedical and mathematical researchers with respect to tumor modeling using the clinical data to develop personalized models of tumor growth and evaluating the effect of different therapies.

  9. Image based modeling of tumor growth.

    PubMed

    Meghdadi, N; Soltani, M; Niroomand-Oscuii, H; Ghalichi, F

    2016-09-01

    Tumors are a main cause of morbidity and mortality worldwide. Despite the efforts of the clinical and research communities, little has been achieved in the past decades in terms of improving the treatment of aggressive tumors. Understanding the underlying mechanism of tumor growth and evaluating the effects of different therapies are valuable steps in predicting the survival time and improving the patients' quality of life. Several studies have been devoted to tumor growth modeling at different levels to improve the clinical outcome by predicting the results of specific treatments. Recent studies have proposed patient-specific models using clinical data usually obtained from clinical images and evaluating the effects of various therapies. The aim of this review is to highlight the imaging role in tumor growth modeling and provide a worthwhile reference for biomedical and mathematical researchers with respect to tumor modeling using the clinical data to develop personalized models of tumor growth and evaluating the effect of different therapies. PMID:27596102

  10. 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

  11. Multiscale modeling of nucleosome dynamics.

    PubMed

    Sharma, Shantanu; Ding, Feng; Dokholyan, Nikolay V

    2007-03-01

    Nucleosomes form the fundamental building blocks of chromatin. Subtle modifications of the constituent histone tails mediate chromatin stability and regulate gene expression. For this reason, it is important to understand structural dynamics of nucleosomes at atomic levels. We report a novel multiscale model of the fundamental chromatin unit, a nucleosome, using a simplified model for rapid discrete molecular dynamics simulations and an all-atom model for detailed structural investigation. Using a simplified structural model, we perform equilibrium simulations of a single nucleosome at various temperatures. We further reconstruct all-atom nucleosome structures from simulation trajectories. We find that histone tails bind to nucleosomal DNA via strong salt-bridge interactions over a wide range of temperatures, suggesting a mechanism of chromatin structural organization whereby histone tails regulate inter- and intranucleosomal assemblies via binding with nucleosomal DNA. We identify specific regions of the histone core H2A/H2B-H4/H3-H3/H4-H2B/H2A, termed "cold sites", which retain a significant fraction of contacts with adjoining residues throughout the simulation, indicating their functional role in nucleosome organization. Cold sites are clustered around H3-H3, H2A-H4 and H4-H2A interhistone interfaces, indicating the necessity of these contacts for nucleosome stability. Essential dynamics analysis of simulation trajectories shows that bending across the H3-H3 is a prominent mode of intranucleosomal dynamics. We postulate that effects of salts on mononucleosomes can be modeled in discrete molecular dynamics by modulating histone-DNA interaction potentials. Local fluctuations in nucleosomal DNA vary significantly along the DNA sequence, suggesting that only a fraction of histone-DNA contacts make strong interactions dominating mononucleosomal dynamics. Our findings suggest that histone tails have a direct functional role in stabilizing higher-order chromatin

  12. 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.

  13. 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.

  14. Image-Based Modeling of Trabecular Bones

    NASA Astrophysics Data System (ADS)

    Rajapakse, Chamith; Gunaratne, Gemunu

    2004-10-01

    Osteoporosis is a major health problem in the U.S. today. The detection and treatment of osteoporosis is currently based on Bone Mineral Density (BMD) measurements. Recent evidence suggests that the low bone mass alone does not account for the entire risk of osteoporotic fractures. It is also been known that the trabecular regions of bones play a major role in the bone strength . Trabecular bone has a complex structure with substantial heterogeneity, anisotropy and asymmetry. Although these properties effect BMD, the role of architecture and tissue material remain uncertain. Computer modeling of trabecular bone can be used predict responses that cannot be obtained experimentally, and they can compute responses that cannot be measured in-vivo. Due to the complexity of the Trabecular Architecture (TA) a model system based on scanned digital images is introduced to get substantial insight of TA and to predict the failure behavior. It is assumed that the added insight provided by these studies will lead to improved diagnostics and treatments of patient-specific osteoporotic fractures.

  15. 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

  16. 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

  17. 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

  18. 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

  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. 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

  1. 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

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. Multi-scale modeling in cell biology

    PubMed Central

    Meier-Schellersheim, Martin; Fraser, Iain D. C.; Klauschen, Frederick

    2009-01-01

    Biomedical research frequently involves performing experiments and developing hypotheses that link different scales of biological systems such as, for instance, the scales of intracellular molecular interactions to the scale of cellular behavior and beyond to the behavior of cell populations. Computational modeling efforts that aim at exploring such multi-scale systems quantitatively with the help of simulations have to incorporate several different simulation techniques due to the different time and space scales involved. Here, we provide a non-technical overview of how different scales of experimental research can be combined with the appropriate computational modeling techniques. We also show that current modeling software permits building and simulating multi-scale models without having to become involved with the underlying technical details of computational modeling. PMID:20448808

  7. 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

  8. Multiscale Models of Breast Cancer Progression

    PubMed Central

    Chakrabarti, Anirikh; Verbridge, Scott; Stroock, Abraham D.; Fischbach, Claudia; Varner, Jeffrey D.

    2013-01-01

    Breast cancer initiation, invasion and metastasis span multiple length and time scales. Molecular events at short length scales lead to an initial tumorigenic population, which left unchecked by immune action, acts at increasingly longer length scales until eventually the cancer cells escape from the primary tumor site. This series of events is highly complex, involving multiple cell types interacting with (and shaping) the microenvironment. Multiscale mathematical models have emerged as a powerful tool to quantitatively integrate the convective-diffusion-reaction processes occurring on the systemic scale, with the molecular signaling processes occurring on the cellular and subcellular scales. In this study, we reviewed the current state of the art in cancer modeling across multiple length scales, with an emphasis on the integration of intracellular signal transduction models with pro-tumorigenic chemical and mechanical microenvironmental cues. First, we reviewed the underlying biomolecular origin of breast cancer, with a special emphasis on angiogenesis. Then, we summarized the development of tissue engineering platforms which could provide highfidelity ex vivo experimental models to identify and validate multiscale simulations. Lastly, we reviewed top-down and bottom-up multiscale strategies that integrate subcellular networks with the microenvironment. We present models of a variety of cancers, in addition to breast cancer specific models. Taken together, we expect as the sophistication of the simulations increase, that multiscale modeling and bottom-up agent-based models in particular will become an increasingly important platform technology for basic scientific discovery, as well as the identification and validation of potentially novel therapeutic targets. PMID:23008097

  9. 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.

  10. Multiscale constitutive modeling of polymer materials

    NASA Astrophysics Data System (ADS)

    Valavala, Pavan Kumar

    Materials are inherently multi-scale in nature consisting of distinct characteristics at various length scales from atoms to bulk material. There are no widely accepted predictive multi-scale modeling techniques that span from atomic level to bulk relating the effects of the structure at the nanometer (10-9 meter) on macro-scale properties. Traditional engineering deals with treating matter as continuous with no internal structure. In contrast to engineers, physicists have dealt with matter in its discrete structure at small length scales to understand fundamental behavior of materials. Multiscale modeling is of great scientific and technical importance as it can aid in designing novel materials that will enable us to tailor properties specific to an application like multi-functional materials. Polymer nanocomposite materials have the potential to provide significant increases in mechanical properties relative to current polymers used for structural applications. The nanoscale reinforcements have the potential to increase the effective interface between the reinforcement and the matrix by orders of magnitude for a given reinforcement volume fraction as relative to traditional micro- or macro-scale reinforcements. To facilitate the development of polymer nanocomposite materials, constitutive relationships must be established that predict the bulk mechanical properties of the materials as a function of the molecular structure. A computational hierarchical multiscale modeling technique is developed to study the bulk-level constitutive behavior of polymeric materials as a function of its molecular chemistry. Various parameters and modeling techniques from computational chemistry to continuum mechanics are utilized for the current modeling method. The cause and effect relationship of the parameters are studied to establish an efficient modeling framework. The proposed methodology is applied to three different polymers and validated using experimental data available in

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. Modelling multiscale aspects of colorectal cancer

    NASA Astrophysics Data System (ADS)

    van Leeuwen, Ingeborg M. M.; Byrne, Helen M.; Johnston, Matthew D.; Edwards, Carina M.; Chapman, S. Jonathan; Bodmer, Walter F.; Maini, Philip K.

    2008-01-01

    Colorectal cancer (CRC) is responsible for nearly half a million deaths annually world-wide [11]. We present a series of mathematical models describing the dynamics of the intestinal epithelium and the kinetics of the molecular pathway most commonly mutated in CRC, the Wnt signalling network. We also discuss how we are coupling such models to build a multiscale model of normal and aberrant guts. This will enable us to combine disparate experimental and clinical data, to investigate interactions between phenomena taking place at different levels of organisation and, eventually, to test the efficacy of new drugs on the system as a whole.

  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. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. Concurrent multiscale modeling of amorphous materials

    NASA Astrophysics Data System (ADS)

    Tan, Vincent

    2013-03-01

    An approach to multiscale modeling of amorphous materials is presented whereby atomistic scale domains coexist with continuum-like domains. The atomistic domains faithfully predict severe deformation while the continuum domains allow the computation to scale up the size of the model without incurring excessive computational costs associated with fully atomistic models and without the introduction of spurious forces across the boundary of atomistic and continuum-like domains. The material domain is firstly constructed as a tessellation of Amorphous Cells (AC). For regions of small deformation, the number of degrees of freedom is then reduced by computing the displacements of only the vertices of the ACs instead of the atoms within. This is achieved by determining, a priori, the atomistic displacements within such Pseudo Amorphous Cells associated with orthogonal deformation modes of the cell. Simulations of nanoscale polymer tribology using full molecular mechanics computation and our multiscale approach give almost identical prediction of indentation force and the strain contours of the polymer. We further demonstrate the capability of performing adaptive simulations during which domains that were discretized into cells revert to full atomistic domains when their strain attain a predetermined threshold. The authors would like to acknowledge the financial support given to this study by the Agency of Science, Technology and Research (ASTAR), Singapore (SERC Grant No. 092 137 0013).

  4. 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

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. A multiscale model for virus capsid dynamics.

    PubMed

    Chen, Changjun; Saxena, Rishu; Wei, Guo-Wei

    2010-01-01

    Viruses are infectious agents that can cause epidemics and pandemics. The understanding of virus formation, evolution, stability, and interaction with host cells is of great importance to the scientific community and public health. Typically, a virus complex in association with its aquatic environment poses a fabulous challenge to theoretical description and prediction. In this work, we propose a differential geometry-based multiscale paradigm to model complex biomolecule systems. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum domain of the fluid mechanical description of the aquatic environment from the microscopic discrete domain of the atomistic description of the biomolecule. A multiscale action functional is constructed as a unified framework to derive the governing equations for the dynamics of different scales. We show that the classical Navier-Stokes equation for the fluid dynamics and Newton's equation for the molecular dynamics can be derived from the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. PMID:20224756

  10. Multiscale modeling for image analysis of brain tumor studies.

    PubMed

    Bauer, Stefan; May, Christian; Dionysiou, Dimitra; Stamatakos, Georgios; Büchler, Philippe; Reyes, Mauricio

    2012-01-01

    Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multiscale, multiphysics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlas-based segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression. PMID:21813362

  11. 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

  12. 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.

  13. 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.

  14. 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+.

  15. Multiscale modelling of nucleosome core particle aggregation.

    PubMed

    Lyubartsev, Alexander P; Korolev, Nikolay; Fan, Yanping; Nordenskiöld, Lars

    2015-02-18

    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 (CoHex(3+)) 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 CoHex(3+). 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, spermidine(3+).

  16. 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

  17. Integrated VR platform for 3D and image-based models: a step toward interactive image-based virtual environments

    NASA Astrophysics Data System (ADS)

    Yoon, Jayoung; Kim, Gerard J.

    2003-04-01

    Traditionally, three dimension models have been used for building virtual worlds, and a data structure called the "scene graph" is often employed to organize these 3D objects in the virtual space. On the other hand, image-based rendering has recently been suggested as a probable alternative VR platform for its photo-realism, however, due to limited interactivity, it has only been used for simple navigation systems. To combine the merits of these two approaches to object/scene representations, this paper proposes for a scene graph structure in which both 3D models and various image-based scenes/objects can be defined, traversed, and rendered together. In fact, as suggested by Shade et al., these different representations can be used as different LOD's for a given object. For instance, an object might be rendered using a 3D model at close range, a billboard at an intermediate range, and as part of an environment map at far range. The ultimate objective of this mixed platform is to breath more interactivity into the image based rendered VE's by employing 3D models as well. There are several technical challenges in devising such a platform: designing scene graph nodes for various types of image based techniques, establishing criteria for LOD/representation selection, handling their transitions, implementing appropriate interaction schemes, and correctly rendering the overall scene. Currently, we have extended the scene graph structure of the Sense8's WorldToolKit, to accommodate new node types for environment maps billboards, moving textures and sprites, "Tour-into-the-Picture" structure, and view interpolated objects. As for choosing the right LOD level, the usual viewing distance and image space criteria are used, however, the switching between the image and 3D model occurs at a distance from the user where the user starts to perceive the object's internal depth. Also, during interaction, regardless of the viewing distance, a 3D representation would be used, it if

  18. MSCALE: A General Utility for Multiscale Modeling.

    PubMed

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

    2011-04-12

    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.

  19. 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.

  20. Multiscale registration of medical images based on edge preserving scale space with application in image-guided radiation therapy

    NASA Astrophysics Data System (ADS)

    Li, Dengwang; Li, Hongsheng; Wan, Honglin; Chen, Jinhu; Gong, Guanzhong; Wang, Hongjun; Wang, Liming; Yin, Yong

    2012-08-01

    Mutual information (MI) is a well-accepted similarity measure for image registration in medical systems. However, MI-based registration faces the challenges of high computational complexity and a high likelihood of being trapped into local optima due to an absence of spatial information. In order to solve these problems, multi-scale frameworks can be used to accelerate registration and improve robustness. Traditional Gaussian pyramid representation is one such technique but it suffers from contour diffusion at coarse levels which may lead to unsatisfactory registration results. In this work, a new multi-scale registration framework called edge preserving multiscale registration (EPMR) was proposed based upon an edge preserving total variation L1 norm (TV-L1) scale space representation. TV-L1 scale space is constructed by selecting edges and contours of images according to their size rather than the intensity values of the image features. This ensures more meaningful spatial information with an EPMR framework for MI-based registration. Furthermore, we design an optimal estimation of the TV-L1 parameter in the EPMR framework by training and minimizing the transformation offset between the registered pairs for automated registration in medical systems. We validated our EPMR method on both simulated mono- and multi-modal medical datasets with ground truth and clinical studies from a combined positron emission tomography/computed tomography (PET/CT) scanner. We compared our registration framework with other traditional registration approaches. Our experimental results demonstrated that our method outperformed other methods in terms of the accuracy and robustness for medical images. EPMR can always achieve a small offset value, which is closer to the ground truth both for mono-modality and multi-modality, and the speed can be increased 5-8% for mono-modality and 10-14% for multi-modality registration under the same condition. Furthermore, clinical application by adaptive

  1. 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

  2. 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.

  3. 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

  4. On dynamic modeling for multiscale turbulence problems

    NASA Astrophysics Data System (ADS)

    Chester, Stuart

    Simulating multiscale flows is a challenge because of the vast computational resources required to follow the large number of degrees of freedom involved. The dynamic procedure (Germano et al., 1991) is a powerful modeling tool in the simulation of inherently multiscale turbulent flows, and is the basis for the two main parts of this work. In the first part, high-Reynolds-number flow over tree-like fractals is considered, with emphasis on the drag forces produced. Using large-eddy simulation (LES) of flow over prefractals with multiple branch generations, the dependence of the tree drag on the inner cutoff scale of the fractal is studied. It is found that the convergence of the drag coefficient towards a value that is cutoff-scale independent is slow enough that directly resolving the geometry of all the relevant small-scale branches is highly impractical. To address this fundamental difficulty, a new numerical modeling technique called Renormalized Numerical Simulation (RNS) is introduced. RNS models the drag of the unresolved branches using drag coefficients measured from both resolved branches and unresolved branches (as modeled in previous iterations of the procedure). The RNS technique and its convergence properties are tested by means of a series of simulations using different levels of resolution. Then, RNS is used to investigate the influence of the tree fractal dimension on the tree drag coefficient. Results illustrate that RNS enables numerical modeling of physical processes associated with fractal geometries using affordable computational resolution. The second part of this work is an analysis of the errors incurred by replacing the test-filtering operator by its truncated Taylor-series expansion, in an effort to simplify implementation of the dynamic procedure in simulations of complex-geometry flows. Errors are quantified using a priori and a posteriori tests of forced isotropic turbulence. Results indicate that second-order truncation of the Taylor

  5. Multiscale modelling of ovarian follicular selection.

    PubMed

    Clément, Frédérique; Monniaux, Danielle

    2013-12-01

    In mammals, the number of ovulations at each ovarian cycle is determined during the terminal phase of follicular development by a tightly controlled follicle selection process. The mechanisms underlying follicle selection take place on different scales and different levels of the gonadotropic axis. These include the endocrine loops between the ovary and the hypothalamic-pituitary complex, the dynamics of follicle populations within the ovary and the dynamics of cell populations within ovarian follicles. A compartmental modelling approach was first designed to describe the cell dynamics in the selected follicle. It laid the basis for a multiscale model formulated with partial differential equations of conservation law type, resulting in the structuring of the follicular cell populations according to cell age and cell maturity. In this model, the selection occurs as a FSH (follicle stimulating hormone)-driven competition between simultaneously developing follicles. The selection output (mono-ovulation, poly-ovulation or anovulation) results from a subtle interplay between the hypothalamus, the pituitary gland and the ovaries, combined with slight differences in the initial conditions or ageing and maturation velocities of the competing follicles. This modelling approach is proposed as a useful complement to experimental studies of follicular development and in turn, the mechanisms of follicle selection raise challenging questions on the mathematical ground.

  6. 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)

  7. Structurally Governed Cell Mechanotransduction through Multiscale Modeling

    NASA Astrophysics Data System (ADS)

    Kang, John; Puskar, Kathleen M.; Ehrlicher, Allen J.; Leduc, Philip R.; Schwartz, Russell S.

    2015-02-01

    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.

  8. 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.

  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 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.

  12. 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].

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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

  4. Multiscale modeling of thermal conductivity of polycrystalline graphene sheets.

    PubMed

    Mortazavi, Bohayra; Pötschke, Markus; Cuniberti, Gianaurelio

    2014-03-21

    We developed a multiscale approach to explore the effective thermal conductivity of polycrystalline graphene sheets. By performing equilibrium molecular dynamics (EMD) simulations, the grain size effect on the thermal conductivity of ultra-fine grained polycrystalline graphene sheets is investigated. Our results reveal that the ultra-fine grained graphene structures have thermal conductivity one order of magnitude smaller than that of pristine graphene. Based on the information provided by the EMD simulations, we constructed finite element models of polycrystalline graphene sheets to probe the thermal conductivity of samples with larger grain sizes. Using the developed multiscale approach, we also investigated the effects of grain size distribution and thermal conductivity of grains on the effective thermal conductivity of polycrystalline graphene. The proposed multiscale approach on the basis of molecular dynamics and finite element methods could be used to evaluate the effective thermal conductivity of polycrystalline graphene and other 2D structures.

  5. 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.

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

    NASA Astrophysics Data System (ADS)

    Macioł, Piotr; Regulski, Krzysztof

    2016-08-01

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

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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

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

    DOE PAGES

    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

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Multiscale Modeling of Particles Embedded in High Speed Flows

    NASA Astrophysics Data System (ADS)

    Davis, Sean; Sen, Oishik; Jacobs, Gustaaf; Udaykumar, H. S.

    2015-06-01

    Problems involving propagation of shock waves through a cloud of particles are inherently multiscale. The system scale is governed by macro-scale conservation equations, which average over solid and fluid phases. The averaging process results in source terms that represent the unresolved momentum exchange between the solid phase and the fluid phase. Typically, such source terms are modeled using empirical correlations derived from physical experiments conducted in a limited parameter space. The focus of the current research is to advance the multiscale modeling of shocked particle-laden gas flows; particle- (i.e. meso-)scale computations are performed to resolve the dynamics of ensembles of particles and closure laws are obtained from the meso-scale for use in the macro-scale equations. Closure models are constructed from meso-scale simulations using the Dynamic Kriging method. The presentation will demonstrate the multiscale approach by connecting meso-scale simulations to an Eulerian-Lagrangian macro-scale model of particle laden flows. The technique is applied to study shock interactions with particle curtains in shock tubes and the results are compared with experimental data in such systems. We gratefully acknowledge the financial support by the Air Force Office of Scientific Research under Grant Number FA9550-12-1-0115 and the National Science Foundation under grant number DMS-115631.

  5. 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.

  6. 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

  7. 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

  8. Multiscale modeling for materials design: Molecular square catalysts

    NASA Astrophysics Data System (ADS)

    Majumder, Debarshi

    In a wide variety of materials, including a number of heterogeneous catalysts, the properties manifested at the process scale are a consequence of phenomena that occur at different time and length scales. Recent experimental developments allow materials to be designed precisely at the nanometer scale. However, the optimum design of such materials requires capabilities to predict the properties at the process scale based on the phenomena occurring at the relevant scales. The thesis research reported here addresses this need to develop multiscale modeling strategies for the design of new materials. As a model system, a new system of materials called molecular squares was studied in this research. Both serial and parallel multiscale strategies and their components were developed as parts of this work. As a serial component, a parameter estimation tool was developed that uses a hierarchical protocol and consists of two different search elements: a global search method implemented using a genetic algorithm that is capable of exploring large parametric space, and a local search method using gradient search techniques that accurately finds the optimum in a localized space. As an essential component of parallel multiscale modeling, different standard as well as specialized computational fluid dynamics (CFD) techniques were explored and developed in order to identify a technique that is best suited to solve a membrane reactor model employing layered films of molecular squares as the heterogeneous catalyst. The coupled set of non-linear partial differential equations (PDEs) representing the continuum model was solved numerically using three different classes of methods: a split-step method using finite difference (FD); domain decomposition in two different forms, one involving three overlapping subdomains and the other involving a gap-tooth scheme; and the multiple-timestep method that was developed in this research. The parallel multiscale approach coupled continuum

  9. Ten organising principles for coupling in multiphysics and multiscale models.

    SciTech Connect

    Larson, J. W.; Mathematics and Computer Science; Australian National Univ.; Univ. of Chicago

    2009-01-01

    Computational science faces new challenges posed by multiphysics and multiscale, or more generally put, coupled models. These systems are composites formed from separate subsystem models that interact via data exchanges. These data dependencies pose a coupling problem, and on distributed-memory computers, a parallel coupling problem. This paper presents a definition of terms and a set of organizing principles for the coupling and parallel coupling problems. It is meant as a first step towards creating a theory of coupled models. These principles are then employed in a case study of a coupled climate model and offer remarkable insight into its structure.

  10. Multiscale model updating of a curved highway bridge

    NASA Astrophysics Data System (ADS)

    Mensah-Bonsu, Priscilla; Jang, Shinae

    2012-04-01

    Finite element model updating based on a multi-scale data is demonstrated on a skewed in-service highway bridge. The multi-scale data approach provides an evidence-based method to create a bound of model class to ensure that the optimum model retains physical connectivity to the real structure. The need for this hybrid approach to model selection comes from the challenges of applying model updating to online structural health monitoring (SHM) strategy based on output-only measurements of in-service highway bridges, which should consider various uncertainties. In vibration-based FE model updating methods, the optimum model is selected by minimizing the error between modal parameters of the model and the real structure. A major drawback of model selection is the probability that the optimum model has no physical connectivity with the real structure. This is because a large set of updating parameters is required to increase accuracy. In this paper, an evidence-based approach to model selection using temperature-induced tilts is implemented in which the cyclical static behavior of a bridge is used to create a bound of possible models. This approach has a strong potential to be applicable to large civil structures with sparse array of sensors.

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

    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

  12. Registration of real and virtual endoscopy--a model and image based approach.

    PubMed

    Kukuk, M; Geiger, B

    2000-01-01

    This paper describes work in progress to integrate real and virtual endoscopy and to apply virtual endoscopy to the intra-operative guidance of endoscopic procedures. We propose a method for real-time tracking of the endoscope's shape and position. Our approach makes use of a simple and small external device, a computer model of a flexible endoscope and an image-based registration technique.

  13. 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.

  14. BioModel engineering for multiscale Systems Biology.

    PubMed

    Heiner, Monika; Gilbert, David

    2013-04-01

    We discuss some motivational challenges arising from the need to model and analyse complex biological systems at multiple scales (spatial and temporal), and present a biomodel engineering framework to address some of these issues within the context of multiscale Systems Biology. Our methodology is based on a structured family of Petri net classes which enables the investigation of a given system using various modelling abstractions: qualitative, stochastic, continuous and hybrid, optionally in a spatial context. We illustrate our approach with case studies demonstrating hierarchical flattening, treatment of space, and hierarchical organisation of space.

  15. A multiscale model for bioimpedance dispersion of liver tissue.

    PubMed

    Huang, W H; Chui, C K; Teoh, S H; Chang, S K Y

    2012-06-01

    Radio-frequency ablation (RFA) has been used in liver surgery to minimize blood loss during tissue division. However, the current RFA tissue division method lacks an effective way of determining the stoppage of blood flow. There is limitation on the current state-of-the-art laser Doppler flow sensor due to its small sensing area. A new technique was proposed to use bioimpedance for blood flow sensing. This paper discusses a new geometrical multiscale model of the liver bioimpedance incorporating blood flow impedance. This model establishes correlation between the physical tissue structure and bioimpedance measurement. The basic Debye structure within a multilevel framework is used in the model to account for bioimpedance dispersion. This dispersion is often explained by the Cole-Cole model that includes a constant phase element without physical explanation. Our model is able to account for reduced blood flow in its output with changes in permittivity in gamma dispersion that is mainly due to the polarization of water molecules. This study demonstrates the potential of a multiscale model in determining the stoppage of blood flow during surgery.

  16. Multiscale modeling of composites subjected to high speed impact

    NASA Astrophysics Data System (ADS)

    Lee, Minhyung; Cha, Myung S.; Shang, Shu; Kim, Nam H.

    2015-06-01

    The simulation of high speed impact into composite panels is a challenging task. This is partly due to the fact macro-scale simulation requires integrating the local response at various locations, i.e. integration points. If a huge number of integration points exist for enhanced accuracy, it is often suggested to calculate the micro-scale simulation using massive parallel processing. In this paper, multiscale modeling methodology has been applied to simulate the relatively thick composite panels subjected to high speed local impact loading. Instead of massive parallel processing, we propose to use surrogate modeling to bridge micro-scale and macro-scale. Multiscale modeling of fracture phenomena of composite materials will consist of (1) micro-scale modeling of fiber-matrix structure using the unit-volume-element technique; (2) macro-scale simulation of composite panels under high strain-rate impact using material response calculated from micro-scale modeling; and (3) surrogate modeling to integrate the two scales. In order to validate the predictions, first we did the material level lab experiment such as tension test. And later we also did the field test of bullet impact into composite panels made of 4 ply and 8 ply fibers. The impact velocity ranges from 300 ~ 600 m/s. Special Thanks to grants (UD120053GD).

  17. Theoretical Frameworks for Multiscale Modeling and Simulation

    PubMed Central

    Zhou, Huan-Xiang

    2014-01-01

    Biomolecular systems have been modeled at a variety of scales, ranging from explicit treatment of electrons and nuclei to continuum description of bulk deformation or velocity. Many challenges of interfacing between scales have been overcome. Multiple models at different scales have been used to study the same system or calculate the same property (e.g., channel conductance). Accurate modeling of biochemical processes under in vivo conditions and the bridging of molecular and subcellular scales will likely soon become reality. PMID:24492203

  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

    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

  20. 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

  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. 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.

  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. Standard Model in multiscale theories and observational constraints

    NASA Astrophysics Data System (ADS)

    Calcagni, Gianluca; Nardelli, Giuseppe; Rodríguez-Fernández, David

    2016-08-01

    We construct and analyze the Standard Model of electroweak and strong interactions in multiscale spacetimes with (i) weighted derivatives and (ii) q -derivatives. Both theories can be formulated in two different frames, called fractional and integer picture. By definition, the fractional picture is where physical predictions should be made. (i) In the theory with weighted derivatives, it is shown that gauge invariance and the requirement of having constant masses in all reference frames make the Standard Model in the integer picture indistinguishable from the ordinary one. Experiments involving only weak and strong forces are insensitive to a change of spacetime dimensionality also in the fractional picture, and only the electromagnetic and gravitational sectors can break the degeneracy. For the simplest multiscale measures with only one characteristic time, length and energy scale t*, ℓ* and E*, we compute the Lamb shift in the hydrogen atom and constrain the multiscale correction to the ordinary result, getting the absolute upper bound t*<10-23 s . For the natural choice α0=1 /2 of the fractional exponent in the measure, this bound is strengthened to t*<10-29 s , corresponding to ℓ*<10-20 m and E*>28 TeV . Stronger bounds are obtained from the measurement of the fine-structure constant. (ii) In the theory with q -derivatives, considering the muon decay rate and the Lamb shift in light atoms, we obtain the independent absolute upper bounds t*<10-13 s and E*>35 MeV . For α0=1 /2 , the Lamb shift alone yields t*<10-27 s , ℓ*<10-19 m and E*>450 GeV .

  6. 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...

  7. 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

  8. 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.

  9. 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.

  10. 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].

  11. 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

  12. 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.

  13. 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

  14. 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.

  15. Multiscale modeling of nanofoams under irradiation

    NASA Astrophysics Data System (ADS)

    Bringa, E. M.; Rodriguez-Nieva, J.; Monk, J. D.; Caro, J. A.; Loeffler, M. J.; Cassidy, T. A.; Johnson, R. E.; Baragiola, R. A.; Farkas, D.

    2012-02-01

    Nanoscale porosity appears in solids under a number of conditions: radiation damage in nuclear reactors, initial stages of ductile failure, in astro-materials, etc. Using molecular dynamics (MD) simulations, we analyze the radiation damage and surface modification of materials with various nanoscale porosities, where experimental techniques can be difficult to use and interpret. We consider (a) irradiation with ions with energies in the range 1-25 keV, of interest for fusion and fission energy applications; (b) swift heavy ion irradiation, with energies up to few GeV, relevant for track formation and interstellar grain evolution. We find that irradiation effects have larger spatial extent than for full-density solids and include the production of point-defects and twins which change the mechanical properties of the samples. We use our MD results as input for a Monte Carlo (MC) code to calculate sputtering yields from nanofoams of different geometries under different irradiation conditions. We also use our MD results to build models which predict possible radiation endurance under intense irradiation.

  16. 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.

  17. Reconstructing 3D CAD models for simulation using imaging-based reverse engineering

    NASA Astrophysics Data System (ADS)

    Voisin, Sophie; Page, David; Koschan, Andreas; Abidi, Mongi

    2006-05-01

    The purpose of this research is to investigate imaging-based methods to reconstruct 3D CAD models of real-world objects. The methodology uses structured lighting technologies such as coded-pattern projection and laser-based triangulation to sample 3D points on the surfaces of objects and then to reconstruct these surfaces from the dense point samples. This reverse engineering (RE) research presents reconstruction results for a military tire that is important to tire-soil simulations. The limitations of this approach are the current level of accuracy that imaging-based systems offer relative to more traditional CMM modeling systems. The benefit however is the potential for denser point samples and increased scanning speeds of objects, and with time, the imaging technologies should continue to improve to compete with CMM accuracy. This approach to RE should lead to high fidelity models of manufactured and prototyped components for comparison to the original CAD models and for simulation analysis. We focus this paper on the data collection and view registration problems within the RE pipeline.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. A High-Order Multiscale Global Atmospheric Model

    NASA Astrophysics Data System (ADS)

    Nair, R. D.

    2015-12-01

    The High-Order Method Modeling Environment (HOMME), developed at NCAR, is a petascale hydrostatic framework, which employs the cubed-sphere grid system and high-order continuous or discontinuous Galerkin (DG) methods. Recently, the HOMME framework is being extended to a non-hydrostatic dynamical core, named as the "High-Order Multiscale Atmospheric Model (HOMAM)." The spatial discretization for HOMAM is based on DG or high-order finite-volume methods. Orography is handled by the terrain-following height-based coordinate system. To alleviate the stringent CFL stability requirement resulting from the vertical aspects of the dynamics, an operator-splitting time integration scheme based on the horizontally explicit and vertically implicit (HEVI) philosophy is adopted for HOMAM. Preliminary results with the benchmark test cases proposed in the Dynamical Core Model Intercomparison project (DCMIP) test-suite will be presented in the seminar.

  3. 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.

  4. 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

  5. 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

  6. A Liver-Centric Multiscale Modeling Framework for Xenobiotics.

    PubMed

    Sluka, James P; Fu, Xiao; Swat, Maciej; Belmonte, Julio M; Cosmanescu, Alin; Clendenon, Sherry G; Wambaugh, John F; Glazier, James A

    2016-01-01

    We describe a multi-scale, liver-centric in silico modeling framework for acetaminophen pharmacology and metabolism. We focus on a computational model to characterize whole body uptake and clearance, liver transport and phase I and phase II metabolism. We do this by incorporating sub-models that span three scales; Physiologically Based Pharmacokinetic (PBPK) modeling of acetaminophen uptake and distribution at the whole body level, cell and blood flow modeling at the tissue/organ level and metabolism at the sub-cellular level. We have used standard modeling modalities at each of the three scales. In particular, we have used the Systems Biology Markup Language (SBML) to create both the whole-body and sub-cellular scales. Our modeling approach allows us to run the individual sub-models separately and allows us to easily exchange models at a particular scale without the need to extensively rework the sub-models at other scales. In addition, the use of SBML greatly facilitates the inclusion of biological annotations directly in the model code. The model was calibrated using human in vivo data for acetaminophen and its sulfate and glucuronate metabolites. We then carried out extensive parameter sensitivity studies including the pairwise interaction of parameters. We also simulated population variation of exposure and sensitivity to acetaminophen. Our modeling framework can be extended to the prediction of liver toxicity following acetaminophen overdose, or used as a general purpose pharmacokinetic model for xenobiotics. PMID:27636091

  7. A Liver-Centric Multiscale Modeling Framework for Xenobiotics

    PubMed Central

    Swat, Maciej; Cosmanescu, Alin; Clendenon, Sherry G.; Wambaugh, John F.; Glazier, James A.

    2016-01-01

    We describe a multi-scale, liver-centric in silico modeling framework for acetaminophen pharmacology and metabolism. We focus on a computational model to characterize whole body uptake and clearance, liver transport and phase I and phase II metabolism. We do this by incorporating sub-models that span three scales; Physiologically Based Pharmacokinetic (PBPK) modeling of acetaminophen uptake and distribution at the whole body level, cell and blood flow modeling at the tissue/organ level and metabolism at the sub-cellular level. We have used standard modeling modalities at each of the three scales. In particular, we have used the Systems Biology Markup Language (SBML) to create both the whole-body and sub-cellular scales. Our modeling approach allows us to run the individual sub-models separately and allows us to easily exchange models at a particular scale without the need to extensively rework the sub-models at other scales. In addition, the use of SBML greatly facilitates the inclusion of biological annotations directly in the model code. The model was calibrated using human in vivo data for acetaminophen and its sulfate and glucuronate metabolites. We then carried out extensive parameter sensitivity studies including the pairwise interaction of parameters. We also simulated population variation of exposure and sensitivity to acetaminophen. Our modeling framework can be extended to the prediction of liver toxicity following acetaminophen overdose, or used as a general purpose pharmacokinetic model for xenobiotics. PMID:27636091

  8. A Liver-Centric Multiscale Modeling Framework for Xenobiotics.

    PubMed

    Sluka, James P; Fu, Xiao; Swat, Maciej; Belmonte, Julio M; Cosmanescu, Alin; Clendenon, Sherry G; Wambaugh, John F; Glazier, James A

    2016-01-01

    We describe a multi-scale, liver-centric in silico modeling framework for acetaminophen pharmacology and metabolism. We focus on a computational model to characterize whole body uptake and clearance, liver transport and phase I and phase II metabolism. We do this by incorporating sub-models that span three scales; Physiologically Based Pharmacokinetic (PBPK) modeling of acetaminophen uptake and distribution at the whole body level, cell and blood flow modeling at the tissue/organ level and metabolism at the sub-cellular level. We have used standard modeling modalities at each of the three scales. In particular, we have used the Systems Biology Markup Language (SBML) to create both the whole-body and sub-cellular scales. Our modeling approach allows us to run the individual sub-models separately and allows us to easily exchange models at a particular scale without the need to extensively rework the sub-models at other scales. In addition, the use of SBML greatly facilitates the inclusion of biological annotations directly in the model code. The model was calibrated using human in vivo data for acetaminophen and its sulfate and glucuronate metabolites. We then carried out extensive parameter sensitivity studies including the pairwise interaction of parameters. We also simulated population variation of exposure and sensitivity to acetaminophen. Our modeling framework can be extended to the prediction of liver toxicity following acetaminophen overdose, or used as a general purpose pharmacokinetic model for xenobiotics.

  9. 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

  10. 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

  11. Multi-Scale Modeling of Hypersonic Gas Flow

    NASA Astrophysics Data System (ADS)

    Boyd, Iain D.

    On March 27, 2004, NASA successfully flew the X-43A hypersonic test flight vehicle at a velocity of 5000 mph to break the aeronautics speed record that had stood for over 35 years. The final flight of the X-43A on November 16, 2004 further increased the speed record to 6,600 mph which is almost ten times the speed of sound. The very high speed attainable by hypersonic airplanes could revolutionize air travel by dramatically reducing inter-continental flight times. For example, a hypersonic flight from New York to Sydney, Australia, a distance of 10,000 miles, would take less than 2 h. Reusable hypersonic vehicles are also being researched to significantly reduce the cost of access to space. Computer modeling of the gas flows around hypersonic vehicles will play a critical part in their development. This article discusses the conditions that can prevail in certain hypersonic gas flows that require a multi-scale modeling approach.

  12. Multiscale models for the growth of avascular tumors

    NASA Astrophysics Data System (ADS)

    Martins, M. L.; Ferreira, S. C.; Vilela, M. J.

    2007-06-01

    In the past 30 years we have witnessed an extraordinary progress on the research in the molecular biology of cancer, but its medical treatment, widely based on empirically established protocols, still has many limitations. One of the reasons for that is the limited quantitative understanding of the dynamics of tumor growth and drug response in the organism. In this review we shall discuss in general terms the use of mathematical modeling and computer simulations related to cancer growth and its applications to improve tumor therapy. Particular emphasis is devoted to multiscale models which permit integration of the rapidly expanding knowledge concerning the molecular basis of cancer and the complex, nonlinear interactions among tumor cells and their microenvironment that will determine the neoplastic growth at the tissue level.

  13. Multiscale modelling of palisade formation in gliobastoma multiforme.

    PubMed

    Caiazzo, Alfonso; Ramis-Conde, Ignacio

    2015-10-21

    Palisades are characteristic tissue aberrations that arise in glioblastomas. Observation of palisades is considered as a clinical indicator of the transition from a noninvasive to an invasive tumour. In this paper we propose a computational model to study the influence of the hypoxic switch in palisade formation. For this we produced three-dimensional realistic simulations, based on a multiscale hybrid model, coupling the evolution of tumour cells and the oxygen diffusion in tissue, that depict the shape of palisades during its formation. Our results can be summarized as follows: (1) the presented simulations can provide clinicians and biologists with a better understanding of three-dimensional structure of palisades as well as of glioblastomas growth dynamics; (2) we show that heterogeneity in cell response to hypoxia is a relevant factor in palisade and pseudopalisade formation; (3) we show how selective processes based on the hypoxia switch influence the tumour proliferation.

  14. 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

  15. 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...

  16. 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

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. A complete multiscale modelling approach for polymer-clay nanocomposites.

    PubMed

    Scocchi, Giulio; Posocco, Paola; Handgraaf, Jan-Willem; Fraaije, Johannes G E M; Fermeglia, Maurizio; Pricl, Sabrina

    2009-08-01

    We present an innovative, multiscale computational approach to probe the behaviour of polymer-clay nanocomposites (PCNs). Our modeling recipe is based on 1) quantum/force-field-based atomistic simulation to derive interaction energies among all system components; 2) mapping of these values onto mesoscopic bead-field (MBF) hybrid-method parameters; 3) mesoscopic simulations to determine system density distributions and morphologies (i.e., intercalated versus exfoliated); and 4) simulations at finite-element levels to calculate the relative macroscopic properties. The entire computational procedure has been applied to two well-known PCN systems, namely Nylon 6/Cloisite 20A and Nylon 6/Cloisite 30B, as test materials, and their mechanical properties were predicted in excellent agreement with the available experimental data. Importantly, our methodology is a truly bottom-up approach, and no "learning from experiment" was needed in any step of the entire procedure. PMID:19575427

  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 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

  8. 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.

  9. Simulating Cancer Growth with Multiscale Agent-Based Modeling

    PubMed Central

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

    2014-01-01

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

  10. Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models.

    PubMed

    Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J

    2014-01-01

    The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work.

  11. Linear theory for filtering nonlinear multiscale systems with model error

    PubMed Central

    Berry, Tyrus; Harlim, John

    2014-01-01

    In this paper, we study filtering of multiscale dynamical systems with model error arising from limitations in resolving the smaller scale processes. In particular, the analysis assumes the availability of continuous-time noisy observations of all components of the slow variables. Mathematically, this paper presents new results on higher order asymptotic expansion of the first two moments of a conditional measure. In particular, we are interested in the application of filtering multiscale problems in which the conditional distribution is defined over the slow variables, given noisy observation of the slow variables alone. From the mathematical analysis, we learn that for a continuous time linear model with Gaussian noise, there exists a unique choice of parameters in a linear reduced model for the slow variables which gives the optimal filtering when only the slow variables are observed. Moreover, these parameters simultaneously give the optimal equilibrium statistical estimates of the underlying system, and as a consequence they can be estimated offline from the equilibrium statistics of the true signal. By examining a nonlinear test model, we show that the linear theory extends in this non-Gaussian, nonlinear configuration as long as we know the optimal stochastic parametrization and the correct observation model. However, when the stochastic parametrization model is inappropriate, parameters chosen for good filter performance may give poor equilibrium statistical estimates and vice versa; this finding is based on analytical and numerical results on our nonlinear test model and the two-layer Lorenz-96 model. Finally, even when the correct stochastic ansatz is given, it is imperative to estimate the parameters simultaneously and to account for the nonlinear feedback of the stochastic parameters into the reduced filter estimates. In numerical experiments on the two-layer Lorenz-96 model, we find that the parameters estimated online, as part of a filtering procedure

  12. 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

  13. 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.

  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. 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.

  16. Cancer systems biology and modeling: microscopic scale and multiscale approaches.

    PubMed

    Masoudi-Nejad, Ali; Bidkhori, Gholamreza; Hosseini Ashtiani, Saman; Najafi, Ali; Bozorgmehr, Joseph H; Wang, Edwin

    2015-02-01

    Cancer has become known as a complex and systematic disease on macroscopic, mesoscopic and microscopic scales. Systems biology employs state-of-the-art computational theories and high-throughput experimental data to model and simulate complex biological procedures such as cancer, which involves genetic and epigenetic, in addition to intracellular and extracellular complex interaction networks. In this paper, different systems biology modeling techniques such as systems of differential equations, stochastic methods, Boolean networks, Petri nets, cellular automata methods and agent-based systems are concisely discussed. We have compared the mentioned formalisms and tried to address the span of applicability they can bear on emerging cancer modeling and simulation approaches. Different scales of cancer modeling, namely, microscopic, mesoscopic and macroscopic scales are explained followed by an illustration of angiogenesis in microscopic scale of the cancer modeling. Then, the modeling of cancer cell proliferation and survival are examined on a microscopic scale and the modeling of multiscale tumor growth is explained along with its advantages.

  17. 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

  18. Statistical Inverse Ray Tracing for Image-Based 3D Modeling.

    PubMed

    Liu, Shubao; Cooper, David B

    2014-10-01

    This paper proposes a new formulation and solution to image-based 3D modeling (aka "multi-view stereo") based on generative statistical modeling and inference. The proposed new approach, named statistical inverse ray tracing, models and estimates the occlusion relationship accurately through optimizing a physically sound image generation model based on volumetric ray tracing. Together with geometric priors, they are put together into a Bayesian formulation known as Markov random field (MRF) model. This MRF model is different from typical MRFs used in image analysis in the sense that the ray clique, which models the ray-tracing process, consists of thousands of random variables instead of two to dozens. To handle the computational challenges associated with large clique size, an algorithm with linear computational complexity is developed by exploiting, using dynamic programming, the recursive chain structure of the ray clique. We further demonstrate the benefit of exact modeling and accurate estimation of the occlusion relationship by evaluating the proposed algorithm on several challenging data sets.

  19. 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

  20. [Change detection from high-resolution remote sensing image based on MSE model].

    PubMed

    Wei, Li-Fei; Wang, Hai-Bo

    2013-03-01

    At present, most of the traditional change detection methods from high-resolution remote sensing image are based on a feature information, the information of multi-feature information cannot be extracted, so it is difficult to detect the complete information. In order to solve this problem, a change detection algorithm of high-resolution remote sensing image based on multiview spectral embedding is proposed in the present paper. Firstly, change image is obtained using traditional difference change detection method, and multi-feature information is extracted. The feature vector information is fused by a MSE model and the complete change information can be obtained. The experimental results show that the detection accuracy of the proposed method is better than the accuracy of traditional methods, and its stability is outstanding.

  1. An automated approach for segmentation of intravascular ultrasound images based on parametric active contour models.

    PubMed

    Vard, Alireza; Jamshidi, Kamal; Movahhedinia, Naser

    2012-06-01

    This paper presents a fully automated approach to detect the intima and media-adventitia borders in intravascular ultrasound images based on parametric active contour models. To detect the intima border, we compute a new image feature applying a combination of short-term autocorrelations calculated for the contour pixels. These feature values are employed to define an energy function of the active contour called normalized cumulative short-term autocorrelation. Exploiting this energy function, the intima border is separated accurately from the blood region contaminated by high speckle noise. To extract media-adventitia boundary, we define a new form of energy function based on edge, texture and spring forces for the active contour. Utilizing this active contour, the media-adventitia border is identified correctly even in presence of branch openings and calcifications. Experimental results indicate accuracy of the proposed methods. In addition, statistical analysis demonstrates high conformity between manual tracing and the results obtained by the proposed approaches.

  2. 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.

  3. 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.

  4. Deconvolution of Poisson-Limited Data Using a Bayesian Multi-Scale Model

    NASA Astrophysics Data System (ADS)

    Kolaczyk, E. D.; Nowak, R. D.

    1999-04-01

    We present a new approach for producing deconvolved spectra and images, based on a novel non-parametric, multi-scale statistical model designed explicitly for Poisson limited data. The framework within which we work is completely general, requiring only that the user specify the manner in which the data were ``blurred'' (for example, through an instrument-specific PSF). Therefore, we anticipate our method serving in problems involving data at any of a variety of energies, especially at the x-ray and gamma-ray levels, for deconvolution problems arising in a variety of missions -- particularly when there is not yet a good analytical model for the source(s). The underlying statistical framework explicitly models the process of (dis)aggregating counts across multiple resolutions. The result is a multi-scale (though not wavelet-based) representation of the source object to be recovered through the deconvolution. Furthermore, this framework is built completely within the context of the original Poisson data likelihood, so that we proceed without the use of statistical approximations (such as chi (2) approximations) or data transformations. Adopting a Bayesian paradigm, a flexible prior probability structure is used to regularize the set of possible solutions to what is formally a statistical inverse problem. This prior is both intuitive and interpretable, in that it models the degree to which counts are allowed to be (dis)aggregated at each location-scale combination. Estimates of the ``deblurred'' source object are obtained in our procedure using standard Bayesian statistical techniques (i.e., based on the mode of the posterior distribution of the object given the data). Despite the generality of this method and the potentially complex structures that may be modeled, these estimates may be produced using an efficient iterative algorithm (i.e., the expectation-maximization (EM) algorithm), wherein iterates at each stage are yielded by closed-form solutions to simple

  5. 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.

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

    NASA Astrophysics Data System (ADS)

    Calkins, M. A.; Julien, K. A.; Aurnou, J. M.; Tobias, S.; Marti, P.

    2015-12-01

    A geostrophically balanced, convection-driven multiscale dynamo model is developed for the plane layer geometry. 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 evolution timescale, and the large-scale thermal evolution timescale. Distinct equations are derived for the cases of order one and low magnetic Prandtl number. It is shown that the low magnetic Prandtl number 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; large-scale ohmic dissipation occurs in thin magnetic boundary layers adjacent to the horizontal boundaries. The new models provide a new theoretical framework for understanding the dynamics of convection-driven dynamos in regimes that are only just becoming accessible to direct numerical simulations.

  7. 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

  8. Relational grounding facilitates development of scientifically useful multiscale models.

    PubMed

    Hunt, C Anthony; Ropella, Glen E P; Lam, Tai ning; Gewitz, Andrew D

    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

  9. Image-based modeling of the hemodynamics in cerebral arterial trees

    NASA Astrophysics Data System (ADS)

    Mut, Fernando; Wright, Susan; Putman, Christopher; Ascoli, Giorgio; Cebral, Juan

    2009-02-01

    Knowledge of the hemodynamics in normal arterial trees of the brain is important to better understand the mechanisms responsible for the initiation and progression of cerebrovascular diseases. Information about the baseline values of hemodynamic variables such as velocity magnitudes, swirling flows, wall shear stress, pressure drops, vascular resistances, etc. is important for characterization of the normal hemodynamics and comparison with pathological states such as aneurysms and stenoses. This paper presents image-based computational hemodynamics models of cerebral arterial trees constructed from magnetic resonance angiography (MRA) images. The construction of large models of cerebral arterial trees is challenging because of the following main reasons: a) it is necessary to acquire high resolution angiographic images covering the entire brain, b) it is necessary to construct topologically correct and geometrically accurate watertight models of the vasculature, and c) the models typically result in large computational grids which make the calculations computationally demanding. This paper presents a methodology to model the hemodynamics in the brain arterial network that combines high resolution MRA at 3T, a vector representation of the vascular structures based on semi-manual segmentation, and a novel algorithm to solve the incompressible flow equations efficiently in tubular geometries. These techniques make the study of the hemodynamics in the cerebral arterial network practical.

  10. 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

  11. 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

  12. Image-based models of cardiac structure in health and disease

    PubMed Central

    Vadakkumpadan, Fijoy; Arevalo, Hermenegild; Prassl, Anton J.; Chen, Junjie; Kickinger, Ferdinand; Kohl, Peter; Plank, Gernot; Trayanova, Natalia

    2010-01-01

    Computational approaches to investigating the electromechanics of healthy and diseased hearts are becoming essential for the comprehensive understanding of cardiac function. In this article, we first present a brief review of existing image-based computational models of cardiac structure. We then provide a detailed explanation of a processing pipeline which we have recently developed for constructing realistic computational models of the heart from high resolution structural and diffusion tensor (DT) magnetic resonance (MR) images acquired ex vivo. The presentation of the pipeline incorporates a review of the methodologies that can be used to reconstruct models of cardiac structure. In this pipeline, the structural image is segmented to reconstruct the ventricles, normal myocardium, and infarct. A finite element mesh is generated from the segmented structural image, and fiber orientations are assigned to the elements based on DTMR data. The methods were applied to construct seven different models of healthy and diseased hearts. These models contain millions of elements, with spatial resolutions in the order of hundreds of microns, providing unprecedented detail in the representation of cardiac structure for simulation studies. PMID:20582162

  13. 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.

  14. Knowledge based system for runtime controlling of multiscale model of ion-exchange solvent extraction

    NASA Astrophysics Data System (ADS)

    Macioł, Piotr; Gotfryd, Leszek; Macioł, Andrzej

    2012-09-01

    The hereby paper concerns the issue of solution of runtime controlling of multiscale model of ion-exchange solvent extraction. It is based on cooperation of a framework applying Agile Multiscale Modeling Methodology (AM3), and the REBIT Knowledge Based System. Ion-exchange solvent extraction has been shortly introduced. Design assumptions of AM3 and theoretical basis of REBIT have been described. Designed workflows and rules for simple laminar/ turbulent flow and extraction processes have been shown.

  15. Multiscale Modeling Methods for Analysis of Failure Modes in Foldcore Sandwich Panels

    NASA Astrophysics Data System (ADS)

    Sturm, R.; Schatrow, P.; Klett, Y.

    2015-12-01

    The paper presents an homogenised core model suitable for use in the analysis of fuselage sandwich panels with folded composite cores under combined loading conditions. Within a multiscale numerical design process a failure criterion was derived for describing the macroscopic behaviour of folded cores under combined loading using a detailed foldcore micromodel. The multiscale modelling method was validated by simulation of combined compression/bending failure of foldcore sandwich panels.

  16. 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.

  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. 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

  19. 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

  20. 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

  1. Image-based quantification and mathematical modeling of spatial heterogeneity in ESC colonies.

    PubMed

    Herberg, Maria; Zerjatke, Thomas; de Back, Walter; Glauche, Ingmar; Roeder, Ingo

    2015-06-01

    Pluripotent embryonic stem cells (ESCs) have the potential to differentiate into cells of all three germ layers. This unique property has been extensively studied on the intracellular, transcriptional level. However, ESCs typically form clusters of cells with distinct size and shape, and establish spatial structures that are vital for the maintenance of pluripotency. Even though it is recognized that the cells' arrangement and local interactions play a role in fate decision processes, the relations between transcriptional and spatial patterns have not yet been studied. We present a systems biology approach which combines live-cell imaging, quantitative image analysis, and multiscale, mathematical modeling of ESC growth. In particular, we develop quantitative measures of the morphology and of the spatial clustering of ESCs with different expression levels and apply them to images of both in vitro and in silico cultures. Using the same measures, we are able to compare model scenarios with different assumptions on cell-cell adhesions and intercellular feedback mechanisms directly with experimental data. Applying our methodology to microscopy images of cultured ESCs, we demonstrate that the emerging colonies are highly variable regarding both morphological and spatial fluorescence patterns. Moreover, we can show that most ESC colonies contain only one cluster of cells with high self-renewing capacity. These cells are preferentially located in the interior of a colony structure. The integrated approach combining image analysis with mathematical modeling allows us to reveal potential transcription factor related cellular and intercellular mechanisms behind the emergence of observed patterns that cannot be derived from images directly. PMID:25605123

  2. 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.

  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. 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

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

    PubMed

    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

  6. 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

  7. 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.

  8. Image-Based Modeling and Precision Medicine: Patient-Specific Carotid and Coronary Plaque Assessment and Predictions

    PubMed Central

    Yang, Chun; Zheng, Jie; Canton, Gador; Bach, Richard; Hatsukami, Thomas S.; Wang, Liang; Yang, Deshan; Billiar, Kristen L.; Yuan, Chun

    2013-01-01

    Atherosclerotic plaques may rupture without warning and cause acute cardiovascular events such as heart attack and stroke. Current clinical screening tools are insufficient to identify those patients with risks early and prevent the adverse events from happening. Medical imaging and image-based modeling have made considerable progress in recent years in identifying plaque morphological and mechanical risk factors which may be used in developing improved patient screening strategies. The key steps and factors in image-based models for human carotid and coronary plaques were illustrated, as well as grand challenges facing the researchers in the field to develop more accurate screening tools. PMID:23362245

  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. Multiscale Modeling of Dewetting Damage in Highly Filled Particulate Composites

    NASA Astrophysics Data System (ADS)

    Geubelle, P. H.; Inglis, H. M.; Kramer, J. D.; Patel, J. J.; Kumar, N. C.; Tan, H.

    2008-02-01

    Particle debonding or dewetting constitutes one of the key damage processes in highly filled particulate composites such as solid propellant and other energetic materials. To analyze this failure process, we have developed a multiscale finite element framework that combines, at the microscale, a nonlinear description of the binder response with a cohesive model of the damage process taking place in a representative periodic unit cell (PUC). To relate micro-scale damage to the macroscopic constitutive response of the material, we employ the mathematical theory of homogenization (MTH). After a description of the numerical scheme, we present the results of the damage response of a highly filled particulate composite subjected to a uniaxial macroscopic strain, and show the direct correlation between the complex damage processes taking place in the PUC and the nonlinear macroscopic constitutive response. We also present a detailed study of the PUC size and a comparison between the finite element MTH-based study and a micromechanics model of the dewetting process.

  11. 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.

  12. Multiscale modeling and simulation of microtubule–motor-protein assemblies

    PubMed Central

    Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; Betterton, M. D.; Shelley, Michael J.

    2016-01-01

    Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate–consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation. PMID:26764729

  13. 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

  14. A Multiscale Tridomain Model for Simulating Bioelectric Gastric Pacing

    PubMed Central

    Sathar, Shameer; Trew, Mark L.; O’Grady, Greg

    2015-01-01

    Goal Gastric motility disorders have been associated with abnormal slow wave electrical activity (‘gastric dysrhythmias’). Gastric pacing is a potential therapy for gastric dysrhythmias, however, new pacing protocols are required that can effectively modulate motility patterns, while being power efficient. This study presents a novel comprehensive 3D multi-scale modeling framework of the human stomach, including anisotropic conduction, capable of evaluating pacing strategies. Methods A high resolution anatomically realistic mesh was generated from CT images taken from a human stomach. Principal conduction axes were calculated and embedded within this model based on a modified Laplace-Dirichlet rule based algorithm. A continuum based tridomain formulation was implemented and evaluated for performance, and used to model the slow wave propagation, which takes into account the two main cell types present in gastric musculature. Model parameters were found by matching predicted normal slow-wave activity to experimental observation and data. These simulation parameters were applied while modeling an external pacing event to entrain slow wave patterns. Results The proposed formulation was found to be 2 times more efficient than a previous formulation for a normal slow wave simulation. Convergence analysis showed that a mesh resolution of ≈ 0.4 –0.5mm is required for an accurate solution process. Conclusion The effect of different pacing frequencies on entrainment demonstrated that the pacing protocols are limited by the frequency of the native propagation and the refractory period of the cellular activity. Significance The model is expected to become an important tool in studying pacing protocols for both efficiency and effectiveness. PMID:26080372

  15. Sport helmet design and virtual impact test by image-based finite element modeling.

    PubMed

    Luo, Yunhua; Liang, Zhaoyang

    2013-01-01

    Head injury has been a major concern in various sports, especially in contact sports such as football and ice hockey. Helmet has been adopted as a protective device in such sports, aiming at preventing or at least alleviating head injuries. However, there exist two challenges in current helmet design and test. One is that the helmet does not fit the subject's head well; the other is that current helmet testing methods are not able to provide accurate information about intracranial pressure and stress/strain level in brain tissues during impact. To meet the challenges, an image-based finite element modeling procedure was proposed to design subject-specific helmet and to conduct virtual impact test. In the procedure, a set of medical images such as computed tomography (CT) and magnetic resonance image (MRI) of the subject's head was used to construct geometric shape of the helmet and to develop a helmet-head finite element model that can be used in the virtual impact test.

  16. 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.

  17. 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

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

    PubMed

    Zhang, Xueqing; Bieberle-Hütter, Anja

    2016-06-01

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

  19. 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

  20. 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

  1. 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

  2. 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.

  3. 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.

  4. A multiscale model of the bone marrow and hematopoiesis

    PubMed Central

    Silva, Ariosto S; Anderson, Alexander R.A.

    2013-01-01

    The bone marrow is necessary for renewal of all hematopoietic cells and critical for maintenance of a wide range of physiologic functions. Multiple human diseases result from bone marrow dysfunction. It is also the site in which “liquid” tumors, including leukemia and multiple myeloma, develop as well as a frequent site of metastases. Understanding the complex cellular and microenvironmental interactions that govern normal bone marrow function as well as diseases and cancers of the bone marrow would be a valuable medical advance. Our goal is the development of a spatially-explicit in silico model of the bone marrow to understand both its normal function and the evolutionary dynamics that govern the emergence of bone marrow malignancy. Here we introduce a multiscale computational model of the bone marrow that incorporates three distinct spatial scales, cell, hematopoietic subunit, whole marrow. Implemented as a fixed lattice 3D cellular automaton, it reproduces the spatial characteristics of the normal bone marrow and is validated against data from the daily production of mature blood cells and response of hematopoiesis after irradiation. The major mechanisms modeled in this work are: (1) replication, specialization and migration of hematopoietic cells, (2) optimized spatial configuration of sinuses and hematopoietic compartments and, (3) intravasation of mature hematopoietic cells into sinuses. Our results, using parameter estimates from literature, recapitulates normal bone marrow function and suggest an explanation for the fractal-like structure of trabeculae and sinuses in the marrow, which would be an optimization of the hematopoietic function in order to maximize the number of mature blood cells produced daily within the volumetric restrictions of the marrow. PMID:21631151

  5. 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

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. 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

  11. Multiscale Multiphysics and Multidomain Models I: Basic Theory.

    PubMed

    Wei, Guo-Wei

    2013-12-01

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

  12. 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

  13. 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.

  14. 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

  15. 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

  16. 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

  17. Multiscale Modeling of Chemistry in Water: Are We There Yet?

    PubMed

    Bulo, Rosa E; Michel, Carine; Fleurat-Lessard, Paul; Sautet, Philippe

    2013-12-10

    This paper critically evaluates the state of the art in combined quantum mechanical/molecular mechanical (QM/MM) approaches to the computational description of chemistry in water and supplies guidelines for the setup of customized multiscale simulations of aqueous processes. We differentiate between structural and dynamic performance, since some tasks, e.g., the reproduction of NMR or UV-vis spectra, require only structural accuracy, while others, i.e., reaction mechanisms, require accurate dynamic data as well. As a model system for aqueous solutions in general, the approaches were tested on a QM water cluster in an environment of MM water molecules. The key difficulty is the description of the possible diffusion of QM molecules into the MM region and vice versa. The flexible inner region ensemble separator (FIRES) approach constrains QM solvent molecules within an active (QM) region. Sorted adaptive partitioning (SAP), difference-based adaptive solvation (DAS), and buffered-force (BF) are all adaptive approaches that use a buffer zone in which solvent molecules gradually adapt from QM to MM (or vice versa). The costs of SAP and DAS are relatively high, while BF is fast but sacrifices conservation of both energy and momentum. Simulations in the limit of an infinitely small buffer zone, where DAS and SAP become equivalent, are discussed as well and referred to as ABRUPT. The best structural accuracy is obtained with DAS, BF, and ABRUPT, all three of similar quality. FIRES performs very well for dynamic properties localized deep within the QM region. By means of elimination DAS emerges as the best overall compromise between structural and dynamic performance. Eliminating the buffer zone (ABRUPT) improves efficiency and still leads to surprisingly good results. While none of the many new flavors are perfect, all together this new field already allows accurate description of a wide range of structural and dynamic properties of aqueous solutions.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Multi-scale modelling of submarine landslide-generated tsunamis

    NASA Astrophysics Data System (ADS)

    Hill, J.; Piggott, M. D.; Collins, G. S.; Smith, R. C.; Allison, P. A.

    2013-12-01

    Submarine landslides can be far larger than terrestrial landslides and many generate destructive tsunamis. The Storegga Slide, offshore Norway, covers an area larger than Scotland and contains 3,000 km3 of material (enough to cover Scotland to a depth of 80 m). This huge slide occurred at 8.2 ka and extends for 800 km down slope. It produced a tsunami with >20 m run-up around the Norwegian Sea, including the Shetlands, and run-ups were typically 3-4 m along the mainland coast of Scotland. The tsunami propagated as far as East Greenland. Northern Europe faces few, if any, other natural hazards that could cause damage on the scale of a repeat Storegga Slide tsunami. Modelling such vast natural disasters is not straightforward. In order to achieve accurate run-up, high resolution is required near the coastlines, but entire oceans must be modelled to account for the vast distances travelled by the wave. Here, we use the open-source, three-dimensional CFD model, Fluidity, to simulate the Storegga landslide-generated tsunami. Fluidity's unstructured meshing allows resolution to vary by orders of magnitude within a single numerical simulation. We present results from multi-scale simulations that capture fine-scale coastal details and at the same time cover a domain spanning the Arctic ocean to capture run-ups on the East Greenland coast. We also compare the effects of modern vs palaeo-bathymetry, which has been neglected in previous numerical modelling studies. Future work will include assessing other potential landslide sites and how landslide dynamics affect the resulting tsunami wave to be used in hazard assessment for Northern Europe. Close-up of the computational mesh around the UK coast, western Norway and as far east as Iceland. The shift in resolution from 750m at the coast to over 20km in open water is clearly visible. Note the high resolution area to the top left which is the Storegga Landslide region.

  9. 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...

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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.

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

    EPA Science Inventory

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

  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 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

  19. Unsteady wall shear stress analysis from image-based computational fluid dynamic aneurysm models under Newtonian and Casson rheological models.

    PubMed

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

    2014-10-01

    The aim of this work was to determine whether or not Newtonian rheology assumption in image-based patient-specific computational fluid dynamics (CFD) cerebrovascular models harboring cerebral aneurysms may affect the hemodynamics characteristics, which have been previously associated with aneurysm progression and rupture. Ten patients with cerebral aneurysms with lobulations were considered. CFD models were reconstructed from 3DRA and 4DCTA images by means of region growing, deformable models, and an advancing front technique. Patient-specific FEM blood flow simulations were performed under Newtonian and Casson rheological models. Wall shear stress (WSS) maps were created and distributions were compared at the end diastole. Regions of lower WSS (lobulation) and higher WSS (neck) were identified. WSS changes in time were analyzed. Maximum, minimum and time-averaged values were calculated and statistically compared. WSS characterization remained unchanged. At high WSS regions, Casson rheology systematically produced higher WSS minimum, maximum and time-averaged values. However, those differences were not statistically significant. At low WSS regions, when averaging over all cases, the Casson model produced higher stresses, although in some cases the Newtonian model did. However, those differences were not significant either. There is no evidence that Newtonian model overestimates WSS. Differences are not statistically significant.

  20. 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

  1. 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.

  2. Integrating Multiple Scales of Hydraulic Conductivity Measurements in Training Image-Based Stochastic Models

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    It has been widely demonstrated that the hydraulic conductivity of an aquifer increases with a larger portion of the aquifer tested. This poses a challenge when different hydraulic conductivity measurements coexist in a field study and have to be integrated simultaneously (e.g. core analysis, slug tests and well tests). While the scaling of hydraulic conductivity can be analytically derived in multiGaussian media, there is no general methodology to simultaneously integrate hydraulic conductivity measurements taken at different scales in highly heterogeneous media. Here we address this issue in the context of multiple-point statistics simulations (MPS). In MPS, the spatial continuity is based on a training image (TI) that contains the variability, connectivity, and structural properties of the medium. The key principle of our methodology is to consider the different scales of hydraulic conductivity as joint variables which are simulated together. Based on a TI that represents the fine-scale spatial variability, we use a classical upscaling method to obtain a series of upscaled TIs that correspond to the different scales at which measurements are available. In our case, the renormalization method is used for this upscaling step, but any upscaling method could be employed. Considered together, the different scales obtained are considered a single multi-scale representation of the initial TI, in a similar fashion as the multiscale pyramids used in image processing. We then use recent MPS simulation methods that allow dealing with multivariate TIs to generate conditional realizations of the different scales together. One characteristic of these realizations is that the possible non-linear relationships between the different simulated scales are statistically similar to the relationships observed in the multiscale TI. Therefore these relationships are considered a reasonable approximation of the renormalization results that were used on the TI. Another characteristic of

  3. 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.

  4. A Bridging Cell Multiscale Methodology to Model the Structural Behaviour of Polymer Matrix Composites

    NASA Astrophysics Data System (ADS)

    Iacobellis, Vincent

    Composite and nanocomposite materials exhibit behaviour which is inherently multiscale, extending from the atomistic to continuum levels. In composites, damage growth tends to occur at the nano and microstructural scale by means of crack growth and fibre-matrix debonding. Concurrent multiscale modeling provides a means of efficiently solving such localized phenomena, however its use in this application has been limited due to a number of existing issues in the multiscale field. These include the seamless transfer of information between continuum and atomistic domains, the small timesteps required for dynamic simulation, and limited research into concurrent multiscale modeling of amorphous polymeric materials. The objective of this thesis is thus twofold: to formulate a generalized approach to solving a coupled atomistic-to-continuum system that addresses these issues and to extend the application space of concurrent multiscale modeling to damage modeling in composite microstructures. To achieve these objectives, a finite element based multiscale technique termed the Bridging Cell Method (BCM), has been formulated with a focus on crystalline material systems. Case studies are then presented that show the effectiveness of the developed technique with respect to full atomistic simulations. The BCM is also demonstrated for applications of stress around a nanovoid, nanoindentation, and crack growth due to monotonic and cyclic loading. Next, the BCM is extended to modeling amorphous polymeric material systems where an adaptive solver and a two-step iterative solution algorithm are introduced. Finally, the amorphous and crystalline BCM is applied to modeling a polymer-graphite interface. This interface model is used to obtain cohesive zone parameters which are used in a cohesive zone model of fibre-matrix interfacial cracking in a composite microstructure. This allows for an investigation of the temperature dependent damage mechanics from the nano to microscale within

  5. 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

  6. 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...

  7. 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.

  8. 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,...

  9. 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

  10. A Multiscale Modeling Demonstration Based on the Pair Correlation Function

    SciTech Connect

    Gao, Carrie Y; Nicholson, Don M; Keffer, David; Edwards, Brian J

    2008-01-01

    For systems with interatomic interactions that are well described by pair-wise potentials, the pair correlation function provides a vehicle for passing information from the molecular level to the macroscopic level of description. In this work, we present a complete demonstration of the use of the pair correlation function to simulate a fluid at the molecular and macroscopic levels. At the molecular level, we describe a monatomic fluid using the Ornstein-Zernike integral equation theory closed with the Percus-Yevick approximation. We show that all of the required thermodynamic properties can be evaluated knowing the pair correlation function. At the macroscopic level, we perform a multiscale simulation with macroscopic evolution equations for the mass, momentum, temperature, and pair correlation function, using molecular-level simulation to provide the boundary conditions. We perform a self-consistency check by comparing the pair correlation function that evolved from the multiscale simulation with the one evaluated at the molecular-level; excellent agreement is achieved.

  11. 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

  12. 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.

  13. 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.

  14. Multiscale systems analysis of root growth and development: modeling beyond the network and cellular scales.

    PubMed

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

    2012-10-01

    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.

  15. 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

  16. 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

  17. Multiscale Modeling of Transport Phenomena and Dendritic Growth in Laser Cladding Processes

    NASA Astrophysics Data System (ADS)

    Tan, Wenda; Wen, Shaoyi; Bailey, Neil; Shin, Yung C.

    2011-12-01

    A multiscale model is developed in this article to investigate the transport phenomena and dendrite growth in the diode-laser-cladding process. A transient model with an improved level-set method is built to simulate the heat/mass transport and the dynamic evolution of the molten pool surface on the macroscale. A novel model integrating the cellular automata (CA) and phase field (PF) methods is used to simulate the dendritic growth of multicomponent alloys in the mushy zone. The multiscale model is validated against the experiments, and the predicted geometry of clad tracks and the predicted dendrite arm spacing of microstructure match reasonably well with the experimental results. The effects of the processing parameters on the track geometry and microstructure are also investigated.

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

    PubMed

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

    2016-01-01

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

  19. 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

  20. 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.

  1. 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.

  2. Resolving Nuclear Reactor Lifetime Extension Questions: A Combined Multiscale Modeling and Positron Characterization approach

    SciTech Connect

    Wirth, B; Asoka-Kumar, P; Denison, A; Glade, S; Howell, R; Marian, J; Odette, G; Sterne, P

    2004-04-06

    The objective of this work is to determine the chemical composition of nanometer precipitates responsible for irradiation hardening and embrittlement of reactor pressure vessel steels, which threaten to limit the operating lifetime of nuclear power plants worldwide. The scientific approach incorporates computational multiscale modeling of radiation damage and microstructural evolution in Fe-Cu-Ni-Mn alloys, and experimental characterization by positron annihilation spectroscopy and small angle neutron scattering. The modeling and experimental results are

  3. Multiscale modeling approach for calculating grain-boundary energies from first principles

    SciTech Connect

    Shenderova, O.A.; Brenner, D.W.; Nazarov, A.A.; Romanov, A.E.; Yang, L.H.

    1998-02-01

    A multiscale modeling approach is proposed for calculating energies of tilt-grain boundaries in covalent materials from first principles over an entire misorientation range for given tilt axes. The method uses energies from density-functional calculations for a few key structures as input into a disclination structural-units model. This approach is demonstrated by calculating energies of {l_angle}001{r_angle}-symmetrical tilt-grain boundaries in diamond. {copyright} {ital 1998} {ital The American Physical Society}

  4. 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...

  5. 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...

  6. 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 (...

  7. 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.

  8. 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.

  9. 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.

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

    PubMed

    Lefkimmiatis, Stamatios; Maragos, Petros; Papandreou, George

    2009-08-01

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

  11. 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.

  12. 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.

  13. 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

  14. 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

  15. mRM - multiscale Routing Model for Land Surface and Hydrologic Models

    NASA Astrophysics Data System (ADS)

    Cuntz, M.; Thober, S.; Mai, J.; Samaniego, L. E.; Gochis, D. J.; Kumar, R.

    2015-12-01

    Routing streamflow through a river network is a basic step within any distributed hydrologic model. It integrates the generated runoff and allows comparison with observed discharge at the outlet of a catchment. The Muskingum routing is a textbook river routing scheme that has been implemented in Earth System Models (e.g., WRF-HYDRO), stand-alone routing schemes (e.g., RAPID), and hydrologic models (e.g., the mesoscale Hydrologic Model). Most implementations suffer from a high computational demand because the spatial routing resolution is fixed to that of the elevation model irrespective of the hydrologic modeling resolution. This is because the model parameters are scale-dependent and cannot be used at other resolutions without re-estimation. Here, we present the multiscale Routing Model (mRM) that allows for a flexible choice of the routing resolution. mRM exploits the Multiscale Parameter Regionalization (MPR) included in the open-source mesoscale Hydrologic Model (mHM, www.ufz.de/mhm) that relates model parameters to physiographic properties and allows to estimate scale-independent model parameters. mRM is currently coupled to mHM and is presented here as stand-alone Free and Open Source Software (FOSS). The mRM source code is highly modular and provides a subroutine for internal re-use in any land surface scheme. mRM is coupled in this work to the state-of-the-art land surface model Noah-MP. Simulation results using mRM are compared with those available in WRF-HYDRO for the Red River during the period 1990-2000. mRM allows to increase the routing resolution from 100m to more than 10km without deteriorating the model performance. Therefore, it speeds up model calculation by reducing the contribution of routing to total runtime from over 80% to less than 5% in the case of WRF-HYDRO. mRM thus makes discharge data available to land surface modeling with only little extra calculations.

  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

    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.

  18. 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.

  19. 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.

  20. 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

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. Integration of multi-scale biosimulation models via light-weight semantics.

    PubMed

    Gennari, John H; Neal, Maxwell L; Carlson, Brian E; Cook, Daniel L

    2008-01-01

    Currently, biosimulation researchers use a variety of computational environments and languages to model biological processes. Ideally, researchers should be able to semiautomatically merge models to more effectively build larger, multi-scale models. However, current modeling methods do not capture the underlying semantics of these models sufficiently to support this type of model construction. In this paper, we both propose a general approach to solve this problem, and we provide a specific example that demonstrates the benefits of our methodology. In particular, we describe three biosimulation models: (1) a cardio-vascular fluid dynamics model, (2) a model of heart rate regulation via baroreceptor control, and (3) a sub-cellular-level model of the arteriolar smooth muscle. Within a light-weight ontological framework, we leverage reference ontologies to match concepts across models. The light-weight ontology then helps us combine our three models into a merged model that can answer questions beyond the scope of any single model.

  11. Aerosol effects on deep convection in a multi-scale aerosol-climate model

    NASA Astrophysics Data System (ADS)

    Wang, M.; Ghan, S. J.; Morrison, H.

    2012-12-01

    Aerosols have been demonstrated to affect convective clouds and precipitation in observations, process models, and regional climate models. However, examining aerosol effects on convective clouds and precipitation in global climate models has been extremely challenging, as until recently the treatments in the few global climate models that include aerosol effects on convective clouds have used conventional cumulus parameterizations and hence have been quite crude. We have recently built a multi-scale aerosol-climate model, PNNL-MMF, which is an extension of a multi-scale modeling framework (MMF) model. The extended model explicitly treats aerosol effects on deep convection using a two-moment cloud microphysics scheme in the cloud-resolving model component of the MMF. In this presentation, we examine aerosol effects on convective clouds at the global scale using the PNNL-MMF model. Our results show that the frequency of precipitation occurrence at a given liquid water path increases with increasing aerosol loading for deep clouds with surface precipitation rate larger than 10 mm/day. This relationship is particularly evident during the summer time, when convection activity is strong, and may indicate invigoration of deep convection by aerosols. The modeled relationship of aerosols, clouds and precipitation is further compared with observations from the ARM long-term sites (e.g., SGP). The causes of the modeled relationship of aerosols, clouds and precipitations are examined by using a pair of 5-year MMF simulations with and without anthropogenic aerosols.

  12. Multiscale modeling of the moist-convective atmosphere — A review

    NASA Astrophysics Data System (ADS)

    Arakawa, A.; Jung, J.-H.

    2011-11-01

    Multiscale modeling of the moist-convective atmosphere is reviewed with an emphasis on the recently proposed approaches of unified parameterization and Quasi-3D (Q3D) Multiscale Modeling Framework (MMF). The cumulus parameterization problem, which was introduced to represent the multiscale effects of moist convection, has been one of the central issues in atmospheric modeling. After a review of the history of cumulus parameterization, it is pointed out that currently there are two families of atmospheric models with quite different formulations of model physics, one represented by the general circulation models (GCMs) and the other by the cloud-resolving models (CRMs). Ideally, these two families of models should be unified so that a continuous transition of model physics from one kind to the other takes place as the resolution changes. This paper discusses two possible routes to achieve the unification. ROUTE I unifies the cumulus parameterization in conventional GCMs and the cloud microphysics parameterization in CRMs. A key to construct such a unified parameterization is to reformulate the vertical eddy transport due to subgrid-scale moist convection in such a way that it vanishes when the resolution is sufficiently high. A preliminary design of the unified parameterization is presented with supporting evidence for its validity. ROUTE II for the unification follows the MMF approach based on a coupled GCM/CRM, originally known as the “super-parameterization”. The Q3D MMF is an attempt to broaden the applicability of the super-parameterization without necessarily using a fully three-dimensional CRM. This is accomplished using a network of cloud-resolving grids with gaps. The basic Q3D algorithm and highlights of preliminary results are reviewed. It is suggested that the hierarchy of future global models should form a “Multiscale Modeling Network (MMN)”, which combines these two routes. With this network, the horizontal resolution of the dynamics core and

  13. 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

  14. A comparison of natural-image-based models of simple-cell coding.

    PubMed

    Willmore, B; Watters, P A; Tolhurst, D J

    2000-01-01

    Models such as that of Olshausen and Field (O&F, 1997 Vision Research 37 3311-3325) and principal components analysis (PCA) have been used to model simple-cell receptive fields, and to try to elucidate the statistical principles underlying visual coding in area V1. They connect the statistical structure of natural images with the statistical structure of the coding used in V1. The O&F model has created particular interest because the basis functions it produces resemble the receptive fields of simple cells. We evaluate these models in terms of their sparseness and dispersal, both of which have been suggested as desirable for efficient visual coding. However, both attributes have been defined ambiguously in the literature, and we have been obliged to formulate specific definitions in order to allow any comparison between models at all. We find that both attributes are strongly affected by any preprocessing (e.g. spectral pseudo-whitening or a logarithmic transformation) which is often applied to images before they are analysed by PCA or the O&F model. We also find that measures of sparseness are affected by the size of the filters--PCA filters with small receptive fields appear sparser than PCA filters with larger spatial extent. Finally, normalisation of the means and variances of filters influences measures of dispersal. It is necessary to control for all of these factors before making any comparisons between different models. Having taken these factors into account, we find that the code produced by the O&F model is somewhat sparser than the code produced by PCA. However, the difference is rather smaller than might have been expected, and a measure of dispersal is required to distinguish clearly between the two models. PMID:11144817

  15. 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.

  16. Image-based modeling for better understanding and assessment of atherosclerotic plaque progression and vulnerability: Data, modeling, validation, uncertainty and predictions

    PubMed Central

    Tang, Dalin; Kamm, Roger D.; Yang, Chun; Zheng, Jie; Canton, Gador; Bach, Richard; Huang, Xueying; Hatsukami, Thomas S.; Zhu, Jian; Ma, Genshan; Maehara, Akiko; Mintz, Gary S.; Yuan, Chun

    2014-01-01

    Medical imaging and image-based modeling have made considerable progress in recent years in identifying atherosclerotic plaque morphological and mechanical risk factors which may be used in developing improved patient screening strategies. However, a clear understanding is needed about what we have achieved and what is really needed to translate research to actual clinical practices and bring benefits to public health. Lack of in vivo data and clinical events to serve as gold standard to validate model predictions is a severe limitation. While this perspective paper provides a review of the key steps and findings of our group in image-based models for human carotid and coronary plaques and a limited review of related work by other groups, we also focus on grand challenges and uncertainties facing the researchers in the field to develop more accurate and predictive patient screening tools. PMID:24480706

  17. A chemical energy approach of avascular tumor growth: multiscale modeling and qualitative results.

    PubMed

    Ampatzoglou, Pantelis; Dassios, George; Hadjinicolaou, Maria; Kourea, Helen P; Vrahatis, Michael N

    2015-01-01

    In the present manuscript we propose a lattice free multiscale model for avascular tumor growth that takes into account the biochemical environment, mitosis, necrosis, cellular signaling and cellular mechanics. This model extends analogous approaches by assuming a function that incorporates the biochemical energy level of the tumor cells and a mechanism that simulates the behavior of cancer stem cells. Numerical simulations of the model are used to investigate the morphology of the tumor at the avascular phase. The obtained results show similar characteristics with those observed in clinical data in the case of the Ductal Carcinoma In Situ (DCIS) of the breast. PMID:26558163

  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. 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. 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

  1. 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

  2. An imaging-based computational model for simulating angiogenesis and tumour oxygenation dynamics

    NASA Astrophysics Data System (ADS)

    Adhikarla, Vikram; Jeraj, Robert

    2016-05-01

    Tumour growth, angiogenesis and oxygenation vary substantially among tumours and significantly impact their treatment outcome. Imaging provides a unique means of investigating these tumour-specific characteristics. Here we propose a computational model to simulate tumour-specific oxygenation changes based on the molecular imaging data. Tumour oxygenation in the model is reflected by the perfused vessel density. Tumour growth depends on its doubling time (T d) and the imaged proliferation. Perfused vessel density recruitment rate depends on the perfused vessel density around the tumour (sMVDtissue) and the maximum VEGF concentration for complete vessel dysfunctionality (VEGFmax). The model parameters were benchmarked to reproduce the dynamics of tumour oxygenation over its entire lifecycle, which is the most challenging test. Tumour oxygenation dynamics were quantified using the peak pO2 (pO2peak) and the time to peak pO2 (t peak). Sensitivity of tumour oxygenation to model parameters was assessed by changing each parameter by 20%. t peak was found to be more sensitive to tumour cell line related doubling time (~30%) as compared to tissue vasculature density (~10%). On the other hand, pO2peak was found to be similarly influenced by the above tumour- and vasculature-associated parameters (~30-40%). Interestingly, both pO2peak and t peak were only marginally affected by VEGFmax (~5%). The development of a poorly oxygenated (hypoxic) core with tumour growth increased VEGF accumulation, thus disrupting the vessel perfusion as well as further increasing hypoxia with time. The model with its benchmarked parameters, is applied to hypoxia imaging data obtained using a [64Cu]Cu-ATSM PET scan of a mouse tumour and the temporal development of the vasculature and hypoxia maps are shown. The work underscores the importance of using tumour-specific input for analysing tumour evolution. An extended model incorporating therapeutic effects can serve as a powerful tool for analysing

  3. 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.

  4. [Segmentation of medical images based on dyadic wavelet transform and active contour model].

    PubMed

    Li, Hong; Wang, Huinan; Chang, Linfeng; Shao, Xiaoli

    2008-12-01

    The interference of noise and the weak edge characteristic of symptom information on medical images prevent the traditional methods of segmentation from having good effects. In this paper is proposed a boundary detection method of focus which is based on dyadic wavelet transform and active contour model. In this method, the true edge points are detected by dyadic wavelet transform and linked by improved fast active contour model algorithm. The result of experiment on MRI of brain shows that the method can remove the influence of noise effective and detect the contour of brain tumor actually. PMID:19166191

  5. 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

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

    DOE PAGES

    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

  7. 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.

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

    NASA Astrophysics Data System (ADS)

    Sondak, D.; Shadid, J. N.; Oberai, A. A.; Pawlowski, R. P.; Cyr, E. C.; Smith, T. M.

    2015-08-01

    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. 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.

  9. 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

  10. Model-based coding of facial images based on facial muscle motion through isodensity maps

    NASA Astrophysics Data System (ADS)

    So, Ikken; Nakamura, Osamu; Minami, Toshi

    1991-11-01

    A model-based coding system has come under serious consideration for the next generation of image coding schemes, aimed at greater efficiency in TV telephone and TV conference systems. In this model-based coding system, the sender's model image is transmitted and stored at the receiving side before the start of the conversation. During the conversation, feature points are extracted from the facial image of the sender and are transmitted to the receiver. The facial expression of the sender facial is reconstructed from the feature points received and a wireframed model constructed at the receiving side. However, the conventional methods have the following problems: (1) Extreme changes of the gray level, such as in wrinkles caused by change of expression, cannot be reconstructed at the receiving side. (2) Extraction of stable feature points from facial images with irregular features such as spectacles or facial hair is very difficult. To cope with the first problem, a new algorithm based on isodensity lines which can represent detailed changes in expression by density correction has already been proposed and good results obtained. As for the second problem, we propose in this paper a new algorithm to reconstruct facial images by transmitting other feature points extracted from isodensity maps.

  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. 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.

  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. 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.

  15. 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

  16. Image-based modeling of hemodynamics in coronary artery aneurysms caused by Kawasaki disease.

    PubMed

    Sengupta, Dibyendu; Kahn, Andrew M; Burns, Jane C; Sankaran, Sethuraman; Shadden, Shawn C; Marsden, Alison L

    2012-07-01

    Kawasaki Disease (KD) is the leading cause of acquired pediatric heart disease. A subset of KD patients develops aneurysms in the coronary arteries, leading to increased risk of thrombosis and myocardial infarction. Currently, there are limited clinical data to guide the management of these patients, and the hemodynamic effects of these aneurysms are unknown. We applied patient-specific modeling to systematically quantify hemodynamics and wall shear stress in coronary arteries with aneurysms caused by KD. We modeled the hemodynamics in the aneurysms using anatomic data obtained by multi-detector computed tomography (CT) in a 10-year-old male subject who suffered KD at age 3 years. The altered hemodynamics were compared to that of a reconstructed normal coronary anatomy using our subject as the model. Computer simulations using a robust finite element framework were used to quantify time-varying shear stresses and particle trajectories in the coronary arteries. We accounted for the cardiac contractility and the microcirculation using physiologic downstream boundary conditions. The presence of aneurysms in the proximal coronary artery leads to flow recirculation, reduced wall shear stress within the aneurysm, and high wall shear stress gradients at the neck of the aneurysm. The wall shear stress in the KD subject (2.95-3.81 dynes/sq cm) was an order of magnitude lower than the normal control model (17.10-27.15 dynes/sq cm). Particle residence times were significantly higher, taking 5 cardiac cycles to fully clear from the aneurysmal regions in the KD subject compared to only 1.3 cardiac cycles from the corresponding regions of the normal model. In this novel quantitative study of hemodynamics in coronary aneurysms caused by KD, we documented markedly abnormal flow patterns that are associated with increased risk of thrombosis. This methodology has the potential to provide further insights into the effects of aneurysms in KD and to help risk stratify patients for

  17. Automatic measurement of vertebral body deformations in CT images based on a 3D parametric model

    NASA Astrophysics Data System (ADS)

    Štern, Darko; Bürmen, Miran; Njagulj, Vesna; Likar, Boštjan; Pernuš, Franjo; Vrtovec, Tomaž

    2012-03-01

    Accurate and objective evaluation of vertebral body deformations represents an important part of the clinical diagnostics and therapy of pathological conditions affecting the spine. Although modern clinical practice is oriented towards threedimensional (3D) imaging techniques, the established methods for the evaluation of vertebral body deformations are based on measurements in two-dimensional (2D) X-ray images. In this paper, we propose a method for automatic measurement of vertebral body deformations in computed tomography (CT) images that is based on efficient modeling of the vertebral body shape with a 3D parametric model. By fitting the 3D model to the vertebral body in the image, quantitative description of normal and pathological vertebral bodies is obtained from the value of 25 parameters of the model. The evaluation of vertebral body deformations is based on the distance of the observed vertebral body from the distribution of the parameter values of normal vertebral bodies in the parametric space. The distribution is obtained from 80 normal vertebral bodies in the training data set and verified with eight normal vertebral bodies in the control data set. The statistically meaningful distance of eight pathological vertebral bodies in the study data set from the distribution of normal vertebral bodies in the parametric space shows that the parameters can be used to successfully model vertebral body deformations in 3D. The proposed method may therefore be used to assess vertebral body deformations in 3D or provide clinically meaningful observations that are not available when using 2D methods that are established in clinical practice.

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

    PubMed

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

    2014-03-25

    3D modeling of cultural heritage objects like artifacts, statues and buildings is nowadays an important tool for virtual museums, preservation and restoration. In this paper, we introduce a method to automatically design a minimal imaging network for the 3D modeling of cultural heritage objects. This becomes important for reducing the image capture time and processing when documenting large and complex sites. Moreover, such a minimal camera network design is desirable for imaging non-digitally documented artifacts in museums and other archeological sites to avoid disturbing the visitors for a long time and/or moving delicate precious objects to complete the documentation task. The developed method is tested on the Iraqi famous statue "Lamassu". Lamassu is a human-headed winged bull of over 4.25 m in height from the era of Ashurnasirpal II (883-859 BC). Close-range photogrammetry is used for the 3D modeling task where a dense ordered imaging network of 45 high resolution images were captured around Lamassu with an object sample distance of 1 mm. These images constitute a dense network and the aim of our study was to apply our method to reduce the number of images for the 3D modeling and at the same time preserve pre-defined point accuracy. Temporary control points were fixed evenly on the body of Lamassu and measured by using a total station for the external validation and scaling purpose. Two network filtering methods are implemented and three different software packages are used to investigate the efficiency of the image orientation and modeling of the statue in the filtered (reduced) image networks. Internal and external validation results prove that minimal image networks can provide highly accurate records and efficiency in terms of visualization, completeness, processing time (>60% reduction) and the final accuracy of 1 mm.

  19. 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

  20. Reproducing snow making strategies with deterministic modeling and image-based validation

    NASA Astrophysics Data System (ADS)

    Allamano, P.; Claps, P.; Poggi, D.

    2012-04-01

    Almost all winter resorts rely on artificial snow production as a surrogate for natural snow when the natural snow cover is missing or inadequate. The sustainability of snowmaking practices represents a debated issue, with two contrasting views: on the one hand the need for enhancing the value of mountain regions in terms of touristic appeal; on the other hand, the question whether the production of artificial snow is sustainable from an environmental point of view. We present here the outcomes of a pilot study aimed at assessing the impact of snowmaking practices on water resources management in the Gressoney valley. The study area is located in the Aosta Valley (North-Western Italy). The total area covered by ski runs is of about 95 ha, with an elevation range of 2000 m and an average snow production over the last 5 seasons of 200.000 m3 of water per year. Daily records of water volume used for artificial snow making were made available by the ski runs administrators for the last 5 seasons along with webcam images taken for the last 2 years. Daily meteorological records (of temperature and precipitation) were retrieved in 5 meteo stations within the district area since 1928 (83 years). The snowpack evolution in the skiable domain is modeled by means of a distributed water balance model which adopts a radiation-temperature index representation to describe snowmelt, and accounts for the topographic complexity of the area by modeling radiation over a very fine terrain grid (10 by 10 m cells). The model requires distributed daily temperature and precipitation as inputs. The snowmelt module is calibrated locally at the five stations. The snow-making module, aimed at synthesizing the production strategies at the district scale, is calibrated by keeping the required average snow cover depths on the ski runs as a free parameter. After calibrating the model parameters, also with the aid of visual comparison of modeled and real snow patterns registered by the webcams, we

  1. 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.

  2. An automatic image-based modelling method applied to forensic infography.

    PubMed

    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

  3. 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

  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.

  5. 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

  6. 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

  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. 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.

  9. 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.

  10. Image-Based Modeling of Blood Flow and Oxygen Transfer in Feto-Placental Capillaries

    PubMed Central

    Brownbill, Paul; Janáček, Jiří; Jirkovská, Marie; Kubínová, Lucie; Chernyavsky, Igor L.; Jensen, Oliver E.

    2016-01-01

    During pregnancy, oxygen diffuses from maternal to fetal blood through villous trees in the placenta. In this paper, we simulate blood flow and oxygen transfer in feto-placental capillaries by converting three-dimensional representations of villous and capillary surfaces, reconstructed from confocal laser scanning microscopy, to finite-element meshes, and calculating values of vascular flow resistance and total oxygen transfer. The relationship between the total oxygen transfer rate and the pressure drop through the capillary is shown to be captured across a wide range of pressure drops by physical scaling laws and an upper bound on the oxygen transfer rate. A regression equation is introduced that can be used to estimate the oxygen transfer in a capillary using the vascular resistance. Two techniques for quantifying the effects of statistical variability, experimental uncertainty and pathological placental structure on the calculated properties are then introduced. First, scaling arguments are used to quantify the sensitivity of the model to uncertainties in the geometry and the parameters. Second, the effects of localized dilations in fetal capillaries are investigated using an idealized axisymmetric model, to quantify the possible effect of pathological placental structure on oxygen transfer. The model predicts how, for a fixed pressure drop through a capillary, oxygen transfer is maximized by an optimal width of the dilation. The results could explain the prevalence of fetal hypoxia in cases of delayed villous maturation, a pathology characterized by a lack of the vasculo-syncytial membranes often seen in conjunction with localized capillary dilations. PMID:27788214

  11. 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

  12. 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.

  13. Estimation of inlet flow rates for image-based aneurysm CFD models: where and how to begin?

    PubMed

    Valen-Sendstad, Kristian; Piccinelli, Marina; KrishnankuttyRema, Resmi; Steinman, David A

    2015-06-01

    Patient-specific flow rates are rarely available for image-based computational fluid dynamics models. Instead, flow rates are often assumed to scale according to the diameters of the arteries of interest. Our goal was to determine how choice of inlet location and scaling law affect such model-based estimation of inflow rates. We focused on 37 internal carotid artery (ICA) aneurysm cases from the Aneurisk cohort. An average ICA flow rate of 245 mL min(-1) was assumed from the literature, and then rescaled for each case according to its inlet diameter squared (assuming a fixed velocity) or cubed (assuming a fixed wall shear stress). Scaling was based on diameters measured at various consistent anatomical locations along the models. Choice of location introduced a modest 17% average uncertainty in model-based flow rate, but within individual cases estimated flow rates could vary by >100 mL min(-1). A square law was found to be more consistent with physiological flow rates than a cube law. Although impact of parent artery truncation on downstream flow patterns is well studied, our study highlights a more insidious and potentially equal impact of truncation site and scaling law on the uncertainty of assumed inlet flow rates and thus, potentially, downstream flow patterns.

  14. 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.

  15. 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.

  16. [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

  17. Multiscale modeling of the human arterial tree on the TeraGrid.

    NASA Astrophysics Data System (ADS)

    Karniadakis, Gerorge

    2009-03-01

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

  18. 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.

  19. Variational multiscale turbulence modelling in a high order spectral element method

    SciTech Connect

    Wasberg, Carl Erik Gjesdal, Thor Reif, Bjorn Anders Pettersson Andreassen, Oyvind

    2009-10-20

    In the variational multiscale (VMS) approach to large eddy simulation (LES), the governing equations are projected onto an a priori scale partitioning of the solution space. This gives an alternative framework for designing and analyzing turbulence models. We describe the implementation of the VMS LES methodology in a high order spectral element method with a nodal basis, and discuss the properties of the proposed scale partitioning. The spectral element code is first validated by doing a direct numerical simulation of fully developed plane channel flow. The performance of the turbulence model is then assessed by several coarse grid simulations of channel flow at different Reynolds numbers.

  20. 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.

  1. Image-based computational models for TAVI planning: from CT images to implant deployment.

    PubMed

    Grbic, Sasa; Mansi, Tommaso; Ionasec, Razvan; Voigt, Ingmar; Houle, Helene; John, Matthias; Schoebinger, Max; Navab, Nassir; Comaniciu, Dorin

    2013-01-01

    Transcatheter aortic valve implantation (TAVI) is becoming the standard choice of care for non-operable patients suffering from severe aortic valve stenosis. As there is no direct view or access to the affected anatomy, accurate preoperative planning is crucial for a successful outcome. The most important decision during planning is selecting the proper implant type and size. Due to the wide variety in device sizes and types and non-circular annulus shapes, there is often no obvious choice for the specific patient. Most clinicians base their final decision on their previous experience. As a first step towards a more predictive planning, we propose an integrated method to estimate the aortic apparatus from CT images and compute implant deployment. Aortic anatomy, which includes aortic root, leaflets and calcifications, is automatically extracted using robust modeling and machine learning algorithms. Then, the finite element method is employed to calculate the deployment of a TAVI implant inside the patient-specific aortic anatomy. The anatomical model was evaluated on 198 CT images, yielding an accuracy of 1.30 +/- 0.23 mm. In eleven subjects, pre- and post-TAVI CT images were available. Errors in predicted implant deployment were of 1.74 +/- 0.40 mm in average and 1.32 mm in the aortic valve annulus region, which is almost three times lower than the average gap of 3 mm between consecutive implant sizes. Our framework may thus constitute a surrogate tool for TAVI planning.

  2. Image-based computational models for TAVI planning: from CT images to implant deployment.

    PubMed

    Grbic, Sasa; Mansi, Tommaso; Ionasec, Razvan; Voigt, Ingmar; Houle, Helene; John, Matthias; Schoebinger, Max; Navab, Nassir; Comaniciu, Dorin

    2013-01-01

    Transcatheter aortic valve implantation (TAVI) is becoming the standard choice of care for non-operable patients suffering from severe aortic valve stenosis. As there is no direct view or access to the affected anatomy, accurate preoperative planning is crucial for a successful outcome. The most important decision during planning is selecting the proper implant type and size. Due to the wide variety in device sizes and types and non-circular annulus shapes, there is often no obvious choice for the specific patient. Most clinicians base their final decision on their previous experience. As a first step towards a more predictive planning, we propose an integrated method to estimate the aortic apparatus from CT images and compute implant deployment. Aortic anatomy, which includes aortic root, leaflets and calcifications, is automatically extracted using robust modeling and machine learning algorithms. Then, the finite element method is employed to calculate the deployment of a TAVI implant inside the patient-specific aortic anatomy. The anatomical model was evaluated on 198 CT images, yielding an accuracy of 1.30 +/- 0.23 mm. In eleven subjects, pre- and post-TAVI CT images were available. Errors in predicted implant deployment were of 1.74 +/- 0.40 mm in average and 1.32 mm in the aortic valve annulus region, which is almost three times lower than the average gap of 3 mm between consecutive implant sizes. Our framework may thus constitute a surrogate tool for TAVI planning. PMID:24579165

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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...

  9. Dynamical seasonal prediction using the global environmental multiscale model with a variable resolution modeling approach

    NASA Astrophysics Data System (ADS)

    Markovic, Marko; Lin, Hai; Winger, Katja

    2012-10-01

    In this work we evaluate seasonal forecasts performed with the global environmental multiscale model (GEM) using a variable resolution approach and with a high-resolution region over different geographical locations. Therefore, using two grid positions, one over North America and the other over the tropical Pacific-eastern Indian Ocean, we compare the seasonal predictions performed with the variable resolution approach with seasonal forecast performed with the uniform grid GEM model. For each model configuration, a ten-member ensemble forecast of 4 months is performed starting from the first of December of selected ENSO winters between 1982 and 2000. The sea surface temperature anomaly of the month preceding the forecast (November) is persisted throughout the forecast period. There is not enough evidence to indicate that a Stretch-Grid configuration has a clear advantage in seasonal prediction compared to a Uniform-Grid configuration. Forecasts with highly resolved grids placed over North America have more accurate seasonal mean anomalies and more skill in representing near surface temperature over the North American continent. For 500-hPa geopotential height, however, no configuration stands out to be consistently superior in forecasting the ENSO related seasonal mean anomalies and skill score.

  10. Implementation of a segmentation method for agricultural fields in aerial sequences of images based on CSAR model

    NASA Astrophysics Data System (ADS)

    Chen, Haijun; Houkes, Zweitze

    1998-09-01

    In this paper, a segmentation method for agricultural fields in aerial sequences of images based on the Circular Symmetri Auto-Regressive (CSAR) model is presented. The image sequences assumed to be acquired by a video camera (RGB-CCD system) from an aeroplane, which moves linearly over the scene. The objects in the scenes being considered in this paper, are agricultural fields. The classes of agricultural fields to be distinguished are determined by the type of crop, e.g. potatoes sugar beet, wheat, etc. In order to recognize and classify these fields from aerial sequence of images, a reliable segmentatio is required. Here texture features are used for segmentation. The implementation of segmentation for agricultural fields in aerial sequences of images is based on CSAR model in texture analysis. By comparing the estimated parameters of CSAR model from different area in an image, the characteristics and the class of a texture may be determined. The paper describes the segmentation method and its evaluation through experiments. Based on segmentation results, classification for surface texture of vegetation from aerial sequences of images is realized.

  11. Multiresolution MAP despeckling of SAR images based on locally adaptive generalized Gaussian pdf modeling.

    PubMed

    Argenti, Fabrizio; Bianchi, Tiziano; Alparone, Luciano

    2006-11-01

    In this paper, a new despeckling method based on undecimated wavelet decomposition and maximum a posteriori MIAP) estimation is proposed. Such a method relies on the assumption that the probability density function (pdf) of each wavelet coefficient is generalized Gaussian (GG). The major novelty of the proposed approach is that the parameters of the GG pdf are taken to be space-varying within each wavelet frame. Thus, they may be adjusted to spatial image context, not only to scale and orientation. Since the MAP equation to be solved is a function of the parameters of the assumed pdf model, the variance and shape factor of the GG function are derived from the theoretical moments, which depend on the moments and joint moments of the observed noisy signal and on the statistics of speckle. The solution of the MAP equation yields the MAP estimate of the wavelet coefficients of the noise-free image. The restored SAR image is synthesized from such coefficients. Experimental results, carried out on both synthetic speckled images and true SAR images, demonstrate that MAP filtering can be successfully applied to SAR images represented in the shift-invariant wavelet domain, without resorting to a logarithmic transformation.

  12. 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.

  13. [Automatic detection of exudates in retinal images based on threshold moving average models].

    PubMed

    Wisaeng, K; Hiransakolwong, N; Pothiruk, E

    2015-01-01

    Since exudate diagnostic procedures require the attention of an expert ophthalmologist as well as regular monitoring of the disease, the workload of expert ophthalmologists will eventually exceed the current screening capabilities. Retinal imaging technology is a current practice screening capability providing a great potential solution. In this paper, a fast and robust automatic detection of exudates based on moving average histogram models of the fuzzy image was applied, and then the better histogram was derived. After segmentation of the exudate candidates, the true exudates were pruned based on Sobel edge detector and automatic Otsu's thresholding algorithm that resulted in the accurate location of the exudates in digital retinal images. To compare the performance of exudate detection methods we have constructed a large database of digital retinal images. The method was trained on a set of 200 retinal images, and tested on a completely independent set of 1220 retinal images. Results show that the exudate detection method performs overall best sensitivity, specificity, and accuracy of 90.42%, 94.60%, and 93.69%, respectively. PMID:26016034

  14. 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

  15. 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.

  16. Computational fluid dynamic simulations of image-based stented coronary bifurcation models.

    PubMed

    Chiastra, Claudio; Morlacchi, Stefano; Gallo, Diego; Morbiducci, Umberto; Cárdenes, Rubén; Larrabide, Ignacio; Migliavacca, Francesco

    2013-07-01

    One of the relevant phenomenon associated with in-stent restenosis in coronary arteries is an altered haemodynamics in the stented region. Computational fluid dynamics (CFD) offers the possibility to investigate the haemodynamics at a level of detail not always accessible within experimental techniques. CFD can quantify and correlate the local haemodynamics structures which might lead to in-stent restenosis. The aim of this work is to study the fluid dynamics of realistic stented coronary artery models which replicate the complete clinical procedure of stent implantation. Two cases of pathologic left anterior descending coronary arteries with their bifurcations are reconstructed from computed tomography angiography and conventional coronary angiography images. Results of wall shear stress and relative residence time show that the wall regions more prone to the risk of restenosis are located next to stent struts, to the bifurcations and to the stent overlapping zone for both investigated cases. Considering a bulk flow analysis, helical flow structures are generated by the curvature of the zone upstream from the stent and by the bifurcation regions. Helical recirculating microstructures are also visible downstream from the stent struts. This study demonstrates the feasibility to virtually investigate the haemodynamics of patient-specific coronary bifurcation geometries.

  17. 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.

  18. 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.

  19. Multiscale model of liver DCE-MRI towards a better understanding of tumor complexity.

    PubMed

    Mescam, Muriel; Kretowski, Marek; Bezy-Wendling, Johanne

    2010-03-01

    The use of quantitative imaging for the characterization of hepatic tumors in magnetic resonance imaging (MRI) can improve the diagnosis and therefore the treatment of these life-threatening tumors. However, image parameters remain difficult to interpret because they result from a mixture of complex processes related to pathophysiology and to acquisition. These processes occur at variable spatial and temporal scales. We propose a multiscale model of liver dynamic contrast-enhanced (DCE) MRI in order to better understand the tumor complexity in images. Our design couples a model of the organ (tissue and vasculature) with a model of the image acquisition. At the macroscopic scale, vascular trees take a prominent place. Regarding the formation of MRI images, we propose a distributed model of parenchymal biodistribution of extracellular contrast agents. Model parameters can be adapted to simulate the tumor development. The sensitivity of the multiscale model of liver DCE-MRI was studied through observations of the influence of two physiological parameters involved in carcinogenesis (arterial flow and capillary permeability) on its outputs (MRI images at arterial and portal phases). Finally, images were simulated for a set of parameters corresponding to the five stages of hepatocarcinogenesis (from regenerative nodules to poorly differentiated HepatoCellular Carcinoma).

  20. 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.

  1. 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)].

  2. 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

  3. 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.

  4. Systematic multiscale parameterization of heterogeneous elastic network models of proteins.

    PubMed

    Lyman, Edward; Pfaendtner, Jim; Voth, Gregory A

    2008-11-01

    We present a method to parameterize heterogeneous elastic network models (heteroENMs) of proteins to reproduce the fluctuations observed in atomistic simulations. Because it is based on atomistic simulation, our method allows the development of elastic coarse-grained models of proteins under different conditions or in different environments. The method is simple and applicable to models at any level of coarse-graining. We validated the method in three systems. First, we computed the persistence length of ADP-bound F-actin, using a heteroENM model. The value of 6.1 +/- 1.6 microm is consistent with the experimentally measured value of 9.0 +/- 0.5 microm. We then compared our method to a uniform elastic network model and a realistic extension algorithm via covariance Hessian (REACH) model of carboxy myoglobin, and found that the heteroENM method more accurately predicted mean-square fluctuations of alpha-carbon atoms. Finally, we showed that the method captures critical differences in effective harmonic interactions for coarse-grained models of the N-terminal Bin/amphiphysin/Rvs (N-BAR) domain of amphiphysin, by building models of N-BAR both bound to a membrane and free in solution.

  5. Lateral organization of complex lipid mixtures from multiscale modeling

    PubMed Central

    Tumaneng, Paul W.; Pandit, Sagar A.; Zhao, Guijun; Scott, H. L.

    2010-01-01

    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. PMID:20151760

  6. Modelling neural informational propagation and functional auditory sensory memory with temporal multi-scale operators.

    PubMed

    Serman, Maja; Serman, Nikola; Griffith, Niall J L

    2007-08-01

    In this paper we prove that both diffusion and the leaky integrators cascade based transport mechanisms have as their inherent property the effect of temporal multi-scaling. The two transport mechanisms are modeled not as convolution based algorithms but as causal physical processes. This implies that propagation of information through a neural map may act as a mechanism for achieving temporal multi-scale analysis in the auditory system. Specifically, we are interested in the effects of such a transport process on the formation and the dynamics of auditory sensory memory. Two temporal models of information propagation are discussed and compared in terms of their ability to model auditory sensory memory effects and the biological plausibility of their structure: the causal diffusion based operator (CD) and the leaky integrator cascade based operator (LINC). We show that temporal multi-scale representations achieved by both models exhibit the effects similar to those of auditory sensory memory (filtering, time delay and binding of information). As regards higher-level functions of auditory sensory memory such as change detection, the LINC operator seems to be a biologically more plausible solution for modeling temporal cortical processing.

  7. 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

  8. 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

  9. 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.

  10. 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

  11. Multiscale model for photoinduced molecular motion in azo polymers.

    PubMed

    Juan, Mathieu L; Plain, Jérôme; Bachelot, Renaud; Royer, Pascal; Gray, Stephen K; Wiederrecht, Gary P

    2009-06-23

    Light-induced isomerization processes in azobenzene-containing polymers produce mass transport that is of much interest for nanoscale imaging and lithography. Yet, despite the development of numerous models to simulate the mass transport mechanism, no model precisely describes all the experimental observations. We develop a new statistical approach that correctly reproduces light-driven mass motion in azobenzene-containing polymers with a high degree of accuracy. Comparisons with experiments show that our model predicts the nanoscale topographic modifications for many different incident field configurations, including optical near-fields produced by plasmonic structures with complex polarization states. In particular, the model allows the detailed molecular motions that lead to these topographic modifications to be identified.

  12. mRM - multiscale Routing Model for Scale-Independent Streamflow Simulations

    NASA Astrophysics Data System (ADS)

    Thober, Stephan; Kumar, Rohini; Samaniego, Luis; Mai, Juliane; Rakovec, Oldrich; Cuntz, Matthias

    2016-04-01

    Routing streamflow through a river network is a basic step within any distributed hydrologic model. It integrates the generated runoff and allows comparison with observed discharge at the outlet of a catchment. The Muskingum routing is a textbook river routing scheme that has been implemented in Earth System Models (e.g., WRF-HYDRO), stand-alone routing schemes (e.g., RAPID) , and hydrologic models (e.g., the mesoscale Hydrologic Model - mHM). Two types of implementations are mostly used. In the first one, the spatial routing resolution is fixed to that of the elevation model irrespective of the hydrologic modeling resolution. This implementation suffers from a high computational demand. In the second one, the spatial resolution is always applied at the hydrologic modelling resolution. This approach requires a scale-independent model behaviour which is often not evaluated. Here, we present the multiscale Routing Model (mRM) that provides a flexible choice of the routing resolution independent of the hydrologic modelling resolution. It incorporates a triangular unit hydrograph for overland flow routing and a Muskingum routing scheme for river routing. mRM provides a scale-independent model behaviour by exploiting the Multiscale Parameter Regionalisation (MPR) included in the open-source mHM (www.ufz.de/mhm). MPR reflects the structure of the landscape within the parametrisation of hydrologic processes. Effective model parameters are derived by upscaling of high-resolution (i.e., landscape resolution) parameters to the hydrologic modelling/routing resolution as proposed in Samaniego et al. 2010 and Kumar et al. 2013. mRM is coupled in this work to the state-of-the-art land surface model Noah-MP. Simulated streamflow is derived for the Ohio River (≈~525 000 km^2) during the period 1990-2000 at resolutions of 0.0625

  13. 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

  14. Image-based biomechanical modeling of aortic wall stress and vessel deformation: response to pulsatile arterial pressure simulations

    NASA Astrophysics Data System (ADS)

    Hazer, Dilana; Bauer, Miriam; Unterhinninghofen, Roland; Dillmann, Rüdiger; Richter, Götz-M.

    2008-03-01

    Image-based modeling of cardiovascular biomechanics may be very helpful for patients with aortic aneurysms to predict the risk of rupture and evaluate the necessity of a surgical intervention. In order to generate a reliable support it is necessary to develop exact patient-specific models that simulate biomechanical parameters and provide individual structural analysis of the state of fatigue and characterize this to the potential of rupture of the aortic wall. The patient-specific geometry used here originates from a CT scan of an Abdominal Aortic Aneurysm (AAA). The computations are based on the Finite Element Method (FEM) and simulate the wall stress distribution and the vessel deformation. The wall transient boundary conditions are based on real time-dependent pressure simulations obtained from a previous computational fluid dynamics study. The physiological wall material properties consider a nonlinear hyperelastic constitutive model, based on realistic ex-vivo analysis of the aneurismal arterial tissue. The results showed complex deformation and stress distribution on the AAA wall. The maximum stresses occurred at the systole and are found around the aneurismal bulge in regions close to inflection points. Biomechanical modeling based on medical images and coupled with patient-specific hemodynamics allows analysing and quantifying the effects of dilatation of the arterial wall due to the pulsatile aortic pressure. It provides a physical and realistic insight into the wall mechanics and enables predictive simulations of AAA growth and assessment of rupture. Further development integrating endovascular models would help evaluating non-invasively individual treatment strategies for optimal placement and improved device design.

  15. 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

  16. An electro-mechanical multiscale model of uterine pregnancy contraction.

    PubMed

    Yochum, Maxime; Laforêt, Jérémy; Marque, Catherine

    2016-10-01

    Detecting preterm labor as early as possible is important because tocolytic drugs are much more likely to delay preterm delivery if administered early. Having good information on the real risk of premature labor also leads to fewer women who do not need aggressive treatment for premature labor threat. Currently, one of the most promising ways to diagnose preterm labor threat is the analysis of the electrohysterogram (EHG). Its characteristics have been related to preterm labor risk but they have not proven to be sufficiently accurate to use in clinical routine. One of the reasons for this is that the physiology of the pregnant uterus is insufficiently understood. Models already exist in literature that simulate either the electrical or the mechanical component of the uterine smooth muscle. Few include both components in a co-simulation of electrical and mechanical aspects. A model that can represent realistically both the electrical and the mechanical behavior of the uterine muscle could be useful for better understanding the EHG and therefore for preterm labor detection. Processing the EHG considers only the electrical component of the uterus but the electrical activity does not seem to explain by itself the synchronization of the uterine muscle that occurs during labor and not at other times. Recent studies have demonstrated that the mechanical behavior of the uterine muscle seems to play an important role in uterus synchronization during labor. The aim of the proposed study is to link three different models of the uterine smooth muscle behavior by using co-simulation. The models go from the electrical activity generated at the cellular level to the mechanical force generated by the muscle and from there to the deformation of the tissue. The results show the feasibility of combining these three models to model a whole uterus contraction on 3D realistic uterus model.

  17. An electro-mechanical multiscale model of uterine pregnancy contraction.

    PubMed

    Yochum, Maxime; Laforêt, Jérémy; Marque, Catherine

    2016-10-01

    Detecting preterm labor as early as possible is important because tocolytic drugs are much more likely to delay preterm delivery if administered early. Having good information on the real risk of premature labor also leads to fewer women who do not need aggressive treatment for premature labor threat. Currently, one of the most promising ways to diagnose preterm labor threat is the analysis of the electrohysterogram (EHG). Its characteristics have been related to preterm labor risk but they have not proven to be sufficiently accurate to use in clinical routine. One of the reasons for this is that the physiology of the pregnant uterus is insufficiently understood. Models already exist in literature that simulate either the electrical or the mechanical component of the uterine smooth muscle. Few include both components in a co-simulation of electrical and mechanical aspects. A model that can represent realistically both the electrical and the mechanical behavior of the uterine muscle could be useful for better understanding the EHG and therefore for preterm labor detection. Processing the EHG considers only the electrical component of the uterus but the electrical activity does not seem to explain by itself the synchronization of the uterine muscle that occurs during labor and not at other times. Recent studies have demonstrated that the mechanical behavior of the uterine muscle seems to play an important role in uterus synchronization during labor. The aim of the proposed study is to link three different models of the uterine smooth muscle behavior by using co-simulation. The models go from the electrical activity generated at the cellular level to the mechanical force generated by the muscle and from there to the deformation of the tissue. The results show the feasibility of combining these three models to model a whole uterus contraction on 3D realistic uterus model. PMID:27567400

  18. Modelling of multiscale nonlinear interaction of elastic waves with three-dimensional cracks.

    PubMed

    Ciampa, Francesco; Barbieri, Ettore; Meo, Michele

    2014-06-01

    This paper presents a nonlinear elastic material model able to simulate the nonlinear effects generated by the interaction of acoustic/ultrasonic waves with damage precursors and micro-cracks in a variety of materials. Such a constitutive model is implemented in an in-house finite element code and exhibits a multiscale nature where the macroscopic behavior of damaged structures can be represented through a contribution of a number of mesoscopic elements, which are composed by a statistical collection of microscopic units. By means of the semi-analytical Landau formulation and Preisach-Mayergoyz space representation, this multiscale model allows the description of the structural response under continuous harmonic excitation of micro-damaged materials showing both anharmonic and dissipative hysteretic effects. In this manner, nonlinear effects observed experimentally, such as the generation of both even and odd harmonics, can be reproduced. In addition, by using Kelvin eigentensors and eigenelastic constants, the wave propagation problem in both isotropic and orthotropic solids was extended to the three-dimensional Cartesian space. The developed model has been verified for a number of different geometrical and material configurations. Particularly, the influence of a small region with classical and non-classical elasticity and the variations of the input amplitudes on the harmonics generation were analyzed.

  19. Multiscale modelling of solid tumour growth: the effect of collagen micromechanics

    PubMed Central

    Wijeratne, Peter A.; Vavourakis, Vasileios; Hipwell, John H.; Voutouri, Chrysovalantis; Papageorgis, Panagiotis; Stylianopoulos, Triantafyllos; Evans, Andrew; Hawkes, David J.

    2015-01-01

    Here we introduce a model of solid tumour growth coupled with a multiscale biomechanical description of the tumour microenvironment, which facilitates the explicit simulation of fibre-fibre and tumour-fibre interactions. We hypothesise that such a model, which provides a purely mechanical description of tumour-host interactions, can be used to explain experimental observations of the effect of collagen micromechanics on solid tumour growth. The model was specified to mouse tumour data and numerical simulations were performed. The multiscale model produced lower stresses than an equivalent continuum-like approach, due to a more realistic remodelling of the collagen microstructure. Furthermore, solid tumour growth was found to cause a passive mechanical realignment of fibres at the tumour boundary from a random to a circumferential orientation. This is in accordance with experimental observations, thus demonstrating that such a response can be explained as purely mechanical. Finally, peritumoural fibre network anisotropy was found to produce anisotropic tumour morphology. The dependency of tumour morphology on the peritumoural microstructure was reduced by adding a load-bearing non-collagenous component to the fibre network constitutive equation. PMID:26564173

  20. 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.

  1. Multi-scale plasticity modeling: Coupled discrete dislocation and continuum crystal plasticity

    NASA Astrophysics Data System (ADS)

    Wallin, M.; Curtin, W. A.; Ristinmaa, M.; Needleman, A.

    A hierarchical multi-scale model that couples a region of material described by discrete dislocation plasticity to a surrounding region described by conventional crystal plasticity is presented. The coupled model is aimed at capturing non-classical plasticity effects such as the long-range stresses associated with a density of geometrically necessary dislocations and source limited plasticity, while also accounting for plastic flow and the associated energy dissipation at much larger scales where such non-classical effects are absent. The key to the model is the treatment of the interface between the discrete and continuum regions, where continuity of tractions and displacements is maintained in an average sense and the flow of net Burgers vector is managed via "passing" of discrete dislocations. The formulation is used to analyze two plane strain problems: (i) tension of a block and (ii) crack growth under mode I loading with various sizes of the discrete dislocation plasticity region surrounding the crack tip. The computed crack growth resistance curves are nearly independent of the size of the discrete dislocation plasticity region for region sizes ranging from 30 μm×30 μm to 10 μm×5 μm. The multi-scale model can reduce the computational time for the mode I crack analysis by a factor of 14 with little or no loss of fidelity in the crack growth predictions.

  2. 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.

  3. 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.

  4. 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

  5. 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

  6. 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

  7. 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

  8. Multi-Scale Distributed Sensitivity Analysis of Radiative Transfer Model

    NASA Astrophysics Data System (ADS)

    Neelam, M.; Mohanty, B.

    2015-12-01

    Amidst nature's great variability and complexity and Soil Moisture Active Passive (SMAP) mission aims to provide high resolution soil moisture products for earth sciences applications. One of the biggest challenges still faced by the remote sensing community are the uncertainties, heterogeneities and scaling exhibited by soil, land cover, topography, precipitation etc. At each spatial scale, there are different levels of uncertainties and heterogeneities. Also, each land surface variable derived from various satellite mission comes with their own error margins. As such, soil moisture retrieval accuracy is affected as radiative model sensitivity changes with space, time, and scale. In this paper, we explore the distributed sensitivity analysis of radiative model under different hydro-climates and spatial scales, 1.5 km, 3 km, 9km and 39km. This analysis is conducted in three different regions Iowa, U.S.A (SMEX02), Arizona, USA (SMEX04) and Winnipeg, Canada (SMAPVEX12). Distributed variables such as soil moisture, soil texture, vegetation and temperature are assumed to be uncertain and are conditionally simulated to obtain uncertain maps, whereas roughness data which is spatially limited are assumed a probability distribution. The relative contribution of the uncertain model inputs to the aggregated model output is also studied, using various aggregation techniques. We use global sensitivity analysis (GSA) to conduct this analysis across spatio-temporal scales. Keywords: Soil moisture, radiative transfer, remote sensing, sensitivity, SMEX02, SMAPVEX12.

  9. Chapter 4: Modeling the Cellulosome Using Multiscale Methods

    SciTech Connect

    Bomble, Y. J.; Crowley, M. F.; Xu, Q.; Himmel, M. E.

    2010-01-01

    Deriving renewable liquid fuels from biomass using microbial conversion, which utilizes free enzymes or cellulosomes for degrading cell wall material to sugars, is an attractive solution for today's energy challenges. The study of the structure and mechanism of these large macromolecular complexes is an active and ongoing research topic worldwide, with the goal of finding ways to improve biomass conversion using cellulosomes. Here, we present methods for illuminating the structure and function of systems of this size and complexity using molecular modeling. We show examples of these methods as applied to a range of sizes and time scales from atomistic models of enzymatic modules to coarse-grained models of the entire cellulosomal complex of scaffold and enzymes. Normal mode analysis, fluctuations, hydrogen-bond analysis of enzymes, as well as sampling techniques for cellulosome assembly are described and the results presented. For example, the mechanism of the immunoglobulin-like module of GH9 proteins is shown to be determined largely by hydrogen bond networks, and the exact hydrogen bonds were identified. Finally, by using coarse-grained modeling and parameter scanning techniques, the assembly of cellulosomal complexes is shown to be dominated by their size and shape and not by their mass.

  10. Multiscale Modeling of Functionalized Nanocarriers in Targeted Drug Delivery

    PubMed Central

    Liu, Jin; Bradley, Ryan; Eckmann, David M.; Ayyaswamy, Portonovo S.; Radhakrishnan, Ravi

    2011-01-01

    Targeted drug delivery using functionalized nanocarriers (NCs) is a strategy in therapeutic and diagnostic applications. In this paper we review the recent development of models at multiple length and time scales and their applications to targeting of antibody functionalized nanocarriers to antigens (receptors) on the endothelial cell (EC) surface. Our mesoscale (100 nm-1 μm) model is based on phenomenological interaction potentials for receptor-ligand interactions, receptor-flexure and resistance offered by glycocalyx. All free parameters are either directly determined from independent biophysical and cell biology experiments or estimated using molecular dynamics simulations. We employ a Metropolis Monte Carlo (MC) strategy in conjunction with the weighted histogram analysis method (WHAM) to compute the free energy landscape (potential of mean force or PMF) associated with the multivalent antigen-antibody interactions mediating the NC binding to EC. The binding affinities (association constants) are then derived from the PMF by computing absolute binding free energy of binding of NC to EC, taking into account the relevant translational and rotational entropy losses of NC and the receptors. We validate our model predictions by comparing the computed binding affinities and PMF to a wide range of experimental measurements, including in vitro cell culture, in vivo endothelial targeting, atomic force microscopy (AFM), and flow chamber experiments. The model predictions agree closely and quantitatively with all types experimental measurements. On this basis, we conclude that our computational protocol represents a quantitative and predictive approach for model driven design and optimization of functionalized NCs in targeted vascular drug delivery. PMID:22116782

  11. 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

  12. 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.

  13. 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

  14. 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.

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

    PubMed

    Mak, Michael; Kim, Taeyoon; Zaman, Muhammad H; Kamm, Roger D

    2015-10-01

    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.

  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. 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.

  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. Electrical conductivity of nanocomposites based on carbon nanotubes: a 3D multiscale modeling approach

    NASA Astrophysics Data System (ADS)

    Grabowski, Krzysztof; Zbyrad, Paulina; Staszewski, Wieslaw J.; Uhl, Tadeusz; Wiatr, Kazimierz; Packo, Pawel

    2016-04-01

    Remarkable electrical properties of carbon nanotubes (CNT) have lead to increased interest in studying CNT- based devices. Many of current researches are devoted to using all kinds of carbon nanomaterials in the con- struction of sensory elements. One of the most common applications is the development of high performance, large scale sensors. Due to the remarkable conductivity of CNT's such devices represent very high sensitivity. However, there are no sufficient tools for studying and designing such sensors. The main objective of this paper is to develop and validate a multiscale numerical model for a carbon nanotubes based sensor. The device utilises the change of electrical conductivity of a nanocomposite material under applied deformation. The nanocomposite consists of a number of CNTs dispersed in polymer matrix. The paper is devoted to the analysis of the impact of spatial distribution of carbon nanotubes in polymer matrix on electrical conductivity of the sensor. One of key elements is also to examine the impact of strain on electric charge ow in such anisotropic composite structures. In the following work a multiscale electro-mechanical model for CNT - based nanocomposites is proposed. The model comprises of two length scales, namely the meso- and the macro-scale for mechanical and electrical domains. The approach allows for evaluation of macro-scale mechanical response of a strain sensor. Electrical properties of polymeric material with certain CNT fractions were derived considering electrical properties of CNTs, their contact and the tunnelling effect.

  20. Friction and adhesion of hierarchical carbon nanotube structures for biomimetic dry adhesives: multiscale modeling.

    PubMed

    Hu, Shihao; Jiang, Haodan; Xia, Zhenhai; Gao, Xiaosheng

    2010-09-01

    With unique hierarchical fibrillar structures on their feet, gecko lizards can walk on vertical walls or even ceilings. Recent experiments have shown that strong binding along the shear direction and easy lifting in the normal direction can be achieved by forming unidirectional carbon nanotube array with laterally distributed tips similar to gecko's feet. In this study, a multiscale modeling approach was developed to analyze friction and adhesion behaviors of this hierarchical fibrillar system. Vertically aligned carbon nanotube array with laterally distributed segments at the end was simulated by coarse grained molecular dynamics. The effects of the laterally distributed segments on friction and adhesion strengths were analyzed, and further adopted as cohesive laws used in finite element analysis at device scale. The results show that the laterally distributed segments play an essential role in achieving high force anisotropy between normal and shear directions in the adhesives. Finite element analysis reveals a new friction-enhanced adhesion mechanism of the carbon nanotube array, which also exists in gecko adhesive system. The multiscale modeling provides an approach to bridge the microlevel structures of the carbon nanotube array with its macrolevel adhesive behaviors, and the predictions from this modeling give an insight into the mechanisms of gecko-mimicking dry adhesives.

  1. 3D multi-scale modelling of mechanical behaviour of sound and leached mortar

    SciTech Connect

    Bernard, F.; Kamali-Bernard, S. Prince, W.

    2008-04-15

    A 3D multi-scale modelling of mechanical properties of cement-based materials approach is presented. The proposed approach provides a quantitative means to estimate and predict the mechanical properties of cement-based materials taking into account the eventual changes in the micro-structure. Two numerical tools are combined. First, the NIST's 3D model (CEMHYD3D) is used to generate a realistic 3D Representative Volume Element of cement-based materials at different scales. Then, multi-scale simulations are performed by using the FE software Abaqus for the calculation of the mechanical behaviour. The approach is then successfully applied to a specific mortar in order to determine firstly its mechanical behaviour under tensile and compression loadings and secondly the evolution of its Young's modulus under the leaching phenomenon. This evolution is a key parameter since the leaching may be critical for the mechanical integrity of concrete structures such as radioactive waste storage systems in which cement-based materials may be largely used. The numerical results of the modelling are consistent with the experimental ones.

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

    PubMed

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

    2013-07-01

    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.

  3. 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.

  4. 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

  5. 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

  6. 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

  7. Multiscale modeling of radiation effects in fcc and bcc metals

    SciTech Connect

    Alonso, E; Caturla, M; Diaz de la Rubia, T; Felter, T; Fluss, M; Perlado, J; Wall, M; Wirth, B

    1999-07-15

    The prospect of using computer simulations to calculate radiation-induced defect production and its influence on microstructure evolution and mechanical property changes during prolonged irradiation of nuclear materials has been a beckoning, yet elusive goal for many years. However, the enormous progress achieved in computational physics for calculating reliable, yet tractable interatomic potentials, coupled with vast improvements in computational power have brought this hope to near reality. In order to develop modeling and simulation tools for predicting the irradiation response of nuclear structural materials, models must be implemented and tested across all relevant length and time scales. We discuss the development and implementation of a modeling methodology that consists of the linkage and hierarchical use of ab initio electronic structure calculations, molecular dynamics (MD) simulations, and kinetic Monte Carlo (KMC) simulations. This methodology can describe length and time scales from nanometers to hundreds of microns and from picoseconds to years, respectively. The ideas are demonstrated in two applications. First, we describe simulations that describe the irradiation and subsequent isochronal annealing of Pb, a low melting point fcc metal, and compare the results to experiments. Second, we show how these methods can be used to investigate damage production and freely migrating defect formation in irradiated V, the key component of candidate low activation alloys for fusion energy applications.

  8. 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.

  9. 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

  10. Web-based workflow planning platform supporting the design and execution of complex multiscale cancer models.

    PubMed

    Sakkalis, Vangelis; Sfakianakis, Stelios; Tzamali, Eleftheria; Marias, Kostas; Stamatakos, Georgios; Misichroni, Fay; Ouzounoglou, Eleftherios; Kolokotroni, Eleni; Dionysiou, Dimitra; Johnson, David; McKeever, Steve; Graf, Norbert

    2014-05-01

    Significant Virtual Physiological Human efforts and projects have been concerned with cancer modeling, especially in the European Commission Seventh Framework research program, with the ambitious goal to approach personalized cancer simulation based on patient-specific data and thereby optimize therapy decisions in the clinical setting. However, building realistic in silico predictive models targeting the clinical practice requires interactive, synergetic approaches to integrate the currently fragmented efforts emanating from the systems biology and computational oncology communities all around the globe. To further this goal, we propose an intelligent graphical workflow planning system that exploits the multiscale and modular nature of cancer and allows building complex cancer models by intuitively linking/interchanging highly specialized models. The system adopts and extends current standardization efforts, key tools, and infrastructure in view of building a pool of reliable and reproducible models capable of improving current therapies and demonstrating the potential for clinical translation of these technologies.

  11. Multi-scale Modeling in Biology: How to Bridge the Gaps between Scales?

    PubMed Central

    Qu, Zhilin; Garfinkel, Alan; Weiss, James N.; Nivala, Melissa

    2011-01-01

    Human physiological functions are regulated across many orders of magnitude in space and time. Integrating the information and dynamics from one scale to another is critical for the understanding of human physiology and the treatment of diseases. Multi-scale modeling, as a computational approach, has been widely adopted by researchers in computational and systems biology. A key unsolved issue is how to represent appropriately the dynamical behaviors of a high-dimensional model of a lower scale by a low-dimensional model of a higher scale, so that it can be used to investigate complex dynamical behaviors at even higher scales of integration. In the article, we first review the widely-used different modeling methodologies and their applications at different scales. We then discuss the gaps between different modeling methodologies and between scales, and discuss potential methods for bridging the gaps between scales. PMID:21704063

  12. 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.

  13. 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

  14. Multiscale modeling and computer simulation of polyhedral oligomeric silsesquioxane assemblies

    NASA Astrophysics Data System (ADS)

    Chan, Elaine R.

    Self-assembly offers a promising strategy for manipulating the bottom-up assembly of nanometer-scale objects into useful structures for many diverse applications. Polyhedral oligomeric silsesquioxane (POSS) molecules are nanoscale building blocks with immense potential for constructing hybrid organic/inorganic materials with superior physical properties. The silicon corners of the inorganic nanocubes can be functionalized with a variety of organic tethers to precisely tailor assembly of the molecules into specific structures. To successfully control fabrication of POSS-based materials requires an understanding of the atomic- and nanoscale processes that occur during the assembly process. In conjunction with ongoing experiments, computer simulations and theory can provide fundamental insight into the self-assembly process, and are valuable tools for identifying and efficiently mapping the vast parameter space of complex POSS/polymer assemblies. The objective of this dissertation is to elucidate the self-assembly properties of polymer-tethered POSS at large length (˜100 nanometers) and time (˜10--100 nanoseconds) scales. These length and time scales are often difficult to assess experimentally. Simulation studies of self-assembly in these regimes require sufficiently large numbers of molecules, and coarse-grained mesoscale models have been developed based on electronic structure calculations and all-atom simulations of small numbers of molecules to reduce overall computation time. Model molecules are initially developed that capture the essential features of connectivity and interaction specificity of mono- and tetratethered POSS nanoparticles functionalized with block copolymer and homopolymer chains. Simulations of these model molecules are conducted over wide ranges of temperature and concentration to probe the influence of tether chemical composition, molecular weight, and number on self-assembly. The tethered POSS systems are predicted to exhibit several of

  15. 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.

  16. 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

  17. 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 Physics material properties experiments. A clear understanding of the physics in experiments at this scale, combined with a robust, flexible and predictive modelling capability, is an important step towards more complex experimental platforms and ICF schemes which rely on high power lasers to achieve ignition. These experiments present a significant modelling challenge, the system is characterised by hydrodynamic effects over nanoseconds, driven by long-pulse lasers or the pre-pulse of the petawatt beams, and fast electron generation, transport, and heating effects over picoseconds, driven by short-pulse high intensity lasers. We describe the approach taken at AWE; to integrate a number of codes which capture the detailed physics for each spatial and temporal scale. Simulations of the heating of buried aluminium microdot targets are discussed and we consider the role such tools can play in understanding the impact of changes to the laser parameters, such as frequency and pre-pulse, as well as understanding effects which are difficult to observe experimentally.

  18. Multiscale model of light harvesting by photosystem II in plants.

    PubMed

    Amarnath, Kapil; Bennett, Doran I G; Schneider, Anna R; Fleming, Graham R

    2016-02-01

    The first step of photosynthesis in plants is the absorption of sunlight by pigments in the antenna complexes of photosystem II (PSII), followed by transfer of the nascent excitation energy to the reaction centers, where long-term storage as chemical energy is initiated. Quantum mechanical mechanisms must be invoked to explain the transport of excitation within individual antenna. However, it is unclear how these mechanisms influence transfer across assemblies of antenna and thus the photochemical yield at reaction centers in the functional thylakoid membrane. Here, we model light harvesting at the several-hundred-nanometer scale of the PSII membrane, while preserving the dominant quantum effects previously observed in individual complexes. We show that excitation moves diffusively through the antenna with a diffusion length of 50 nm until it reaches a reaction center, where charge separation serves as an energetic trap. The diffusion length is a single parameter that incorporates the enhancing effect of excited state delocalization on individual rates of energy transfer as well as the complex kinetics that arise due to energy transfer and loss by decay to the ground state. The diffusion length determines PSII's high quantum efficiency in ideal conditions, as well as how it is altered by the membrane morphology and the closure of reaction centers. We anticipate that the model will be useful in resolving the nonphotochemical quenching mechanisms that PSII employs in conditions of high light stress.

  19. Multiscale model of light harvesting by photosystem II in plants

    PubMed Central

    Amarnath, Kapil; Bennett, Doran I. G.; Schneider, Anna R.; Fleming, Graham R.

    2016-01-01

    The first step of photosynthesis in plants is the absorption of sunlight by pigments in the antenna complexes of photosystem II (PSII), followed by transfer of the nascent excitation energy to the reaction centers, where long-term storage as chemical energy is initiated. Quantum mechanical mechanisms must be invoked to explain the transport of excitation within individual antenna. However, it is unclear how these mechanisms influence transfer across assemblies of antenna and thus the photochemical yield at reaction centers in the functional thylakoid membrane. Here, we model light harvesting at the several-hundred-nanometer scale of the PSII membrane, while preserving the dominant quantum effects previously observed in individual complexes. We show that excitation moves diffusively through the antenna with a diffusion length of 50 nm until it reaches a reaction center, where charge separation serves as an energetic trap. The diffusion length is a single parameter that incorporates the enhancing effect of excited state delocalization on individual rates of energy transfer as well as the complex kinetics that arise due to energy transfer and loss by decay to the ground state. The diffusion length determines PSII’s high quantum efficiency in ideal conditions, as well as how it is altered by the membrane morphology and the closure of reaction centers. We anticipate that the model will be useful in resolving the nonphotochemical quenching mechanisms that PSII employs in conditions of high light stress. PMID:26787911

  20. Multiscale modeling of high-strength fibers and fabrics

    NASA Astrophysics Data System (ADS)

    Thomas, John A.; Shanaman, Matthew T.; Lomicka, Christian L.; Boyle, Mike P.; Calderon-Colon, Xiomara; LaBarre, Erin D.; Tiffany, Jason E.; Trexler, Morgan M.

    2012-06-01

    Using a combination of electronic structure calculations, molecular dynamics simulations, and finite-element analysis, we examine the physical mechanisms governing the performance of Kevlar®/carbon composite fibers over a variety of length scales. To begin, we use electronic structure calculations to examine the molecular structure of Kevlar polymers, and quantitatively compare the intramolecular interactions to the non-bonded intermolecular interactions. We then quantify the potential energy landscape between polymers, and fit this data to a potential function for use in molecular dynamics simulations. From molecular dynamics simulations, we calculate the stiffness and elastic modulus of pristine Kevlar fibrils and Kevlar/carbon composite fibrils. We then use a finite-element model of Kevlar fabric to examine how changes in the mechanical properties of the fibers affect the ballistic response of the fabric. These findings provide insight into how carbon fragments, which influence the nanostructure of the polymer, can enhance the ballistic performance of Kevlar fabric layers.

  1. OMEGA: The operational multiscale environment model with grid adaptivity

    SciTech Connect

    Bacon, D.P.

    1995-07-01

    This review talk describes the OMEGA code, used for weather simulation and the modeling of aerosol transport through the atmosphere. Omega employs a 3D mesh of wedge shaped elements (triangles when viewed from above) that adapt with time. Because wedges are laid out in layers of triangular elements, the scheme can utilize structured storage and differencing techniques along the elevation coordinate, and is thus a hybrid of structured and unstructured methods. The utility of adaptive gridding in this moded, near geographic features such as coastlines, where material properties change discontinuously, is illustrated. Temporal adaptivity was used additionally to track moving internal fronts, such as clouds of aerosol contaminants. The author also discusses limitations specific to this problem, including manipulation of huge data bases and fixed turn-around times. In practice, the latter requires a carefully tuned optimization between accuracy and computation speed.

  2. Multiscale Modeling of Thermal Conductivity of Polymer/Carbon Nanocomposites

    NASA Technical Reports Server (NTRS)

    Clancy, Thomas C.; Frankland, Sarah-Jane V.; Hinkley, Jeffrey A.; Gates, Thomas S.

    2010-01-01

    Molecular dynamics simulation was used to estimate the interfacial thermal (Kapitza) resistance between nanoparticles and amorphous and crystalline polymer matrices. Bulk thermal conductivities of the nanocomposites were then estimated using an established effective medium approach. To study functionalization, oligomeric ethylene-vinyl alcohol copolymers were chemically bonded to a single wall carbon nanotube. The results, in a poly(ethylene-vinyl acetate) matrix, are similar to those obtained previously for grafted linear hydrocarbon chains. To study the effect of noncovalent functionalization, two types of polyethylene matrices. -- aligned (extended-chain crystalline) vs. amorphous (random coils) were modeled. Both matrices produced the same interfacial thermal resistance values. Finally, functionalization of edges and faces of plate-like graphite nanoparticles was found to be only modestly effective in reducing the interfacial thermal resistance and improving the composite thermal conductivity

  3. Multiscale analysis of the murine intestine for modeling human diseases

    PubMed Central

    Lyons, Jesse; Herring, Charles A.; Banerjee, Amrita; Simmons, Alan J.

    2015-01-01

    When functioning properly, the intestine is one of the key interfaces between the human body and its environment. It is responsible for extracting nutrients from our food and excreting our waste products. It provides an environment for a host of healthful microbes and serves as a first defense against pathogenic ones. These processes require tight homeostatic controls, which are provided by the interactions of a complex mix of epithelial, stromal, neural and immune cells, as well as the resident microflora. This homeostasis can be disrupted by invasive microbes, genetic lesions, and carcinogens, resulting in diseases such Clostridium difficile infection, inflammatory bowel disease (IBD) and cancer. Enormous strides have been made in understanding how this important organ functions in health and disease using everything from cell culture systems to animal models to human tissue samples. This has resulted in better therapies for all of these diseases, but there is still significant room for improvement. In the United States alone, 14000 people per year die of C. difficile, up to 1.6 million people suffer from IBD, and more than 50000 people die every year from colon cancer. Because these and other intestinal diseases arise from complex interactions between the different components of the gut ecosystem, we propose that systems approaches that address this complexity in an integrative manner may eventually lead to improved therapeutics that deliver lasting cures. This review will discuss the use of systems biology for studying intestinal diseases in vivo with particular emphasis on mouse models. Additionally, it will focus on established experimental techniques that have been used to drive this systems-level analysis, and emerging techniques that will push this field forward in the future. PMID:26040649

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  5. Modeling the rheology of suspensions with high-viscosity solvents: A predictive multiscale approach

    NASA Astrophysics Data System (ADS)

    Chatterjee, Athonu; Heine, David R.; Rovelstad, Amy L.; Wu, Lung-Ming

    2009-08-01

    In this paper, a multiscale approach spanning atomistic and mesoscopic regimes to model the rheology of suspensions that have strongly interacting particles in highly viscous solvents is presented. The model suspensions studied here have 65% sucrose solution—a Newtonian fluid with a viscosity of 170 cP at room temperature—as the solvent phase with ceramic particles of sizes on the order of a few μms as the dispersed (solute) phase. A multiscale approach is proposed to quantitatively account for the effect of the properties of constituent materials on the bulk rheology of the suspension apart from the effect of hydrodynamic factors. A dissipative particle dynamics-type particle-based approach is adopted to which material-specific, mesoscopic force fields developed using molecular dynamics are fed. Issues pertaining to the handling of the vast spectrum of time and length scales present and an appropriate Gallilean-invariant thermostat for solvent dynamics are addressed and resolved. Numerical calculations compare reasonably well to experimentally measured viscosities up to reasonably high Peclet numbers (˜104) .

  6. Assessing the effects of anthropogenic aerosols on Pacific storm track using a multiscale global climate model.

    PubMed

    Wang, Yuan; Wang, Minghuai; Zhang, Renyi; Ghan, Steven J; Lin, Yun; Hu, Jiaxi; Pan, Bowen; Levy, Misti; Jiang, Jonathan H; Molina, Mario J

    2014-05-13

    Atmospheric aerosols affect weather and global general circulation by modifying cloud and precipitation processes, but the magnitude of cloud adjustment by aerosols remains