Sample records for multiscale dynamical systems

  1. 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.

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

    PubMed

    Lu, Zhao; Sun, Jing; Butts, Kenneth

    2014-05-01

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

  3. Multiscale Reactive Molecular Dynamics

    DTIC Science & Technology

    2012-08-15

    biology cannot be described without considering electronic and nuclear-level dynamics and their coupling to slower, cooperative motions of the system ...coupling to slower, cooperative motions of the system . These inherently multiscale problems require computationally efficient and accurate methods to...condensed phase systems with computational efficiency orders of magnitudes greater than currently possible with ab initio simulation methods, thus

  4. Multiscale equation-free algorithms for molecular dynamics

    NASA Astrophysics Data System (ADS)

    Abi Mansour, Andrew

    Molecular dynamics is a physics-based computational tool that has been widely employed to study the dynamics and structure of macromolecules and their assemblies at the atomic scale. However, the efficiency of molecular dynamics simulation is limited because of the broad spectrum of timescales involved. To overcome this limitation, an equation-free algorithm is presented for simulating these systems using a multiscale model cast in terms of atomistic and coarse-grained variables. Both variables are evolved in time in such a way that the cross-talk between short and long scales is preserved. In this way, the coarse-grained variables guide the evolution of the atom-resolved states, while the latter provide the Newtonian physics for the former. While the atomistic variables are evolved using short molecular dynamics runs, time advancement at the coarse-grained level is achieved with a scheme that uses information from past and future states of the system while accounting for both the stochastic and deterministic features of the coarse-grained dynamics. To complete the multiscale cycle, an atom-resolved state consistent with the updated coarse-grained variables is recovered using algorithms from mathematical optimization. This multiscale paradigm is extended to nanofluidics using concepts from hydrodynamics, and it is demonstrated for macromolecular and nanofluidic systems. A toolkit is developed for prototyping these algorithms, which are then implemented within the GROMACS simulation package and released as an open source multiscale simulator.

  5. 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...

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

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

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

  7. Multiscale analysis of information dynamics for linear multivariate processes.

    PubMed

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

    2016-08-01

    In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving average (MA) component, we describe how to represent the resulting VARMA process using statespace (SS) models and how to exploit the SS model parameters to compute analytical measures of information storage and information transfer for the original and rescaled processes. The framework is then used to quantify multiscale information dynamics for simulated unidirectionally and bidirectionally coupled VAR processes, showing that rescaling may lead to insightful patterns of information storage and transfer but also to potentially misleading behaviors.

  8. Differential Geometry Based Multiscale Models

    PubMed Central

    Wei, Guo-Wei

    2010-01-01

    Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atom-istic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier–Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson–Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson–Nernst–Planck equations that are coupled to generalized Navier–Stokes equations for fluid dynamics, Newton's equation for molecular dynamics, and potential and surface driving geometric flows for the micro-macro interface. For excessively large aqueous macromolecular complexes in chemistry and biology, we further develop differential geometry based multiscale fluid-electro-elastic models to replace the expensive molecular dynamics description with an alternative elasticity formulation. PMID:20169418

  9. Suppression of chaos at slow variables by rapidly mixing fast dynamics through linear energy-preserving coupling

    NASA Astrophysics Data System (ADS)

    Abramov, R. V.

    2011-12-01

    Chaotic multiscale dynamical systems are common in many areas of science, one of the examples being the interaction of the low-frequency dynamics in the atmosphere with the fast turbulent weather dynamics. One of the key questions about chaotic multiscale systems is how the fast dynamics affects chaos at the slow variables, and, therefore, impacts uncertainty and predictability of the slow dynamics. Here we demonstrate that the linear slow-fast coupling with the total energy conservation property promotes the suppression of chaos at the slow variables through the rapid mixing at the fast variables, both theoretically and through numerical simulations. A suitable mathematical framework is developed, connecting the slow dynamics on the tangent subspaces to the infinite-time linear response of the mean state to a constant external forcing at the fast variables. Additionally, it is shown that the uncoupled dynamics for the slow variables may remain chaotic while the complete multiscale system loses chaos and becomes completely predictable at the slow variables through increasing chaos and turbulence at the fast variables. This result contradicts the common sense intuition, where, naturally, one would think that coupling a slow weakly chaotic system with another much faster and much stronger chaotic system would result in general increase of chaos at the slow variables.

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

    PubMed

    Lu, Zhao; Sun, Jing; Butts, Kenneth

    2016-02-03

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

  11. A concurrent multiscale micromorphic molecular dynamics

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

    Li, Shaofan, E-mail: shaofan@berkeley.edu; Tong, Qi

    2015-04-21

    In this work, we have derived a multiscale micromorphic molecular dynamics (MMMD) from first principle to extend the (Andersen)-Parrinello-Rahman molecular dynamics to mesoscale and continuum scale. The multiscale micromorphic molecular dynamics is a con-current three-scale dynamics that couples a fine scale molecular dynamics, a mesoscale micromorphic dynamics, and a macroscale nonlocal particle dynamics together. By choosing proper statistical closure conditions, we have shown that the original Andersen-Parrinello-Rahman molecular dynamics is the homogeneous and equilibrium case of the proposed multiscale micromorphic molecular dynamics. In specific, we have shown that the Andersen-Parrinello-Rahman molecular dynamics can be rigorously formulated and justified from firstmore » principle, and its general inhomogeneous case, i.e., the three scale con-current multiscale micromorphic molecular dynamics can take into account of macroscale continuum mechanics boundary condition without the limitation of atomistic boundary condition or periodic boundary conditions. The discovered multiscale scale structure and the corresponding multiscale dynamics reveal a seamless transition from atomistic scale to continuum scale and the intrinsic coupling mechanism among them based on first principle formulation.« less

  12. Complexity multiscale asynchrony measure and behavior for interacting financial dynamics

    NASA Astrophysics Data System (ADS)

    Yang, Ge; Wang, Jun; Niu, Hongli

    2016-08-01

    A stochastic financial price process is proposed and investigated by the finite-range multitype contact dynamical system, in an attempt to study the nonlinear behaviors of real asset markets. The viruses spreading process in a finite-range multitype system is used to imitate the interacting behaviors of diverse investment attitudes in a financial market, and the empirical research on descriptive statistics and autocorrelation behaviors of return time series is performed for different values of propagation rates. Then the multiscale entropy analysis is adopted to study several different shuffled return series, including the original return series, the corresponding reversal series, the random shuffled series, the volatility shuffled series and the Zipf-type shuffled series. Furthermore, we propose and compare the multiscale cross-sample entropy and its modification algorithm called composite multiscale cross-sample entropy. We apply them to study the asynchrony of pairs of time series under different time scales.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  14. Dynamics of a neural system with a multiscale architecture

    PubMed Central

    Breakspear, Michael; Stam, Cornelis J

    2005-01-01

    The architecture of the brain is characterized by a modular organization repeated across a hierarchy of spatial scales—neurons, minicolumns, cortical columns, functional brain regions, and so on. It is important to consider that the processes governing neural dynamics at any given scale are not only determined by the behaviour of other neural structures at that scale, but also by the emergent behaviour of smaller scales, and the constraining influence of activity at larger scales. In this paper, we introduce a theoretical framework for neural systems in which the dynamics are nested within a multiscale architecture. In essence, the dynamics at each scale are determined by a coupled ensemble of nonlinear oscillators, which embody the principle scale-specific neurobiological processes. The dynamics at larger scales are ‘slaved’ to the emergent behaviour of smaller scales through a coupling function that depends on a multiscale wavelet decomposition. The approach is first explicated mathematically. Numerical examples are then given to illustrate phenomena such as between-scale bifurcations, and how synchronization in small-scale structures influences the dynamics in larger structures in an intuitive manner that cannot be captured by existing modelling approaches. A framework for relating the dynamical behaviour of the system to measured observables is presented and further extensions to capture wave phenomena and mode coupling are suggested. PMID:16087448

  15. Multiscale structure in eco-evolutionary dynamics

    NASA Astrophysics Data System (ADS)

    Stacey, Blake C.

    In a complex system, the individual components are neither so tightly coupled or correlated that they can all be treated as a single unit, nor so uncorrelated that they can be approximated as independent entities. Instead, patterns of interdependency lead to structure at multiple scales of organization. Evolution excels at producing such complex structures. In turn, the existence of these complex interrelationships within a biological system affects the evolutionary dynamics of that system. I present a mathematical formalism for multiscale structure, grounded in information theory, which makes these intuitions quantitative, and I show how dynamics defined in terms of population genetics or evolutionary game theory can lead to multiscale organization. For complex systems, "more is different," and I address this from several perspectives. Spatial host--consumer models demonstrate the importance of the structures which can arise due to dynamical pattern formation. Evolutionary game theory reveals the novel effects which can result from multiplayer games, nonlinear payoffs and ecological stochasticity. Replicator dynamics in an environment with mesoscale structure relates to generalized conditionalization rules in probability theory. The idea of natural selection "acting at multiple levels" has been mathematized in a variety of ways, not all of which are equivalent. We will face down the confusion, using the experience developed over the course of this thesis to clarify the situation.

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

    NASA Astrophysics Data System (ADS)

    Sun, Xiaodan; Xiao, Yanni

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

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

    NASA Astrophysics Data System (ADS)

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

    2018-02-01

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

  18. 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

  19. A global "imaging'' view on systems approaches in immunology.

    PubMed

    Ludewig, Burkhard; Stein, Jens V; Sharpe, James; Cervantes-Barragan, Luisa; Thiel, Volker; Bocharov, Gennady

    2012-12-01

    The immune system exhibits an enormous complexity. High throughput methods such as the "-omic'' technologies generate vast amounts of data that facilitate dissection of immunological processes at ever finer resolution. Using high-resolution data-driven systems analysis, causal relationships between complex molecular processes and particular immunological phenotypes can be constructed. However, processes in tissues, organs, and the organism itself (so-called higher level processes) also control and regulate the molecular (lower level) processes. Reverse systems engineering approaches, which focus on the examination of the structure, dynamics and control of the immune system, can help to understand the construction principles of the immune system. Such integrative mechanistic models can properly describe, explain, and predict the behavior of the immune system in health and disease by combining both higher and lower level processes. Moving from molecular and cellular levels to a multiscale systems understanding requires the development of methodologies that integrate data from different biological levels into multiscale mechanistic models. In particular, 3D imaging techniques and 4D modeling of the spatiotemporal dynamics of immune processes within lymphoid tissues are central for such integrative approaches. Both dynamic and global organ imaging technologies will be instrumental in facilitating comprehensive multiscale systems immunology analyses as discussed in this review. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Characterising Dynamic Instability in High Water-Cut Oil-Water Flows Using High-Resolution Microwave Sensor Signals

    NASA Astrophysics Data System (ADS)

    Liu, Weixin; Jin, Ningde; Han, Yunfeng; Ma, Jing

    2018-06-01

    In the present study, multi-scale entropy algorithm was used to characterise the complex flow phenomena of turbulent droplets in high water-cut oil-water two-phase flow. First, we compared multi-scale weighted permutation entropy (MWPE), multi-scale approximate entropy (MAE), multi-scale sample entropy (MSE) and multi-scale complexity measure (MCM) for typical nonlinear systems. The results show that MWPE presents satisfied variability with scale and anti-noise ability. Accordingly, we conducted an experiment of vertical upward oil-water two-phase flow with high water-cut and collected the signals of a high-resolution microwave resonant sensor, based on which two indexes, the entropy rate and mean value of MWPE, were extracted. Besides, the effects of total flow rate and water-cut on these two indexes were analysed. Our researches show that MWPE is an effective method to uncover the dynamic instability of oil-water two-phase flow with high water-cut.

  1. Components for Atomistic-to-Continuum Multiscale Modeling of Flow in Micro- and Nanofluidic Systems

    DOE PAGES

    Adalsteinsson, Helgi; Debusschere, Bert J.; Long, Kevin R.; ...

    2008-01-01

    Micro- and nanofluidics pose a series of significant challenges for science-based modeling. Key among those are the wide separation of length- and timescales between interface phenomena and bulk flow and the spatially heterogeneous solution properties near solid-liquid interfaces. It is not uncommon for characteristic scales in these systems to span nine orders of magnitude from the atomic motions in particle dynamics up to evolution of mass transport at the macroscale level, making explicit particle models intractable for all but the simplest systems. Recently, atomistic-to-continuum (A2C) multiscale simulations have gained a lot of interest as an approach to rigorously handle particle-levelmore » dynamics while also tracking evolution of large-scale macroscale behavior. While these methods are clearly not applicable to all classes of simulations, they are finding traction in systems in which tight-binding, and physically important, dynamics at system interfaces have complex effects on the slower-evolving large-scale evolution of the surrounding medium. These conditions allow decomposition of the simulation into discrete domains, either spatially or temporally. In this paper, we describe how features of domain decomposed simulation systems can be harnessed to yield flexible and efficient software for multiscale simulations of electric field-driven micro- and nanofluidics.« less

  2. Multiscale Macromolecular Simulation: Role of Evolving Ensembles

    PubMed Central

    Singharoy, A.; Joshi, H.; Ortoleva, P.J.

    2013-01-01

    Multiscale analysis provides an algorithm for the efficient simulation of macromolecular assemblies. This algorithm involves the coevolution of a quasiequilibrium probability density of atomic configurations and the Langevin dynamics of spatial coarse-grained variables denoted order parameters (OPs) characterizing nanoscale system features. In practice, implementation of the probability density involves the generation of constant OP ensembles of atomic configurations. Such ensembles are used to construct thermal forces and diffusion factors that mediate the stochastic OP dynamics. Generation of all-atom ensembles at every Langevin timestep is computationally expensive. Here, multiscale computation for macromolecular systems is made more efficient by a method that self-consistently folds in ensembles of all-atom configurations constructed in an earlier step, history, of the Langevin evolution. This procedure accounts for the temporal evolution of these ensembles, accurately providing thermal forces and diffusions. It is shown that efficiency and accuracy of the OP-based simulations is increased via the integration of this historical information. Accuracy improves with the square root of the number of historical timesteps included in the calculation. As a result, CPU usage can be decreased by a factor of 3-8 without loss of accuracy. The algorithm is implemented into our existing force-field based multiscale simulation platform and demonstrated via the structural dynamics of viral capsomers. PMID:22978601

  3. Dynamical mechanism in aero-engine gas path system using minimum spanning tree and detrended cross-correlation analysis

    NASA Astrophysics Data System (ADS)

    Dong, Keqiang; Zhang, Hong; Gao, You

    2017-01-01

    Identifying the mutual interaction in aero-engine gas path system is a crucial problem that facilitates the understanding of emerging structures in complex system. By employing the multiscale multifractal detrended cross-correlation analysis method to aero-engine gas path system, the cross-correlation characteristics between gas path system parameters are established. Further, we apply multiscale multifractal detrended cross-correlation distance matrix and minimum spanning tree to investigate the mutual interactions of gas path variables. The results can infer that the low-spool rotor speed (N1) and engine pressure ratio (EPR) are main gas path parameters. The application of proposed method contributes to promote our understanding of the internal mechanisms and structures of aero-engine dynamics.

  4. Multiscale agent-based cancer modeling.

    PubMed

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

    2009-04-01

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

  5. The Discontinuous Galerkin Method for the Multiscale Modeling of Dynamics of Crystalline Solids

    DTIC Science & Technology

    2007-08-26

    number. 1. REPORT DATE 26 AUG 2007 2 . REPORT TYPE 3. DATES COVERED 00-00-2007 to 00-00-2007 4. TITLE AND SUBTITLE The Discontinuous Galerkin...Dynamics method (MAAD) [ 2 ], the bridging scale method [47], the bridging domain methods [48], the heterogeneous multiscale method (HMM) [23, 36, 24], and...method consists of three components, 1. a macro solver for the continuum model, 2 . a micro solver to equilibrate the atomistic system locally to the appro

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

    NASA Astrophysics Data System (ADS)

    Naimark, O.

    2017-09-01

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

  7. Multiscale Granger causality

    NASA Astrophysics Data System (ADS)

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

    2017-10-01

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

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

    Makarov, Pavel V., E-mail: pvm@ispms.tsc.ru

    An evolutionary approach to earthquake development is proposed. A medium under loading is treated as a multiscale nonlinear dynamic system. Its failure involves a number of stages typical of any dynamic system: dynamic chaos, self-organized criticality, and global stability loss in the final stage of its evolution. In the latter stage, the system evolves in a blow-up mode accompanied by catastrophic superfast movements of the elements of this geomedium.

  9. A Multiscale Model for Virus Capsid Dynamics

    PubMed Central

    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. Suppression of chaos at slow variables by rapidly mixing fast dynamics

    NASA Astrophysics Data System (ADS)

    Abramov, R.

    2012-04-01

    One of the key questions about chaotic multiscale systems is how the fast dynamics affects chaos at the slow variables, and, therefore, impacts uncertainty and predictability of the slow dynamics. Here we demonstrate that the linear slow-fast coupling with the total energy conservation property promotes the suppression of chaos at the slow variables through the rapid mixing at the fast variables, both theoretically and through numerical simulations. A suitable mathematical framework is developed, connecting the slow dynamics on the tangent subspaces to the infinite-time linear response of the mean state to a constant external forcing at the fast variables. Additionally, it is shown that the uncoupled dynamics for the slow variables may remain chaotic while the complete multiscale system loses chaos and becomes completely predictable at the slow variables through increasing chaos and turbulence at the fast variables. This result contradicts the common sense intuition, where, naturally, one would think that coupling a slow weakly chaotic system with another much faster and much stronger mixing system would result in general increase of chaos at the slow variables.

  11. 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.

  12. 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

  13. Multiscale Cloud System Modeling

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Moncrieff, Mitchell W.

    2009-01-01

    The central theme of this paper is to describe how cloud system resolving models (CRMs) of grid spacing approximately 1 km have been applied to various important problems in atmospheric science across a wide range of spatial and temporal scales and how these applications relate to other modeling approaches. A long-standing problem concerns the representation of organized precipitating convective cloud systems in weather and climate models. Since CRMs resolve the mesoscale to large scales of motion (i.e., 10 km to global) they explicitly address the cloud system problem. By explicitly representing organized convection, CRMs bypass restrictive assumptions associated with convective parameterization such as the scale gap between cumulus and large-scale motion. Dynamical models provide insight into the physical mechanisms involved with scale interaction and convective organization. Multiscale CRMs simulate convective cloud systems in computational domains up to global and have been applied in place of contemporary convective parameterizations in global models. Multiscale CRMs pose a new challenge for model validation, which is met in an integrated approach involving CRMs, operational prediction systems, observational measurements, and dynamical models in a new international project: the Year of Tropical Convection, which has an emphasis on organized tropical convection and its global effects.

  14. Multiscale modeling of sickle anemia blood blow by Dissipative Partice Dynamics

    NASA Astrophysics Data System (ADS)

    Lei, Huan; Caswell, Bruce; Karniadakis, George

    2011-11-01

    A multi-scale model for sickle red blood cell is developed based on Dissipative Particle Dynamics (DPD). Different cell morphologies (sickle, granular, elongated shapes) typically observed in in vitro and in vivo are constructed and the deviations from the biconcave shape is quantified by the Asphericity and Elliptical shape factors. The rheology of sickle blood is studied in both shear and pipe flow systems. The flow resistance obtained from both systems exhibits a larger value than the healthy blood flow due to the abnormal cell properties. However, the vaso-occulusion phenomenon, reported in a recent microfluid experiment, is not observed in the pipe flow system unless the adhesive interactions between sickle blood cells and endothelium properly introduced into the model.

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

    PubMed

    Hamdi, Mustapha

    2009-12-02

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

  16. Imaging multi-scale dynamics in vivo with spiral volumetric optoacoustic tomography

    NASA Astrophysics Data System (ADS)

    Deán-Ben, X. Luís.; Fehm, Thomas F.; Ford, Steven J.; Gottschalk, Sven; Razansky, Daniel

    2017-03-01

    Imaging dynamics in living organisms is essential for the understanding of biological complexity. While multiple imaging modalities are often required to cover both microscopic and macroscopic spatial scales, dynamic phenomena may also extend over different temporal scales, necessitating the use of different imaging technologies based on the trade-off between temporal resolution and effective field of view. Optoacoustic (photoacoustic) imaging has been shown to offer the exclusive capability to link multiple spatial scales ranging from organelles to entire organs of small animals. Yet, efficient visualization of multi-scale dynamics remained difficult with state-of-the-art systems due to inefficient trade-offs between image acquisition and effective field of view. Herein, we introduce a spiral volumetric optoacoustic tomography (SVOT) technique that provides spectrally-enriched high-resolution optical absorption contrast across multiple spatio-temporal scales. We demonstrate that SVOT can be used to monitor various in vivo dynamics, from video-rate volumetric visualization of cardiac-associated motion in whole organs to high-resolution imaging of pharmacokinetics in larger regions. The multi-scale dynamic imaging capability thus emerges as a powerful and unique feature of the optoacoustic technology that adds to the multiple advantages of this technology for structural, functional and molecular imaging.

  17. Combining Coarse-Grained Protein Models with Replica-Exchange All-Atom Molecular Dynamics

    PubMed Central

    Wabik, Jacek; Kmiecik, Sebastian; Gront, Dominik; Kouza, Maksim; Koliński, Andrzej

    2013-01-01

    We describe a combination of all-atom simulations with CABS, a well-established coarse-grained protein modeling tool, into a single multiscale protocol. The simulation method has been tested on the C-terminal beta hairpin of protein G, a model system of protein folding. After reconstructing atomistic details, conformations derived from the CABS simulation were subjected to replica-exchange molecular dynamics simulations with OPLS-AA and AMBER99sb force fields in explicit solvent. Such a combination accelerates system convergence several times in comparison with all-atom simulations starting from the extended chain conformation, demonstrated by the analysis of melting curves, the number of native-like conformations as a function of time and secondary structure propagation. The results strongly suggest that the proposed multiscale method could be an efficient and accurate tool for high-resolution studies of protein folding dynamics in larger systems. PMID:23665897

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

    PubMed

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

    2015-02-01

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

  19. All-Atom Multiscale Molecular Dynamics Theory and Simulation of Self-Assembly, Energy Transfer and Structural Transition in Nanosystems

    NASA Astrophysics Data System (ADS)

    Espinosa Duran, John Michael

    The study of nanosystems and their emergent properties requires the development of multiscale computational models, theories and methods that preserve atomic and femtosecond resolution, to reveal details that cannot be resolved experimentally today. Considering this, three long time scale phenomena were studied using molecular dynamics and multiscale methods: self-assembly of organic molecules on graphite, energy transfer in nanosystems, and structural transition in vault nanoparticles. Molecular dynamics simulations of the self-assembly of alkoxybenzonitriles with different tail lengths on graphite were performed to learn about intermolecular interactions and phases exhibited by self-organized materials. This is important for the design of ordered self-assembled organic photovoltaic materials with greater efficiency than the disordered blends. Simulations revealed surface dynamical behaviors that cannot be resolved experimentally today due to the lack of spatiotemporal resolution. Atom-resolved structures predicted by simulations agreed with scanning tunneling microscopy images and unit cell measurements. Then, a multiscale theory based on the energy density as a field variable is developed to study energy transfer in nanoscale systems. For applications like photothermal microscopy or cancer phototherapy is required to understand how the energy is transferred to/from nanosystems. This multiscale theory could be applied in this context and here is tested for cubic nanoparticles immersed in water for energy being transferred to/from the nanoparticle. The theory predicts the energy transfer dynamics and reveals phenomena that cannot be described by current phenomenological theories. Finally, temperature-triggered structural transitions were revealed for vault nanoparticles using molecular dynamics and multiscale simulations. Vault is a football-shaped supramolecular assembly very distinct from the commonly observed icosahedral viruses. It has very promising applications in drug delivery and has been extensively studied experimentally. Sub-microsecond multiscale simulations at 310 K on the vault revealed the opening and closing of fractures near the shoulder while preserving the overall structure. This fracture mechanism could explain the uptake and release of small drugs while maintaining the overall structure. Higher temperature simulations show the generation of large fractures near the waist, which enables interaction of the external medium with the inner vault residues. Simulation results agreed with microscopy and spectroscopy measurements, and revealed new structures and mechanisms.

  20. Coupling of ab initio density functional theory and molecular dynamics for the multiscale modeling of carbon nanotubes

    NASA Astrophysics Data System (ADS)

    Ng, T. Y.; Yeak, S. H.; Liew, K. M.

    2008-02-01

    A multiscale technique is developed that couples empirical molecular dynamics (MD) and ab initio density functional theory (DFT). An overlap handshaking region between the empirical MD and ab initio DFT regions is formulated and the interaction forces between the carbon atoms are calculated based on the second-generation reactive empirical bond order potential, the long-range Lennard-Jones potential as well as the quantum-mechanical DFT derived forces. A density of point algorithm is also developed to track all interatomic distances in the system, and to activate and establish the DFT and handshaking regions. Through parallel computing, this multiscale method is used here to study the dynamic behavior of single-walled carbon nanotubes (SWCNTs) under asymmetrical axial compression. The detection of sideways buckling due to the asymmetrical axial compression is reported and discussed. It is noted from this study on SWCNTs that the MD results may be stiffer compared to those with electron density considerations, i.e. first-principle ab initio methods.

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

    PubMed Central

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

    2012-01-01

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

  2. Nonlinear dynamics of the complex multi-scale network

    NASA Astrophysics Data System (ADS)

    Makarov, Vladimir V.; Kirsanov, Daniil; Goremyko, Mikhail; Andreev, Andrey; Hramov, Alexander E.

    2018-04-01

    In this paper, we study the complex multi-scale network of nonlocally coupled oscillators for the appearance of chimera states. Chimera is a special state in which, in addition to the asynchronous cluster, there are also completely synchronous parts in the system. We show that the increase of nodes in subgroups leads to the destruction of the synchronous interaction within the common ring and to the narrowing of the chimera region.

  3. Multiscale Particle-Based Modeling of Flowing Platelets in Blood Plasma Using Dissipative Particle Dynamics and Coarse Grained Molecular Dynamics

    PubMed Central

    Zhang, Peng; Gao, Chao; Zhang, Na; Slepian, Marvin J.; Deng, Yuefan; Bluestein, Danny

    2014-01-01

    We developed a multiscale particle-based model of platelets, to study the transport dynamics of shear stresses between the surrounding fluid and the platelet membrane. This model facilitates a more accurate prediction of the activation potential of platelets by viscous shear stresses - one of the major mechanisms leading to thrombus formation in cardiovascular diseases and in prosthetic cardiovascular devices. The interface of the model couples coarse-grained molecular dynamics (CGMD) with dissipative particle dynamics (DPD). The CGMD handles individual platelets while the DPD models the macroscopic transport of blood plasma in vessels. A hybrid force field is formulated for establishing a functional interface between the platelet membrane and the surrounding fluid, in which the microstructural changes of platelets may respond to the extracellular viscous shear stresses transferred to them. The interaction between the two systems preserves dynamic properties of the flowing platelets, such as the flipping motion. Using this multiscale particle-based approach, we have further studied the effects of the platelet elastic modulus by comparing the action of the flow-induced shear stresses on rigid and deformable platelet models. The results indicate that neglecting the platelet deformability may overestimate the stress on the platelet membrane, which in turn may lead to erroneous predictions of the platelet activation under viscous shear flow conditions. This particle-based fluid-structure interaction multiscale model offers for the first time a computationally feasible approach for simulating deformable platelets interacting with viscous blood flow, aimed at predicting flow induced platelet activation by using a highly resolved mapping of the stress distribution on the platelet membrane under dynamic flow conditions. PMID:25530818

  4. A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system

    PubMed Central

    Li, Xin; Liu, Shaomin; Xiao, Qin; Ma, Mingguo; Jin, Rui; Che, Tao; Wang, Weizhen; Hu, Xiaoli; Xu, Ziwei; Wen, Jianguang; Wang, Liangxu

    2017-01-01

    We introduce a multiscale dataset obtained from Heihe Watershed Allied Telemetry Experimental Research (HiWATER) in an oasis-desert area in 2012. Upscaling of eco-hydrological processes on a heterogeneous surface is a grand challenge. Progress in this field is hindered by the poor availability of multiscale observations. HiWATER is an experiment designed to address this challenge through instrumentation on hierarchically nested scales to obtain multiscale and multidisciplinary data. The HiWATER observation system consists of a flux observation matrix of eddy covariance towers, large aperture scintillometers, and automatic meteorological stations; an eco-hydrological sensor network of soil moisture and leaf area index; hyper-resolution airborne remote sensing using LiDAR, imaging spectrometer, multi-angle thermal imager, and L-band microwave radiometer; and synchronical ground measurements of vegetation dynamics, and photosynthesis processes. All observational data were carefully quality controlled throughout sensor calibration, data collection, data processing, and datasets generation. The data are freely available at figshare and the Cold and Arid Regions Science Data Centre. The data should be useful for elucidating multiscale eco-hydrological processes and developing upscaling methods. PMID:28654086

  5. Multiscale analysis of heart rate dynamics: entropy and time irreversibility measures.

    PubMed

    Costa, Madalena D; Peng, Chung-Kang; Goldberger, Ary L

    2008-06-01

    Cardiovascular signals are largely analyzed using traditional time and frequency domain measures. However, such measures fail to account for important properties related to multiscale organization and non-equilibrium dynamics. The complementary role of conventional signal analysis methods and emerging multiscale techniques, is, therefore, an important frontier area of investigation. The key finding of this presentation is that two recently developed multiscale computational tools--multiscale entropy and multiscale time irreversibility--are able to extract information from cardiac interbeat interval time series not contained in traditional methods based on mean, variance or Fourier spectrum (two-point correlation) techniques. These new methods, with careful attention to their limitations, may be useful in diagnostics, risk stratification and detection of toxicity of cardiac drugs.

  6. Multiscale Analysis of Heart Rate Dynamics: Entropy and Time Irreversibility Measures

    PubMed Central

    Peng, Chung-Kang; Goldberger, Ary L.

    2016-01-01

    Cardiovascular signals are largely analyzed using traditional time and frequency domain measures. However, such measures fail to account for important properties related to multiscale organization and nonequilibrium dynamics. The complementary role of conventional signal analysis methods and emerging multiscale techniques, is, therefore, an important frontier area of investigation. The key finding of this presentation is that two recently developed multiscale computational tools— multiscale entropy and multiscale time irreversibility—are able to extract information from cardiac interbeat interval time series not contained in traditional methods based on mean, variance or Fourier spectrum (two-point correlation) techniques. These new methods, with careful attention to their limitations, may be useful in diagnostics, risk stratification and detection of toxicity of cardiac drugs. PMID:18172763

  7. Constrained approximation of effective generators for multiscale stochastic reaction networks and application to conditioned path sampling

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

    Cotter, Simon L., E-mail: simon.cotter@manchester.ac.uk

    2016-10-15

    Efficient analysis and simulation of multiscale stochastic systems of chemical kinetics is an ongoing area for research, and is the source of many theoretical and computational challenges. In this paper, we present a significant improvement to the constrained approach, which is a method for computing effective dynamics of slowly changing quantities in these systems, but which does not rely on the quasi-steady-state assumption (QSSA). The QSSA can cause errors in the estimation of effective dynamics for systems where the difference in timescales between the “fast” and “slow” variables is not so pronounced. This new application of the constrained approach allowsmore » us to compute the effective generator of the slow variables, without the need for expensive stochastic simulations. This is achieved by finding the null space of the generator of the constrained system. For complex systems where this is not possible, or where the constrained subsystem is itself multiscale, the constrained approach can then be applied iteratively. This results in breaking the problem down into finding the solutions to many small eigenvalue problems, which can be efficiently solved using standard methods. Since this methodology does not rely on the quasi steady-state assumption, the effective dynamics that are approximated are highly accurate, and in the case of systems with only monomolecular reactions, are exact. We will demonstrate this with some numerics, and also use the effective generators to sample paths of the slow variables which are conditioned on their endpoints, a task which would be computationally intractable for the generator of the full system.« less

  8. Multiscale Molecular Dynamics Model for Heterogeneous Charged Systems

    NASA Astrophysics Data System (ADS)

    Stanton, L. G.; Glosli, J. N.; Murillo, M. S.

    2018-04-01

    Modeling matter across large length scales and timescales using molecular dynamics simulations poses significant challenges. These challenges are typically addressed through the use of precomputed pair potentials that depend on thermodynamic properties like temperature and density; however, many scenarios of interest involve spatiotemporal variations in these properties, and such variations can violate assumptions made in constructing these potentials, thus precluding their use. In particular, when a system is strongly heterogeneous, most of the usual simplifying assumptions (e.g., spherical potentials) do not apply. Here, we present a multiscale approach to orbital-free density functional theory molecular dynamics (OFDFT-MD) simulations that bridges atomic, interionic, and continuum length scales to allow for variations in hydrodynamic quantities in a consistent way. Our multiscale approach enables simulations on the order of micron length scales and 10's of picosecond timescales, which exceeds current OFDFT-MD simulations by many orders of magnitude. This new capability is then used to study the heterogeneous, nonequilibrium dynamics of a heated interface characteristic of an inertial-confinement-fusion capsule containing a plastic ablator near a fuel layer composed of deuterium-tritium ice. At these scales, fundamental assumptions of continuum models are explored; features such as the separation of the momentum fields among the species and strong hydrogen jetting from the plastic into the fuel region are observed, which had previously not been seen in hydrodynamic simulations.

  9. A combined molecular dynamics/micromechanics/finite element approach for multiscale constitutive modeling of nanocomposites with interface effects

    NASA Astrophysics Data System (ADS)

    Yang, B. J.; Shin, H.; Lee, H. K.; Kim, H.

    2013-12-01

    We introduce a multiscale framework based on molecular dynamic (MD) simulation, micromechanics, and finite element method (FEM). A micromechanical model, which considers influences of the interface properties, nanoparticle (NP) size, and microcracks, is developed. Then, we perform MD simulations to characterize the mechanical properties of the nanocomposite system (silica/nylon 6) with varying volume fraction and size of NPs. By comparing the MD with micromechanics results, intrinsic physical properties at interfacial region are derived. Finally, we implement the developed model in the FEM code with the derived interfacial parameters, and predict the mechanical behavior of the nanocomposite at the macroscopic scale.

  10. Multiscale Analysis of Time Irreversibility Based on Phase-Space Reconstruction and Horizontal Visibility Graph Approach

    NASA Astrophysics Data System (ADS)

    Zhang, Yongping; Shang, Pengjian; Xiong, Hui; Xia, Jianan

    Time irreversibility is an important property of nonequilibrium dynamic systems. A visibility graph approach was recently proposed, and this approach is generally effective to measure time irreversibility of time series. However, its result may be unreliable when dealing with high-dimensional systems. In this work, we consider the joint concept of time irreversibility and adopt the phase-space reconstruction technique to improve this visibility graph approach. Compared with the previous approach, the improved approach gives a more accurate estimate for the irreversibility of time series, and is more effective to distinguish irreversible and reversible stochastic processes. We also use this approach to extract the multiscale irreversibility to account for the multiple inherent dynamics of time series. Finally, we apply the approach to detect the multiscale irreversibility of financial time series, and succeed to distinguish the time of financial crisis and the plateau. In addition, Asian stock indexes away from other indexes are clearly visible in higher time scales. Simulations and real data support the effectiveness of the improved approach when detecting time irreversibility.

  11. A preliminary investigation of the growth of an aneurysm with a multiscale monolithic Fluid-Structure interaction solver

    NASA Astrophysics Data System (ADS)

    Cerroni, D.; Manservisi, S.; Pozzetti, G.

    2015-11-01

    In this work we investigate the potentialities of multi-scale engineering techniques to approach complex problems related to biomedical and biological fields. In particular we study the interaction between blood and blood vessel focusing on the presence of an aneurysm. The study of each component of the cardiovascular system is very difficult due to the fact that the movement of the fluid and solid is determined by the rest of system through dynamical boundary conditions. The use of multi-scale techniques allows us to investigate the effect of the whole loop on the aneurysm dynamic. A three-dimensional fluid-structure interaction model for the aneurysm is developed and coupled to a mono-dimensional one for the remaining part of the cardiovascular system, where a point zero-dimensional model for the heart is provided. In this manner it is possible to achieve rigorous and quantitative investigations of the cardiovascular disease without loosing the system dynamic. In order to study this biomedical problem we use a monolithic fluid-structure interaction (FSI) model where the fluid and solid equations are solved together. The use of a monolithic solver allows us to handle the convergence issues caused by large deformations. By using this monolithic approach different solid and fluid regions are treated as a single continuum and the interface conditions are automatically taken into account. In this way the iterative process characteristic of the commonly used segregated approach, it is not needed any more.

  12. Time irreversibility of financial time series based on higher moments and multiscale Kullback-Leibler divergence

    NASA Astrophysics Data System (ADS)

    Li, Jinyang; Shang, Pengjian

    2018-07-01

    Irreversibility is an important property of time series. In this paper, we propose the higher moments and multiscale Kullback-Leibler divergence to analyze time series irreversibility. The higher moments Kullback-Leibler divergence (HMKLD) can amplify irreversibility and make the irreversibility variation more obvious. Therefore, many time series whose irreversibility is hard to be found are also able to show the variations. We employ simulated data and financial stock data to test and verify this method, and find that HMKLD of stock data is growing in the form of fluctuations. As for multiscale Kullback-Leibler divergence (MKLD), it is very complex in the dynamic system, so that exploring the law of simulation and stock system is difficult. In conventional multiscale entropy method, the coarse-graining process is non-overlapping, however we apply a different coarse-graining process and obtain a surprising discovery. The result shows when the scales are 4 and 5, their entropy is nearly similar, which demonstrates MKLD is efficient to display characteristics of time series irreversibility.

  13. Multiscale simulations of patchy particle systems combining Molecular Dynamics, Path Sampling and Green's Function Reaction Dynamics

    NASA Astrophysics Data System (ADS)

    Bolhuis, Peter

    Important reaction-diffusion processes, such as biochemical networks in living cells, or self-assembling soft matter, span many orders in length and time scales. In these systems, the reactants' spatial dynamics at mesoscopic length and time scales of microns and seconds is coupled to the reactions between the molecules at microscopic length and time scales of nanometers and milliseconds. This wide range of length and time scales makes these systems notoriously difficult to simulate. While mean-field rate equations cannot describe such processes, the mesoscopic Green's Function Reaction Dynamics (GFRD) method enables efficient simulation at the particle level provided the microscopic dynamics can be integrated out. Yet, many processes exhibit non-trivial microscopic dynamics that can qualitatively change the macroscopic behavior, calling for an atomistic, microscopic description. The recently developed multiscale Molecular Dynamics Green's Function Reaction Dynamics (MD-GFRD) approach combines GFRD for simulating the system at the mesocopic scale where particles are far apart, with microscopic Molecular (or Brownian) Dynamics, for simulating the system at the microscopic scale where reactants are in close proximity. The association and dissociation of particles are treated with rare event path sampling techniques. I will illustrate the efficiency of this method for patchy particle systems. Replacing the microscopic regime with a Markov State Model avoids the microscopic regime completely. The MSM is then pre-computed using advanced path-sampling techniques such as multistate transition interface sampling. I illustrate this approach on patchy particle systems that show multiple modes of binding. MD-GFRD is generic, and can be used to efficiently simulate reaction-diffusion systems at the particle level, including the orientational dynamics, opening up the possibility for large-scale simulations of e.g. protein signaling networks.

  14. Multi-Scale Scattering Transform in Music Similarity Measuring

    NASA Astrophysics Data System (ADS)

    Wang, Ruobai

    Scattering transform is a Mel-frequency spectrum based, time-deformation stable method, which can be used in evaluating music similarity. Compared with Dynamic time warping, it has better performance in detecting similar audio signals under local time-frequency deformation. Multi-scale scattering means to combine scattering transforms of different window lengths. This paper argues that, multi-scale scattering transform is a good alternative of dynamic time warping in music similarity measuring. We tested the performance of multi-scale scattering transform against other popular methods, with data designed to represent different conditions.

  15. Dynamics of Oceanic Motions

    DTIC Science & Technology

    1997-09-30

    research is multiscale , interdisciplinary and generic. The methods are applicable to an arbitrary region of the coastal and/or deep ocean and across the...dynamics. OBJECTIVES General objectives are: (I) To determine for the coastal and/or coupled deep ocean the multiscale processes which occur: i) in...Straits and the eastern basin; iii) extension and application of our balance of terms scheme (EVA) to multiscale , interdisciplinary fields with data

  16. A FRAMEWORK FOR FINE-SCALE COMPUTATIONAL FLUID DYNAMICS AIR QUALITY MODELING AND ANALYSIS

    EPA Science Inventory

    This paper discusses a framework for fine-scale CFD modeling that may be developed to complement the present Community Multi-scale Air Quality (CMAQ) modeling system which itself is a computational fluid dynamics model. A goal of this presentation is to stimulate discussions on w...

  17. A Multiscale Closed-Loop Cardiovascular Model, with Applications to Heart Pacing and Hemorrhage

    NASA Astrophysics Data System (ADS)

    Canuto, Daniel; Eldredge, Jeff; Chong, Kwitae; Benharash, Peyman; Dutson, Erik

    2017-11-01

    A computational tool is developed for simulating the dynamic response of the human cardiovascular system to various stressors and injuries. The tool couples zero-dimensional models of the heart, pulmonary vasculature, and peripheral vasculature to one-dimensional models of the major systemic arteries. To simulate autonomic response, this multiscale circulatory model is integrated with a feedback model of the baroreflex, allowing control of heart rate, cardiac contractility, and peripheral impedance. The performance of the tool is demonstrated in two scenarios: increasing heart rate by stimulating the sympathetic nervous system, and an acute 10 percent hemorrhage from the left femoral artery.

  18. Model reduction of multiscale chemical langevin equations: a numerical case study.

    PubMed

    Sotiropoulos, Vassilios; Contou-Carrere, Marie-Nathalie; Daoutidis, Prodromos; Kaznessis, Yiannis N

    2009-01-01

    Two very important characteristics of biological reaction networks need to be considered carefully when modeling these systems. First, models must account for the inherent probabilistic nature of systems far from the thermodynamic limit. Often, biological systems cannot be modeled with traditional continuous-deterministic models. Second, models must take into consideration the disparate spectrum of time scales observed in biological phenomena, such as slow transcription events and fast dimerization reactions. In the last decade, significant efforts have been expended on the development of stochastic chemical kinetics models to capture the dynamics of biomolecular systems, and on the development of robust multiscale algorithms, able to handle stiffness. In this paper, the focus is on the dynamics of reaction sets governed by stiff chemical Langevin equations, i.e., stiff stochastic differential equations. These are particularly challenging systems to model, requiring prohibitively small integration step sizes. We describe and illustrate the application of a semianalytical reduction framework for chemical Langevin equations that results in significant gains in computational cost.

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

    NASA Astrophysics Data System (ADS)

    Yan, Jihong; Guo, Chaozhong; Wang, Xing

    2011-05-01

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

  20. Multiscale Modeling of Multiphase Fluid Flow

    DTIC Science & Technology

    2016-08-01

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

  1. Multiscale multifractal DCCA and complexity behaviors of return intervals for Potts price model

    NASA Astrophysics Data System (ADS)

    Wang, Jie; Wang, Jun; Stanley, H. Eugene

    2018-02-01

    To investigate the characteristics of extreme events in financial markets and the corresponding return intervals among these events, we use a Potts dynamic system to construct a random financial time series model of the attitudes of market traders. We use multiscale multifractal detrended cross-correlation analysis (MM-DCCA) and Lempel-Ziv complexity (LZC) perform numerical research of the return intervals for two significant China's stock market indices and for the proposed model. The new MM-DCCA method is based on the Hurst surface and provides more interpretable cross-correlations of the dynamic mechanism between different return interval series. We scale the LZC method with different exponents to illustrate the complexity of return intervals in different scales. Empirical studies indicate that the proposed return intervals from the Potts system and the real stock market indices hold similar statistical properties.

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

    Ortoleva, Peter J.

    Illustrative embodiments of systems and methods for the deductive multiscale simulation of macromolecules are disclosed. In one illustrative embodiment, a deductive multiscale simulation method may include (i) constructing a set of order parameters that model one or more structural characteristics of a macromolecule, (ii) simulating an ensemble of atomistic configurations for the macromolecule using instantaneous values of the set of order parameters, (iii) simulating thermal-average forces and diffusivities for the ensemble of atomistic configurations, and (iv) evolving the set of order parameters via Langevin dynamics using the thermal-average forces and diffusivities.

  3. Modeling Impact-induced Failure of Polysilicon MEMS: A Multi-scale Approach.

    PubMed

    Mariani, Stefano; Ghisi, Aldo; Corigliano, Alberto; Zerbini, Sarah

    2009-01-01

    Failure of packaged polysilicon micro-electro-mechanical systems (MEMS) subjected to impacts involves phenomena occurring at several length-scales. In this paper we present a multi-scale finite element approach to properly allow for: (i) the propagation of stress waves inside the package; (ii) the dynamics of the whole MEMS; (iii) the spreading of micro-cracking in the failing part(s) of the sensor. Through Monte Carlo simulations, some effects of polysilicon micro-structure on the failure mode are elucidated.

  4. Good coupling for the multiscale patch scheme on systems with microscale heterogeneity

    NASA Astrophysics Data System (ADS)

    Bunder, J. E.; Roberts, A. J.; Kevrekidis, I. G.

    2017-05-01

    Computational simulation of microscale detailed systems is frequently only feasible over spatial domains much smaller than the macroscale of interest. The 'equation-free' methodology couples many small patches of microscale computations across space to empower efficient computational simulation over macroscale domains of interest. Motivated by molecular or agent simulations, we analyse the performance of various coupling schemes for patches when the microscale is inherently 'rough'. As a canonical problem in this universality class, we systematically analyse the case of heterogeneous diffusion on a lattice. Computer algebra explores how the dynamics of coupled patches predict the large scale emergent macroscale dynamics of the computational scheme. We determine good design for the coupling of patches by comparing the macroscale predictions from patch dynamics with the emergent macroscale on the entire domain, thus minimising the computational error of the multiscale modelling. The minimal error on the macroscale is obtained when the coupling utilises averaging regions which are between a third and a half of the patch. Moreover, when the symmetry of the inter-patch coupling matches that of the underlying microscale structure, patch dynamics predicts the desired macroscale dynamics to any specified order of error. The results confirm that the patch scheme is useful for macroscale computational simulation of a range of systems with microscale heterogeneity.

  5. Design of microcamera for field curvature and distortion correction in monocentric multiscale foveated imaging system

    NASA Astrophysics Data System (ADS)

    Wu, Xiongxiong; Wang, Xiaorui; Zhang, Jianlei; Yuan, Ying; Chen, Xiaoxiang

    2017-04-01

    To realize large field of view (FOV) and high-resolution dynamic gaze of the moving target, this paper proposes the monocentric multiscale foveated (MMF) imaging system based on monocentric multiscale design and foveated imaging. First we present the MMF imaging system concept. Then we analyze large field curvature and distortion of the secondary image when the spherical intermediate image produced by the primary monocentric objective lens is relayed by the microcameras. Further a type of zoom endoscope objective lens is selected as the initial structure and optimized to minimize the field curvature and distortion with ZEMAX optical design software. The simulation results show that the maximum field curvature in full field of view is below 0.25 mm and the maximum distortion in full field of view is below 0.6%, which can meet the requirements of the microcamera in the proposed MMF imaging system. In addition, a simple doublet is used to design the foveated imaging system. Results of the microcamera together with the foveated imager compose the results of the whole MMF imaging system.

  6. A coupling method for a cardiovascular simulation model which includes the Kalman filter.

    PubMed

    Hasegawa, Yuki; Shimayoshi, Takao; Amano, Akira; Matsuda, Tetsuya

    2012-01-01

    Multi-scale models of the cardiovascular system provide new insight that was unavailable with in vivo and in vitro experiments. For the cardiovascular system, multi-scale simulations provide a valuable perspective in analyzing the interaction of three phenomenons occurring at different spatial scales: circulatory hemodynamics, ventricular structural dynamics, and myocardial excitation-contraction. In order to simulate these interactions, multiscale cardiovascular simulation systems couple models that simulate different phenomena. However, coupling methods require a significant amount of calculation, since a system of non-linear equations must be solved for each timestep. Therefore, we proposed a coupling method which decreases the amount of calculation by using the Kalman filter. In our method, the Kalman filter calculates approximations for the solution to the system of non-linear equations at each timestep. The approximations are then used as initial values for solving the system of non-linear equations. The proposed method decreases the number of iterations required by 94.0% compared to the conventional strong coupling method. When compared with a smoothing spline predictor, the proposed method required 49.4% fewer iterations.

  7. Differential morphology and image processing.

    PubMed

    Maragos, P

    1996-01-01

    Image processing via mathematical morphology has traditionally used geometry to intuitively understand morphological signal operators and set or lattice algebra to analyze them in the space domain. We provide a unified view and analytic tools for morphological image processing that is based on ideas from differential calculus and dynamical systems. This includes ideas on using partial differential or difference equations (PDEs) to model distance propagation or nonlinear multiscale processes in images. We briefly review some nonlinear difference equations that implement discrete distance transforms and relate them to numerical solutions of the eikonal equation of optics. We also review some nonlinear PDEs that model the evolution of multiscale morphological operators and use morphological derivatives. Among the new ideas presented, we develop some general 2-D max/min-sum difference equations that model the space dynamics of 2-D morphological systems (including the distance computations) and some nonlinear signal transforms, called slope transforms, that can analyze these systems in a transform domain in ways conceptually similar to the application of Fourier transforms to linear systems. Thus, distance transforms are shown to be bandpass slope filters. We view the analysis of the multiscale morphological PDEs and of the eikonal PDE solved via weighted distance transforms as a unified area in nonlinear image processing, which we call differential morphology, and briefly discuss its potential applications to image processing and computer vision.

  8. 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.

  9. MMS at NRL

    NASA Image and Video Library

    2014-08-04

    NASA Administrator Charles Bolden listens to Magnetospheric Multiscale (MMS) Mission Project Manager Craig Tooley talk about the MMS mission outside of a Naval Research Laboratory cleanroom where one of four Magnetospheric Multiscale (MMS) spacecraft is currently undergoing testing, Monday, August 4, 2014, in Washington. The Magnetospheric Multiscale, or MMS, mission will study the mystery of how magnetic fields around Earth connect and disconnect, explosively releasing energy via a process known as magnetic reconnection. The four identical spacecraft are scheduled to launch in 2015 from Cape Canaveral and will orbit around Earth in varying formations through the dynamic magnetic system surrounding our planet to provide the first three-dimensional views of the magnetic reconnection process. The goal of the STP Program is to understand the fundamental physical processes of the space environment from the sun to Earth, other planets, and the extremes of the solar system boundary. Photo Credit: (NASA/Bill Ingalls)

  10. Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement

    PubMed Central

    Han, Zhenyu; Sun, Shouzheng; Fu, Hongya; Fu, Yunzhong

    2017-01-01

    Automated fiber placement (AFP) process includes a variety of energy forms and multi-scale effects. This contribution proposes a novel multi-scale low-entropy method aiming at optimizing processing parameters in an AFP process, where multi-scale effect, energy consumption, energy utilization efficiency and mechanical properties of micro-system could be taken into account synthetically. Taking a carbon fiber/epoxy prepreg as an example, mechanical properties of macro–meso–scale are obtained by Finite Element Method (FEM). A multi-scale energy transfer model is then established to input the macroscopic results into the microscopic system as its boundary condition, which can communicate with different scales. Furthermore, microscopic characteristics, mainly micro-scale adsorption energy, diffusion coefficient entropy–enthalpy values, are calculated under different processing parameters based on molecular dynamics method. Low-entropy region is then obtained in terms of the interrelation among entropy–enthalpy values, microscopic mechanical properties (interface adsorbability and matrix fluidity) and processing parameters to guarantee better fluidity, stronger adsorption, lower energy consumption and higher energy quality collaboratively. Finally, nine groups of experiments are carried out to verify the validity of the simulation results. The results show that the low-entropy optimization method can reduce void content effectively, and further improve the mechanical properties of laminates. PMID:28869520

  11. Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement.

    PubMed

    Han, Zhenyu; Sun, Shouzheng; Fu, Hongya; Fu, Yunzhong

    2017-09-03

    Automated fiber placement (AFP) process includes a variety of energy forms and multi-scale effects. This contribution proposes a novel multi-scale low-entropy method aiming at optimizing processing parameters in an AFP process, where multi-scale effect, energy consumption, energy utilization efficiency and mechanical properties of micro-system could be taken into account synthetically. Taking a carbon fiber/epoxy prepreg as an example, mechanical properties of macro-meso-scale are obtained by Finite Element Method (FEM). A multi-scale energy transfer model is then established to input the macroscopic results into the microscopic system as its boundary condition, which can communicate with different scales. Furthermore, microscopic characteristics, mainly micro-scale adsorption energy, diffusion coefficient entropy-enthalpy values, are calculated under different processing parameters based on molecular dynamics method. Low-entropy region is then obtained in terms of the interrelation among entropy-enthalpy values, microscopic mechanical properties (interface adsorbability and matrix fluidity) and processing parameters to guarantee better fluidity, stronger adsorption, lower energy consumption and higher energy quality collaboratively. Finally, nine groups of experiments are carried out to verify the validity of the simulation results. The results show that the low-entropy optimization method can reduce void content effectively, and further improve the mechanical properties of laminates.

  12. Multi-scale modeling of spin transport in organic semiconductors

    NASA Astrophysics Data System (ADS)

    Hemmatiyan, Shayan; Souza, Amaury; Kordt, Pascal; McNellis, Erik; Andrienko, Denis; Sinova, Jairo

    In this work, we present our theoretical framework to simulate simultaneously spin and charge transport in amorphous organic semiconductors. By combining several techniques e.g. molecular dynamics, density functional theory and kinetic Monte Carlo, we are be able to study spin transport in the presence of anisotropy, thermal effects, magnetic and electric field effects in a realistic morphologies of amorphous organic systems. We apply our multi-scale approach to investigate the spin transport in amorphous Alq3 (Tris(8-hydroxyquinolinato)aluminum) and address the underlying spin relaxation mechanism in this system as a function of temperature, bias voltage, magnetic field and sample thickness.

  13. Tone mapping infrared images using conditional filtering-based multi-scale retinex

    NASA Astrophysics Data System (ADS)

    Luo, Haibo; Xu, Lingyun; Hui, Bin; Chang, Zheng

    2015-10-01

    Tone mapping can be used to compress the dynamic range of the image data such that it can be fitted within the range of the reproduction media and human vision. The original infrared images that captured with infrared focal plane arrays (IFPA) are high dynamic images, so tone mapping infrared images is an important component in the infrared imaging systems, and it has become an active topic in recent years. In this paper, we present a tone mapping framework using multi-scale retinex. Firstly, a Conditional Gaussian Filter (CGF) was designed to suppress "halo" effect. Secondly, original infrared image is decomposed into a set of images that represent the mean of the image at different spatial resolutions by applying CGF of different scale. And then, a set of images that represent the multi-scale details of original image is produced by dividing the original image pointwise by the decomposed image. Thirdly, the final detail image is reconstructed by weighted sum of the multi-scale detail images together. Finally, histogram scaling and clipping is adopted to remove outliers and scale the detail image, 0.1% of the pixels are clipped at both extremities of the histogram. Experimental results show that the proposed algorithm efficiently increases the local contrast while preventing "halo" effect and provides a good rendition of visual effect.

  14. Variational coarse-graining procedure for dynamic homogenization

    NASA Astrophysics Data System (ADS)

    Liu, Chenchen; Reina, Celia

    2017-07-01

    We present a variational coarse-graining framework for heterogeneous media in the spirit of FE2 methods, that allows for a seamless transition from the traditional static scenario to dynamic loading conditions, while being applicable to general material behavior as well as to discrete or continuous representations of the material and its deformation, e.g., finite element discretizations or atomistic systems. The method automatically delivers the macroscopic equations of motion together with the generalization of Hill's averaging relations to the dynamic setting. These include the expression of the macroscopic stresses and linear momentum as a function of the microscopic fields. We further demonstrate with a proof of concept example, that the proposed theoretical framework can be used to perform multiscale numerical simulations. The results are compared with standard single-scale finite element simulations, showcasing the capability of the method to capture the dispersive nature of the medium in the range of frequencies permitted by the multiscale strategy.

  15. Final Technical Report: Mathematical Foundations for Uncertainty Quantification in Materials Design

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

    Plechac, Petr; Vlachos, Dionisios G.

    We developed path-wise information theory-based and goal-oriented sensitivity analysis and parameter identification methods for complex high-dimensional dynamics and in particular of non-equilibrium extended molecular systems. The combination of these novel methodologies provided the first methods in the literature which are capable to handle UQ questions for stochastic complex systems with some or all of the following features: (a) multi-scale stochastic models such as (bio)chemical reaction networks, with a very large number of parameters, (b) spatially distributed systems such as Kinetic Monte Carlo or Langevin Dynamics, (c) non-equilibrium processes typically associated with coupled physico-chemical mechanisms, driven boundary conditions, hybrid micro-macro systems,more » etc. A particular computational challenge arises in simulations of multi-scale reaction networks and molecular systems. Mathematical techniques were applied to in silico prediction of novel materials with emphasis on the effect of microstructure on model uncertainty quantification (UQ). We outline acceleration methods to make calculations of real chemistry feasible followed by two complementary tasks on structure optimization and microstructure-induced UQ.« less

  16. Capturing Multiscale Phenomena via Adaptive Mesh Refinement (AMR) in 2D and 3D Atmospheric Flows

    NASA Astrophysics Data System (ADS)

    Ferguson, J. O.; Jablonowski, C.; Johansen, H.; McCorquodale, P.; Ullrich, P. A.; Langhans, W.; Collins, W. D.

    2017-12-01

    Extreme atmospheric events such as tropical cyclones are inherently complex multiscale phenomena. Such phenomena are a challenge to simulate in conventional atmosphere models, which typically use rather coarse uniform-grid resolutions. To enable study of these systems, Adaptive Mesh Refinement (AMR) can provide sufficient local resolution by dynamically placing high-resolution grid patches selectively over user-defined features of interest, such as a developing cyclone, while limiting the total computational burden of requiring such high-resolution globally. This work explores the use of AMR with a high-order, non-hydrostatic, finite-volume dynamical core, which uses the Chombo AMR library to implement refinement in both space and time on a cubed-sphere grid. The characteristics of the AMR approach are demonstrated via a series of idealized 2D and 3D test cases designed to mimic atmospheric dynamics and multiscale flows. In particular, new shallow-water test cases with forcing mechanisms are introduced to mimic the strengthening of tropical cyclone-like vortices and to include simplified moisture and convection processes. The forced shallow-water experiments quantify the improvements gained from AMR grids, assess how well transient features are preserved across grid boundaries, and determine effective refinement criteria. In addition, results from idealized 3D test cases are shown to characterize the accuracy and stability of the non-hydrostatic 3D AMR dynamical core.

  17. Hierarchical Multiscale Modeling of Macromolecules and their Assemblies

    PubMed Central

    Ortoleva, P.; Singharoy, A.; Pankavich, S.

    2013-01-01

    Soft materials (e.g., enveloped viruses, liposomes, membranes and supercooled liquids) simultaneously deform or display collective behaviors, while undergoing atomic scale vibrations and collisions. While the multiple space-time character of such systems often makes traditional molecular dynamics simulation impractical, a multiscale approach has been presented that allows for long-time simulation with atomic detail based on the co-evolution of slowly-varying order parameters (OPs) with the quasi-equilibrium probability density of atomic configurations. However, this approach breaks down when the structural change is extreme, or when nearest-neighbor connectivity of atoms is not maintained. In the current study, a self-consistent approach is presented wherein OPs and a reference structure co-evolve slowly to yield long-time simulation for dynamical soft-matter phenomena such as structural transitions and self-assembly. The development begins with the Liouville equation for N classical atoms and an ansatz on the form of the associated N-atom probability density. Multiscale techniques are used to derive Langevin equations for the coupled OP-configurational dynamics. The net result is a set of equations for the coupled stochastic dynamics of the OPs and centers of mass of the subsystems that constitute a soft material body. The theory is based on an all-atom methodology and an interatomic force field, and therefore enables calibration-free simulations of soft matter, such as macromolecular assemblies. PMID:23671457

  18. 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.

  19. Dynamic evaluation of CMAQ part I: Separating the effects of changing emissions and changing meteorology on ozone levels between 2002 and 2005 in the eastern US

    EPA Science Inventory

    A dynamic evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.1 was conducted to evaluate the model's ability to predict changes in ozone levels between 2002 and 2005, a time period characterized by emission reductions associated with the EPA's N...

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

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

    Tim Schulze

    2012-11-01

    The general theme of this research has been to expand the capabilities of a simulation technique, Kinetic Monte Carlo (KMC) and apply it to study self-assembled nano-structures on epitaxial thin films. KMC simulates thin film growth and evolution by replacing the detailed dynamics of the system's evolution, which might otherwise be studied using molecular dynamics, with an appropriate stochastic process.

  1. A Generalized Hybrid Multiscale Modeling Approach for Flow and Reactive Transport in Porous Media

    NASA Astrophysics Data System (ADS)

    Yang, X.; Meng, X.; Tang, Y. H.; Guo, Z.; Karniadakis, G. E.

    2017-12-01

    Using emerging understanding of biological and environmental processes at fundamental scales to advance predictions of the larger system behavior requires the development of multiscale approaches, and there is strong interest in coupling models at different scales together in a hybrid multiscale simulation framework. A limited number of hybrid multiscale simulation methods have been developed for subsurface applications, mostly using application-specific approaches for model coupling. The proposed generalized hybrid multiscale approach is designed with minimal intrusiveness to the at-scale simulators (pre-selected) and provides a set of lightweight C++ scripts to manage a complex multiscale workflow utilizing a concurrent coupling approach. The workflow includes at-scale simulators (using the lattice-Boltzmann method, LBM, at the pore and Darcy scale, respectively), scripts for boundary treatment (coupling and kriging), and a multiscale universal interface (MUI) for data exchange. The current study aims to apply the generalized hybrid multiscale modeling approach to couple pore- and Darcy-scale models for flow and mixing-controlled reaction with precipitation/dissolution in heterogeneous porous media. The model domain is packed heterogeneously that the mixing front geometry is more complex and not known a priori. To address those challenges, the generalized hybrid multiscale modeling approach is further developed to 1) adaptively define the locations of pore-scale subdomains, 2) provide a suite of physical boundary coupling schemes and 3) consider the dynamic change of the pore structures due to mineral precipitation/dissolution. The results are validated and evaluated by comparing with single-scale simulations in terms of velocities, reactive concentrations and computing cost.

  2. Improving resolution of dynamic communities in human brain networks through targeted node removal

    PubMed Central

    Turner, Benjamin O.; Miller, Michael B.; Carlson, Jean M.

    2017-01-01

    Current approaches to dynamic community detection in complex networks can fail to identify multi-scale community structure, or to resolve key features of community dynamics. We propose a targeted node removal technique to improve the resolution of community detection. Using synthetic oscillator networks with well-defined “ground truth” communities, we quantify the community detection performance of a common modularity maximization algorithm. We show that the performance of the algorithm on communities of a given size deteriorates when these communities are embedded in multi-scale networks with communities of different sizes, compared to the performance in a single-scale network. We demonstrate that targeted node removal during community detection improves performance on multi-scale networks, particularly when removing the most functionally cohesive nodes. Applying this approach to network neuroscience, we compare dynamic functional brain networks derived from fMRI data taken during both repetitive single-task and varied multi-task experiments. After the removal of regions in visual cortex, the most coherent functional brain area during the tasks, community detection is better able to resolve known functional brain systems into communities. In addition, node removal enables the algorithm to distinguish clear differences in brain network dynamics between these experiments, revealing task-switching behavior that was not identified with the visual regions present in the network. These results indicate that targeted node removal can improve spatial and temporal resolution in community detection, and they demonstrate a promising approach for comparison of network dynamics between neuroscientific data sets with different resolution parameters. PMID:29261662

  3. A Kalman Filter for Mass Property and Thrust Identification of the Spin-Stabilized Magnetospheric Multiscale Formation

    NASA Technical Reports Server (NTRS)

    Queen, Steven Z.

    2015-01-01

    The Magnetospheric Multiscale (MMS) mission consists of four identically instrumented, spin-stabilized observatories, elliptically orbiting the Earth in a tetrahedron formation. For the operational success of the mission, on-board systems must be able to deliver high-precision orbital adjustment maneuvers. On MMS, this is accomplished using feedback from on-board star sensors in tandem with accelerometers whose measurements are dynamically corrected for errors associated with a spinning platform. In order to determine the required corrections to the measured acceleration, precise estimates of attitude, rate, and mass-properties are necessary. To this end, both an on-board and ground-based Multiplicative Extended Kalman Filter (MEKF) were formulated and implemented in order to estimate the dynamic and quasi-static properties of the spacecraft.

  4. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2015-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Hadden, 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.

  7. Quantifying complexity of financial short-term time series by composite multiscale entropy measure

    NASA Astrophysics Data System (ADS)

    Niu, Hongli; Wang, Jun

    2015-05-01

    It is significant to study the complexity of financial time series since the financial market is a complex evolved dynamic system. Multiscale entropy is a prevailing method used to quantify the complexity of a time series. Due to its less reliability of entropy estimation for short-term time series at large time scales, a modification method, the composite multiscale entropy, is applied to the financial market. To qualify its effectiveness, its applications in the synthetic white noise and 1 / f noise with different data lengths are reproduced first in the present paper. Then it is introduced for the first time to make a reliability test with two Chinese stock indices. After conducting on short-time return series, the CMSE method shows the advantages in reducing deviations of entropy estimation and demonstrates more stable and reliable results when compared with the conventional MSE algorithm. Finally, the composite multiscale entropy of six important stock indices from the world financial markets is investigated, and some useful and interesting empirical results are obtained.

  8. Multiscale structure of time series revealed by the monotony spectrum.

    PubMed

    Vamoş, Călin

    2017-03-01

    Observation of complex systems produces time series with specific dynamics at different time scales. The majority of the existing numerical methods for multiscale analysis first decompose the time series into several simpler components and the multiscale structure is given by the properties of their components. We present a numerical method which describes the multiscale structure of arbitrary time series without decomposing them. It is based on the monotony spectrum defined as the variation of the mean amplitude of the monotonic segments with respect to the mean local time scale during successive averagings of the time series, the local time scales being the durations of the monotonic segments. The maxima of the monotony spectrum indicate the time scales which dominate the variations of the time series. We show that the monotony spectrum can correctly analyze a diversity of artificial time series and can discriminate the existence of deterministic variations at large time scales from the random fluctuations. As an application we analyze the multifractal structure of some hydrological time series.

  9. A multiscale computational model of spatially resolved calcium cycling in cardiac myocytes: from detailed cleft dynamics to the whole cell concentration profiles

    PubMed Central

    Vierheller, Janine; Neubert, Wilhelm; Falcke, Martin; Gilbert, Stephen H.; Chamakuri, Nagaiah

    2015-01-01

    Mathematical modeling of excitation-contraction coupling (ECC) in ventricular cardiac myocytes is a multiscale problem, and it is therefore difficult to develop spatially detailed simulation tools. ECC involves gradients on the length scale of 100 nm in dyadic spaces and concentration profiles along the 100 μm of the whole cell, as well as the sub-millisecond time scale of local concentration changes and the change of lumenal Ca2+ content within tens of seconds. Our concept for a multiscale mathematical model of Ca2+ -induced Ca2+ release (CICR) and whole cardiomyocyte electrophysiology incorporates stochastic simulation of individual LC- and RyR-channels, spatially detailed concentration dynamics in dyadic clefts, rabbit membrane potential dynamics, and a system of partial differential equations for myoplasmic and lumenal free Ca2+ and Ca2+-binding molecules in the bulk of the cell. We developed a novel computational approach to resolve the concentration gradients from dyadic space to cell level by using a quasistatic approximation within the dyad and finite element methods for integrating the partial differential equations. We show whole cell Ca2+-concentration profiles using three previously published RyR-channel Markov schemes. PMID:26441674

  10. Weighted multiscale Rényi permutation entropy of nonlinear time series

    NASA Astrophysics Data System (ADS)

    Chen, Shijian; Shang, Pengjian; Wu, Yue

    2018-04-01

    In this paper, based on Rényi permutation entropy (RPE), which has been recently suggested as a relative measure of complexity in nonlinear systems, we propose multiscale Rényi permutation entropy (MRPE) and weighted multiscale Rényi permutation entropy (WMRPE) to quantify the complexity of nonlinear time series over multiple time scales. First, we apply MPRE and WMPRE to the synthetic data and make a comparison of modified methods and RPE. Meanwhile, the influence of the change of parameters is discussed. Besides, we interpret the necessity of considering not only multiscale but also weight by taking the amplitude into account. Then MRPE and WMRPE methods are employed to the closing prices of financial stock markets from different areas. By observing the curves of WMRPE and analyzing the common statistics, stock markets are divided into 4 groups: (1) DJI, S&P500, and HSI, (2) NASDAQ and FTSE100, (3) DAX40 and CAC40, and (4) ShangZheng and ShenCheng. Results show that the standard deviations of weighted methods are smaller, showing WMRPE is able to ensure the results more robust. Besides, WMPRE can provide abundant dynamical properties of complex systems, and demonstrate the intrinsic mechanism.

  11. Symmetry breaking, mixing, instability, and low-frequency variability in a minimal Lorenz-like system.

    PubMed

    Lucarini, Valerio; Fraedrich, Klaus

    2009-08-01

    Starting from the classical Saltzman two-dimensional convection equations, we derive via a severe spectral truncation a minimal 10 ODE system which includes the thermal effect of viscous dissipation. Neglecting this process leads to a dynamical system which includes a decoupled generalized Lorenz system. The consideration of this process breaks an important symmetry and couples the dynamics of fast and slow variables, with the ensuing modifications to the structural properties of the attractor and of the spectral features. When the relevant nondimensional number (Eckert number Ec) is different from zero, an additional time scale of O(Ec(-1)) is introduced in the system, as shown with standard multiscale analysis and made clear by several numerical evidences. Moreover, the system is ergodic and hyperbolic, the slow variables feature long-term memory with 1/f(3/2) power spectra, and the fast variables feature amplitude modulation. Increasing the strength of the thermal-viscous feedback has a stabilizing effect, as both the metric entropy and the Kaplan-Yorke attractor dimension decrease monotonically with Ec. The analyzed system features very rich dynamics: it overcomes some of the limitations of the Lorenz system and might have prototypical value in relevant processes in complex systems dynamics, such as the interaction between slow and fast variables, the presence of long-term memory, and the associated extreme value statistics. This analysis shows how neglecting the coupling of slow and fast variables only on the basis of scale analysis can be catastrophic. In fact, this leads to spurious invariances that affect essential dynamical properties (ergodicity, hyperbolicity) and that cause the model losing ability in describing intrinsically multiscale processes.

  12. Hybrid particle-continuum simulations coupling Brownian dynamics and local dynamic density functional theory.

    PubMed

    Qi, Shuanhu; Schmid, Friederike

    2017-11-08

    We present a multiscale hybrid particle-field scheme for the simulation of relaxation and diffusion behavior of soft condensed matter systems. It combines particle-based Brownian dynamics and field-based local dynamics in an adaptive sense such that particles can switch their level of resolution on the fly. The switching of resolution is controlled by a tuning function which can be chosen at will according to the geometry of the system. As an application, the hybrid scheme is used to study the kinetics of interfacial broadening of a polymer blend, and is validated by comparing the results to the predictions from pure Brownian dynamics and pure local dynamics calculations.

  13. Shock waves simulated using the dual domain material point method combined with molecular dynamics

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

    Zhang, Duan Z.; Dhakal, Tilak Raj

    Here in this work we combine the dual domain material point method with molecular dynamics in an attempt to create a multiscale numerical method to simulate materials undergoing large deformations with high strain rates. In these types of problems, the material is often in a thermodynamically nonequilibrium state, and conventional constitutive relations or equations of state are often not available. In this method, the closure quantities, such as stress, at each material point are calculated from a molecular dynamics simulation of a group of atoms surrounding the material point. Rather than restricting the multiscale simulation in a small spatial region,more » such as phase interfaces, or crack tips, this multiscale method can be used to consider nonequilibrium thermodynamic effects in a macroscopic domain. This method takes the advantage that the material points only communicate with mesh nodes, not among themselves; therefore molecular dynamics simulations for material points can be performed independently in parallel. The dual domain material point method is chosen for this multiscale method because it can be used in history dependent problems with large deformation without generating numerical noise as material points move across cells, and also because of its convergence and conservation properties. In conclusion, to demonstrate the feasibility and accuracy of this method, we compare the results of a shock wave propagation in a cerium crystal calculated using the direct molecular dynamics simulation with the results from this combined multiscale calculation.« less

  14. Shock waves simulated using the dual domain material point method combined with molecular dynamics

    DOE PAGES

    Zhang, Duan Z.; Dhakal, Tilak Raj

    2017-01-17

    Here in this work we combine the dual domain material point method with molecular dynamics in an attempt to create a multiscale numerical method to simulate materials undergoing large deformations with high strain rates. In these types of problems, the material is often in a thermodynamically nonequilibrium state, and conventional constitutive relations or equations of state are often not available. In this method, the closure quantities, such as stress, at each material point are calculated from a molecular dynamics simulation of a group of atoms surrounding the material point. Rather than restricting the multiscale simulation in a small spatial region,more » such as phase interfaces, or crack tips, this multiscale method can be used to consider nonequilibrium thermodynamic effects in a macroscopic domain. This method takes the advantage that the material points only communicate with mesh nodes, not among themselves; therefore molecular dynamics simulations for material points can be performed independently in parallel. The dual domain material point method is chosen for this multiscale method because it can be used in history dependent problems with large deformation without generating numerical noise as material points move across cells, and also because of its convergence and conservation properties. In conclusion, to demonstrate the feasibility and accuracy of this method, we compare the results of a shock wave propagation in a cerium crystal calculated using the direct molecular dynamics simulation with the results from this combined multiscale calculation.« less

  15. Multi-Scale Morphological Analysis of Conductance Signals in Vertical Upward Gas-Liquid Two-Phase Flow

    NASA Astrophysics Data System (ADS)

    Lian, Enyang; Ren, Yingyu; Han, Yunfeng; Liu, Weixin; Jin, Ningde; Zhao, Junying

    2016-11-01

    The multi-scale analysis is an important method for detecting nonlinear systems. In this study, we carry out experiments and measure the fluctuation signals from a rotating electric field conductance sensor with eight electrodes. We first use a recurrence plot to recognise flow patterns in vertical upward gas-liquid two-phase pipe flow from measured signals. Then we apply a multi-scale morphological analysis based on the first-order difference scatter plot to investigate the signals captured from the vertical upward gas-liquid two-phase flow loop test. We find that the invariant scaling exponent extracted from the multi-scale first-order difference scatter plot with the bisector of the second-fourth quadrant as the reference line is sensitive to the inhomogeneous distribution characteristics of the flow structure, and the variation trend of the exponent is helpful to understand the process of breakup and coalescence of the gas phase. In addition, we explore the dynamic mechanism influencing the inhomogeneous distribution of the gas phase in terms of adaptive optimal kernel time-frequency representation. The research indicates that the system energy is a factor influencing the distribution of the gas phase and the multi-scale morphological analysis based on the first-order difference scatter plot is an effective method for indicating the inhomogeneous distribution of the gas phase in gas-liquid two-phase flow.

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

    PubMed

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

    2017-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

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

  18. Complexity and multifractal behaviors of multiscale-continuum percolation financial system for Chinese stock markets

    NASA Astrophysics Data System (ADS)

    Zeng, Yayun; Wang, Jun; Xu, Kaixuan

    2017-04-01

    A new financial agent-based time series model is developed and investigated by multiscale-continuum percolation system, which can be viewed as an extended version of continuum percolation system. In this financial model, for different parameters of proportion and density, two Poisson point processes (where the radii of points represent the ability of receiving or transmitting information among investors) are applied to model a random stock price process, in an attempt to investigate the fluctuation dynamics of the financial market. To validate its effectiveness and rationality, we compare the statistical behaviors and the multifractal behaviors of the simulated data derived from the proposed model with those of the real stock markets. Further, the multiscale sample entropy analysis is employed to study the complexity of the returns, and the cross-sample entropy analysis is applied to measure the degree of asynchrony of return autocorrelation time series. The empirical results indicate that the proposed financial model can simulate and reproduce some significant characteristics of the real stock markets to a certain extent.

  19. 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.

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

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

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

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

  1. Recent applications of boxed molecular dynamics: a simple multiscale technique for atomistic simulations.

    PubMed

    Booth, Jonathan; Vazquez, Saulo; Martinez-Nunez, Emilio; Marks, Alison; Rodgers, Jeff; Glowacki, David R; Shalashilin, Dmitrii V

    2014-08-06

    In this paper, we briefly review the boxed molecular dynamics (BXD) method which allows analysis of thermodynamics and kinetics in complicated molecular systems. BXD is a multiscale technique, in which thermodynamics and long-time dynamics are recovered from a set of short-time simulations. In this paper, we review previous applications of BXD to peptide cyclization, solution phase organic reaction dynamics and desorption of ions from self-assembled monolayers (SAMs). We also report preliminary results of simulations of diamond etching mechanisms and protein unfolding in atomic force microscopy experiments. The latter demonstrate a correlation between the protein's structural motifs and its potential of mean force. Simulations of these processes by standard molecular dynamics (MD) is typically not possible, because the experimental time scales are very long. However, BXD yields well-converged and physically meaningful results. Compared with other methods of accelerated MD, our BXD approach is very simple; it is easy to implement, and it provides an integrated approach for simultaneously obtaining both thermodynamics and kinetics. It also provides a strategy for obtaining statistically meaningful dynamical results in regions of configuration space that standard MD approaches would visit only very rarely.

  2. Dynamic Heterogeneous Multiscale Filtration Model: Probing Micro- and Macroscopic Filtration Characteristics of Gasoline Particulate Filters.

    PubMed

    Gong, Jian; Viswanathan, Sandeep; Rothamer, David A; Foster, David E; Rutland, Christopher J

    2017-10-03

    Motivated by high filtration efficiency (mass- and number-based) and low pressure drop requirements for gasoline particulate filters (GPFs), a previously developed heterogeneous multiscale filtration (HMF) model is extended to simulate dynamic filtration characteristics of GPFs. This dynamic HMF model is based on a probability density function (PDF) description of the pore size distribution and classical filtration theory. The microstructure of the porous substrate in a GPF is resolved and included in the model. Fundamental particulate filtration experiments were conducted using an exhaust filtration analysis (EFA) system for model validation. The particulate in the filtration experiments was sampled from a spark-ignition direct-injection (SIDI) gasoline engine. With the dynamic HMF model, evolution of the microscopic characteristics of the substrate (pore size distribution, porosity, permeability, and deposited particulate inside the porous substrate) during filtration can be probed. Also, predicted macroscopic filtration characteristics including particle number concentration and normalized pressure drop show good agreement with the experimental data. The resulting dynamic HMF model can be used to study the dynamic particulate filtration process in GPFs with distinct microstructures, serving as a powerful tool for GPF design and optimization.

  3. Multiscale turbulence models based on convected fluid microstructure

    NASA Astrophysics Data System (ADS)

    Holm, Darryl D.; Tronci, Cesare

    2012-11-01

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

  4. Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems.

    PubMed

    Ouyang, Fang-Yan; Zheng, Bo; Jiang, Xiong-Fei

    2015-01-01

    The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode.

  5. A systems theoretic approach to analysis and control of mammalian circadian dynamics

    PubMed Central

    Abel, John H.; Doyle, Francis J.

    2016-01-01

    The mammalian circadian clock is a complex multi-scale, multivariable biological control system. In the past two decades, methods from systems engineering have led to numerous insights into the architecture and functionality of this system. In this review, we examine the mammalian circadian system through a process systems lens. We present a mathematical framework for examining the cellular circadian oscillator, and show recent extensions for understanding population-scale dynamics. We provide an overview of the routes by which the circadian system can be systemically manipulated, and present in silico proof of concept results for phase resetting of the clock via model predictive control. PMID:28496287

  6. Mesoscopic modelling and simulation of soft matter.

    PubMed

    Schiller, Ulf D; Krüger, Timm; Henrich, Oliver

    2017-12-20

    The deformability of soft condensed matter often requires modelling of hydrodynamical aspects to gain quantitative understanding. This, however, requires specialised methods that can resolve the multiscale nature of soft matter systems. We review a number of the most popular simulation methods that have emerged, such as Langevin dynamics, dissipative particle dynamics, multi-particle collision dynamics, sometimes also referred to as stochastic rotation dynamics, and the lattice-Boltzmann method. We conclude this review with a short glance at current compute architectures for high-performance computing and community codes for soft matter simulation.

  7. Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations

    NASA Astrophysics Data System (ADS)

    Petsev, Nikolai D.; Leal, L. Gary; Shell, M. Scott

    2017-12-01

    Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely resolved (e.g., molecular dynamics) and coarse-grained (e.g., continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 084115 (2016)], simulated using a particle-based continuum method known as smoothed dissipative particle dynamics. An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.

  8. MMS at NRL

    NASA Image and Video Library

    2014-08-04

    Engineers work on one of four Magnetospheric Multiscale (MMS) spacecraft in a cleanroom at the Naval Research Lab, Monday, August 4, 2014, in Washington. The Magnetospheric Multiscale, or MMS, mission will study the mystery of how magnetic fields around Earth connect and disconnect, explosively releasing energy via a process known as magnetic reconnection. The four identical spacecraft are scheduled to launch in 2015 from Cape Canaveral and will orbit around Earth in varying formations through the dynamic magnetic system surrounding our planet to provide the first three-dimensional views of the magnetic reconnection process. The goal of the STP Program is to understand the fundamental physical processes of the space environment from the sun to Earth, other planets, and the extremes of the solar system boundary. Photo Credit: (NASA/Bill Ingalls)

  9. Multi-scale Modeling of Chromosomal DNA in Living Cells

    NASA Astrophysics Data System (ADS)

    Spakowitz, Andrew

    The organization and dynamics of chromosomal DNA play a pivotal role in a range of biological processes, including gene regulation, homologous recombination, replication, and segregation. Establishing a quantitative theoretical model of DNA organization and dynamics would be valuable in bridging the gap between the molecular-level packaging of DNA and genome-scale chromosomal processes. Our research group utilizes analytical theory and computational modeling to establish a predictive theoretical model of chromosomal organization and dynamics. In this talk, I will discuss our efforts to develop multi-scale polymer models of chromosomal DNA that are both sufficiently detailed to address specific protein-DNA interactions while capturing experimentally relevant time and length scales. I will demonstrate how these modeling efforts are capable of quantitatively capturing aspects of behavior of chromosomal DNA in both prokaryotic and eukaryotic cells. This talk will illustrate that capturing dynamical behavior of chromosomal DNA at various length scales necessitates a range of theoretical treatments that accommodate the critical physical contributions that are relevant to in vivo behavior at these disparate length and time scales. National Science Foundation, Physics of Living Systems Program (PHY-1305516).

  10. Penetration into Granular Earth Materials (Topic H): A Multi-scale Physics-Based Approach Towards Developing a Greater Understanding of Dynamically Loaded Heterogeneous Systems

    DTIC Science & Technology

    2016-08-01

    7 2.1. DYNAMIC DART GUN EXPERIMENTS...penetration, and cavity formation associated with high-speed projectile penetration of sand. A new half-inch gun was constructed for this project. A...inch gun with them. Data was collected utilizing NSWC’s Cordin 550, 64 frame, high-speed camera. In addition, several student participated in the

  11. Multiscale X-ray and Proton Imaging of Bismuth-Tin Solidification

    NASA Astrophysics Data System (ADS)

    Gibbs, P. J.; Imhoff, S. D.; Morris, C. L.; Merrill, F. E.; Wilde, C. H.; Nedrow, P.; Mariam, F. G.; Fezzaa, K.; Lee, W.-K.; Clarke, A. J.

    2014-08-01

    The formation of structural patterns during metallic solidification is complex and multiscale in nature, ranging from the nanometer scale, where solid-liquid interface properties are important, to the macroscale, where casting mold filling and intended heat transfer are crucial. X-ray and proton imaging can directly interrogate structure, solute, and fluid flow development in metals from the microscale to the macroscale. X-rays permit high spatio-temporal resolution imaging of microscopic solidification dynamics in thin metal sections. Similarly, high-energy protons permit imaging of mesoscopic and macroscopic solidification dynamics in large sample volumes. In this article, we highlight multiscale x-ray and proton imaging of bismuth-tin alloy solidification to illustrate dynamic measurement of crystal growth rates and solute segregation profiles that can be that can be acquired using these techniques.

  12. Personalized medicine: from genotypes, molecular phenotypes and the quantified self, towards improved medicine.

    PubMed

    Dudley, Joel T; Listgarten, Jennifer; Stegle, Oliver; Brenner, Steven E; Parts, Leopold

    2015-01-01

    Advances in molecular profiling and sensor technologies are expanding the scope of personalized medicine beyond genotypes, providing new opportunities for developing richer and more dynamic multi-scale models of individual health. Recent studies demonstrate the value of scoring high-dimensional microbiome, immune, and metabolic traits from individuals to inform personalized medicine. Efforts to integrate multiple dimensions of clinical and molecular data towards predictive multi-scale models of individual health and wellness are already underway. Improved methods for mining and discovery of clinical phenotypes from electronic medical records and technological developments in wearable sensor technologies present new opportunities for mapping and exploring the critical yet poorly characterized "phenome" and "envirome" dimensions of personalized medicine. There are ambitious new projects underway to collect multi-scale molecular, sensor, clinical, behavioral, and environmental data streams from large population cohorts longitudinally to enable more comprehensive and dynamic models of individual biology and personalized health. Personalized medicine stands to benefit from inclusion of rich new sources and dimensions of data. However, realizing these improvements in care relies upon novel informatics methodologies, tools, and systems to make full use of these data to advance both the science and translational applications of personalized medicine.

  13. Multiscale Poincaré plots for visualizing the structure of heartbeat time series.

    PubMed

    Henriques, Teresa S; Mariani, Sara; Burykin, Anton; Rodrigues, Filipa; Silva, Tiago F; Goldberger, Ary L

    2016-02-09

    Poincaré delay maps are widely used in the analysis of cardiac interbeat interval (RR) dynamics. To facilitate visualization of the structure of these time series, we introduce multiscale Poincaré (MSP) plots. Starting with the original RR time series, the method employs a coarse-graining procedure to create a family of time series, each of which represents the system's dynamics in a different time scale. Next, the Poincaré plots are constructed for the original and the coarse-grained time series. Finally, as an optional adjunct, color can be added to each point to represent its normalized frequency. We illustrate the MSP method on simulated Gaussian white and 1/f noise time series. The MSP plots of 1/f noise time series reveal relative conservation of the phase space area over multiple time scales, while those of white noise show a marked reduction in area. We also show how MSP plots can be used to illustrate the loss of complexity when heartbeat time series from healthy subjects are compared with those from patients with chronic (congestive) heart failure syndrome or with atrial fibrillation. This generalized multiscale approach to Poincaré plots may be useful in visualizing other types of time series.

  14. Multiscale Molecular Dynamics Simulations of Beta-Amyloid Interactions with Neurons

    NASA Astrophysics Data System (ADS)

    Qiu, Liming; Vaughn, Mark; Cheng, Kelvin

    2012-10-01

    Early events of human beta-amyloid protein interactions with cholesterol-containing membranes are critical to understanding the pathogenesis of Alzheimer's disease (AD) and to exploring new therapeutic interventions of AD. Atomistic molecular dynamics (AMD) simulations have been extensively used to study the protein-lipid interaction at high atomic resolutions. However, traditional MD simulations are not efficient in sampling the phase space of complex lipid/protein systems with rugged free energy landscapes. Meanwhile, coarse-grained MD (CGD) simulations are efficient in the phase space sampling but suffered from low spatial resolutions and from the fact that the energy landscapes are not identical to those of the AMD. Here, a multiscale approach was employed to simulate the protein-lipid interactions of beta-amyloid upon its release from proteolysis residing in the neuronal membranes. We utilized a forward (AMD to CGD) and reverse (CGD-AMD) strategy to explore new transmembrane and surface protein configuration and evaluate the stabilization mechanisms by measuring the residue-specific protein-lipid or protein conformations. The detailed molecular interactions revealed in this multiscale MD approach will provide new insights into understanding the early molecular events leading to the pathogenesis of AD.

  15. Turbulence sources, character, and effects in the stable boundary layer: Insights from multi-scale direct numerical simulations and new, high-resolution measurements

    NASA Astrophysics Data System (ADS)

    Fritts, Dave; Wang, Ling; Balsley, Ben; Lawrence, Dale

    2013-04-01

    A number of sources contribute to intermittent small-scale turbulence in the stable boundary layer (SBL). These include Kelvin-Helmholtz instability (KHI), gravity wave (GW) breaking, and fluid intrusions, among others. Indeed, such sources arise naturally in response to even very simple "multi-scale" superpositions of larger-scale GWs and smaller-scale GWs, mean flows, or fine structure (FS) throughout the atmosphere and the oceans. We describe here results of two direct numerical simulations (DNS) of these GW-FS interactions performed at high resolution and high Reynolds number that allow exploration of these turbulence sources and the character and effects of the turbulence that arises in these flows. Results include episodic turbulence generation, a broad range of turbulence scales and intensities, PDFs of dissipation fields exhibiting quasi-log-normal and more complex behavior, local turbulent mixing, and "sheet and layer" structures in potential temperature that closely resemble high-resolution measurements. Importantly, such multi-scale dynamics differ from their larger-scale, quasi-monochromatic gravity wave or quasi-horizontally homogeneous shear flow instabilities in significant ways. The ability to quantify such multi-scale dynamics with new, very high-resolution measurements is also advancing rapidly. New in-situ sensors on small, unmanned aerial vehicles (UAVs), balloons, or tethered systems are enabling definition of SBL (and deeper) environments and turbulence structure and dissipation fields with high spatial and temporal resolution and precision. These new measurement and modeling capabilities promise significant advances in understanding small-scale instability and turbulence dynamics, in quantifying their roles in mixing, transport, and evolution of the SBL environment, and in contributing to improved parameterizations of these dynamics in mesoscale, numerical weather prediction, climate, and general circulation models. We expect such measurement and modeling capabilities to also aid in the design of new and more comprehensive future SBL measurement programs.

  16. Multi-scale genetic dynamic modelling I : an algorithm to compute generators.

    PubMed

    Kirkilionis, Markus; Janus, Ulrich; Sbano, Luca

    2011-09-01

    We present a new approach or framework to model dynamic regulatory genetic activity. The framework is using a multi-scale analysis based upon generic assumptions on the relative time scales attached to the different transitions of molecular states defining the genetic system. At micro-level such systems are regulated by the interaction of two kinds of molecular players: macro-molecules like DNA or polymerases, and smaller molecules acting as transcription factors. The proposed genetic model then represents the larger less abundant molecules with a finite discrete state space, for example describing different conformations of these molecules. This is in contrast to the representations of the transcription factors which are-like in classical reaction kinetics-represented by their particle number only. We illustrate the method by considering the genetic activity associated to certain configurations of interacting genes that are fundamental to modelling (synthetic) genetic clocks. A largely unknown question is how different molecular details incorporated via this more realistic modelling approach lead to different macroscopic regulatory genetic models which dynamical behaviour might-in general-be different for different model choices. The theory will be applied to a real synthetic clock in a second accompanying article (Kirkilioniset al., Theory Biosci, 2011).

  17. 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

  18. Uncertainty Analysis and Control in Nonlinear, Multiscale, Interconnected Systems

    DTIC Science & Technology

    2009-10-22

    effects of asymmetry on mitigating limit cycle oscillations in aeroengines . This work earlier lead to development of a patent and a uercial product...oscillator models. 5 Honors/Awards • The PI gave a plenary lecture at the , Second International Conference on Dynamics, Vibration and Control in Beijing

  19. Multi-Scale Multi-Domain Model | Transportation Research | NREL

    Science.gov Websites

    framework for NREL's MSMD model. NREL's MSMD model quantifies the impacts of electrical/thermal pathway : NREL Macroscopic design factors and highly dynamic environmental conditions significantly influence the design of affordable, long-lasting, high-performing, and safe large battery systems. The MSMD framework

  20. The Virtual Liver Project: Modeling Tissue Response To Chemicals Through Multiscale Simulation

    EPA Science Inventory

    The US EPA Virtual Liver Project is aimed at simulating the risk of toxic effects from environmental chemicals in silico. The computational systems model of organ injury due to chronic chemical exposure is based on: (i) the dynamics of perturbed molecular pathways, (ii) their lin...

  1. An evaluation of noise reduction algorithms for particle-based fluid simulations in multi-scale applications

    NASA Astrophysics Data System (ADS)

    Zimoń, M. J.; Prosser, R.; Emerson, D. R.; Borg, M. K.; Bray, D. J.; Grinberg, L.; Reese, J. M.

    2016-11-01

    Filtering of particle-based simulation data can lead to reduced computational costs and enable more efficient information transfer in multi-scale modelling. This paper compares the effectiveness of various signal processing methods to reduce numerical noise and capture the structures of nano-flow systems. In addition, a novel combination of these algorithms is introduced, showing the potential of hybrid strategies to improve further the de-noising performance for time-dependent measurements. The methods were tested on velocity and density fields, obtained from simulations performed with molecular dynamics and dissipative particle dynamics. Comparisons between the algorithms are given in terms of performance, quality of the results and sensitivity to the choice of input parameters. The results provide useful insights on strategies for the analysis of particle-based data and the reduction of computational costs in obtaining ensemble solutions.

  2. Multi-scale Food Energy and Water Dynamics in the Blue Nile Highlands

    NASA Astrophysics Data System (ADS)

    Zaitchik, B. F.; Simane, B.; Block, P. J.; Foltz, J.; Mueller-Mahn, D.; Gilioli, G.; Sciarretta, A.

    2017-12-01

    The Ethiopian highlands are often called the "water tower of Africa," giving rise to major transboundary rivers. Rapid hydropower development is quickly transforming these highlands into the "power plant of Africa" as well. For local people, however, they are first and foremost a land of small farms, devoted primarily to subsistence agriculture. Under changing climate, rapid national economic growth, and steadily increasing population and land pressures, these mountains and their inhabitants have become the focal point of a multi-scale food-energy-water nexus with significant implications across East Africa. Here we examine coupled natural-human system dynamics that emerge when basin and nation scale resource development strategies are superimposed on a local economy that is largely subsistence based. Sensitivity to local and remote climate shocks are considered, as is the role of Earth Observation in understanding and informing management of food-energy-water resources across scales.

  3. Multi-scale modeling of irradiation effects in spallation neutron source materials

    NASA Astrophysics Data System (ADS)

    Yoshiie, T.; Ito, T.; Iwase, H.; Kaneko, Y.; Kawai, M.; Kishida, I.; Kunieda, S.; Sato, K.; Shimakawa, S.; Shimizu, F.; Hashimoto, S.; Hashimoto, N.; Fukahori, T.; Watanabe, Y.; Xu, Q.; Ishino, S.

    2011-07-01

    Changes in mechanical property of Ni under irradiation by 3 GeV protons were estimated by multi-scale modeling. The code consisted of four parts. The first part was based on the Particle and Heavy-Ion Transport code System (PHITS) code for nuclear reactions, and modeled the interactions between high energy protons and nuclei in the target. The second part covered atomic collisions by particles without nuclear reactions. Because the energy of the particles was high, subcascade analysis was employed. The direct formation of clusters and the number of mobile defects were estimated using molecular dynamics (MD) and kinetic Monte-Carlo (kMC) methods in each subcascade. The third part considered damage structural evolutions estimated by reaction kinetic analysis. The fourth part involved the estimation of mechanical property change using three-dimensional discrete dislocation dynamics (DDD). Using the above four part code, stress-strain curves for high energy proton irradiated Ni were obtained.

  4. Multiscale Modeling of PEEK Using Reactive Molecular Dynamics Modeling and Micromechanics

    NASA Technical Reports Server (NTRS)

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

    2018-01-01

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

  5. Formalizing Knowledge in Multi-Scale Agent-Based Simulations

    PubMed Central

    Somogyi, Endre; Sluka, James P.; Glazier, James A.

    2017-01-01

    Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused. PMID:29338063

  6. Formalizing Knowledge in Multi-Scale Agent-Based Simulations.

    PubMed

    Somogyi, Endre; Sluka, James P; Glazier, James A

    2016-10-01

    Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused.

  7. ProtoMD: A prototyping toolkit for multiscale molecular dynamics

    NASA Astrophysics Data System (ADS)

    Somogyi, Endre; Mansour, Andrew Abi; Ortoleva, Peter J.

    2016-05-01

    ProtoMD is a toolkit that facilitates the development of algorithms for multiscale molecular dynamics (MD) simulations. It is designed for multiscale methods which capture the dynamic transfer of information across multiple spatial scales, such as the atomic to the mesoscopic scale, via coevolving microscopic and coarse-grained (CG) variables. ProtoMD can be also be used to calibrate parameters needed in traditional CG-MD methods. The toolkit integrates 'GROMACS wrapper' to initiate MD simulations, and 'MDAnalysis' to analyze and manipulate trajectory files. It facilitates experimentation with a spectrum of coarse-grained variables, prototyping rare events (such as chemical reactions), or simulating nanocharacterization experiments such as terahertz spectroscopy, AFM, nanopore, and time-of-flight mass spectroscopy. ProtoMD is written in python and is freely available under the GNU General Public License from github.com/CTCNano/proto_md.

  8. Multiscale modeling and simulation of microtubule-motor-protein assemblies

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  9. Multiscale modeling and simulation of microtubule-motor-protein assemblies.

    PubMed

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

    2015-01-01

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

  10. 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

  11. Nonlinear Dynamics of Complex Coevolutionary Systems in Historical Times

    NASA Astrophysics Data System (ADS)

    Perdigão, Rui A. P.

    2016-04-01

    A new theoretical paradigm for statistical-dynamical modeling of complex coevolutionary systems is introduced, with the aim to provide historical geoscientists with a practical tool to analyse historical data and its underlying phenomenology. Historical data is assumed to represent the history of dynamical processes of physical and socio-economic nature. If processes and their governing laws are well understood, they are often treated with traditional dynamical equations: deterministic approach. If the governing laws are unknown or impracticable, the process is often treated as if being random (even if it is not): statistical approach. Although single eventful details - such as the exact spatiotemporal structure of a particular hydro-meteorological incident - may often be elusive to a detailed analysis, the overall dynamics exhibit group properties summarized by a simple set of categories or dynamical regimes at multiple scales - from local short-lived convection patterns to large-scale hydro-climatic regimes. The overwhelming microscale complexity is thus conveniently wrapped into a manageable group entity, such as a statistical distribution. In a stationary setting whereby the distribution is assumed to be invariant, alternating regimes are approachable as dynamical intermittence. For instance, in the context of bimodal climatic oscillations such as NAO and ENSO, each mode corresponds to a dynamical regime or phase. However, given external forcings or longer-term internal variability and multiscale coevolution, the structural properties of the system may change. These changes in the dynamical structure bring about a new distribution and associated regimes. The modes of yesteryear may no longer exist as such in the new structural order of the system. In this context, aside from regime intermittence, the system exhibits structural regime change. New oscillations may emerge whilst others fade into the annals of history, e.g. particular climate fluctuations during the Little Ice Age. Traditional theories of stochastic processes and dynamical systems are grounded on the existence of so-called dynamical invariants; properties that remain unchanged as the dynamics unfold, assuming structural invariance and ergodicity of the underlying system. However, such theories are no longer optimal when trying to understand and model long-term historical records of coevolutionary systems. A new paradigm is thus needed. Therefore, we introduce a new class of dynamical systems that reinvent themselves as the dynamics unfold. Rather than only changing variables and parameters under a rigid framework, the governing laws are malleable themselves. The novel formulation captures and explains the coevolutionary dynamics of multiscale hydroclimatic systems, bringing along a physically sound understanding of their regimes, transitions and extremes over a long-term history.

  12. MMS at NRL

    NASA Image and Video Library

    2014-08-04

    One of four Magnetospheric Multiscale (MMS) spacecraft, in the background, is seen in a cleanroom at the Naval Research Lab’s, Naval Center for Space Technology, Monday, August 4, 2014, in Washington. The Magnetospheric Multiscale, or MMS, mission will study the mystery of how magnetic fields around Earth connect and disconnect, explosively releasing energy via a process known as magnetic reconnection. The four identical spacecraft are scheduled to launch in 2015 from Cape Canaveral and will orbit around Earth in varying formations through the dynamic magnetic system surrounding our planet to provide the first three-dimensional views of the magnetic reconnection process. The goal of the STP Program is to understand the fundamental physical processes of the space environment from the sun to Earth, other planets, and the extremes of the solar system boundary. Photo Credit: (NASA/Bill Ingalls)

  13. Perspective: Differential dynamic microscopy extracts multi-scale activity in complex fluids and biological systems

    NASA Astrophysics Data System (ADS)

    Cerbino, Roberto; Cicuta, Pietro

    2017-09-01

    Differential dynamic microscopy (DDM) is a technique that exploits optical microscopy to obtain local, multi-scale quantitative information about dynamic samples, in most cases without user intervention. It is proving extremely useful in understanding dynamics in liquid suspensions, soft materials, cells, and tissues. In DDM, image sequences are analyzed via a combination of image differences and spatial Fourier transforms to obtain information equivalent to that obtained by means of light scattering techniques. Compared to light scattering, DDM offers obvious advantages, principally (a) simplicity of the setup; (b) possibility of removing static contributions along the optical path; (c) power of simultaneous different microscopy contrast mechanisms; and (d) flexibility of choosing an analysis region, analogous to a scattering volume. For many questions, DDM has also advantages compared to segmentation/tracking approaches and to correlation techniques like particle image velocimetry. The very straightforward DDM approach, originally demonstrated with bright field microscopy of aqueous colloids, has lately been used to probe a variety of other complex fluids and biological systems with many different imaging methods, including dark-field, differential interference contrast, wide-field, light-sheet, and confocal microscopy. The number of adopting groups is rapidly increasing and so are the applications. Here, we briefly recall the working principles of DDM, we highlight its advantages and limitations, we outline recent experimental breakthroughs, and we provide a perspective on future challenges and directions. DDM can become a standard primary tool in every laboratory equipped with a microscope, at the very least as a first bias-free automated evaluation of the dynamics in a system.

  14. Traditional Chinese medicine: potential approaches from modern dynamical complexity theories.

    PubMed

    Ma, Yan; Zhou, Kehua; Fan, Jing; Sun, Shuchen

    2016-03-01

    Despite the widespread use of traditional Chinese medicine (TCM) in clinical settings, proving its effectiveness via scientific trials is still a challenge. TCM views the human body as a complex dynamical system, and focuses on the balance of the human body, both internally and with its external environment. Such fundamental concepts require investigations using system-level quantification approaches, which are beyond conventional reductionism. Only methods that quantify dynamical complexity can bring new insights into the evaluation of TCM. In a previous article, we briefly introduced the potential value of Multiscale Entropy (MSE) analysis in TCM. This article aims to explain the existing challenges in TCM quantification, to introduce the consistency of dynamical complexity theories and TCM theories, and to inspire future system-level research on health and disease.

  15. Methods for High-Order Multi-Scale and Stochastic Problems Analysis, Algorithms, and Applications

    DTIC Science & Technology

    2016-10-17

    finite volume schemes, discontinuous Galerkin finite element method, and related methods, for solving computational fluid dynamics (CFD) problems and...approximation for finite element methods. (3) The development of methods of simulation and analysis for the study of large scale stochastic systems of...laws, finite element method, Bernstein-Bezier finite elements , weakly interacting particle systems, accelerated Monte Carlo, stochastic networks 16

  16. Development of Improved Algorithms and Multiscale Modeling Capability with SUNTANS

    DTIC Science & Technology

    2013-09-30

    solves the Navier-Stokes equations under the Boussinesq approximation (Fringer et al.,2006). The formulation is based on the method outlined by...stratified systems . Figure 4 shows a nonhydrostatic isopycnal simulation of oscillatory flow in a continuously stratified fluid over a Gaussian sill. This...Modeling the Earth System , Boulder (invited). Sankaranarayanan, S., and Fringer, O. B., 2013, "Dynamics of barotropic low-frequency fluctuations in

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

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

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

    2009-05-01

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

  18. Studying the dynamics of interbeat interval time series of healthy and congestive heart failure subjects using scale based symbolic entropy analysis

    PubMed Central

    Awan, Imtiaz; Aziz, Wajid; Habib, Nazneen; Alowibdi, Jalal S.; Saeed, Sharjil; Nadeem, Malik Sajjad Ahmed; Shah, Syed Ahsin Ali

    2018-01-01

    Considerable interest has been devoted for developing a deeper understanding of the dynamics of healthy biological systems and how these dynamics are affected due to aging and disease. Entropy based complexity measures have widely been used for quantifying the dynamics of physical and biological systems. These techniques have provided valuable information leading to a fuller understanding of the dynamics of these systems and underlying stimuli that are responsible for anomalous behavior. The single scale based traditional entropy measures yielded contradictory results about the dynamics of real world time series data of healthy and pathological subjects. Recently the multiscale entropy (MSE) algorithm was introduced for precise description of the complexity of biological signals, which was used in numerous fields since its inception. The original MSE quantified the complexity of coarse-grained time series using sample entropy. The original MSE may be unreliable for short signals because the length of the coarse-grained time series decreases with increasing scaling factor τ, however, MSE works well for long signals. To overcome the drawback of original MSE, various variants of this method have been proposed for evaluating complexity efficiently. In this study, we have proposed multiscale normalized corrected Shannon entropy (MNCSE), in which instead of using sample entropy, symbolic entropy measure NCSE has been used as an entropy estimate. The results of the study are compared with traditional MSE. The effectiveness of the proposed approach is demonstrated using noise signals as well as interbeat interval signals from healthy and pathological subjects. The preliminary results of the study indicate that MNCSE values are more stable and reliable than original MSE values. The results show that MNCSE based features lead to higher classification accuracies in comparison with the MSE based features. PMID:29771977

  19. Studying the dynamics of interbeat interval time series of healthy and congestive heart failure subjects using scale based symbolic entropy analysis.

    PubMed

    Awan, Imtiaz; Aziz, Wajid; Shah, Imran Hussain; Habib, Nazneen; Alowibdi, Jalal S; Saeed, Sharjil; Nadeem, Malik Sajjad Ahmed; Shah, Syed Ahsin Ali

    2018-01-01

    Considerable interest has been devoted for developing a deeper understanding of the dynamics of healthy biological systems and how these dynamics are affected due to aging and disease. Entropy based complexity measures have widely been used for quantifying the dynamics of physical and biological systems. These techniques have provided valuable information leading to a fuller understanding of the dynamics of these systems and underlying stimuli that are responsible for anomalous behavior. The single scale based traditional entropy measures yielded contradictory results about the dynamics of real world time series data of healthy and pathological subjects. Recently the multiscale entropy (MSE) algorithm was introduced for precise description of the complexity of biological signals, which was used in numerous fields since its inception. The original MSE quantified the complexity of coarse-grained time series using sample entropy. The original MSE may be unreliable for short signals because the length of the coarse-grained time series decreases with increasing scaling factor τ, however, MSE works well for long signals. To overcome the drawback of original MSE, various variants of this method have been proposed for evaluating complexity efficiently. In this study, we have proposed multiscale normalized corrected Shannon entropy (MNCSE), in which instead of using sample entropy, symbolic entropy measure NCSE has been used as an entropy estimate. The results of the study are compared with traditional MSE. The effectiveness of the proposed approach is demonstrated using noise signals as well as interbeat interval signals from healthy and pathological subjects. The preliminary results of the study indicate that MNCSE values are more stable and reliable than original MSE values. The results show that MNCSE based features lead to higher classification accuracies in comparison with the MSE based features.

  20. Sustainable design and manufacturing of multifunctional polymer nanocomposite coatings: A multiscale systems approach

    NASA Astrophysics Data System (ADS)

    Xiao, Jie

    Polymer nanocomposites have a great potential to be a dominant coating material in a wide range of applications in the automotive, aerospace, ship-making, construction, and pharmaceutical industries. However, how to realize design sustainability of this type of nanostructured materials and how to ensure the true optimality of the product quality and process performance in coating manufacturing remain as a mountaintop area. The major challenges arise from the intrinsic multiscale nature of the material-process-product system and the need to manipulate the high levels of complexity and uncertainty in design and manufacturing processes. This research centers on the development of a comprehensive multiscale computational methodology and a computer-aided tool set that can facilitate multifunctional nanocoating design and application from novel function envisioning and idea refinement, to knowledge discovery and design solution derivation, and further to performance testing in industrial applications and life cycle analysis. The principal idea is to achieve exceptional system performance through concurrent characterization and optimization of materials, product and associated manufacturing processes covering a wide range of length and time scales. Multiscale modeling and simulation techniques ranging from microscopic molecular modeling to classical continuum modeling are seamlessly coupled. The tight integration of different methods and theories at individual scales allows the prediction of macroscopic coating performance from the fundamental molecular behavior. Goal-oriented design is also pursued by integrating additional methods for bio-inspired dynamic optimization and computational task management that can be implemented in a hierarchical computing architecture. Furthermore, multiscale systems methodologies are developed to achieve the best possible material application towards sustainable manufacturing. Automotive coating manufacturing, that involves paint spay and curing, is specifically discussed in this dissertation. Nevertheless, the multiscale considerations for sustainable manufacturing, the novel concept of IPP control, and the new PPDE-based optimization method are applicable to other types of manufacturing, e.g., metal coating development through electroplating. It is demonstrated that the methodological development in this dissertation can greatly facilitate experimentalists in novel material invention and new knowledge discovery. At the same time, they can provide scientific guidance and reveal various new opportunities and effective strategies for sustainable manufacturing.

  1. Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems

    PubMed Central

    Ouyang, Fang-Yan; Zheng, Bo; Jiang, Xiong-Fei

    2015-01-01

    The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode. PMID:26427063

  2. Wavelet-based multiscale analysis of minimum toe clearance variability in the young and elderly during walking.

    PubMed

    Khandoker, Ahsan H; Karmakar, Chandan K; Begg, Rezaul K; Palaniswami, Marimuthu

    2007-01-01

    As humans age or are influenced by pathology of the neuromuscular system, gait patterns are known to adjust, accommodating for reduced function in the balance control system. The aim of this study was to investigate the effectiveness of a wavelet based multiscale analysis of a gait variable [minimum toe clearance (MTC)] in deriving indexes for understanding age-related declines in gait performance and screening of balance impairments in the elderly. MTC during walking on a treadmill for 30 healthy young, 27 healthy elderly and 10 falls risk elderly subjects with a history of tripping falls were analyzed. The MTC signal from each subject was decomposed to eight detailed signals at different wavelet scales by using the discrete wavelet transform. The variances of detailed signals at scales 8 to 1 were calculated. The multiscale exponent (beta) was then estimated from the slope of the variance progression at successive scales. The variance at scale 5 was significantly (p<0.01) different between young and healthy elderly group. Results also suggest that the Beta between scales 1 to 2 are effective for recognizing falls risk gait patterns. Results have implication for quantifying gait dynamics in normal, ageing and pathological conditions. Early detection of gait pattern changes due to ageing and balance impairments using wavelet-based multiscale analysis might provide the opportunity to initiate preemptive measures to be undertaken to avoid injurious falls.

  3. Adaptive resolution simulation of a biomolecule and its hydration shell: Structural and dynamical properties

    NASA Astrophysics Data System (ADS)

    Fogarty, Aoife C.; Potestio, Raffaello; Kremer, Kurt

    2015-05-01

    A fully atomistic modelling of many biophysical and biochemical processes at biologically relevant length- and time scales is beyond our reach with current computational resources, and one approach to overcome this difficulty is the use of multiscale simulation techniques. In such simulations, when system properties necessitate a boundary between resolutions that falls within the solvent region, one can use an approach such as the Adaptive Resolution Scheme (AdResS), in which solvent particles change their resolution on the fly during the simulation. Here, we apply the existing AdResS methodology to biomolecular systems, simulating a fully atomistic protein with an atomistic hydration shell, solvated in a coarse-grained particle reservoir and heat bath. Using as a test case an aqueous solution of the regulatory protein ubiquitin, we first confirm the validity of the AdResS approach for such systems, via an examination of protein and solvent structural and dynamical properties. We then demonstrate how, in addition to providing a computational speedup, such a multiscale AdResS approach can yield otherwise inaccessible physical insights into biomolecular function. We use our methodology to show that protein structure and dynamics can still be correctly modelled using only a few shells of atomistic water molecules. We also discuss aspects of the AdResS methodology peculiar to biomolecular simulations.

  4. Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations

    DOE PAGES

    Petsev, Nikolai Dimitrov; Leal, L. Gary; Shell, M. Scott

    2017-12-21

    Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely-resolved (e.g. molecular dynamics) and coarse-grained (e.g. continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 84115 (2016)], simulatedmore » using a particle-based continuum method known as smoothed dissipative particle dynamics (SDPD). An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.« less

  5. Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations

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

    Petsev, Nikolai Dimitrov; Leal, L. Gary; Shell, M. Scott

    Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely-resolved (e.g. molecular dynamics) and coarse-grained (e.g. continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 84115 (2016)], simulatedmore » using a particle-based continuum method known as smoothed dissipative particle dynamics (SDPD). An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.« less

  6. Tinker-HP: a massively parallel molecular dynamics package for multiscale simulations of large complex systems with advanced point dipole polarizable force fields.

    PubMed

    Lagardère, Louis; Jolly, Luc-Henri; Lipparini, Filippo; Aviat, Félix; Stamm, Benjamin; Jing, Zhifeng F; Harger, Matthew; Torabifard, Hedieh; Cisneros, G Andrés; Schnieders, Michael J; Gresh, Nohad; Maday, Yvon; Ren, Pengyu Y; Ponder, Jay W; Piquemal, Jean-Philip

    2018-01-28

    We present Tinker-HP, a massively MPI parallel package dedicated to classical molecular dynamics (MD) and to multiscale simulations, using advanced polarizable force fields (PFF) encompassing distributed multipoles electrostatics. Tinker-HP is an evolution of the popular Tinker package code that conserves its simplicity of use and its reference double precision implementation for CPUs. Grounded on interdisciplinary efforts with applied mathematics, Tinker-HP allows for long polarizable MD simulations on large systems up to millions of atoms. We detail in the paper the newly developed extension of massively parallel 3D spatial decomposition to point dipole polarizable models as well as their coupling to efficient Krylov iterative and non-iterative polarization solvers. The design of the code allows the use of various computer systems ranging from laboratory workstations to modern petascale supercomputers with thousands of cores. Tinker-HP proposes therefore the first high-performance scalable CPU computing environment for the development of next generation point dipole PFFs and for production simulations. Strategies linking Tinker-HP to Quantum Mechanics (QM) in the framework of multiscale polarizable self-consistent QM/MD simulations are also provided. The possibilities, performances and scalability of the software are demonstrated via benchmarks calculations using the polarizable AMOEBA force field on systems ranging from large water boxes of increasing size and ionic liquids to (very) large biosystems encompassing several proteins as well as the complete satellite tobacco mosaic virus and ribosome structures. For small systems, Tinker-HP appears to be competitive with the Tinker-OpenMM GPU implementation of Tinker. As the system size grows, Tinker-HP remains operational thanks to its access to distributed memory and takes advantage of its new algorithmic enabling for stable long timescale polarizable simulations. Overall, a several thousand-fold acceleration over a single-core computation is observed for the largest systems. The extension of the present CPU implementation of Tinker-HP to other computational platforms is discussed.

  7. MULTISCALE MODEL OF CRISPR-INDUCED COEVOLUTIONARY DYNAMICS: DIVERSIFICATION AT THE INTERFACE OF LAMARCK AND DARWIN

    PubMed Central

    Childs, Lauren M; Held, Nicole L; Young, Mark J; Whitaker, Rachel J; Weitz, Joshua S

    2012-01-01

    The CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) system is a recently discovered type of adaptive immune defense in bacteria and archaea that functions via directed incorporation of viral and plasmid DNA into host genomes. Here, we introduce a multiscale model of dynamic coevolution between hosts and viruses in an ecological context that incorporates CRISPR immunity principles. We analyze the model to test whether and how CRISPR immunity induces host and viral diversification and the maintenance of many coexisting strains. We show that hosts and viruses coevolve to form highly diverse communities. We observe the punctuated replacement of existent strains, such that populations have very low similarity compared over the long term. However, in the short term, we observe evolutionary dynamics consistent with both incomplete selective sweeps of novel strains (as single strains and coalitions) and the recurrence of previously rare strains. Coalitions of multiple dominant host strains are predicted to arise because host strains can have nearly identical immune phenotypes mediated by CRISPR defense albeit with different genotypes. We close by discussing how our explicit eco-evolutionary model of CRISPR immunity can help guide efforts to understand the drivers of diversity seen in microbial communities where CRISPR systems are active. PMID:22759281

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

    NASA Astrophysics Data System (ADS)

    Comer, Joanne; Indiana Olbert, Agnieszka; Nash, Stephen; Hartnett, Michael

    2017-02-01

    Urban developments in coastal zones are often exposed to natural hazards such as flooding. In this research, a state-of-the-art, multi-scale nested flood (MSN_Flood) model is applied to simulate complex coastal-fluvial urban flooding due to combined effects of tides, surges and river discharges. Cork city on Ireland's southwest coast is a study case. The flood modelling system comprises a cascade of four dynamically linked models that resolve the hydrodynamics of Cork Harbour and/or its sub-region at four scales: 90, 30, 6 and 2 m. Results demonstrate that the internalization of the nested boundary through the use of ghost cells combined with a tailored adaptive interpolation technique creates a highly dynamic moving boundary that permits flooding and drying of the nested boundary. This novel feature of MSN_Flood provides a high degree of choice regarding the location of the boundaries to the nested domain and therefore flexibility in model application. The nested MSN_Flood model through dynamic downscaling facilitates significant improvements in accuracy of model output without incurring the computational expense of high spatial resolution over the entire model domain. The urban flood model provides full characteristics of water levels and flow regimes necessary for flood hazard identification and flood risk assessment.

  9. Supergranulation and multiscale flows in the solar photosphere. Global observations vs. a theory of anisotropic turbulent convection

    NASA Astrophysics Data System (ADS)

    Rincon, F.; Roudier, T.; Schekochihin, A. A.; Rieutord, M.

    2017-03-01

    The Sun provides us with the only spatially well-resolved astrophysical example of turbulent thermal convection. While various aspects of solar photospheric turbulence, such as granulation (one-Megameter horizontal scale), are well understood, the questions of the physical origin and dynamical organization of larger-scale flows, such as the 30-Megameters supergranulation and flows deep in the solar convection zone, remain largely open in spite of their importance for solar dynamics and magnetism. Here, we present a new critical global observational characterization of multiscale photospheric flows and subsequently formulate an anisotropic extension of the Bolgiano-Obukhov theory of hydrodynamic stratified turbulence that may explain several of their distinctive dynamical properties. Our combined analysis suggests that photospheric flows in the horizontal range of scales between supergranulation and granulation have a typical vertical correlation scale of 2.5 to 4 Megameters and operate in a strongly anisotropic, self-similar, nonlinear, buoyant dynamical regime. While the theory remains speculative at this stage, it lends itself to quantitative comparisons with future high-resolution acoustic tomography of subsurface layers and advanced numerical models. Such a validation exercise may also lead to new insights into the asymptotic dynamical regimes in which other, unresolved turbulent anisotropic astrophysical fluid systems supporting waves or instabilities operate.

  10. Multivariate multiscale entropy of financial markets

    NASA Astrophysics Data System (ADS)

    Lu, Yunfan; Wang, Jun

    2017-11-01

    In current process of quantifying the dynamical properties of the complex phenomena in financial market system, the multivariate financial time series are widely concerned. In this work, considering the shortcomings and limitations of univariate multiscale entropy in analyzing the multivariate time series, the multivariate multiscale sample entropy (MMSE), which can evaluate the complexity in multiple data channels over different timescales, is applied to quantify the complexity of financial markets. Its effectiveness and advantages have been detected with numerical simulations with two well-known synthetic noise signals. For the first time, the complexity of four generated trivariate return series for each stock trading hour in China stock markets is quantified thanks to the interdisciplinary application of this method. We find that the complexity of trivariate return series in each hour show a significant decreasing trend with the stock trading time progressing. Further, the shuffled multivariate return series and the absolute multivariate return series are also analyzed. As another new attempt, quantifying the complexity of global stock markets (Asia, Europe and America) is carried out by analyzing the multivariate returns from them. Finally we utilize the multivariate multiscale entropy to assess the relative complexity of normalized multivariate return volatility series with different degrees.

  11. Multiscale entropy analysis of human gait dynamics

    NASA Astrophysics Data System (ADS)

    Costa, M.; Peng, C.-K.; L. Goldberger, Ary; Hausdorff, Jeffrey M.

    2003-12-01

    We compare the complexity of human gait time series from healthy subjects under different conditions. Using the recently developed multiscale entropy algorithm, which provides a way to measure complexity over a range of scales, we observe that normal spontaneous walking has the highest complexity when compared to slow and fast walking and also to walking paced by a metronome. These findings have implications for modeling locomotor control and for quantifying gait dynamics in physiologic and pathologic states.

  12. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

  14. Predictive Models for Dynamic Brittle Fracture and Damage at High-velocity Impact in Multilayered Targets

    DTIC Science & Technology

    2016-11-01

    layered glass/PC systems,Functionally Graded Materials (FGMs), polycrystalline AlON, and fiber-reinforced composite (FRC) materials. For the first time we...multi-layered glass/PC systems,Functionally Graded Materials (FGMs), polycrystalline AlON, and fiber-reinforced composite (FRC) materials. For the... Composite Lamina with Peridynamics, International Journal for Multiscale Computational Engineering, (12 2011): 0. doi: Florin Bobaru, Youn Doh Ha

  15. Multiscale systems biology of trauma-induced coagulopathy.

    PubMed

    Tsiklidis, Evan; Sims, Carrie; Sinno, Talid; Diamond, Scott L

    2018-07-01

    Trauma with hypovolemic shock is an extreme pathological state that challenges the body to maintain blood pressure and oxygenation in the face of hemorrhagic blood loss. In conjunction with surgical actions and transfusion therapy, survival requires the patient's blood to maintain hemostasis to stop bleeding. The physics of the problem are multiscale: (a) the systemic circulation sets the global blood pressure in response to blood loss and resuscitation therapy, (b) local tissue perfusion is altered by localized vasoregulatory mechanisms and bleeding, and (c) altered blood and vessel biology resulting from the trauma as well as local hemodynamics control the assembly of clotting components at the site of injury. Building upon ongoing modeling efforts to simulate arterial or venous thrombosis in a diseased vasculature, computer simulation of trauma-induced coagulopathy is an emerging approach to understand patient risk and predict response. Despite uncertainties in quantifying the patient's dynamic injury burden, multiscale systems biology may help link blood biochemistry at the molecular level to multiorgan responses in the bleeding patient. As an important goal of systems modeling, establishing early metrics of a patient's high-dimensional trajectory may help guide transfusion therapy or warn of subsequent later stage bleeding or thrombotic risks. This article is categorized under: Analytical and Computational Methods > Computational Methods Biological Mechanisms > Regulatory Biology Models of Systems Properties and Processes > Mechanistic Models. © 2018 Wiley Periodicals, Inc.

  16. DIAGNOSTIC EVALUATION OF NUMBERICAL AIR QUALITY MODELS WITH SPECIALIZED AMBIENT OBSERVATIONS: TESTING THE COMMUNITY MULTISCALE AIR QUALITY MODELING SYSTEM (CMAQ) AT SELECTED SOS 95 GROUND SITES

    EPA Science Inventory

    Three probes for diagnosing photochemical dynamics are presented and applied to specialized ambient surface-level observations and to a numerical photochemical model to better understand rates of production and other process information in the atmosphere and in the model. Howeve...

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

    PubMed Central

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

    2014-01-01

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

  18. Multiscale analysis of the correlation of processing parameters on viscidity of composites fabricated by automated fiber placement

    NASA Astrophysics Data System (ADS)

    Han, Zhenyu; Sun, Shouzheng; Fu, Yunzhong; Fu, Hongya

    2017-10-01

    Viscidity is an important physical indicator for assessing fluidity of resin that is beneficial to contact resin with the fibers effectively and reduce manufacturing defects during automated fiber placement (AFP) process. However, the effect of processing parameters on viscidity evolution is rarely studied during AFP process. In this paper, viscidities under different scales are analyzed based on multi-scale analysis method. Firstly, viscous dissipation energy (VDE) within meso-unit under different processing parameters is assessed by using finite element method (FEM). According to multi-scale energy transfer model, meso-unit energy is used as the boundary condition for microscopic analysis. Furthermore, molecular structure of micro-system is built by molecular dynamics (MD) method. And viscosity curves are then obtained by integrating stress autocorrelation function (SACF) with time. Finally, the correlation characteristics of processing parameters to viscosity are revealed by using gray relational analysis method (GRAM). A group of processing parameters is found out to achieve the stability of viscosity and better fluidity of resin.

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

    PubMed

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

    2014-01-01

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

  20. Enhancement tuning and control for high dynamic range images in multi-scale locally adaptive contrast enhancement algorithms

    NASA Astrophysics Data System (ADS)

    Cvetkovic, Sascha D.; Schirris, Johan; de With, Peter H. N.

    2009-01-01

    For real-time imaging in surveillance applications, visibility of details is of primary importance to ensure customer confidence. If we display High Dynamic-Range (HDR) scenes whose contrast spans four or more orders of magnitude on a conventional monitor without additional processing, results are unacceptable. Compression of the dynamic range is therefore a compulsory part of any high-end video processing chain because standard monitors are inherently Low- Dynamic Range (LDR) devices with maximally two orders of display dynamic range. In real-time camera processing, many complex scenes are improved with local contrast enhancements, bringing details to the best possible visibility. In this paper, we show how a multi-scale high-frequency enhancement scheme, in which gain is a non-linear function of the detail energy, can be used for the dynamic range compression of HDR real-time video camera signals. We also show the connection of our enhancement scheme to the processing way of the Human Visual System (HVS). Our algorithm simultaneously controls perceived sharpness, ringing ("halo") artifacts (contrast) and noise, resulting in a good balance between visibility of details and non-disturbance of artifacts. The overall quality enhancement, suitable for both HDR and LDR scenes, is based on a careful selection of the filter types for the multi-band decomposition and a detailed analysis of the signal per frequency band.

  1. 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...

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

    PubMed

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

    2017-11-25

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

  3. Magnetospheric Multiscale (MMS) [video

    NASA Image and Video Library

    2014-05-09

    MMS Spacecraft Animation The Magnetospheric Multiscale (MMS) mission is a Solar Terrestrial Probes mission comprising four identically instrumented spacecraft that will use Earth's magnetosphere as a laboratory to study the microphysics of three fundamental plasma processes: magnetic reconnection, energetic particle acceleration, and turbulence. These processes occur in all astrophysical plasma systems but can be studied in situ only in our solar system and most efficiently only in Earth's magnetosphere, where they control the dynamics of the geospace environment and play an important role in the processes known as "space weather." Learn more about MMS at www.nasa.gov/mms Learn more about MMS at www.nasa.gov/mms Credit NASA/Goddard The Magnetospheric Multiscale, or MMS, will study how the sun and the Earth's magnetic fields connect and disconnect, an explosive process that can accelerate particles through space to nearly the speed of light. This process is called magnetic reconnection and can occur throughout all space. NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

  4. Magnetospheric Multiscale (MMS)

    NASA Image and Video Library

    2017-12-08

    MMS Spacecraft Animation The Magnetospheric Multiscale (MMS) mission is a Solar Terrestrial Probes mission comprising four identically instrumented spacecraft that will use Earth's magnetosphere as a laboratory to study the microphysics of three fundamental plasma processes: magnetic reconnection, energetic particle acceleration, and turbulence. These processes occur in all astrophysical plasma systems but can be studied in situ only in our solar system and most efficiently only in Earth's magnetosphere, where they control the dynamics of the geospace environment and play an important role in the processes known as "space weather." Learn more about MMS at www.nasa.gov/mms Learn more about MMS at www.nasa.gov/mms Credit NASA/Chris Gunn The Magnetospheric Multiscale, or MMS, will study how the sun and the Earth's magnetic fields connect and disconnect, an explosive process that can accelerate particles through space to nearly the speed of light. This process is called magnetic reconnection and can occur throughout all space. NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

  5. Decreased complexity of glucose dynamics in diabetes: evidence from multiscale entropy analysis of continuous glucose monitoring system data.

    PubMed

    Chen, Jin-Long; Chen, Pin-Fan; Wang, Hung-Ming

    2014-07-15

    Parameters of glucose dynamics recorded by the continuous glucose monitoring system (CGMS) could help in the control of glycemic fluctuations, which is important in diabetes management. Multiscale entropy (MSE) analysis has recently been developed to measure the complexity of physical and physiological time sequences. A reduced MSE complexity index indicates the increased repetition patterns of the time sequence, and, thus, a decreased complexity in this system. No study has investigated the MSE analysis of glucose dynamics in diabetes. This study was designed to compare the complexity of glucose dynamics between the diabetic patients (n = 17) and the control subjects (n = 13), who were matched for sex, age, and body mass index via MSE analysis using the CGMS data. Compared with the control subjects, the diabetic patients revealed a significant increase (P < 0.001) in the mean (diabetic patients 166.0 ± 10.4 vs. control subjects 93.3 ± 1.5 mg/dl), the standard deviation (51.7 ± 4.3 vs. 11.1 ± 0.5 mg/dl), and the mean amplitude of glycemic excursions (127.0 ± 9.2 vs. 27.7 ± 1.3 mg/dl) of the glucose levels; and a significant decrease (P < 0.001) in the MSE complexity index (5.09 ± 0.23 vs. 7.38 ± 0.28). In conclusion, the complexity of glucose dynamics is decreased in diabetes. This finding implies the reactivity of glucoregulation is impaired in the diabetic patients. Such impairment presenting as an increased regularity of glycemic fluctuating pattern could be detected by MSE analysis. Thus, the MSE complexity index could potentially be used as a biomarker in the monitoring of diabetes.

  6. Multiscale Physical and Biological Dynamics in the Philippines Archipelago: Predictions and Processes

    DTIC Science & Technology

    2011-01-01

    for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE 2010 2. REPORT...TYPE 3. DATES COVERED 00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE MultiscalePhysical and Biological Dynamics in the Philippines Archipelago...chemistry,  and   radioisotopes  in  the  Southeast  Asian  Basins.  J.  Geophys.  Res.,  91:14,345-­‐14,354.   Cabrera

  7. A Multimode Optical Imaging System for Preclinical Applications In Vivo: Technology Development, Multiscale Imaging, and Chemotherapy Assessment

    PubMed Central

    Hwang, Jae Youn; Wachsmann-Hogiu, Sebastian; Ramanujan, V. Krishnan; Ljubimova, Julia; Gross, Zeev; Gray, Harry B.; Medina-Kauwe, Lali K.; Farkas, Daniel L.

    2012-01-01

    Purpose Several established optical imaging approaches have been applied, usually in isolation, to preclinical studies; however, truly useful in vivo imaging may require a simultaneous combination of imaging modalities to examine dynamic characteristics of cells and tissues. We developed a new multimode optical imaging system designed to be application-versatile, yielding high sensitivity, and specificity molecular imaging. Procedures We integrated several optical imaging technologies, including fluorescence intensity, spectral, lifetime, intravital confocal, two-photon excitation, and bioluminescence, into a single system that enables functional multiscale imaging in animal models. Results The approach offers a comprehensive imaging platform for kinetic, quantitative, and environmental analysis of highly relevant information, with micro-to-macroscopic resolution. Applied to small animals in vivo, this provides superior monitoring of processes of interest, represented here by chemo-/nanoconstruct therapy assessment. Conclusions This new system is versatile and can be optimized for various applications, of which cancer detection and targeted treatment are emphasized here. PMID:21874388

  8. Multiscaling for systems with a broad continuum of characteristic lengths and times: Structural transitions in nanocomposites.

    PubMed

    Pankavich, S; Ortoleva, P

    2010-06-01

    The multiscale approach to N-body systems is generalized to address the broad continuum of long time and length scales associated with collective behaviors. A technique is developed based on the concept of an uncountable set of time variables and of order parameters (OPs) specifying major features of the system. We adopt this perspective as a natural extension of the commonly used discrete set of time scales and OPs which is practical when only a few, widely separated scales exist. The existence of a gap in the spectrum of time scales for such a system (under quasiequilibrium conditions) is used to introduce a continuous scaling and perform a multiscale analysis of the Liouville equation. A functional-differential Smoluchowski equation is derived for the stochastic dynamics of the continuum of Fourier component OPs. A continuum of spatially nonlocal Langevin equations for the OPs is also derived. The theory is demonstrated via the analysis of structural transitions in a composite material, as occurs for viral capsids and molecular circuits.

  9. Active learning of constitutive relation from mesoscopic dynamics for macroscopic modeling of non-Newtonian flows

    NASA Astrophysics Data System (ADS)

    Zhao, Lifei; Li, Zhen; Caswell, Bruce; Ouyang, Jie; Karniadakis, George Em

    2018-06-01

    We simulate complex fluids by means of an on-the-fly coupling of the bulk rheology to the underlying microstructure dynamics. In particular, a continuum model of polymeric fluids is constructed without a pre-specified constitutive relation, but instead it is actively learned from mesoscopic simulations where the dynamics of polymer chains is explicitly computed. To couple the bulk rheology of polymeric fluids and the microscale dynamics of polymer chains, the continuum approach (based on the finite volume method) provides the transient flow field as inputs for the (mesoscopic) dissipative particle dynamics (DPD), and in turn DPD returns an effective constitutive relation to close the continuum equations. In this multiscale modeling procedure, we employ an active learning strategy based on Gaussian process regression (GPR) to minimize the number of expensive DPD simulations, where adaptively selected DPD simulations are performed only as necessary. Numerical experiments are carried out for flow past a circular cylinder of a non-Newtonian fluid, modeled at the mesoscopic level by bead-spring chains. The results show that only five DPD simulations are required to achieve an effective closure of the continuum equations at Reynolds number Re = 10. Furthermore, when Re is increased to 100, only one additional DPD simulation is required for constructing an extended GPR-informed model closure. Compared to traditional message-passing multiscale approaches, applying an active learning scheme to multiscale modeling of non-Newtonian fluids can significantly increase the computational efficiency. Although the method demonstrated here obtains only a local viscosity from the polymer dynamics, it can be extended to other multiscale models of complex fluids whose macro-rheology is unknown.

  10. Effects of polymer graft properties on protein adsorption and transport in ion exchange chromatography: a multiscale modeling study.

    PubMed

    Basconi, Joseph E; Carta, Giorgio; Shirts, Michael R

    2015-04-14

    Multiscale simulation is used to study the adsorption of lysozyme onto ion exchangers obtained by grafting charged polymers into a porous matrix, in systems with various polymer properties and strengths of electrostatic interaction. Molecular dynamics simulations show that protein partitioning into the polymer-filled pore space increases with the overall charge content of the polymers, while the diffusivity in the pore space decreases. However, the combination of greatly increased partitioning and modestly decreased diffusion results in macroscopic transport rates that increase as a function of charge content, as the large concentration driving force due to enhanced pore space partitioning outweighs the reduction in the pore space diffusivity. Matrices having greater charge associated with the grafted polymers also exhibit more diffuse intraparticle concentration profiles during transient adsorption. In systems with a high charge content per polymer and a low protein loading, the polymers preferentially partition toward the surface due to favorable interactions with the surface-bound protein. These results demonstrate the potential of multiscale modeling to illuminate qualitative trends between molecular properties and the adsorption equilibria and kinetic properties observable on macroscopic scales.

  11. Multiscale high-order/low-order (HOLO) algorithms and applications

    NASA Astrophysics Data System (ADS)

    Chacón, L.; Chen, G.; Knoll, D. A.; Newman, C.; Park, H.; Taitano, W.; Willert, J. A.; Womeldorff, G.

    2017-02-01

    We review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.

  12. Multiscale modelling for tokamak pedestals

    NASA Astrophysics Data System (ADS)

    Abel, I. G.

    2018-04-01

    Pedestal modelling is crucial to predict the performance of future fusion devices. Current modelling efforts suffer either from a lack of kinetic physics, or an excess of computational complexity. To ameliorate these problems, we take a first-principles multiscale approach to the pedestal. We will present three separate sets of equations, covering the dynamics of edge localised modes (ELMs), the inter-ELM pedestal and pedestal turbulence, respectively. Precisely how these equations should be coupled to each other is covered in detail. This framework is completely self-consistent; it is derived from first principles by means of an asymptotic expansion of the fundamental Vlasov-Landau-Maxwell system in appropriate small parameters. The derivation exploits the narrowness of the pedestal region, the smallness of the thermal gyroradius and the low plasma (the ratio of thermal to magnetic pressures) typical of current pedestal operation to achieve its simplifications. The relationship between this framework and gyrokinetics is analysed, and possibilities to directly match our systems of equations onto multiscale gyrokinetics are explored. A detailed comparison between our model and other models in the literature is performed. Finally, the potential for matching this framework onto an open-field-line region is briefly discussed.

  13. Multistructure index in revealing complexity of regulatory mechanisms of human cardiovascular system at rest and orthostatic stress in healthy humans

    NASA Astrophysics Data System (ADS)

    Makowiec, Danuta; Graff, Beata; Struzik, Zbigniew R.

    2017-02-01

    Biological regulation is sufficiently complex to pose an enduring challenge for characterization of both its equilibrium and transient non-equilibrium dynamics. Two univariate but coupled observables, heart rate and systolic blood pressure, are commonly characterized in the benchmark example of the human cardiovascular regulatory system. Asymmetric distributions of accelerations and decelerations of heart rate, as well as rises and falls in systolic blood pressure, recorded in humans during a head-up tilt test provide insights into the dynamics of cardiovascular response to a rapid, controlled deregulation of the system's homeostasis. The baroreflex feedback loop is assumed to be the fundamental physiological mechanism for ensuring homeostatic blood supply to distant organs at rest and during orthostatic stress, captured in a classical beat-to-beat autoregressive model of baroreflex by de Boer et al. (1987). For model corroboration, a multistructure index statistic is proposed, seamlessly evaluating the size spectrum of magnitudes of neural reflexes such as baroreflex, responsible for maintaining the homeostatic dynamics. The multistructure index exposes a distinctly different dynamics of multiscale asymmetry between results obtained from real-life signals recorded from healthy subjects and those simulated using both the classical and perturbed versions of the model. Nonlinear effects observed suggest the pronounced presence of complex mechanisms resulting from baroreflex regulation when a human is at rest, which is aggravated in the system's response to orthostatic stress. Using our methodology of multistructure index, we therefore show a marked difference between model and real-life scenarios, which we attribute to multiscale asymmetry of non-linear origin in real-life signals, which we are not reproducible by the classical model.

  14. Contour Tracking in Echocardiographic Sequences via Sparse Representation and Dictionary Learning

    PubMed Central

    Huang, Xiaojie; Dione, Donald P.; Compas, Colin B.; Papademetris, Xenophon; Lin, Ben A.; Bregasi, Alda; Sinusas, Albert J.; Staib, Lawrence H.; Duncan, James S.

    2013-01-01

    This paper presents a dynamical appearance model based on sparse representation and dictionary learning for tracking both endocardial and epicardial contours of the left ventricle in echocardiographic sequences. Instead of learning offline spatiotemporal priors from databases, we exploit the inherent spatiotemporal coherence of individual data to constraint cardiac contour estimation. The contour tracker is initialized with a manual tracing of the first frame. It employs multiscale sparse representation of local image appearance and learns online multiscale appearance dictionaries in a boosting framework as the image sequence is segmented frame-by-frame sequentially. The weights of multiscale appearance dictionaries are optimized automatically. Our region-based level set segmentation integrates a spectrum of complementary multilevel information including intensity, multiscale local appearance, and dynamical shape prediction. The approach is validated on twenty-six 4D canine echocardiographic images acquired from both healthy and post-infarct canines. The segmentation results agree well with expert manual tracings. The ejection fraction estimates also show good agreement with manual results. Advantages of our approach are demonstrated by comparisons with a conventional pure intensity model, a registration-based contour tracker, and a state-of-the-art database-dependent offline dynamical shape model. We also demonstrate the feasibility of clinical application by applying the method to four 4D human data sets. PMID:24292554

  15. Dynamic information routing in complex networks

    PubMed Central

    Kirst, Christoph; Timme, Marc; Battaglia, Demian

    2016-01-01

    Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function. PMID:27067257

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

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

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

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

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

  18. Multiscale modeling of current-induced switching in magnetic tunnel junctions using ab initio spin-transfer torques

    NASA Astrophysics Data System (ADS)

    Ellis, Matthew O. A.; Stamenova, Maria; Sanvito, Stefano

    2017-12-01

    There exists a significant challenge in developing efficient magnetic tunnel junctions with low write currents for nonvolatile memory devices. With the aim of analyzing potential materials for efficient current-operated magnetic junctions, we have developed a multi-scale methodology combining ab initio calculations of spin-transfer torque with large-scale time-dependent simulations using atomistic spin dynamics. In this work we introduce our multiscale approach, including a discussion on a number of possible schemes for mapping the ab initio spin torques into the spin dynamics. We demonstrate this methodology on a prototype Co/MgO/Co/Cu tunnel junction showing that the spin torques are primarily acting at the interface between the Co free layer and MgO. Using spin dynamics we then calculate the reversal switching times for the free layer and the critical voltages and currents required for such switching. Our work provides an efficient, accurate, and versatile framework for designing novel current-operated magnetic devices, where all the materials details are taken into account.

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

    DOE PAGES

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

    2018-04-04

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

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

    PubMed

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

    2017-12-05

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

  1. Multi-scale correlations in different futures markets

    NASA Astrophysics Data System (ADS)

    Bartolozzi, M.; Mellen, C.; di Matteo, T.; Aste, T.

    2007-07-01

    In the present work we investigate the multiscale nature of the correlations for high frequency data (1 min) in different futures markets over a period of two years, starting on the 1st of January 2003 and ending on the 31st of December 2004. In particular, by using the concept of local Hurst exponent, we point out how the behaviour of this parameter, usually considered as a benchmark for persistency/antipersistency recognition in time series, is largely time-scale dependent in the market context. These findings are a direct consequence of the intrinsic complexity of a system where trading strategies are scale-adaptive. Moreover, our analysis points out different regimes in the dynamical behaviour of the market indices under consideration.

  2. Antipsychotics reverse abnormal EEG complexity in drug-naïve schizophrenia: A multiscale entropy analysis

    PubMed Central

    Takahashi, Tetsuya; Cho, Raymond Y.; Mizuno, Tomoyuki; Kikuchi, Mitsuru; Murata, Tetsuhito; Takahashi, Koichi; Wada, Yuji

    2010-01-01

    Multiscale entropy (MSE) analysis is a novel entropy-based approach for measuring dynamical complexity in physiological systems over a range of temporal scales. To evaluate this analytic approach as an aid to elucidating the pathophysiologic mechanisms in schizophrenia, we examined MSE in EEG activity in drug-naïve schizophrenia subjects pre- and post-treatment with antipsychotics in comparison with traditional EEG analysis. We recorded eyes-closed resting state EEG from frontal, temporal, parietal and occipital regions in drug-naïve 22 schizophrenia and 24 age-matched healthy control subjects. Fifteen patients were re-evaluated within 2–8 weeks after the initiation of antipsychotic treatment. For each participant, MSE was calculated on one continuous 60 second epoch for each experimental session. Schizophrenia subjects showed significantly higher complexity at higher time scales (lower frequencies), than that of healthy controls in fronto-centro-temporal, but not in parieto-occipital regions. Post-treatment, this higher complexity decreased to healthy control subject levels selectively in fronto-central regions, while the increased complexity in temporal sites remained higher. Comparative power analysis identified spectral slowing in frontal regions in pre-treatment schizophrenia subjects, consistent with previous findings, whereas no antipsychotic treatment effect was observed. In summary, multiscale entropy measures identified abnormal dynamical EEG signal complexity in anterior brain areas in schizophrenia that normalized selectively in fronto-central areas with antipsychotic treatment. These findings show that entropy-based analytic methods may serve as a novel approach for characterizing and understanding abnormal cortical dynamics in schizophrenia, and elucidating the therapeutic mechanisms of antipsychotics. PMID:20149880

  3. Nonlinear multiscale interactions and internal dynamics underlying a typical eddy-shedding event at Luzon Strait

    NASA Astrophysics Data System (ADS)

    Zhao, Yuan-Bing; Liang, X. San; Gan, Jianping

    2016-11-01

    Eddy-shedding is a highly nonlinear process that presents a major challenge in geophysical fluid dynamics. Using the newly developed localized multiscale energy and vorticity analysis (MS-EVA), this study investigates an observed typical warm eddy-shedding event as the Kuroshio passes the Luzon Strait, in order to gain insight into the underlying internal dynamics. Through multiscale window transform (MWT), it is found that the loop-form Kuroshio intrusion into the South China Sea (SCS) is not a transient feature, but a quasi-equilibrium state of the system. A mesoscale reconstruction reveals that the eddy does not have its origin at the intrusion path, but comes from the Northwest Pacific. It propagates westward, preceded by a cyclonic (cold) eddy, through the Kuroshio into the SCS. As the eddy pair runs across the main current, the cold one weakens and the warm one intensifies through a mixed instability. In its development, another cold eddy is generated to its southeast, which also experiences a mixed instability. It develops rapidly and cuts the warm eddy off the stream. Both the warm and cold eddies then propagate westward in the form of a Rossby wave (first baroclinic mode). As the eddies approach the Dongsha Islands, they experience another baroclinic instability, accompanied by a sudden accumulation of eddy available potential energy. This part of potential energy is converted to eddy kinetic energy through buoyancy conversion, and is afterward transferred back to the large-scale field through inverse cascading, greatly reducing the intensity of the eddy and eventually leading to its demise.

  4. From seconds to months: an overview of multi-scale dynamics of mobile telephone calls

    NASA Astrophysics Data System (ADS)

    Saramäki, Jari; Moro, Esteban

    2015-06-01

    Big Data on electronic records of social interactions allow approaching human behaviour and sociality from a quantitative point of view with unforeseen statistical power. Mobile telephone Call Detail Records (CDRs), automatically collected by telecom operators for billing purposes, have proven especially fruitful for understanding one-to-one communication patterns as well as the dynamics of social networks that are reflected in such patterns. We present an overview of empirical results on the multi-scale dynamics of social dynamics and networks inferred from mobile telephone calls. We begin with the shortest timescales and fastest dynamics, such as burstiness of call sequences between individuals, and "zoom out" towards longer temporal and larger structural scales, from temporal motifs formed by correlated calls between multiple individuals to long-term dynamics of social groups. We conclude this overview with a future outlook.

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

    Du, Qiang

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

  6. Voltage Imaging of Waking Mouse Cortex Reveals Emergence of Critical Neuronal Dynamics

    PubMed Central

    Scott, Gregory; Fagerholm, Erik D.; Mutoh, Hiroki; Leech, Robert; Sharp, David J.; Shew, Woodrow L.

    2014-01-01

    Complex cognitive processes require neuronal activity to be coordinated across multiple scales, ranging from local microcircuits to cortex-wide networks. However, multiscale cortical dynamics are not well understood because few experimental approaches have provided sufficient support for hypotheses involving multiscale interactions. To address these limitations, we used, in experiments involving mice, genetically encoded voltage indicator imaging, which measures cortex-wide electrical activity at high spatiotemporal resolution. Here we show that, as mice recovered from anesthesia, scale-invariant spatiotemporal patterns of neuronal activity gradually emerge. We show for the first time that this scale-invariant activity spans four orders of magnitude in awake mice. In contrast, we found that the cortical dynamics of anesthetized mice were not scale invariant. Our results bridge empirical evidence from disparate scales and support theoretical predictions that the awake cortex operates in a dynamical regime known as criticality. The criticality hypothesis predicts that small-scale cortical dynamics are governed by the same principles as those governing larger-scale dynamics. Importantly, these scale-invariant principles also optimize certain aspects of information processing. Our results suggest that during the emergence from anesthesia, criticality arises as information processing demands increase. We expect that, as measurement tools advance toward larger scales and greater resolution, the multiscale framework offered by criticality will continue to provide quantitative predictions and insight on how neurons, microcircuits, and large-scale networks are dynamically coordinated in the brain. PMID:25505314

  7. Analysis of Hepatitis C Virus Decline during Treatment with the Protease Inhibitor Danoprevir Using a Multiscale Model

    DOE PAGES

    Rong, Libin; Guedj, Jeremie; Dahari, Harel; ...

    2013-03-14

    The current paradigm for studying hepatitis C virus (HCV) dynamics in patients utilizes a standard viral dynamic model that keeps track of uninfected (target) cells, infected cells, and virus. The model does not account for the dynamics of intracellular viral replication, which is the major target of direct-acting antiviral agents (DAAs). In this paper, we describe and study a recently developed multiscale age-structured model that explicitly considers the potential effects of DAAs on intracellular viral RNA production, degradation, and secretion as virus into the circulation. We show that when therapy significantly blocks both intracellular viral RNA production and virus secretion,more » the serum viral load decline has three phases, with slopes reflecting the rate of serum viral clearance, the rate of loss of intracellular viral RNA, and the rate of loss of intracellular replication templates and infected cells, respectively. We also derive analytical approximations of the multiscale model and use one of them to analyze data from patients treated for 14 days with the HCV protease inhibitor danoprevir. Analysis suggests that danoprevir significantly blocks intracellular viral production (with mean effectiveness 99.2%), enhances intracellular viral RNA degradation about 5-fold, and moderately inhibits viral secretion (with mean effectiveness 56%). Finally, the multiscale model can be used to study viral dynamics in patients treated with other DAAs and explore their mechanisms of action in treatment of hepatitis C.« less

  8. 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.

  9. A complete categorization of multiscale models of infectious disease systems.

    PubMed

    Garira, Winston

    2017-12-01

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

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

    PubMed Central

    Mathur, Rohit; Xing, Jia; Gilliam, Robert; Sarwar, Golam; Hogrefe, Christian; Pleim, Jonathan; Pouliot, George; Roselle, Shawn; Spero, Tanya L.; Wong, David C.; Young, Jeffrey

    2018-01-01

    The Community Multiscale Air Quality (CMAQ) modeling system is extended to simulate ozone, particulate matter, and related precursor distributions throughout the Northern Hemisphere. Modelled processes were examined and enhanced to suitably represent the extended space and time scales for such applications. Hemispheric scale simulations with CMAQ and the Weather Research and Forecasting (WRF) model are performed for multiple years. Model capabilities for a range of applications including episodic long-range pollutant transport, long-term trends in air pollution across the Northern Hemisphere, and air pollution-climate interactions are evaluated through detailed comparison with available surface, aloft, and remotely sensed observations. The expansion of CMAQ to simulate the hemispheric scales provides a framework to examine interactions between atmospheric processes occurring at various spatial and temporal scales with physical, chemical, and dynamical consistency. PMID:29681922

  11. MMS at NRL

    NASA Image and Video Library

    2014-08-04

    A photograph showing what all four Magnetospheric Multiscale (MMS) spacecraft look like when stacked is seen taped to the window of a Naval Research Laboratory cleanroom where one of the four spacecraft is undergoing testing, Monday, August 4, 2014, in Washington. The Magnetospheric Multiscale, or MMS, mission will study the mystery of how magnetic fields around Earth connect and disconnect, explosively releasing energy via a process known as magnetic reconnection. The four identical spacecraft are scheduled to launch in 2015 from Cape Canaveral and will orbit around Earth in varying formations through the dynamic magnetic system surrounding our planet to provide the first three-dimensional views of the magnetic reconnection process. The goal of the STP Program is to understand the fundamental physical processes of the space environment from the sun to Earth, other planets, and the extremes of the solar system boundary. Photo Credit: (NASA/Bill Ingalls)

  12. Multiscale numerical simulations of magnetoconvection at low magnetic Prandtl and Rossby numbers.

    NASA Astrophysics Data System (ADS)

    Maffei, S.; Calkins, M. A.; Julien, K. A.; Marti, P.

    2017-12-01

    The dynamics of the Earth's outer core is characterized by low values of the Rossby (Ro), Ekman and magnetic Prandtl numbers. These values indicate the large spectra of temporal and spatial scales that need to be accounted for in realistic numerical simulations of the system. Current direct numerical simulation are not capable of reaching this extreme regime, suggesting that a new class of models is required to account for the rich dynamics expected in the natural system. Here we present results from a quasi-geostrophic, multiscale model based on the scale separation implied by the low Ro typical of rapidly rotating systems. We investigate a plane layer geometry where convection is driven by an imposed temperature gradient and the hydrodynamic equations are modified by a large scale magnetic field. Analytical investigation shows that at values of thermal and magnetic Prandtl numbers relevant for liquid metals, the energetic requirements for the onset of convection is not significantly altered even in the presence of strong magnetic fields. Results from strongly forced nonlinear numerical simulations show the presence of an inverse cascade, typical of 2-D turbulence, when no or weak magnetic field is applied. For higher values of the magnetic field the inverse cascade is quenched.

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

    Fogarty, Aoife C., E-mail: fogarty@mpip-mainz.mpg.de; Potestio, Raffaello, E-mail: potestio@mpip-mainz.mpg.de; Kremer, Kurt, E-mail: kremer@mpip-mainz.mpg.de

    A fully atomistic modelling of many biophysical and biochemical processes at biologically relevant length- and time scales is beyond our reach with current computational resources, and one approach to overcome this difficulty is the use of multiscale simulation techniques. In such simulations, when system properties necessitate a boundary between resolutions that falls within the solvent region, one can use an approach such as the Adaptive Resolution Scheme (AdResS), in which solvent particles change their resolution on the fly during the simulation. Here, we apply the existing AdResS methodology to biomolecular systems, simulating a fully atomistic protein with an atomistic hydrationmore » shell, solvated in a coarse-grained particle reservoir and heat bath. Using as a test case an aqueous solution of the regulatory protein ubiquitin, we first confirm the validity of the AdResS approach for such systems, via an examination of protein and solvent structural and dynamical properties. We then demonstrate how, in addition to providing a computational speedup, such a multiscale AdResS approach can yield otherwise inaccessible physical insights into biomolecular function. We use our methodology to show that protein structure and dynamics can still be correctly modelled using only a few shells of atomistic water molecules. We also discuss aspects of the AdResS methodology peculiar to biomolecular simulations.« less

  14. Stochastic Ocean Predictions with Dynamically-Orthogonal Primitive Equations

    NASA Astrophysics Data System (ADS)

    Subramani, D. N.; Haley, P., Jr.; Lermusiaux, P. F. J.

    2017-12-01

    The coastal ocean is a prime example of multiscale nonlinear fluid dynamics. Ocean fields in such regions are complex and intermittent with unstationary heterogeneous statistics. Due to the limited measurements, there are multiple sources of uncertainties, including the initial conditions, boundary conditions, forcing, parameters, and even the model parameterizations and equations themselves. For efficient and rigorous quantification and prediction of these uncertainities, the stochastic Dynamically Orthogonal (DO) PDEs for a primitive equation ocean modeling system with a nonlinear free-surface are derived and numerical schemes for their space-time integration are obtained. Detailed numerical studies with idealized-to-realistic regional ocean dynamics are completed. These include consistency checks for the numerical schemes and comparisons with ensemble realizations. As an illustrative example, we simulate the 4-d multiscale uncertainty in the Middle Atlantic/New York Bight region during the months of Jan to Mar 2017. To provide intitial conditions for the uncertainty subspace, uncertainties in the region were objectively analyzed using historical data. The DO primitive equations were subsequently integrated in space and time. The probability distribution function (pdf) of the ocean fields is compared to in-situ, remote sensing, and opportunity data collected during the coincident POSYDON experiment. Results show that our probabilistic predictions had skill and are 3- to 4- orders of magnitude faster than classic ensemble schemes.

  15. Multiscale Modeling of Plasmon-Exciton Dynamics of Malachite Green Monolayers on Gold Nanoparticles

    NASA Astrophysics Data System (ADS)

    Smith, Holden; Karam, Tony; Haber, Louis; Lopata, Kenneth

    A multi-scale hybrid quantum/classical approach using classical electrodynamics and a collection of discrete two level quantum system is used to investigate the coupling dynamics of malachite green monolayers adsorbed to the surface of a spherical gold nanoparticle (NP). This method utilizes finite difference time domain (FDTD) to describe the plasmonic response of the NP and a two-level quantum description for the molecule via the Maxwell/Liouville equation. The molecular parameters are parameterized using CASPT2 for the energies and transition dipole moments, with the dephasing lifetime fit to experiment. This approach is suited to simulating thousands of molecules on the surface of a plasmonic NP. There is good agreement with experimental extinction measurements, predicting the plasmon and molecule depletions. Additionally, this model captures the polariton peaks overlapped with a Fano-type resonance profile observed in the experimental extinction measurements. This technique shows promise for modeling plasmon/molecule interactions in chemical sensing and light harvesting in multi-chromophore systems. This material is based upon work supported by the National Science Foundation under the NSF EPSCoR Cooperative Agreement No. EPS-1003897 and the Louisiana Board of Regents Research Competitiveness Subprogram under Contract Number LEQSF(2014-17)-RD-A-0.

  16. Multiscale Modeling of Plasmon-Exciton Dynamics of Malachite Green Monolayers on Gold Nanoparticles

    NASA Astrophysics Data System (ADS)

    Smith, Holden; Karam, Tony; Haber, Louis; Lopata, Kenneth

    A multi-scale hybrid quantum/classical approach using classical electrodynamics and a collection of discrete two-level quantum system is used to investigate the coupling dynamics of malachite green monolayers adsorbed to the surface of a spherical gold nanoparticle (NP). This method utilizes finite difference time domain (FDTD) to describe the plasmonic response of the NP and a two-level quantum description for the molecule via the Maxwell/Liouville equation. The molecular parameters are parameterized using CASPT2 for the energies and transition dipole moments, with the dephasing lifetime fit to experiment. This approach is suited to simulating thousands of molecules on the surface of a plasmonic NP. There is good agreement with experimental extinction measurements, predicting the plasmon and molecule depletions. Additionally, this model captures the polariton peaks overlapped with a Fano-type resonance profile observed in the experimental extinction measurements. This technique shows promise for modeling plasmon/molecule interactions in chemical sensing and light harvesting in multi-chromophore systems. This material is based upon work supported by the National Science Foundation under the NSF EPSCoR Cooperative Agreement No. EPS-1003897 and by the Louisiana Board of Regents Research Competitiveness Subprogram under Contract Number LEQSF(2014-17)-RD-A-0.

  17. EEMD-based multiscale ICA method for slewing bearing fault detection and diagnosis

    NASA Astrophysics Data System (ADS)

    Žvokelj, Matej; Zupan, Samo; Prebil, Ivan

    2016-05-01

    A novel multivariate and multiscale statistical process monitoring method is proposed with the aim of detecting incipient failures in large slewing bearings, where subjective influence plays a minor role. The proposed method integrates the strengths of the Independent Component Analysis (ICA) multivariate monitoring approach with the benefits of Ensemble Empirical Mode Decomposition (EEMD), which adaptively decomposes signals into different time scales and can thus cope with multiscale system dynamics. The method, which was named EEMD-based multiscale ICA (EEMD-MSICA), not only enables bearing fault detection but also offers a mechanism of multivariate signal denoising and, in combination with the Envelope Analysis (EA), a diagnostic tool. The multiscale nature of the proposed approach makes the method convenient to cope with data which emanate from bearings in complex real-world rotating machinery and frequently represent the cumulative effect of many underlying phenomena occupying different regions in the time-frequency plane. The efficiency of the proposed method was tested on simulated as well as real vibration and Acoustic Emission (AE) signals obtained through conducting an accelerated run-to-failure lifetime experiment on a purpose-built laboratory slewing bearing test stand. The ability to detect and locate the early-stage rolling-sliding contact fatigue failure of the bearing indicates that AE and vibration signals carry sufficient information on the bearing condition and that the developed EEMD-MSICA method is able to effectively extract it, thereby representing a reliable bearing fault detection and diagnosis strategy.

  18. Multiscale Metabolic Modeling: Dynamic Flux Balance Analysis on a Whole-Plant Scale1[W][OPEN

    PubMed Central

    Grafahrend-Belau, Eva; Junker, Astrid; Eschenröder, André; Müller, Johannes; Schreiber, Falk; Junker, Björn H.

    2013-01-01

    Plant metabolism is characterized by a unique complexity on the cellular, tissue, and organ levels. On a whole-plant scale, changing source and sink relations accompanying plant development add another level of complexity to metabolism. With the aim of achieving a spatiotemporal resolution of source-sink interactions in crop plant metabolism, a multiscale metabolic modeling (MMM) approach was applied that integrates static organ-specific models with a whole-plant dynamic model. Allowing for a dynamic flux balance analysis on a whole-plant scale, the MMM approach was used to decipher the metabolic behavior of source and sink organs during the generative phase of the barley (Hordeum vulgare) plant. It reveals a sink-to-source shift of the barley stem caused by the senescence-related decrease in leaf source capacity, which is not sufficient to meet the nutrient requirements of sink organs such as the growing seed. The MMM platform represents a novel approach for the in silico analysis of metabolism on a whole-plant level, allowing for a systemic, spatiotemporally resolved understanding of metabolic processes involved in carbon partitioning, thus providing a novel tool for studying yield stability and crop improvement. PMID:23926077

  19. Multiscale Analysis of Delamination of Carbon Fiber-Epoxy Laminates with Carbon Nanotubes

    NASA Technical Reports Server (NTRS)

    Riddick, Jaret C.; Frankland, SJV; Gates, TS

    2006-01-01

    A multi-scale analysis is presented to parametrically describe the Mode I delamination of a carbon fiber/epoxy laminate. In the midplane of the laminate, carbon nanotubes are included for the purposes of selectively enhancing the fracture toughness of the laminate. To analyze carbon fiber epoxy carbon nanotube laminate, the multi-scale methodology presented here links a series of parameterizations taken at various length scales ranging from the atomistic through the micromechanical to the structural level. At the atomistic scale molecular dynamics simulations are performed in conjunction with an equivalent continuum approach to develop constitutive properties for representative volume elements of the molecular structure of components of the laminate. The molecular-level constitutive results are then used in the Mori-Tanaka micromechanics to develop bulk properties for the epoxy-carbon nanotube matrix system. In order to demonstrate a possible application of this multi-scale methodology, a double cantilever beam specimen is modeled. An existing analysis is employed which uses discrete springs to model the fiber bridging affect during delamination propagation. In the absence of empirical data or a damage mechanics model describing the effect of CNTs on fracture toughness, several tractions laws are postulated, linking CNT volume fraction to fiber bridging in a DCB specimen. Results from this demonstration are presented in terms of DCB specimen load-displacement responses.

  20. Accelerated sampling by infinite swapping of path integral molecular dynamics with surface hopping

    NASA Astrophysics Data System (ADS)

    Lu, Jianfeng; Zhou, Zhennan

    2018-02-01

    To accelerate the thermal equilibrium sampling of multi-level quantum systems, the infinite swapping limit of a recently proposed multi-level ring polymer representation is investigated. In the infinite swapping limit, the ring polymer evolves according to an averaged Hamiltonian with respect to all possible surface index configurations of the ring polymer and thus connects the surface hopping approach to the mean-field path-integral molecular dynamics. A multiscale integrator for the infinite swapping limit is also proposed to enable efficient sampling based on the limiting dynamics. Numerical results demonstrate the huge improvement of sampling efficiency of the infinite swapping compared with the direct simulation of path-integral molecular dynamics with surface hopping.

  1. Coupling all-atom molecular dynamics simulations of ions in water with Brownian dynamics.

    PubMed

    Erban, Radek

    2016-02-01

    Molecular dynamics (MD) simulations of ions (K + , Na + , Ca 2+ and Cl - ) in aqueous solutions are investigated. Water is described using the SPC/E model. A stochastic coarse-grained description for ion behaviour is presented and parametrized using MD simulations. It is given as a system of coupled stochastic and ordinary differential equations, describing the ion position, velocity and acceleration. The stochastic coarse-grained model provides an intermediate description between all-atom MD simulations and Brownian dynamics (BD) models. It is used to develop a multiscale method which uses all-atom MD simulations in parts of the computational domain and (less detailed) BD simulations in the remainder of the domain.

  2. Universality classes of fluctuation dynamics in hierarchical complex systems

    NASA Astrophysics Data System (ADS)

    Macêdo, A. M. S.; González, Iván R. Roa; Salazar, D. S. P.; Vasconcelos, G. L.

    2017-03-01

    A unified approach is proposed to describe the statistics of the short-time dynamics of multiscale complex systems. The probability density function of the relevant time series (signal) is represented as a statistical superposition of a large time-scale distribution weighted by the distribution of certain internal variables that characterize the slowly changing background. The dynamics of the background is formulated as a hierarchical stochastic model whose form is derived from simple physical constraints, which in turn restrict the dynamics to only two possible classes. The probability distributions of both the signal and the background have simple representations in terms of Meijer G functions. The two universality classes for the background dynamics manifest themselves in the signal distribution as two types of tails: power law and stretched exponential, respectively. A detailed analysis of empirical data from classical turbulence and financial markets shows excellent agreement with the theory.

  3. Multiscale Simulations of Dynamics of Ferroelectric Domains

    NASA Astrophysics Data System (ADS)

    Liu, Shi

    Ferroelectrics with switchable polarization have many important technological applications, which heavily rely on the interactions between the polarization and external perturbations. Understanding the dynamical response of ferroelectric materials is crucial for the discovery and development of new design principles and engineering strategies for optimized and breakthrough applications of ferroelectrics. We developed a multiscale computational approach that combines methods at different length and time scales to elucidate the connection between local structures, domain dynamics, and macroscopic finite-temperature properties of ferroelectrics. We started from first-principles calculations of ferroelectrics to build a model interatomic potential, enabling large-scale molecular dynamics (MD) simulations. The atomistic insights of nucleation and growth at the domain wall obtained from MD were then incorporated into a continuum model within the framework of Landau-Ginzburg-Devonshire theory. This progressive theoretical framework allows for the first time an efficient and accurate estimation of macroscopic properties such as the coercive field for a broad range of ferroelectrics from first-principles. This multiscale approach has also been applied to explore the effect of dipolar defects on ferroelectric switching and to understand the origin of giant electro-strain coupling. ONR, NSF, Carnegie Institution for Science.

  4. A Multiscale Vision Model applied to analyze EIT images of the solar corona

    NASA Astrophysics Data System (ADS)

    Portier-Fozzani, F.; Vandame, B.; Bijaoui, A.; Maucherat, A. J.; EIT Team

    2001-07-01

    The large dynamic range provided by the SOHO/EIT CCD (1 : 5000) is needed to observe the large EUV zoom of coronal structures from coronal homes up to flares. Histograms show that often a wide dynamic range is present in each image. Extracting hidden structures in the background level requires specific techniques such as the use of the Multiscale Vision Model (MVM, Bijaoui et al., 1998). This method, based on wavelet transformations optimizes detection of various size objects, however complex they may be. Bijaoui et al. built the Multiscale Vision Model to extract small dynamical structures from noise, mainly for studying galaxies. In this paper, we describe requirements for the use of this method with SOHO/EIT images (calibration, size of the image, dynamics of the subimage, etc.). Two different areas were studied revealing hidden structures: (1) classical coronal mass ejection (CME) formation and (2) a complex group of active regions with its evolution. The aim of this paper is to define carefully the constraints for this new method of imaging the solar corona with SOHO/EIT. Physical analysis derived from multi-wavelength observations will later complete these first results.

  5. Adaptive simplification of complex multiscale systems.

    PubMed

    Chiavazzo, Eliodoro; Karlin, Ilya

    2011-03-01

    A fully adaptive methodology is developed for reducing the complexity of large dissipative systems. This represents a significant step toward extracting essential physical knowledge from complex systems, by addressing the challenging problem of a minimal number of variables needed to exactly capture the system dynamics. Accurate reduced description is achieved, by construction of a hierarchy of slow invariant manifolds, with an embarrassingly simple implementation in any dimension. The method is validated with the autoignition of the hydrogen-air mixture where a reduction to a cascade of slow invariant manifolds is observed.

  6. On the interplay between mathematics and biology. Hallmarks toward a new systems biology

    NASA Astrophysics Data System (ADS)

    Bellomo, Nicola; Elaiw, Ahmed; Althiabi, Abdullah M.; Alghamdi, Mohammed Ali

    2015-03-01

    This paper proposes a critical analysis of the existing literature on mathematical tools developed toward systems biology approaches and, out of this overview, develops a new approach whose main features can be briefly summarized as follows: derivation of mathematical structures suitable to capture the complexity of biological, hence living, systems, modeling, by appropriate mathematical tools, Darwinian type dynamics, namely mutations followed by selection and evolution. Moreover, multiscale methods to move from genes to cells, and from cells to tissue are analyzed in view of a new systems biology approach.

  7. Peridynamic Multiscale Finite Element Methods

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

    Costa, Timothy; Bond, Stephen D.; Littlewood, David John

    The problem of computing quantum-accurate design-scale solutions to mechanics problems is rich with applications and serves as the background to modern multiscale science research. The prob- lem can be broken into component problems comprised of communicating across adjacent scales, which when strung together create a pipeline for information to travel from quantum scales to design scales. Traditionally, this involves connections between a) quantum electronic structure calculations and molecular dynamics and between b) molecular dynamics and local partial differ- ential equation models at the design scale. The second step, b), is particularly challenging since the appropriate scales of molecular dynamic andmore » local partial differential equation models do not overlap. The peridynamic model for continuum mechanics provides an advantage in this endeavor, as the basic equations of peridynamics are valid at a wide range of scales limiting from the classical partial differential equation models valid at the design scale to the scale of molecular dynamics. In this work we focus on the development of multiscale finite element methods for the peridynamic model, in an effort to create a mathematically consistent channel for microscale information to travel from the upper limits of the molecular dynamics scale to the design scale. In particular, we first develop a Nonlocal Multiscale Finite Element Method which solves the peridynamic model at multiple scales to include microscale information at the coarse-scale. We then consider a method that solves a fine-scale peridynamic model to build element-support basis functions for a coarse- scale local partial differential equation model, called the Mixed Locality Multiscale Finite Element Method. Given decades of research and development into finite element codes for the local partial differential equation models of continuum mechanics there is a strong desire to couple local and nonlocal models to leverage the speed and state of the art of local models with the flexibility and accuracy of the nonlocal peridynamic model. In the mixed locality method this coupling occurs across scales, so that the nonlocal model can be used to communicate material heterogeneity at scales inappropriate to local partial differential equation models. Additionally, the computational burden of the weak form of the peridynamic model is reduced dramatically by only requiring that the model be solved on local patches of the simulation domain which may be computed in parallel, taking advantage of the heterogeneous nature of next generation computing platforms. Addition- ally, we present a novel Galerkin framework, the 'Ambulant Galerkin Method', which represents a first step towards a unified mathematical analysis of local and nonlocal multiscale finite element methods, and whose future extension will allow the analysis of multiscale finite element methods that mix models across scales under certain assumptions of the consistency of those models.« less

  8. Multi-scale lung modeling.

    PubMed

    Tawhai, Merryn H; Bates, Jason H T

    2011-05-01

    Multi-scale modeling of biological systems has recently become fashionable due to the growing power of digital computers as well as to the growing realization that integrative systems behavior is as important to life as is the genome. While it is true that the behavior of a living organism must ultimately be traceable to all its components and their myriad interactions, attempting to codify this in its entirety in a model misses the insights gained from understanding how collections of system components at one level of scale conspire to produce qualitatively different behavior at higher levels. The essence of multi-scale modeling thus lies not in the inclusion of every conceivable biological detail, but rather in the judicious selection of emergent phenomena appropriate to the level of scale being modeled. These principles are exemplified in recent computational models of the lung. Airways responsiveness, for example, is an organ-level manifestation of events that begin at the molecular level within airway smooth muscle cells, yet it is not necessary to invoke all these molecular events to accurately describe the contraction dynamics of a cell, nor is it necessary to invoke all phenomena observable at the level of the cell to account for the changes in overall lung function that occur following methacholine challenge. Similarly, the regulation of pulmonary vascular tone has complex origins within the individual smooth muscle cells that line the blood vessels but, again, many of the fine details of cell behavior average out at the level of the organ to produce an effect on pulmonary vascular pressure that can be described in much simpler terms. The art of multi-scale lung modeling thus reduces not to being limitlessly inclusive, but rather to knowing what biological details to leave out.

  9. Dislocation dynamics: simulation of plastic flow of bcc metals

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

    Lassila, D H

    This is the final report for the LDRD strategic initiative entitled ''Dislocation Dynamic: Simulation of Plastic Flow of bcc Metals'' (tracking code: 00-SI-011). This report is comprised of 6 individual sections. The first is an executive summary of the project and describes the overall project goal, which is to establish an experimentally validated 3D dislocation dynamics simulation. This first section also gives some information of LLNL's multi-scale modeling efforts associated with the plasticity of bcc metals, and the role of this LDRD project in the multiscale modeling program. The last five sections of this report are journal articles that weremore » produced during the course of the FY-2000 efforts.« less

  10. Multiscale model for microstructure evolution in multiphase materials: Application to the growth of isolated inclusions in presence of elasticity.

    PubMed

    Perez, Danny; Lewis, Laurent J

    2006-09-01

    We present a multiscale model based on the classical lattice time-dependent density-functional theory to study microstructure evolution in multiphase systems. As a first test of the method, we study the static and dynamic properties of isolated inclusions. Three cases are explored: elastically homogeneous systems, elastically inhomogeneous systems with soft inclusions, and elastically inhomogeneous systems with hard inclusions. The equilibrium properties of inclusions are shown to be consistent with previous results: both homogeneous and hard inclusions adopt a circular shape independent of their size, whereas soft inclusions are circular below a critical radius and elliptic above. In all cases, the Gibbs-Thomson relation is obeyed, except for a change in the prefactor at the critical radius in soft inclusions. Under growth conditions, homogeneous inclusions exhibit a Mullins-Sekerka shape instability [W. Mullins and R. Sekerka, J. Appl. Phys. 34, 323 (1963)], whereas in inhomogeneous systems, the growth of perturbations follows the Leo-Sekerka model [P. Leo and R. Sekerka, Acta Metall. 37, 3139 (1989)]. For soft inclusions, the mode instability regime is gradually replaced by a tip-growing mechanism, which leads to stable, strongly out-of-equilibrium shapes even at very low supersaturation. This mechanism is shown to significantly affect the growth dynamics of soft inclusions, whereas dynamical corrections to the growth rates are negligible in homogeneous and hard inclusions. Finally, due to its microscopic formulation, the model is shown to automatically take into account phenomena caused by the presence of the underlying discrete lattice: anisotropy of the interfacial energy, anisotropy of the kinetics, and preferential excitation of shape perturbations commensurate with the rotational symmetry of the lattice.

  11. Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites

    DTIC Science & Technology

    2016-03-09

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

  12. Design of Energetic Ionic Liquids (Preprint)

    DTIC Science & Technology

    2008-05-07

    mesoscale-level simulations of bulk ionic liquids based upon multiscale coarse graining techniques. 15. SUBJECT TERMS 16. SECURITY...simulations utilizing polarizable force fields, and mesoscale-level simulations of bulk ionic liquids based upon multiscale coarse graining...Simulations of the Energetic Ionic Liquid 1-hydroxyethyl-4-amino-1, 2, 4- triazolium Nitrate (HEATN): Molecular dynamics (MD) simulations have been

  13. Tinker-HP: a massively parallel molecular dynamics package for multiscale simulations of large complex systems with advanced point dipole polarizable force fields† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc04531j

    PubMed Central

    Lagardère, Louis; Jolly, Luc-Henri; Lipparini, Filippo; Aviat, Félix; Stamm, Benjamin; Jing, Zhifeng F.; Harger, Matthew; Torabifard, Hedieh; Cisneros, G. Andrés; Schnieders, Michael J.; Gresh, Nohad; Maday, Yvon; Ren, Pengyu Y.; Ponder, Jay W.

    2017-01-01

    We present Tinker-HP, a massively MPI parallel package dedicated to classical molecular dynamics (MD) and to multiscale simulations, using advanced polarizable force fields (PFF) encompassing distributed multipoles electrostatics. Tinker-HP is an evolution of the popular Tinker package code that conserves its simplicity of use and its reference double precision implementation for CPUs. Grounded on interdisciplinary efforts with applied mathematics, Tinker-HP allows for long polarizable MD simulations on large systems up to millions of atoms. We detail in the paper the newly developed extension of massively parallel 3D spatial decomposition to point dipole polarizable models as well as their coupling to efficient Krylov iterative and non-iterative polarization solvers. The design of the code allows the use of various computer systems ranging from laboratory workstations to modern petascale supercomputers with thousands of cores. Tinker-HP proposes therefore the first high-performance scalable CPU computing environment for the development of next generation point dipole PFFs and for production simulations. Strategies linking Tinker-HP to Quantum Mechanics (QM) in the framework of multiscale polarizable self-consistent QM/MD simulations are also provided. The possibilities, performances and scalability of the software are demonstrated via benchmarks calculations using the polarizable AMOEBA force field on systems ranging from large water boxes of increasing size and ionic liquids to (very) large biosystems encompassing several proteins as well as the complete satellite tobacco mosaic virus and ribosome structures. For small systems, Tinker-HP appears to be competitive with the Tinker-OpenMM GPU implementation of Tinker. As the system size grows, Tinker-HP remains operational thanks to its access to distributed memory and takes advantage of its new algorithmic enabling for stable long timescale polarizable simulations. Overall, a several thousand-fold acceleration over a single-core computation is observed for the largest systems. The extension of the present CPU implementation of Tinker-HP to other computational platforms is discussed. PMID:29732110

  14. Fluid-Solid Interaction and Multiscale Dynamic Processes: Experimental Approach

    NASA Astrophysics Data System (ADS)

    Arciniega-Ceballos, Alejandra; Spina, Laura; Mendo-Pérez, Gerardo M.; Guzmán-Vázquez, Enrique; Scheu, Bettina; Sánchez-Sesma, Francisco J.; Dingwell, Donald B.

    2017-04-01

    The speed and the style of a pressure drop in fluid-filled conduits determines the dynamics of multiscale processes and the elastic interaction between the fluid and the confining solid. To observe this dynamics we performed experiments using fluid-filled transparent tubes (15-50 cm long, 2-4 cm diameter and 0.3-1 cm thickness) instrumented with high-dynamic piezoelectric sensors and filmed the evolution of these processes with a high speed camera. We analyzed the response of Newtonian fluids to slow and sudden pressure drops from 3 bar-10 MPa to ambient pressure. We used fluids with viscosities of mafic to intermediate silicate melts of 1 to 1000 Pa s and water. The processes observed are fluid mass expansion, fluid flow, jets, bubbles nucleation, growth, coalescence and collapse, degassing, foam building at the surface and vertical wagging. All these processes (in fine and coarse scales) are triggered by the pressure drop and are sequentially coupled in time while interacting with the solid. During slow decompression, the multiscale processes are recognized occurring within specific pressure intervals, and exhibit a localized distribution along the conduit. In this, degassing predominates near the surface and may present piston-like oscillations. In contrast, during sudden decompression the fluid-flow reaches higher velocities, the dynamics is dominated by a sequence of gas-packet pulses driving jets of the gas-fluid mixture. The evolution of this multiscale phenomenon generates complex non-stationary microseismic signals recorded along the conduit. We discuss distinctive characteristics of these signals depending on the decompression style and compare them with synthetics. These synthetics are obtained numerically under an averaging modeling scheme, that accounted for the stress-strain of the cyclic dynamic interaction between the fluid and the solid wall, assuming an incompressible and viscous fluid that flows while the elastic solid responds oscillating. Analysis of time series, both experimental and synthetics, synchronized with high-speed imaging enables the explanation and interpretation of distinct phases of the dynamics of these fluids and the extraction of time and frequency characteristics of the individual processes. We observed that the effects of both, pressure drop triggering function and viscosity, control the characteristics of the micro-signals in time and frequency. This suggests the great potential that experimental and numerical approaches provide to untangle from field volcanic seismograms the multiscale processes of the stress field, driving forces and fluid-rock interaction that determine the volcanic conduit dynamics.

  15. Refined composite multiscale weighted-permutation entropy of financial time series

    NASA Astrophysics Data System (ADS)

    Zhang, Yongping; Shang, Pengjian

    2018-04-01

    For quantifying the complexity of nonlinear systems, multiscale weighted-permutation entropy (MWPE) has recently been proposed. MWPE has incorporated amplitude information and been applied to account for the multiple inherent dynamics of time series. However, MWPE may be unreliable, because its estimated values show large fluctuation for slight variation of the data locations, and a significant distinction only for the different length of time series. Therefore, we propose the refined composite multiscale weighted-permutation entropy (RCMWPE). By comparing the RCMWPE results with other methods' results on both synthetic data and financial time series, RCMWPE method shows not only the advantages inherited from MWPE but also lower sensitivity to the data locations, more stable and much less dependent on the length of time series. Moreover, we present and discuss the results of RCMWPE method on the daily price return series from Asian and European stock markets. There are significant differences between Asian markets and European markets, and the entropy values of Hang Seng Index (HSI) are close to but higher than those of European markets. The reliability of the proposed RCMWPE method has been supported by simulations on generated and real data. It could be applied to a variety of fields to quantify the complexity of the systems over multiple scales more accurately.

  16. Multiscale high-order/low-order (HOLO) algorithms and applications

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

    Chacon, Luis; Chen, Guangye; Knoll, Dana Alan

    Here, we review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. Themore » HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.« less

  17. Multiscale high-order/low-order (HOLO) algorithms and applications

    DOE PAGES

    Chacon, Luis; Chen, Guangye; Knoll, Dana Alan; ...

    2016-11-11

    Here, we review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. Themore » HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.« less

  18. Multiscale recurrence analysis of spatio-temporal data

    NASA Astrophysics Data System (ADS)

    Riedl, M.; Marwan, N.; Kurths, J.

    2015-12-01

    The description and analysis of spatio-temporal dynamics is a crucial task in many scientific disciplines. In this work, we propose a method which uses the mapogram as a similarity measure between spatially distributed data instances at different time points. The resulting similarity values of the pairwise comparison are used to construct a recurrence plot in order to benefit from established tools of recurrence quantification analysis and recurrence network analysis. In contrast to other recurrence tools for this purpose, the mapogram approach allows the specific focus on different spatial scales that can be used in a multi-scale analysis of spatio-temporal dynamics. We illustrate this approach by application on mixed dynamics, such as traveling parallel wave fronts with additive noise, as well as more complicate examples, pseudo-random numbers and coupled map lattices with a semi-logistic mapping rule. Especially the complicate examples show the usefulness of the multi-scale consideration in order to take spatial pattern of different scales and with different rhythms into account. So, this mapogram approach promises new insights in problems of climatology, ecology, or medicine.

  19. Multiscale recurrence analysis of spatio-temporal data.

    PubMed

    Riedl, M; Marwan, N; Kurths, J

    2015-12-01

    The description and analysis of spatio-temporal dynamics is a crucial task in many scientific disciplines. In this work, we propose a method which uses the mapogram as a similarity measure between spatially distributed data instances at different time points. The resulting similarity values of the pairwise comparison are used to construct a recurrence plot in order to benefit from established tools of recurrence quantification analysis and recurrence network analysis. In contrast to other recurrence tools for this purpose, the mapogram approach allows the specific focus on different spatial scales that can be used in a multi-scale analysis of spatio-temporal dynamics. We illustrate this approach by application on mixed dynamics, such as traveling parallel wave fronts with additive noise, as well as more complicate examples, pseudo-random numbers and coupled map lattices with a semi-logistic mapping rule. Especially the complicate examples show the usefulness of the multi-scale consideration in order to take spatial pattern of different scales and with different rhythms into account. So, this mapogram approach promises new insights in problems of climatology, ecology, or medicine.

  20. Generalized composite multiscale permutation entropy and Laplacian score based rolling bearing fault diagnosis

    NASA Astrophysics Data System (ADS)

    Zheng, Jinde; Pan, Haiyang; Yang, Shubao; Cheng, Junsheng

    2018-01-01

    Multiscale permutation entropy (MPE) is a recently proposed nonlinear dynamic method for measuring the randomness and detecting the nonlinear dynamic change of time series and can be used effectively to extract the nonlinear dynamic fault feature from vibration signals of rolling bearing. To solve the drawback of coarse graining process in MPE, an improved MPE method called generalized composite multiscale permutation entropy (GCMPE) was proposed in this paper. Also the influence of parameters on GCMPE and its comparison with the MPE are studied by analyzing simulation data. GCMPE was applied to the fault feature extraction from vibration signal of rolling bearing and then based on the GCMPE, Laplacian score for feature selection and the Particle swarm optimization based support vector machine, a new fault diagnosis method for rolling bearing was put forward in this paper. Finally, the proposed method was applied to analyze the experimental data of rolling bearing. The analysis results show that the proposed method can effectively realize the fault diagnosis of rolling bearing and has a higher fault recognition rate than the existing methods.

  1. Towards a Multiscale Approach to Cybersecurity Modeling

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

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

    2013-11-12

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

  2. Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

    NASA Astrophysics Data System (ADS)

    Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt; Stuehn, Torsten

    2017-11-01

    Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach, the theoretical modeling and scaling laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. These two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.

  3. Navigation Operations for the Magnetospheric Multiscale Mission

    NASA Technical Reports Server (NTRS)

    Long, Anne; Farahmand, Mitra; Carpenter, Russell

    2015-01-01

    The Magnetospheric Multiscale (MMS) mission employs four identical spinning spacecraft flying in highly elliptical Earth orbits. These spacecraft will fly in a series of tetrahedral formations with separations of less than 10 km. MMS navigation operations use onboard navigation to satisfy the mission definitive orbit and time determination requirements and in addition to minimize operations cost and complexity. The onboard navigation subsystem consists of the Navigator GPS receiver with Goddard Enhanced Onboard Navigation System (GEONS) software, and an Ultra-Stable Oscillator. The four MMS spacecraft are operated from a single Mission Operations Center, which includes a Flight Dynamics Operations Area (FDOA) that supports MMS navigation operations, as well as maneuver planning, conjunction assessment and attitude ground operations. The System Manager component of the FDOA automates routine operations processes. The GEONS Ground Support System component of the FDOA provides the tools needed to support MMS navigation operations. This paper provides an overview of the MMS mission and associated navigation requirements and constraints and discusses MMS navigation operations and the associated MMS ground system components built to support navigation-related operations.

  4. Community Multiscale Air Quality Model

    EPA Science Inventory

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

  5. Multi-scale computational modeling of developmental biology.

    PubMed

    Setty, Yaki

    2012-08-01

    Normal development of multicellular organisms is regulated by a highly complex process in which a set of precursor cells proliferate, differentiate and move, forming over time a functioning tissue. To handle their complexity, developmental systems can be studied over distinct scales. The dynamics of each scale is determined by the collective activity of entities at the scale below it. I describe a multi-scale computational approach for modeling developmental systems and detail the methodology through a synthetic example of a developmental system that retains key features of real developmental systems. I discuss the simulation of the system as it emerges from cross-scale and intra-scale interactions and describe how an in silico study can be carried out by modifying these interactions in a way that mimics in vivo experiments. I highlight biological features of the results through a comparison with findings in Caenorhabditis elegans germline development and finally discuss about the applications of the approach in real developmental systems and propose future extensions. The source code of the model of the synthetic developmental system can be found in www.wisdom.weizmann.ac.il/~yaki/MultiScaleModel. yaki.setty@gmail.com Supplementary data are available at Bioinformatics online.

  6. A simple, stable, and accurate linear tetrahedral finite element for transient, nearly, and fully incompressible solid dynamics: A dynamic variational multiscale approach [A simple, stable, and accurate tetrahedral finite element for transient, nearly incompressible, linear and nonlinear elasticity: A dynamic variational multiscale approach

    DOE PAGES

    Scovazzi, Guglielmo; Carnes, Brian; Zeng, Xianyi; ...

    2015-11-12

    Here, we propose a new approach for the stabilization of linear tetrahedral finite elements in the case of nearly incompressible transient solid dynamics computations. Our method is based on a mixed formulation, in which the momentum equation is complemented by a rate equation for the evolution of the pressure field, approximated with piece-wise linear, continuous finite element functions. The pressure equation is stabilized to prevent spurious pressure oscillations in computations. Incidentally, it is also shown that many stabilized methods previously developed for the static case do not generalize easily to transient dynamics. Extensive tests in the context of linear andmore » nonlinear elasticity are used to corroborate the claim that the proposed method is robust, stable, and accurate.« less

  7. A simple, stable, and accurate linear tetrahedral finite element for transient, nearly, and fully incompressible solid dynamics: A dynamic variational multiscale approach [A simple, stable, and accurate tetrahedral finite element for transient, nearly incompressible, linear and nonlinear elasticity: A dynamic variational multiscale approach

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

    Scovazzi, Guglielmo; Carnes, Brian; Zeng, Xianyi

    Here, we propose a new approach for the stabilization of linear tetrahedral finite elements in the case of nearly incompressible transient solid dynamics computations. Our method is based on a mixed formulation, in which the momentum equation is complemented by a rate equation for the evolution of the pressure field, approximated with piece-wise linear, continuous finite element functions. The pressure equation is stabilized to prevent spurious pressure oscillations in computations. Incidentally, it is also shown that many stabilized methods previously developed for the static case do not generalize easily to transient dynamics. Extensive tests in the context of linear andmore » nonlinear elasticity are used to corroborate the claim that the proposed method is robust, stable, and accurate.« less

  8. Mood states modulate complexity in heartbeat dynamics: A multiscale entropy analysis

    NASA Astrophysics Data System (ADS)

    Valenza, G.; Nardelli, M.; Bertschy, G.; Lanata, A.; Scilingo, E. P.

    2014-07-01

    This paper demonstrates that heartbeat complex dynamics is modulated by different pathological mental states. Multiscale entropy analysis was performed on R-R interval series gathered from the electrocardiogram of eight bipolar patients who exhibited mood states among depression, hypomania, and euthymia, i.e., good affective balance. Three different methodologies for the choice of the sample entropy radius value were also compared. We show that the complexity level can be used as a marker of mental states being able to discriminate among the three pathological mood states, suggesting to use heartbeat complexity as a more objective clinical biomarker for mental disorders.

  9. A Multi-Scale Method for Dynamics Simulation in Continuum Solvent Models I: Finite-Difference Algorithm for Navier-Stokes Equation.

    PubMed

    Xiao, Li; Cai, Qin; Li, Zhilin; Zhao, Hongkai; Luo, Ray

    2014-11-25

    A multi-scale framework is proposed for more realistic molecular dynamics simulations in continuum solvent models by coupling a molecular mechanics treatment of solute with a fluid mechanics treatment of solvent. This article reports our initial efforts to formulate the physical concepts necessary for coupling the two mechanics and develop a 3D numerical algorithm to simulate the solvent fluid via the Navier-Stokes equation. The numerical algorithm was validated with multiple test cases. The validation shows that the algorithm is effective and stable, with observed accuracy consistent with our design.

  10. An open source platform for multi-scale spatially distributed simulations of microbial ecosystems

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

    Segre, Daniel

    2014-08-14

    The goal of this project was to develop a tool for facilitating simulation, validation and discovery of multiscale dynamical processes in microbial ecosystems. This led to the development of an open-source software platform for Computation Of Microbial Ecosystems in Time and Space (COMETS). COMETS performs spatially distributed time-dependent flux balance based simulations of microbial metabolism. Our plan involved building the software platform itself, calibrating and testing it through comparison with experimental data, and integrating simulations and experiments to address important open questions on the evolution and dynamics of cross-feeding interactions between microbial species.

  11. 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

  12. Multiscale Simulation of Microbe Structure and Dynamics

    PubMed Central

    Joshi, Harshad; Singharoy, Abhishek; Sereda, Yuriy V.; Cheluvaraja, Srinath C.; Ortoleva, Peter J.

    2012-01-01

    A multiscale mathematical and computational approach is developed that captures the hierarchical organization of a microbe. It is found that a natural perspective for understanding a microbe is in terms of a hierarchy of variables at various levels of resolution. This hierarchy starts with the N -atom description and terminates with order parameters characterizing a whole microbe. This conceptual framework is used to guide the analysis of the Liouville equation for the probability density of the positions and momenta of the N atoms constituting the microbe and its environment. Using multiscale mathematical techniques, we derive equations for the co-evolution of the order parameters and the probability density of the N-atom state. This approach yields a rigorous way to transfer information between variables on different space-time scales. It elucidates the interplay between equilibrium and far-from-equilibrium processes underlying microbial behavior. It also provides framework for using coarse-grained nanocharacterization data to guide microbial simulation. It enables a methodical search for free-energy minimizing structures, many of which are typically supported by the set of macromolecules and membranes constituting a given microbe. This suite of capabilities provides a natural framework for arriving at a fundamental understanding of microbial behavior, the analysis of nanocharacterization data, and the computer-aided design of nanostructures for biotechnical and medical purposes. Selected features of the methodology are demonstrated using our multiscale bionanosystem simulator DeductiveMultiscaleSimulator. Systems used to demonstrate the approach are structural transitions in the cowpea chlorotic mosaic virus, RNA of satellite tobacco mosaic virus, virus-like particles related to human papillomavirus, and iron-binding protein lactoferrin. PMID:21802438

  13. Multiscale Electrodynamics/Time-Dependent Density Functional Theory Modeling of Coupled Plasmon/Molecule Excitations

    NASA Astrophysics Data System (ADS)

    Lopata, Kenneth; Smith, Holden

    The coupled dynamics of molecular chromophores and plasmons at surface of metal nanostructures are important for a range of processes such as molecular sensing, light harvesting, and near-field photochemistry. Modeling these dynamics from first principles, however, is challenging, as the large system sizes precludes a purely quantum mechanical treatment. In this talk I will present an approach based on propagating the plasmonic currents and fields using electrodynamics (finite-difference time-domain) with each chromophore described using an isolated quantum sub-region embedded in the overall classical background. This approach can be readily parallelized over these quantum regions, which enables large multiscale simulations of tens or hundreds of dyes, each of which is described individually by real-time time-dependent density functional theory. Application to gold nanoparticles coated with malachite green and rhodamine 6G monolayers shows good agreement with experimentally measured coupling spectra, including the polariton peaks, as well as the plasmon and molecular depletions. This research was supported by the Louisiana Board of Regents Research Competitiveness Subprogram under Contract Number LEQSF(2014-17)-RD-A-0.

  14. Advances and challenges in logical modeling of cell cycle regulation: perspective for multi-scale, integrative yeast cell models

    PubMed Central

    Todd, Robert G.; van der Zee, Lucas

    2016-01-01

    Abstract The eukaryotic cell cycle is robustly designed, with interacting molecules organized within a definite topology that ensures temporal precision of its phase transitions. Its underlying dynamics are regulated by molecular switches, for which remarkable insights have been provided by genetic and molecular biology efforts. In a number of cases, this information has been made predictive, through computational models. These models have allowed for the identification of novel molecular mechanisms, later validated experimentally. Logical modeling represents one of the youngest approaches to address cell cycle regulation. We summarize the advances that this type of modeling has achieved to reproduce and predict cell cycle dynamics. Furthermore, we present the challenge that this type of modeling is now ready to tackle: its integration with intracellular networks, and its formalisms, to understand crosstalks underlying systems level properties, ultimate aim of multi-scale models. Specifically, we discuss and illustrate how such an integration may be realized, by integrating a minimal logical model of the cell cycle with a metabolic network. PMID:27993914

  15. Fault detection method for railway wheel flat using an adaptive multiscale morphological filter

    NASA Astrophysics Data System (ADS)

    Li, Yifan; Zuo, Ming J.; Lin, Jianhui; Liu, Jianxin

    2017-02-01

    This study explores the capacity of the morphology analysis for railway wheel flat fault detection. A dynamic model of vehicle systems with 56 degrees of freedom was set up along with a wheel flat model to calculate the dynamic responses of axle box. The vehicle axle box vibration signal is complicated because it not only contains the information of wheel defect, but also includes track condition information. Thus, how to extract the influential features of wheels from strong background noise effectively is a typical key issue for railway wheel fault detection. In this paper, an algorithm for adaptive multiscale morphological filtering (AMMF) was proposed, and its effect was evaluated by a simulated signal. And then this algorithm was employed to study the axle box vibration caused by wheel flats, as well as the influence of track irregularity and vehicle running speed on diagnosis results. Finally, the effectiveness of the proposed method was verified by bench testing. Research results demonstrate that the AMMF extracts the influential characteristic of axle box vibration signals effectively and can diagnose wheel flat faults in real time.

  16. Multiscale System Theory

    DTIC Science & Technology

    1990-02-21

    LIDS-P-1953 Multiscale System Theory Albert Benveniste IRISA-INRIA, Campus de Beaulieu 35042 RENNES CEDEX, FRANCE Ramine Nikoukhah INRIA...TITLE AND SUBTITLE Multiscale System Theory 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e...the development of a corresponding system theory and a theory of stochastic processes and their estimation. The research presented in this and several

  17. Multiscale permutation entropy analysis of EEG recordings during sevoflurane anesthesia

    NASA Astrophysics Data System (ADS)

    Li, Duan; Li, Xiaoli; Liang, Zhenhu; Voss, Logan J.; Sleigh, Jamie W.

    2010-08-01

    Electroencephalogram (EEG) monitoring of the effect of anesthetic drugs on the central nervous system has long been used in anesthesia research. Several methods based on nonlinear dynamics, such as permutation entropy (PE), have been proposed to analyze EEG series during anesthesia. However, these measures are still single-scale based and may not completely describe the dynamical characteristics of complex EEG series. In this paper, a novel measure combining multiscale PE information, called CMSPE (composite multi-scale permutation entropy), was proposed for quantifying the anesthetic drug effect on EEG recordings during sevoflurane anesthesia. Three sets of simulated EEG series during awake, light and deep anesthesia were used to select the parameters for the multiscale PE analysis: embedding dimension m, lag τ and scales to be integrated into the CMSPE index. Then, the CMSPE index and raw single-scale PE index were applied to EEG recordings from 18 patients who received sevoflurane anesthesia. Pharmacokinetic/pharmacodynamic (PKPD) modeling was used to relate the measured EEG indices and the anesthetic drug concentration. Prediction probability (Pk) statistics and correlation analysis with the response entropy (RE) index, derived from the spectral entropy (M-entropy module; GE Healthcare, Helsinki, Finland), were investigated to evaluate the effectiveness of the new proposed measure. It was found that raw single-scale PE was blind to subtle transitions between light and deep anesthesia, while the CMSPE index tracked these changes accurately. Around the time of loss of consciousness, CMSPE responded significantly more rapidly than the raw PE, with the absolute slopes of linearly fitted response versus time plots of 0.12 (0.09-0.15) and 0.10 (0.06-0.13), respectively. The prediction probability Pk of 0.86 (0.85-0.88) and 0.85 (0.80-0.86) for CMSPE and raw PE indicated that the CMSPE index correlated well with the underlying anesthetic effect. The correlation coefficient for the comparison between the CMSPE index and RE index of 0.84 (0.80-0.88) was significantly higher than the raw PE index of 0.75 (0.66-0.84). The results show that the CMSPE outperforms the raw single-scale PE in reflecting the sevoflurane drug effect on the central nervous system.

  18. Multiscale digital Arabidopsis predicts individual organ and whole-organism growth.

    PubMed

    Chew, Yin Hoon; Wenden, Bénédicte; Flis, Anna; Mengin, Virginie; Taylor, Jasper; Davey, Christopher L; Tindal, Christopher; Thomas, Howard; Ougham, Helen J; de Reffye, Philippe; Stitt, Mark; Williams, Mathew; Muetzelfeldt, Robert; Halliday, Karen J; Millar, Andrew J

    2014-09-30

    Understanding how dynamic molecular networks affect whole-organism physiology, analogous to mapping genotype to phenotype, remains a key challenge in biology. Quantitative models that represent processes at multiple scales and link understanding from several research domains can help to tackle this problem. Such integrated models are more common in crop science and ecophysiology than in the research communities that elucidate molecular networks. Several laboratories have modeled particular aspects of growth in Arabidopsis thaliana, but it was unclear whether these existing models could productively be combined. We test this approach by constructing a multiscale model of Arabidopsis rosette growth. Four existing models were integrated with minimal parameter modification (leaf water content and one flowering parameter used measured data). The resulting framework model links genetic regulation and biochemical dynamics to events at the organ and whole-plant levels, helping to understand the combined effects of endogenous and environmental regulators on Arabidopsis growth. The framework model was validated and tested with metabolic, physiological, and biomass data from two laboratories, for five photoperiods, three accessions, and a transgenic line, highlighting the plasticity of plant growth strategies. The model was extended to include stochastic development. Model simulations gave insight into the developmental control of leaf production and provided a quantitative explanation for the pleiotropic developmental phenotype caused by overexpression of miR156, which was an open question. Modular, multiscale models, assembling knowledge from systems biology to ecophysiology, will help to understand and to engineer plant behavior from the genome to the field.

  19. Parallel algorithm for multiscale atomistic/continuum simulations using LAMMPS

    NASA Astrophysics Data System (ADS)

    Pavia, F.; Curtin, W. A.

    2015-07-01

    Deformation and fracture processes in engineering materials often require simultaneous descriptions over a range of length and time scales, with each scale using a different computational technique. Here we present a high-performance parallel 3D computing framework for executing large multiscale studies that couple an atomic domain, modeled using molecular dynamics and a continuum domain, modeled using explicit finite elements. We use the robust Coupled Atomistic/Discrete-Dislocation (CADD) displacement-coupling method, but without the transfer of dislocations between atoms and continuum. The main purpose of the work is to provide a multiscale implementation within an existing large-scale parallel molecular dynamics code (LAMMPS) that enables use of all the tools associated with this popular open-source code, while extending CADD-type coupling to 3D. Validation of the implementation includes the demonstration of (i) stability in finite-temperature dynamics using Langevin dynamics, (ii) elimination of wave reflections due to large dynamic events occurring in the MD region and (iii) the absence of spurious forces acting on dislocations due to the MD/FE coupling, for dislocations further than 10 Å from the coupling boundary. A first non-trivial example application of dislocation glide and bowing around obstacles is shown, for dislocation lengths of ∼50 nm using fewer than 1 000 000 atoms but reproducing results of extremely large atomistic simulations at much lower computational cost.

  20. Multiscale implementation of infinite-swap replica exchange molecular dynamics.

    PubMed

    Yu, Tang-Qing; Lu, Jianfeng; Abrams, Cameron F; Vanden-Eijnden, Eric

    2016-10-18

    Replica exchange molecular dynamics (REMD) is a popular method to accelerate conformational sampling of complex molecular systems. The idea is to run several replicas of the system in parallel at different temperatures that are swapped periodically. These swaps are typically attempted every few MD steps and accepted or rejected according to a Metropolis-Hastings criterion. This guarantees that the joint distribution of the composite system of replicas is the normalized sum of the symmetrized product of the canonical distributions of these replicas at the different temperatures. Here we propose a different implementation of REMD in which (i) the swaps obey a continuous-time Markov jump process implemented via Gillespie's stochastic simulation algorithm (SSA), which also samples exactly the aforementioned joint distribution and has the advantage of being rejection free, and (ii) this REMD-SSA is combined with the heterogeneous multiscale method to accelerate the rate of the swaps and reach the so-called infinite-swap limit that is known to optimize sampling efficiency. The method is easy to implement and can be trivially parallelized. Here we illustrate its accuracy and efficiency on the examples of alanine dipeptide in vacuum and C-terminal β-hairpin of protein G in explicit solvent. In this latter example, our results indicate that the landscape of the protein is a triple funnel with two folded structures and one misfolded structure that are stabilized by H-bonds.

  1. Spectral characteristics of background error covariance and multiscale data assimilation

    DOE PAGES

    Li, Zhijin; Cheng, Xiaoping; Gustafson, Jr., William I.; ...

    2016-05-17

    The steady increase of the spatial resolutions of numerical atmospheric and oceanic circulation models has occurred over the past decades. Horizontal grid spacing down to the order of 1 km is now often used to resolve cloud systems in the atmosphere and sub-mesoscale circulation systems in the ocean. These fine resolution models encompass a wide range of temporal and spatial scales, across which dynamical and statistical properties vary. In particular, dynamic flow systems at small scales can be spatially localized and temporarily intermittent. Difficulties of current data assimilation algorithms for such fine resolution models are numerically and theoretically examined. Ourmore » analysis shows that the background error correlation length scale is larger than 75 km for streamfunctions and is larger than 25 km for water vapor mixing ratios, even for a 2-km resolution model. A theoretical analysis suggests that such correlation length scales prevent the currently used data assimilation schemes from constraining spatial scales smaller than 150 km for streamfunctions and 50 km for water vapor mixing ratios. Moreover, our results highlight the need to fundamentally modify currently used data assimilation algorithms for assimilating high-resolution observations into the aforementioned fine resolution models. Lastly, within the framework of four-dimensional variational data assimilation, a multiscale methodology based on scale decomposition is suggested and challenges are discussed.« less

  2. Integrating Multiscale Modeling with Drug Effects for Cancer Treatment.

    PubMed

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

    2015-01-01

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

  3. Multiscale analysis of the intensity fluctuation in a time series of dynamic speckle patterns.

    PubMed

    Federico, Alejandro; Kaufmann, Guillermo H

    2007-04-10

    We propose the application of a method based on the discrete wavelet transform to detect, identify, and measure scaling behavior in dynamic speckle. The multiscale phenomena presented by a sample and displayed by its speckle activity are analyzed by processing the time series of dynamic speckle patterns. The scaling analysis is applied to the temporal fluctuation of the speckle intensity and also to the two derived data sets generated by its magnitude and sign. The application of the method is illustrated by analyzing paint-drying processes and bruising in apples. The results are discussed taking into account the different time organizations obtained for the scaling behavior of the magnitude and the sign of the intensity fluctuation.

  4. Noise and poise: Enhancement of postural complexity in the elderly with a stochastic-resonance based therapy

    NASA Astrophysics Data System (ADS)

    Costa, M.; Priplata, A. A.; Lipsitz, L. A.; Wu, Z.; Huang, N. E.; Goldberger, A. L.; Peng, C.-K.

    2007-03-01

    Pathologic states are associated with a loss of dynamical complexity. Therefore, therapeutic interventions that increase physiologic complexity may enhance health status. Using multiscale entropy analysis, we show that the postural sway dynamics of healthy young and healthy elderly subjects are more complex than that of elderly subjects with a history of falls. Application of subsensory noise to the feet has been demonstrated to improve postural stability in the elderly. We next show that this therapy significantly increases the multiscale complexity of sway fluctuations in healthy elderly subjects. Quantification of changes in dynamical complexity of biologic variability may be the basis of a new approach to assessing risk and to predicting the efficacy of clinical interventions, including noise-based therapies.

  5. Three-Dimensional Multiscale Modeling of Dendritic Spacing Selection During Al-Si Directional Solidification

    NASA Astrophysics Data System (ADS)

    Tourret, Damien; Clarke, Amy J.; Imhoff, Seth D.; Gibbs, Paul J.; Gibbs, John W.; Karma, Alain

    2015-08-01

    We present a three-dimensional extension of the multiscale dendritic needle network (DNN) model. This approach enables quantitative simulations of the unsteady dynamics of complex hierarchical networks in spatially extended dendritic arrays. We apply the model to directional solidification of Al-9.8 wt.%Si alloy and directly compare the model predictions with measurements from experiments with in situ x-ray imaging. We focus on the dynamical selection of primary spacings over a range of growth velocities, and the influence of sample geometry on the selection of spacings. Simulation results show good agreement with experiments. The computationally efficient DNN model opens new avenues for investigating the dynamics of large dendritic arrays at scales relevant to solidification experiments and processes.

  6. 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.

  7. Multiscale modeling of brain dynamics: from single neurons and networks to mathematical tools.

    PubMed

    Siettos, Constantinos; Starke, Jens

    2016-09-01

    The extreme complexity of the brain naturally requires mathematical modeling approaches on a large variety of scales; the spectrum ranges from single neuron dynamics over the behavior of groups of neurons to neuronal network activity. Thus, the connection between the microscopic scale (single neuron activity) to macroscopic behavior (emergent behavior of the collective dynamics) and vice versa is a key to understand the brain in its complexity. In this work, we attempt a review of a wide range of approaches, ranging from the modeling of single neuron dynamics to machine learning. The models include biophysical as well as data-driven phenomenological models. The discussed models include Hodgkin-Huxley, FitzHugh-Nagumo, coupled oscillators (Kuramoto oscillators, Rössler oscillators, and the Hindmarsh-Rose neuron), Integrate and Fire, networks of neurons, and neural field equations. In addition to the mathematical models, important mathematical methods in multiscale modeling and reconstruction of the causal connectivity are sketched. The methods include linear and nonlinear tools from statistics, data analysis, and time series analysis up to differential equations, dynamical systems, and bifurcation theory, including Granger causal connectivity analysis, phase synchronization connectivity analysis, principal component analysis (PCA), independent component analysis (ICA), and manifold learning algorithms such as ISOMAP, and diffusion maps and equation-free techniques. WIREs Syst Biol Med 2016, 8:438-458. doi: 10.1002/wsbm.1348 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

  8. Finding Multi-scale Connectivity in Our Geospace Observational System: A New Perspective for Total Electron Content Data Through Network Analysis

    NASA Astrophysics Data System (ADS)

    McGranaghan, R. M.; Mannucci, A. J.; Verkhoglyadova, O. P.; Malik, N.

    2017-12-01

    How do we evolve beyond current traditional methods in order to innovate into the future? In what disruptive innovations will the next frontier of space physics and aeronomy (SPA) be grounded? We believe the answer to these compelling, yet equally challenging, questions lies in a shift of focus: from a narrow, field-specific view to a radically inclusive, interdisciplinary new modus operandi at the intersection of SPA and the information and data sciences. Concretely addressing these broader themes, we present results from a novel technique for knowledge discovery in the magnetosphere-ionosphere-thermosphere (MIT) system: complex network analysis (NA). We share findings from the first NA of ionospheric total electron content (TEC) data, including hemispheric and interplanetary magnetic field clock angle dependencies [1]. Our work shows that NA complements more traditional approaches for the investigation of TEC structure and dynamics, by both reaffirming well-established understanding, giving credence to the method, and identifying new connections, illustrating the exciting potential. We contextualize these new results through a discussion of the potential of data-driven discovery in the MIT system when innovative data science techniques are embraced. We address implications and potentially disruptive data analysis approaches for SPA in terms of: 1) the future of the geospace observational system; 2) understanding multi-scale phenomena; and 3) machine learning. [1] McGranaghan, R. M., A. J. Mannucci, O. Verkhoglyadova, and N. Malik (2017), Finding multiscale connectivity in our geospace observational system: Network analysis of total electron content, J. Geophys. Res. Space Physics, 122, doi:10.1002/2017JA024202.

  9. Concussion As a Multi-Scale Complex System: An Interdisciplinary Synthesis of Current Knowledge

    PubMed Central

    Kenzie, Erin S.; Parks, Elle L.; Bigler, Erin D.; Lim, Miranda M.; Chesnutt, James C.; Wakeland, Wayne

    2017-01-01

    Traumatic brain injury (TBI) has been called “the most complicated disease of the most complex organ of the body” and is an increasingly high-profile public health issue. Many patients report long-term impairments following even “mild” injuries, but reliable criteria for diagnosis and prognosis are lacking. Every clinical trial for TBI treatment to date has failed to demonstrate reliable and safe improvement in outcomes, and the existing body of literature is insufficient to support the creation of a new classification system. Concussion, or mild TBI, is a highly heterogeneous phenomenon, and numerous factors interact dynamically to influence an individual’s recovery trajectory. Many of the obstacles faced in research and clinical practice related to TBI and concussion, including observed heterogeneity, arguably stem from the complexity of the condition itself. To improve understanding of this complexity, we review the current state of research through the lens provided by the interdisciplinary field of systems science, which has been increasingly applied to biomedical issues. The review was conducted iteratively, through multiple phases of literature review, expert interviews, and systems diagramming and represents the first phase in an effort to develop systems models of concussion. The primary focus of this work was to examine concepts and ways of thinking about concussion that currently impede research design and block advancements in care of TBI. Results are presented in the form of a multi-scale conceptual framework intended to synthesize knowledge across disciplines, improve research design, and provide a broader, multi-scale model for understanding concussion pathophysiology, classification, and treatment. PMID:29033888

  10. Using the PORS Problems to Examine Evolutionary Optimization of Multiscale Systems

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

    Reinhart, Zachary; Molian, Vaelan; Bryden, Kenneth

    2013-01-01

    Nearly all systems of practical interest are composed of parts assembled across multiple scales. For example, an agrodynamic system is composed of flora and fauna on one scale; soil types, slope, and water runoff on another scale; and management practice and yield on another scale. Or consider an advanced coal-fired power plant: combustion and pollutant formation occurs on one scale, the plant components on another scale, and the overall performance of the power system is measured on another. In spite of this, there are few practical tools for the optimization of multiscale systems. This paper examines multiscale optimization of systemsmore » composed of discrete elements using the plus-one-recall-store (PORS) problem as a test case or study problem for multiscale systems. From this study, it is found that by recognizing the constraints and patterns present in discrete multiscale systems, the solution time can be significantly reduced and much more complex problems can be optimized.« less

  11. Multiscale complex network analysis: An approach to study spatiotemporal rainfall pattern in south Germany

    NASA Astrophysics Data System (ADS)

    Agarwal, Ankit; Marwan, Norbert; Rathinasamy, Maheswaran; Oeztuerk, Ugur; Merz, Bruno; Kurths, Jürgen

    2017-04-01

    Understanding of the climate sytems has been of tremendous importance to different branches such as agriculture, flood, drought and water resources management etc. In this regard, complex networks analysis and time series analysis attracted considerable attention, owing to their potential role in understanding the climate system through characteristic properties. One of the basic requirements in studying climate network dynamics is to identify connections in space or time or space-time, depending upon the purpose. Although a wide variety of approaches have been developed and applied to identify and analyse spatio-temporal relationships by climate networks, there is still further need for improvements in particular when considering precipitation time series or interactions on different scales. In this regard, recent developments in the area of network theory, especially complex networks, offer new avenues, both for their generality about systems and for their holistic perspective about spatio-temporal relationships. The present study has made an attempt to apply the ideas developed in the field of complex networks to examine connections in regional climate networks with particular focus on multiscale spatiotemporal connections. This paper proposes a novel multiscale understanding of regional climate networks using wavelets. The proposed approach is applied to daily precipitation records observed at 543 selected stations from south Germany for a period of 110 years (1901-2010). Further, multiscale community mining is performed on the same study region to shed more light on the underlying processes at different time scales. Various network measure and tools so far employed provide micro-level (individual station) and macro-level (community structure) information of the network. It is interesting to investigate how the result of this study can be useful for future climate predictions and for evaluating climate models on their implementation regarding heavy precipitation. Keywords: Complex network, event synchronization, wavelet, regional climate network, multiscale community mining

  12. Multiscale functions, scale dynamics, and applications to partial differential equations

    NASA Astrophysics Data System (ADS)

    Cresson, Jacky; Pierret, Frédéric

    2016-05-01

    Modeling phenomena from experimental data always begins with a choice of hypothesis on the observed dynamics such as determinism, randomness, and differentiability. Depending on these choices, different behaviors can be observed. The natural question associated to the modeling problem is the following: "With a finite set of data concerning a phenomenon, can we recover its underlying nature? From this problem, we introduce in this paper the definition of multi-scale functions, scale calculus, and scale dynamics based on the time scale calculus [see Bohner, M. and Peterson, A., Dynamic Equations on Time Scales: An Introduction with Applications (Springer Science & Business Media, 2001)] which is used to introduce the notion of scale equations. These definitions will be illustrated on the multi-scale Okamoto's functions. Scale equations are analysed using scale regimes and the notion of asymptotic model for a scale equation under a particular scale regime. The introduced formalism explains why a single scale equation can produce distinct continuous models even if the equation is scale invariant. Typical examples of such equations are given by the scale Euler-Lagrange equation. We illustrate our results using the scale Newton's equation which gives rise to a non-linear diffusion equation or a non-linear Schrödinger equation as asymptotic continuous models depending on the particular fractional scale regime which is considered.

  13. A Multi-scale Computational Platform to Mechanistically Assess the Effect of Genetic Variation on Drug Responses in Human Erythrocyte Metabolism

    PubMed Central

    Bordbar, Aarash; Palsson, Bernhard O.

    2016-01-01

    Progress in systems medicine brings promise to addressing patient heterogeneity and individualized therapies. Recently, genome-scale models of metabolism have been shown to provide insight into the mechanistic link between drug therapies and systems-level off-target effects while being expanded to explicitly include the three-dimensional structure of proteins. The integration of these molecular-level details, such as the physical, structural, and dynamical properties of proteins, notably expands the computational description of biochemical network-level properties and the possibility of understanding and predicting whole cell phenotypes. In this study, we present a multi-scale modeling framework that describes biological processes which range in scale from atomistic details to an entire metabolic network. Using this approach, we can understand how genetic variation, which impacts the structure and reactivity of a protein, influences both native and drug-induced metabolic states. As a proof-of-concept, we study three enzymes (catechol-O-methyltransferase, glucose-6-phosphate dehydrogenase, and glyceraldehyde-3-phosphate dehydrogenase) and their respective genetic variants which have clinically relevant associations. Using all-atom molecular dynamic simulations enables the sampling of long timescale conformational dynamics of the proteins (and their mutant variants) in complex with their respective native metabolites or drug molecules. We find that changes in a protein’s structure due to a mutation influences protein binding affinity to metabolites and/or drug molecules, and inflicts large-scale changes in metabolism. PMID:27467583

  14. A Multi-scale Computational Platform to Mechanistically Assess the Effect of Genetic Variation on Drug Responses in Human Erythrocyte Metabolism.

    PubMed

    Mih, Nathan; Brunk, Elizabeth; Bordbar, Aarash; Palsson, Bernhard O

    2016-07-01

    Progress in systems medicine brings promise to addressing patient heterogeneity and individualized therapies. Recently, genome-scale models of metabolism have been shown to provide insight into the mechanistic link between drug therapies and systems-level off-target effects while being expanded to explicitly include the three-dimensional structure of proteins. The integration of these molecular-level details, such as the physical, structural, and dynamical properties of proteins, notably expands the computational description of biochemical network-level properties and the possibility of understanding and predicting whole cell phenotypes. In this study, we present a multi-scale modeling framework that describes biological processes which range in scale from atomistic details to an entire metabolic network. Using this approach, we can understand how genetic variation, which impacts the structure and reactivity of a protein, influences both native and drug-induced metabolic states. As a proof-of-concept, we study three enzymes (catechol-O-methyltransferase, glucose-6-phosphate dehydrogenase, and glyceraldehyde-3-phosphate dehydrogenase) and their respective genetic variants which have clinically relevant associations. Using all-atom molecular dynamic simulations enables the sampling of long timescale conformational dynamics of the proteins (and their mutant variants) in complex with their respective native metabolites or drug molecules. We find that changes in a protein's structure due to a mutation influences protein binding affinity to metabolites and/or drug molecules, and inflicts large-scale changes in metabolism.

  15. Study of Static Microchannel Plate Saturation Effects for the Fast Plasma Investigation Dual Electron Spectrometers on NASA's Magnetospheric MultiScale Mission

    NASA Technical Reports Server (NTRS)

    Avanov, L. A.; Gliese, U.; Pollock, C. J.; Moore, T. E.; Chornay, D. J.; Barrie, A. C.; Kujawski, J. T.; Gershman, D. J.; Tucker, C. J.; Mariano, A.; hide

    2015-01-01

    Imaging detecting systems based on microchannel plates (MCPs) are the most common for low energy plasma measurements for both space borne and ground applications. One of the key parameters of these detection systems is the dynamic range of the MCP's response to the input fluxes of charged particles. For most applications the dynamic range of the linear response should be as wide as possible. This is especially true for the Dual Electron Spectrometers (DESs) of the Fast Plasma Investigation (FPI) on NASA's Magnetospheric MultiScale (MMS) mission because a wide range of input fluxes are expected. To make use of the full available dynamic range, it is important to understand the MCP response behavior beyond the linear regime where the MCPs start to saturate. We have performed extensive studies of this during the characterization and calibration of the DES instruments and have identified several saturation effects of the detection system. The MCP itself exhibits saturation when the channels lack the ability to replenish charge sufficiently rapidly. It is found and will be shown that the ground system can significantly impact the correct measurement of this effect. As the MCP starts to saturate, the resulting pulse height distribution (PHD) changes shape and location (with less pulse height values), which leads to truncation of the PHD by the threshold set on the detection system discriminator. Finally, the detection system pulse amplifier exhibits saturation as the input flux drives pulse rates greater than its linear response speed. All of these effects effectively change the dead time of the overall detection system and as a result can affect the quality and interpretation of the flight data. We present results of detection system saturation effects and their interaction with special emphasis on the MCP related effects.

  16. System-level view of geospace dynamics: Challenges for high-latitude ground-based observations

    NASA Astrophysics Data System (ADS)

    Donovan, E.

    2014-12-01

    Increasingly, research programs including GEM, CEDAR, GEMSIS, GO Canada, and others are focusing on how geospace works as a system. Coupling sits at the heart of system level dynamics. In all cases, coupling is accomplished via fundamental processes such as reconnection and plasma waves, and can be between regions, energy ranges, species, scales, and energy reservoirs. Three views of geospace are required to attack system level questions. First, we must observe the fundamental processes that accomplish the coupling. This "observatory view" requires in situ measurements by satellite-borne instruments or remote sensing from powerful well-instrumented ground-based observatories organized around, for example, Incoherent Scatter Radars. Second, we need to see how this coupling is controlled and what it accomplishes. This demands quantitative observations of the system elements that are being coupled. This "multi-scale view" is accomplished by networks of ground-based instruments, and by global imaging from space. Third, if we take geospace as a whole, the system is too complicated, so at the top level we need time series of simple quantities such as indices that capture important aspects of the system level dynamics. This requires a "key parameter view" that is typically provided through indices such as AE and DsT. With the launch of MMS, and ongoing missions such as THEMIS, Cluster, Swarm, RBSP, and ePOP, we are entering a-once-in-a-lifetime epoch with a remarkable fleet of satellites probing processes at key regions throughout geospace, so the observatory view is secure. With a few exceptions, our key parameter view provides what we need. The multi-scale view, however, is compromised by space/time scales that are important but under-sampled, combined extent of coverage and resolution that falls short of what we need, and inadequate conjugate observations. In this talk, I present an overview of what we need for taking system level research to its next level, and how high latitude ground based observations can address these challenges.

  17. Multi-scale modelling of supercapacitors: From molecular simulations to a transmission line model

    NASA Astrophysics Data System (ADS)

    Pean, C.; Rotenberg, B.; Simon, P.; Salanne, M.

    2016-09-01

    We perform molecular dynamics simulations of a typical nanoporous-carbon based supercapacitor. The organic electrolyte consists in 1-ethyl-3-methylimidazolium and hexafluorophosphate ions dissolved in acetonitrile. We simulate systems at equilibrium, for various applied voltages. This allows us to determine the relevant thermodynamic (capacitance) and transport (in-pore resistivities) properties. These quantities are then injected in a transmission line model for testing its ability to predict the charging properties of the device. The results from this macroscopic model are in good agreement with non-equilibrium molecular dynamics simulations, which validates its use for interpreting electrochemical impedance experiments.

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

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

    Kevrekidis, Ioannis G.

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

  19. Exploring a multi-scale method for molecular simulation in continuum solvent model: Explicit simulation of continuum solvent as an incompressible fluid.

    PubMed

    Xiao, Li; Luo, Ray

    2017-12-07

    We explored a multi-scale algorithm for the Poisson-Boltzmann continuum solvent model for more robust simulations of biomolecules. In this method, the continuum solvent/solute interface is explicitly simulated with a numerical fluid dynamics procedure, which is tightly coupled to the solute molecular dynamics simulation. There are multiple benefits to adopt such a strategy as presented below. At this stage of the development, only nonelectrostatic interactions, i.e., van der Waals and hydrophobic interactions, are included in the algorithm to assess the quality of the solvent-solute interface generated by the new method. Nevertheless, numerical challenges exist in accurately interpolating the highly nonlinear van der Waals term when solving the finite-difference fluid dynamics equations. We were able to bypass the challenge rigorously by merging the van der Waals potential and pressure together when solving the fluid dynamics equations and by considering its contribution in the free-boundary condition analytically. The multi-scale simulation method was first validated by reproducing the solute-solvent interface of a single atom with analytical solution. Next, we performed the relaxation simulation of a restrained symmetrical monomer and observed a symmetrical solvent interface at equilibrium with detailed surface features resembling those found on the solvent excluded surface. Four typical small molecular complexes were then tested, both volume and force balancing analyses showing that these simple complexes can reach equilibrium within the simulation time window. Finally, we studied the quality of the multi-scale solute-solvent interfaces for the four tested dimer complexes and found that they agree well with the boundaries as sampled in the explicit water simulations.

  20. Stress Distribution During Deformation of Polycrystalline Aluminum by Molecular-Dynamics and Finite-Element Modeling

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

    In this paper, a multiscale modelling strategy is used to study the effect of grain-boundary sliding on stress localization in a polycrystalline microstructure with an uneven distribution of grain size. The development of the molecular dynamics (MD) analysis used to interrogate idealized grain microstructures with various types of grain boundaries and the multiscale modelling strategies for modelling large systems of grains is discussed. Both molecular-dynamics and finite-element (FE) simulations for idealized polycrystalline models of identical geometry are presented with the purpose of demonstrating the effectiveness of the adapted finite-element method using cohesive zone models to reproduce grain-boundary sliding and its effect on the stress distribution in a polycrystalline metal. The yield properties of the grain-boundary interface, used in the FE simulations, are extracted from a MD simulation on a bicrystal. The models allow for the study of the load transfer between adjacent grains of very different size through grain-boundary sliding during deformation. A large-scale FE simulation of 100 grains of a typical microstructure is then presented to reveal that the stress distribution due to grain-boundary sliding during uniform tensile strain can lead to stress localization of two to three times the background stress, thus suggesting a significant effect on the failure properties of the metal.

  1. On the interplay between mathematics and biology: hallmarks toward a new systems biology.

    PubMed

    Bellomo, Nicola; Elaiw, Ahmed; Althiabi, Abdullah M; Alghamdi, Mohammed Ali

    2015-03-01

    This paper proposes a critical analysis of the existing literature on mathematical tools developed toward systems biology approaches and, out of this overview, develops a new approach whose main features can be briefly summarized as follows: derivation of mathematical structures suitable to capture the complexity of biological, hence living, systems, modeling, by appropriate mathematical tools, Darwinian type dynamics, namely mutations followed by selection and evolution. Moreover, multiscale methods to move from genes to cells, and from cells to tissue are analyzed in view of a new systems biology approach. Copyright © 2014 Elsevier B.V. All rights reserved.

  2. Scale-dependent intrinsic entropies of complex time series.

    PubMed

    Yeh, Jia-Rong; Peng, Chung-Kang; Huang, Norden E

    2016-04-13

    Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal's complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease. © 2016 The Author(s).

  3. State estimation and prediction using clustered particle filters.

    PubMed

    Lee, Yoonsang; Majda, Andrew J

    2016-12-20

    Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors.

  4. Multiscale Multilevel Approach to Solution of Nanotechnology Problems

    NASA Astrophysics Data System (ADS)

    Polyakov, Sergey; Podryga, Viktoriia

    2018-02-01

    The paper is devoted to a multiscale multilevel approach for the solution of nanotechnology problems on supercomputer systems. The approach uses the combination of continuum mechanics models and the Newton dynamics for individual particles. This combination includes three scale levels: macroscopic, mesoscopic and microscopic. For gas-metal technical systems the following models are used. The quasihydrodynamic system of equations is used as a mathematical model at the macrolevel for gas and solid states. The system of Newton equations is used as a mathematical model at the mesoand microlevels; it is written for nanoparticles of the medium and larger particles moving in the medium. The numerical implementation of the approach is based on the method of splitting into physical processes. The quasihydrodynamic equations are solved by the finite volume method on grids of different types. The Newton equations of motion are solved by Verlet integration in each cell of the grid independently or in groups of connected cells. In the framework of the general methodology, four classes of algorithms and methods of their parallelization are provided. The parallelization uses the principles of geometric parallelism and the efficient partitioning of the computational domain. A special dynamic algorithm is used for load balancing the solvers. The testing of the developed approach was made by the example of the nitrogen outflow from a balloon with high pressure to a vacuum chamber through a micronozzle and a microchannel. The obtained results confirm the high efficiency of the developed methodology.

  5. State estimation and prediction using clustered particle filters

    PubMed Central

    Lee, Yoonsang; Majda, Andrew J.

    2016-01-01

    Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors. PMID:27930332

  6. Network representations of immune system complexity

    PubMed Central

    Subramanian, Naeha; Torabi-Parizi, Parizad; Gottschalk, Rachel A.; Germain, Ronald N.; Dutta, Bhaskar

    2015-01-01

    The mammalian immune system is a dynamic multi-scale system composed of a hierarchically organized set of molecular, cellular and organismal networks that act in concert to promote effective host defense. These networks range from those involving gene regulatory and protein-protein interactions underlying intracellular signaling pathways and single cell responses to increasingly complex networks of in vivo cellular interaction, positioning and migration that determine the overall immune response of an organism. Immunity is thus not the product of simple signaling events but rather non-linear behaviors arising from dynamic, feedback-regulated interactions among many components. One of the major goals of systems immunology is to quantitatively measure these complex multi-scale spatial and temporal interactions, permitting development of computational models that can be used to predict responses to perturbation. Recent technological advances permit collection of comprehensive datasets at multiple molecular and cellular levels while advances in network biology support representation of the relationships of components at each level as physical or functional interaction networks. The latter facilitate effective visualization of patterns and recognition of emergent properties arising from the many interactions of genes, molecules, and cells of the immune system. We illustrate the power of integrating ‘omics’ and network modeling approaches for unbiased reconstruction of signaling and transcriptional networks with a focus on applications involving the innate immune system. We further discuss future possibilities for reconstruction of increasingly complex cellular and organism-level networks and development of sophisticated computational tools for prediction of emergent immune behavior arising from the concerted action of these networks. PMID:25625853

  7. Multi-scale calculation based on dual domain material point method combined with molecular dynamics

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

    Dhakal, Tilak Raj

    This dissertation combines the dual domain material point method (DDMP) with molecular dynamics (MD) in an attempt to create a multi-scale numerical method to simulate materials undergoing large deformations with high strain rates. In these types of problems, the material is often in a thermodynamically non-equilibrium state, and conventional constitutive relations are often not available. In this method, the closure quantities, such as stress, at each material point are calculated from a MD simulation of a group of atoms surrounding the material point. Rather than restricting the multi-scale simulation in a small spatial region, such as phase interfaces, or crackmore » tips, this multi-scale method can be used to consider non-equilibrium thermodynamic e ects in a macroscopic domain. This method takes advantage that the material points only communicate with mesh nodes, not among themselves; therefore MD simulations for material points can be performed independently in parallel. First, using a one-dimensional shock problem as an example, the numerical properties of the original material point method (MPM), the generalized interpolation material point (GIMP) method, the convected particle domain interpolation (CPDI) method, and the DDMP method are investigated. Among these methods, only the DDMP method converges as the number of particles increases, but the large number of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the computation. The numerical properties of the multiscale method are investigated as well as the results from this multi-scale calculation are compared of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the computation. The numerical properties of the multiscale method are investigated as well as the results from this multi-scale calculation are compared with direct MD simulation results to demonstrate the feasibility of the method. Also, the multi-scale method is applied for a two dimensional problem of jet formation around copper notch under a strong impact.« less

  8. Consequences of chirality on the dynamics of a water-soluble supramolecular polymer.

    PubMed

    Baker, Matthew B; Albertazzi, Lorenzo; Voets, Ilja K; Leenders, Christianus M A; Palmans, Anja R A; Pavan, Giovanni M; Meijer, E W

    2015-02-20

    The rational design of supramolecular polymers in water is imperative for their widespread use, but the design principles for these systems are not well understood. Herein, we employ a multi-scale (spatial and temporal) approach to differentiate two analogous water-soluble supramolecular polymers: one with and one without a stereogenic methyl. Initially aiming simply to understand the molecular behaviour of these systems in water, we find that while the fibres may look identical, the introduction of homochirality imparts a higher level of internal order to the supramolecular polymer. Although this increased order does not seem to affect the basic dimensions of the supramolecular fibres, the equilibrium dynamics of the polymers differ by almost an order of magnitude. This report represents the first observation of a structure/property relationship with regard to equilibrium dynamics in water-soluble supramolecular polymers.

  9. Consequences of chirality on the dynamics of a water-soluble supramolecular polymer

    NASA Astrophysics Data System (ADS)

    Baker, Matthew B.; Albertazzi, Lorenzo; Voets, Ilja K.; Leenders, Christianus M. A.; Palmans, Anja R. A.; Pavan, Giovanni M.; Meijer, E. W.

    2015-02-01

    The rational design of supramolecular polymers in water is imperative for their widespread use, but the design principles for these systems are not well understood. Herein, we employ a multi-scale (spatial and temporal) approach to differentiate two analogous water-soluble supramolecular polymers: one with and one without a stereogenic methyl. Initially aiming simply to understand the molecular behaviour of these systems in water, we find that while the fibres may look identical, the introduction of homochirality imparts a higher level of internal order to the supramolecular polymer. Although this increased order does not seem to affect the basic dimensions of the supramolecular fibres, the equilibrium dynamics of the polymers differ by almost an order of magnitude. This report represents the first observation of a structure/property relationship with regard to equilibrium dynamics in water-soluble supramolecular polymers.

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

    NASA Astrophysics Data System (ADS)

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

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

  11. Magnetospheric MultiScale (MMS) System Manager

    NASA Technical Reports Server (NTRS)

    Schiff, Conrad; Maher, Francis Alfred; Henely, Sean Philip; Rand, David

    2014-01-01

    The Magnetospheric MultiScale (MMS) mission is an ambitious NASA space science mission in which 4 spacecraft are flown in tight formation about a highly elliptical orbit. Each spacecraft has multiple instruments that measure particle and field compositions in the Earths magnetosphere. By controlling the members relative motion, MMS can distinguish temporal and spatial fluctuations in a way that a single spacecraft cannot.To achieve this control, 2 sets of four maneuvers, distributed evenly across the spacecraft must be performed approximately every 14 days. Performing a single maneuver on an individual spacecraft is usually labor intensive and the complexity becomes clearly increases with four. As a result, the MMS flight dynamics team turned to the System Manager to put the routine or error-prone under machine control freeing the analysts for activities that require human judgment.The System Manager is an expert system that is capable of handling operations activities associated with performing MMS maneuvers. As an expert system, it can work off a known schedule, launching jobs based on a one-time occurrence or on a set reoccurring schedule. It is also able to detect situational changes and use event-driven programming to change schedules, adapt activities, or call for help.

  12. A Multi-Scale Method for Dynamics Simulation in Continuum Solvent Models I: Finite-Difference Algorithm for Navier-Stokes Equation

    PubMed Central

    Xiao, Li; Cai, Qin; Li, Zhilin; Zhao, Hongkai; Luo, Ray

    2014-01-01

    A multi-scale framework is proposed for more realistic molecular dynamics simulations in continuum solvent models by coupling a molecular mechanics treatment of solute with a fluid mechanics treatment of solvent. This article reports our initial efforts to formulate the physical concepts necessary for coupling the two mechanics and develop a 3D numerical algorithm to simulate the solvent fluid via the Navier-Stokes equation. The numerical algorithm was validated with multiple test cases. The validation shows that the algorithm is effective and stable, with observed accuracy consistent with our design. PMID:25404761

  13. Using Multi-scale Dynamic Rupture Models to Improve Ground Motion Estimates: ALCF-2 Early Science Program Technical Report

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

    Ely, Geoffrey P.

    2013-10-31

    This project uses dynamic rupture simulations to investigate high-frequency seismic energy generation. The relevant phenomena (frictional breakdown, shear heating, effective normal-stress fluctuations, material damage, etc.) controlling rupture are strongly interacting and span many orders of magnitude in spatial scale, requiring highresolution simulations that couple disparate physical processes (e.g., elastodynamics, thermal weakening, pore-fluid transport, and heat conduction). Compounding the computational challenge, we know that natural faults are not planar, but instead have roughness that can be approximated by power laws potentially leading to large, multiscale fluctuations in normal stress. The capacity to perform 3D rupture simulations that couple these processes willmore » provide guidance for constructing appropriate source models for high-frequency ground motion simulations. The improved rupture models from our multi-scale dynamic rupture simulations will be used to conduct physicsbased (3D waveform modeling-based) probabilistic seismic hazard analysis (PSHA) for California. These calculation will provide numerous important seismic hazard results, including a state-wide extended earthquake rupture forecast with rupture variations for all significant events, a synthetic seismogram catalog for thousands of scenario events and more than 5000 physics-based seismic hazard curves for California.« less

  14. Prediction of Thermal Transport Properties of Materials with Microstructural Complexity

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

    Chen, Youping

    This project aims at overcoming the major obstacle standing in the way of progress in dynamic multiscale simulation, which is the lack of a concurrent atomistic-continuum method that allows phonons, heat and defects to pass through the atomistic-continuum interface. The research has led to the development of a concurrent atomistic-continuum (CAC) methodology for multiscale simulations of materials microstructural, mechanical and thermal transport behavior. Its efficacy has been tested and demonstrated through simulations of dislocation dynamics and phonon transport coupled with microstructural evolution in a variety of materials and through providing visual evidences of the nature of phonon transport, such asmore » showing the propagation of heat pulses in single and polycrystalline solids is partially ballistic and partially diffusive. In addition to providing understanding on phonon scattering with phase interface and with grain boundaries, the research has contributed a multiscale simulation tool for understanding of the behavior of complex materials and has demonstrated the capability of the tool in simulating the dynamic, in situ experimental studies of nonequilibrium transient transport processes in material samples that are at length scales typically inaccessible by atomistically resolved methods.« less

  15. Multiscale polar theory of microtubule and motor-protein assemblies

    DOE PAGES

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

    2015-01-27

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

  16. A fault diagnosis scheme for planetary gearboxes using modified multi-scale symbolic dynamic entropy and mRMR feature selection

    NASA Astrophysics Data System (ADS)

    Li, Yongbo; Yang, Yuantao; Li, Guoyan; Xu, Minqiang; Huang, Wenhu

    2017-07-01

    Health condition identification of planetary gearboxes is crucial to reduce the downtime and maximize productivity. This paper aims to develop a novel fault diagnosis method based on modified multi-scale symbolic dynamic entropy (MMSDE) and minimum redundancy maximum relevance (mRMR) to identify the different health conditions of planetary gearbox. MMSDE is proposed to quantify the regularity of time series, which can assess the dynamical characteristics over a range of scales. MMSDE has obvious advantages in the detection of dynamical changes and computation efficiency. Then, the mRMR approach is introduced to refine the fault features. Lastly, the obtained new features are fed into the least square support vector machine (LSSVM) to complete the fault pattern identification. The proposed method is numerically and experimentally demonstrated to be able to recognize the different fault types of planetary gearboxes.

  17. Simultaneous multiscale measurements on dynamic deformation of a magnesium alloy with synchrotron x-ray imaging and diffraction

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

    Lu, L.; Sun, T.; Fezzaa, K.

    Dynamic split Hopkinson pressure bar experiments with in situ synchrotron x-ray imaging and diffraction are conducted on a rolled magnesium alloy at high strain rates of ~5500 s-1. High speed multiscale measurements including stress–strain curves (macroscale), strain fields (mesoscale), and diffraction patterns (microscale) are obtained simultaneously, revealing strong anisotropy in deformation across different length scales. {1012} extension twinning induces homogenized strain fields and gives rise to rapid increase in strain hardening rate, while dislocation motion leads to inhomogeneous deformation and a decrease in strain hardening rate. During the early stage of plastic deformation, twinning is dominant in dynamic compression, whilemore » dislocation motion prevails in quasi-static loading, manifesting a strain-rate dependence of deformation.« less

  18. Three-dimensional multiscale modeling of dendritic spacing selection during Al-Si directional solidification

    DOE PAGES

    Tourret, Damien; Clarke, Amy J.; Imhoff, Seth D.; ...

    2015-05-27

    We present a three-dimensional extension of the multiscale dendritic needle network (DNN) model. This approach enables quantitative simulations of the unsteady dynamics of complex hierarchical networks in spatially extended dendritic arrays. We apply the model to directional solidification of Al-9.8 wt.%Si alloy and directly compare the model predictions with measurements from experiments with in situ x-ray imaging. The focus is on the dynamical selection of primary spacings over a range of growth velocities, and the influence of sample geometry on the selection of spacings. Simulation results show good agreement with experiments. The computationally efficient DNN model opens new avenues formore » investigating the dynamics of large dendritic arrays at scales relevant to solidification experiments and processes.« less

  19. Interacting Multiscale Acoustic Vortices as Coherent Excitations in Dust Acoustic Wave Turbulence

    NASA Astrophysics Data System (ADS)

    Lin, Po-Cheng; I, Lin

    2018-03-01

    In this work, using three-dimensional intermittent dust acoustic wave turbulence in a dusty plasma as a platform and multidimensional empirical mode decomposition into different-scale modes in the 2 +1 D spatiotemporal space, we demonstrate the experimental observation of the interacting multiscale acoustic vortices, winding around wormlike amplitude hole filaments coinciding with defect filaments, as the basic coherent excitations for acoustic-type wave turbulence. For different decomposed modes, the self-similar rescaled stretched exponential lifetime histograms of amplitude hole filaments, and the self-similar power spectra of dust density fluctuations, indicate that similar dynamical rules are followed over a wide range of scales. In addition to the intermode acoustic vortex pair generation, propagation, or annihilation, the intra- and intermode interactions of acoustic vortices with the same or opposite helicity, their entanglement and synchronization, are found to be the key dynamical processes in acoustic wave turbulence, akin to the interacting multiscale vortices around wormlike cores observed in hydrodynamic turbulence.

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

    PubMed Central

    Ong, Frank; Lustig, Michael

    2016-01-01

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

  1. Coarse-grained molecular dynamics simulations for giant protein-DNA complexes

    NASA Astrophysics Data System (ADS)

    Takada, Shoji

    Biomolecules are highly hierarchic and intrinsically flexible. Thus, computational modeling calls for multi-scale methodologies. We have been developing a coarse-grained biomolecular model where on-average 10-20 atoms are grouped into one coarse-grained (CG) particle. Interactions among CG particles are tuned based on atomistic interactions and the fluctuation matching algorithm. CG molecular dynamics methods enable us to simulate much longer time scale motions of much larger molecular systems than fully atomistic models. After broad sampling of structures with CG models, we can easily reconstruct atomistic models, from which one can continue conventional molecular dynamics simulations if desired. Here, we describe our CG modeling methodology for protein-DNA complexes, together with various biological applications, such as the DNA duplication initiation complex, model chromatins, and transcription factor dynamics on chromatin-like environment.

  2. Multi-Scale Impact and Compression-After-Impact Modeling of Reinforced Benzoxazine/Epoxy Composites using Micromechanics Approach

    NASA Astrophysics Data System (ADS)

    Montero, Marc Villa; Barjasteh, Ehsan; Baid, Harsh K.; Godines, Cody; Abdi, Frank; Nikbin, Kamran

    A multi-scale micromechanics approach along with finite element (FE) model predictive tool is developed to analyze low-energy-impact damage footprint and compression-after-impact (CAI) of composite laminates which is also tested and verified with experimental data. Effective fiber and matrix properties were reverse-engineered from lamina properties using an optimization algorithm and used to assess damage at the micro-level during impact and post-impact FE simulations. Progressive failure dynamic analysis (PFDA) was performed for a two step-process simulation. Damage mechanisms at the micro-level were continuously evaluated during the analyses. Contribution of each failure mode was tracked during the simulations and damage and delamination footprint size and shape were predicted to understand when, where and why failure occurred during both impact and CAI events. The composite laminate was manufactured by the vacuum infusion of the aero-grade toughened Benzoxazine system into the fabric preform. Delamination footprint was measured using C-scan data from the impacted panels and compared with the predicated values obtained from proposed multi-scale micromechanics coupled with FE analysis. Furthermore, the residual strength was predicted from the load-displacement curve and compared with the experimental values as well.

  3. Multiscale modeling and computation of optically manipulated nano devices

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

    Bao, Gang, E-mail: baog@zju.edu.cn; Liu, Di, E-mail: richardl@math.msu.edu; Luo, Songting, E-mail: luos@iastate.edu

    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, andmore » 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.« less

  4. Multiscale spectroscopy using a monolithic liquid core waveguide with laterally attached fiber ports.

    PubMed

    Kröckel, Lars; Frosch, Torsten; Schmidt, Markus A

    2015-05-22

    In conventional absorption spectrometers, the range of accessible concentrations of analytes in aqueous solution is significantly limited by the dynamic range of the measurement system. Here we introduce the concept of multiscale spectroscopy allowing extending that range by orders of magnitude within one single device. The concept relies on using multiple light-sample interaction lengths, boosting the accessible concentration range by a particular extension factor. We experimentally implement our concept by a liquid core waveguide having multiple fiber ports side-wise attached to the waveguide, thus probing the light propagating inside the core at predefined distances from the input. This configuration provides three orders of magnitude of interaction length in one device. To verify the concept we exemplarily determine the concentrations of nitrate and of Rhodamine 6G in water, showing one hundred times improved measurement capabilities. The multiscale spectrometer uses the entire sample volume and allows the simultaneous measurement of fluorescence and attenuance. Due to its integrated design and the extended measurements capabilities, we anticipate application of our device in many application-relevant areas such as water quality analysis or environmental science. Copyright © 2015 Elsevier B.V. All rights reserved.

  5. Stochastic simulation of multiscale complex systems with PISKaS: A rule-based approach.

    PubMed

    Perez-Acle, Tomas; Fuenzalida, Ignacio; Martin, Alberto J M; Santibañez, Rodrigo; Avaria, Rodrigo; Bernardin, Alejandro; Bustos, Alvaro M; Garrido, Daniel; Dushoff, Jonathan; Liu, James H

    2018-03-29

    Computational simulation is a widely employed methodology to study the dynamic behavior of complex systems. Although common approaches are based either on ordinary differential equations or stochastic differential equations, these techniques make several assumptions which, when it comes to biological processes, could often lead to unrealistic models. Among others, model approaches based on differential equations entangle kinetics and causality, failing when complexity increases, separating knowledge from models, and assuming that the average behavior of the population encompasses any individual deviation. To overcome these limitations, simulations based on the Stochastic Simulation Algorithm (SSA) appear as a suitable approach to model complex biological systems. In this work, we review three different models executed in PISKaS: a rule-based framework to produce multiscale stochastic simulations of complex systems. These models span multiple time and spatial scales ranging from gene regulation up to Game Theory. In the first example, we describe a model of the core regulatory network of gene expression in Escherichia coli highlighting the continuous model improvement capacities of PISKaS. The second example describes a hypothetical outbreak of the Ebola virus occurring in a compartmentalized environment resembling cities and highways. Finally, in the last example, we illustrate a stochastic model for the prisoner's dilemma; a common approach from social sciences describing complex interactions involving trust within human populations. As whole, these models demonstrate the capabilities of PISKaS providing fertile scenarios where to explore the dynamics of complex systems. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  6. Acoustic solitons in waveguides with Helmholtz resonators: transmission line approach.

    PubMed

    Achilleos, V; Richoux, O; Theocharis, G; Frantzeskakis, D J

    2015-02-01

    We report experimental results and study theoretically soliton formation and propagation in an air-filled acoustic waveguide side loaded with Helmholtz resonators. We propose a theoretical modeling of the system, which relies on a transmission-line approach, leading to a nonlinear dynamical lattice model. The latter allows for an analytical description of the various soliton solutions for the pressure, which are found by means of dynamical systems and multiscale expansion techniques. These solutions include Boussinesq-like and Korteweg-de Vries pulse-shaped solitons that are observed in the experiment, as well as nonlinear Schrödinger envelope solitons, that are predicted theoretically. The analytical predictions are in excellent agreement with direct numerical simulations and in qualitative agreement with the experimental observations.

  7. Multiscale molecular dynamics simulations of rotary motor proteins.

    PubMed

    Ekimoto, Toru; Ikeguchi, Mitsunori

    2018-04-01

    Protein functions require specific structures frequently coupled with conformational changes. The scale of the structural dynamics of proteins spans from the atomic to the molecular level. Theoretically, all-atom molecular dynamics (MD) simulation is a powerful tool to investigate protein dynamics because the MD simulation is capable of capturing conformational changes obeying the intrinsically structural features. However, to study long-timescale dynamics, efficient sampling techniques and coarse-grained (CG) approaches coupled with all-atom MD simulations, termed multiscale MD simulations, are required to overcome the timescale limitation in all-atom MD simulations. Here, we review two examples of rotary motor proteins examined using free energy landscape (FEL) analysis and CG-MD simulations. In the FEL analysis, FEL is calculated as a function of reaction coordinates, and the long-timescale dynamics corresponding to conformational changes is described as transitions on the FEL surface. Another approach is the utilization of the CG model, in which the CG parameters are tuned using the fluctuation matching methodology with all-atom MD simulations. The long-timespan dynamics is then elucidated straightforwardly by using CG-MD simulations.

  8. Scalable High-order Methods for Multi-Scale Problems: Analysis, Algorithms and Application

    DTIC Science & Technology

    2016-02-26

    Karniadakis, “Resilient algorithms for reconstructing and simulating gappy flow fields in CFD ”, Fluid Dynamic Research, vol. 47, 051402, 2015. 2. Y. Yu, H...simulation, domain decomposition, CFD , gappy data, estimation theory, and gap-tooth algorithm. 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...objective of this project was to develop a general CFD framework for multifidelity simula- tions to target multiscale problems but also resilience in

  9. Chest CT window settings with multiscale adaptive histogram equalization: pilot study.

    PubMed

    Fayad, Laura M; Jin, Yinpeng; Laine, Andrew F; Berkmen, Yahya M; Pearson, Gregory D; Freedman, Benjamin; Van Heertum, Ronald

    2002-06-01

    Multiscale adaptive histogram equalization (MAHE), a wavelet-based algorithm, was investigated as a method of automatic simultaneous display of the full dynamic contrast range of a computed tomographic image. Interpretation times were significantly lower for MAHE-enhanced images compared with those for conventionally displayed images. Diagnostic accuracy, however, was insufficient in this pilot study to allow recommendation of MAHE as a replacement for conventional window display.

  10. Opendf - An Implementation of the Dual Fermion Method for Strongly Correlated Systems

    NASA Astrophysics Data System (ADS)

    Antipov, Andrey E.; LeBlanc, James P. F.; Gull, Emanuel

    The dual fermion method is a multiscale approach for solving lattice problems of interacting strongly correlated systems. In this paper, we present the opendfcode, an open-source implementation of the dual fermion method applicable to fermionic single- orbital lattice models in dimensions D = 1, 2, 3 and 4. The method is built on a dynamical mean field starting point, which neglects all local correlations, and perturbatively adds spatial correlations. Our code is distributed as an open-source package under the GNU public license version 2.

  11. Enabling Microscopic Simulators to Perform System Level Tasks: A System-Identification Based, Closure-on-Demand Toolkit for Multiscale Simulation Stability/Bifurcation Analysis, Optimization and Control

    DTIC Science & Technology

    2006-10-01

    The objective was to construct a bridge between existing and future microscopic simulation codes ( kMC , MD, MC, BD, LB etc.) and traditional, continuum...kinetic Monte Carlo, kMC , equilibrium MC, Lattice-Boltzmann, LB, Brownian Dynamics, BD, or general agent-based, AB) simulators. It also, fortuitously...cond-mat/0310460 at arXiv.org. 27. Coarse Projective kMC Integration: Forward/Reverse Initial and Boundary Value Problems", R. Rico-Martinez, C. W

  12. Dynamical Approach Study of Spurious Numerics in Nonlinear Computations

    NASA Technical Reports Server (NTRS)

    Yee, H. C.; Mansour, Nagi (Technical Monitor)

    2002-01-01

    The last two decades have been an era when computation is ahead of analysis and when very large scale practical computations are increasingly used in poorly understood multiscale complex nonlinear physical problems and non-traditional fields. Ensuring a higher level of confidence in the predictability and reliability (PAR) of these numerical simulations could play a major role in furthering the design, understanding, affordability and safety of our next generation air and space transportation systems, and systems for planetary and atmospheric sciences, and in understanding the evolution and origin of life. The need to guarantee PAR becomes acute when computations offer the ONLY way of solving these types of data limited problems. Employing theory from nonlinear dynamical systems, some building blocks to ensure a higher level of confidence in PAR of numerical simulations have been revealed by the author and world expert collaborators in relevant fields. Five building blocks with supporting numerical examples were discussed. The next step is to utilize knowledge gained by including nonlinear dynamics, bifurcation and chaos theories as an integral part of the numerical process. The third step is to design integrated criteria for reliable and accurate algorithms that cater to the different multiscale nonlinear physics. This includes but is not limited to the construction of appropriate adaptive spatial and temporal discretizations that are suitable for the underlying governing equations. In addition, a multiresolution wavelets approach for adaptive numerical dissipation/filter controls for high speed turbulence, acoustics and combustion simulations will be sought. These steps are corner stones for guarding against spurious numerical solutions that are solutions of the discretized counterparts but are not solutions of the underlying governing equations.

  13. Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction

    NASA Technical Reports Server (NTRS)

    Li, Zhijin; Chao, Yi; Li, P. Peggy

    2012-01-01

    A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.

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

    Rong, Libin; Guedj, Jeremie; Dahari, Harel

    The current paradigm for studying hepatitis C virus (HCV) dynamics in patients utilizes a standard viral dynamic model that keeps track of uninfected (target) cells, infected cells, and virus. The model does not account for the dynamics of intracellular viral replication, which is the major target of direct-acting antiviral agents (DAAs). In this paper, we describe and study a recently developed multiscale age-structured model that explicitly considers the potential effects of DAAs on intracellular viral RNA production, degradation, and secretion as virus into the circulation. We show that when therapy significantly blocks both intracellular viral RNA production and virus secretion,more » the serum viral load decline has three phases, with slopes reflecting the rate of serum viral clearance, the rate of loss of intracellular viral RNA, and the rate of loss of intracellular replication templates and infected cells, respectively. We also derive analytical approximations of the multiscale model and use one of them to analyze data from patients treated for 14 days with the HCV protease inhibitor danoprevir. Analysis suggests that danoprevir significantly blocks intracellular viral production (with mean effectiveness 99.2%), enhances intracellular viral RNA degradation about 5-fold, and moderately inhibits viral secretion (with mean effectiveness 56%). Finally, the multiscale model can be used to study viral dynamics in patients treated with other DAAs and explore their mechanisms of action in treatment of hepatitis C.« less

  15. Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

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

    Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt

    Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach and paper, the theoretical modeling and scalingmore » laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. Finally, these two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.« less

  16. Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

    DOE PAGES

    Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt; ...

    2017-11-27

    Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach and paper, the theoretical modeling and scalingmore » laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. Finally, these two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.« less

  17. Multiscale modeling of the dynamics of multicellular systems

    NASA Astrophysics Data System (ADS)

    Kosztin, Ioan

    2011-03-01

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

  18. Intermediate scale plasma density irregularities in the polar ionosphere inferred from radio occultation

    NASA Astrophysics Data System (ADS)

    Shume, E. B.; Komjathy, A.; Langley, R. B.; Verkhoglyadova, O. P.; Butala, M.; Mannucci, A. J.

    2014-12-01

    In this research, we report intermediate scale plasma density irregularities in the high-latitude ionosphere inferred from high-resolution radio occultation (RO) measurements in the CASSIOPE (CAScade Smallsat and IOnospheric Polar Explorer) - GPS (Global Positioning System) satellites radio link. The high inclination of the CASSIOPE satellite and high rate of signal receptionby the occultation antenna of the GPS Attitude, Positioning and Profiling (GAP) instrument on the Enhanced Polar Outflow Probe platform on CASSIOPE enable a high temporal and spatial resolution investigation of the dynamics of the polar ionosphere, magnetosphere-ionospherecoupling, solar wind effects, etc. with unprecedented details compared to that possible in the past. We have carried out high spatial resolution analysis in altitude and geomagnetic latitude of scintillation-producing plasma density irregularities in the polar ionosphere. Intermediate scale, scintillation-producing plasma density irregularities, which corresponds to 2 to 40 km spatial scales were inferred by applying multi-scale spectral analysis on the RO phase delay measurements. Using our multi-scale spectral analysis approach and Polar Operational Environmental Satellites (POES) and Defense Meteorological Satellite Program (DMSP) observations, we infer that the irregularity scales and phase scintillations have distinct features in the auroral oval and polar cap regions. In specific terms, we found that large length scales and and more intense phase scintillations are prevalent in the auroral oval compared to the polar cap region. Hence, the irregularity scales and phase scintillation characteristics are a function of the solar wind and the magnetospheric forcing. Multi-scale analysis may become a powerful diagnostic tool for characterizing how the ionosphere is dynamically driven by these factors.

  19. Multiscale molecular dynamics simulations of membrane remodeling by Bin/Amphiphysin/Rvs family proteins

    NASA Astrophysics Data System (ADS)

    Chun, Chan; Haohua, Wen; Lanyuan, Lu; Jun, Fan

    2016-01-01

    Membrane curvature is no longer thought of as a passive property of the membrane; rather, it is considered as an active, regulated state that serves various purposes in the cell such as between cells and organelle definition. While transport is usually mediated by tiny membrane bubbles known as vesicles or membrane tubules, such communication requires complex interplay between the lipid bilayers and cytosolic proteins such as members of the Bin/Amphiphysin/Rvs (BAR) superfamily of proteins. With rapid developments in novel experimental techniques, membrane remodeling has become a rapidly emerging new field in recent years. Molecular dynamics (MD) simulations are important tools for obtaining atomistic information regarding the structural and dynamic aspects of biological systems and for understanding the physics-related aspects. The availability of more sophisticated experimental data poses challenges to the theoretical community for developing novel theoretical and computational techniques that can be used to better interpret the experimental results to obtain further functional insights. In this review, we summarize the general mechanisms underlying membrane remodeling controlled or mediated by proteins. While studies combining experiments and molecular dynamics simulations recall existing mechanistic models, concurrently, they extend the role of different BAR domain proteins during membrane remodeling processes. We review these recent findings, focusing on how multiscale molecular dynamics simulations aid in understanding the physical basis of BAR domain proteins, as a representative of membrane-remodeling proteins. Project supported by the National Natural Science Foundation of China (Grant No. 21403182) and the Research Grants Council of Hong Kong, China (Grant No. CityU 21300014).

  20. Adaptive two-regime method: Application to front propagation

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

    Robinson, Martin, E-mail: martin.robinson@maths.ox.ac.uk; Erban, Radek, E-mail: erban@maths.ox.ac.uk; Flegg, Mark, E-mail: mark.flegg@monash.edu

    2014-03-28

    The Adaptive Two-Regime Method (ATRM) is developed for hybrid (multiscale) stochastic simulation of reaction-diffusion problems. It efficiently couples detailed Brownian dynamics simulations with coarser lattice-based models. The ATRM is a generalization of the previously developed Two-Regime Method [Flegg et al., J. R. Soc., Interface 9, 859 (2012)] to multiscale problems which require a dynamic selection of regions where detailed Brownian dynamics simulation is used. Typical applications include a front propagation or spatio-temporal oscillations. In this paper, the ATRM is used for an in-depth study of front propagation in a stochastic reaction-diffusion system which has its mean-field model given in termsmore » of the Fisher equation [R. Fisher, Ann. Eugen. 7, 355 (1937)]. It exhibits a travelling reaction front which is sensitive to stochastic fluctuations at the leading edge of the wavefront. Previous studies into stochastic effects on the Fisher wave propagation speed have focused on lattice-based models, but there has been limited progress using off-lattice (Brownian dynamics) models, which suffer due to their high computational cost, particularly at the high molecular numbers that are necessary to approach the Fisher mean-field model. By modelling only the wavefront itself with the off-lattice model, it is shown that the ATRM leads to the same Fisher wave results as purely off-lattice models, but at a fraction of the computational cost. The error analysis of the ATRM is also presented for a morphogen gradient model.« less

  1. Structural dynamics of the lac repressor-DNA complex revealed by a multiscale simulation.

    PubMed

    Villa, Elizabeth; Balaeff, Alexander; Schulten, Klaus

    2005-05-10

    A multiscale simulation of a complex between the lac repressor protein (LacI) and a 107-bp-long DNA segment is reported. The complex between the repressor and two operator DNA segments is described by all-atom molecular dynamics; the size of the simulated system comprises either 226,000 or 314,000 atoms. The DNA loop connecting the operators is modeled as a continuous elastic ribbon, described mathematically by the nonlinear Kirchhoff differential equations with boundary conditions obtained from the coordinates of the terminal base pairs of each operator. The forces stemming from the looped DNA are included in the molecular dynamics simulations; the loop structure and the forces are continuously recomputed because the protein motions during the simulations shift the operators and the presumed termini of the loop. The simulations reveal the structural dynamics of the LacI-DNA complex in unprecedented detail. The multiple domains of LacI exhibit remarkable structural stability during the simulation, moving much like rigid bodies. LacI is shown to absorb the strain from the looped DNA mainly through its mobile DNA-binding head groups. Even with large fluctuating forces applied, the head groups tilt strongly and keep their grip on the operator DNA, while the remainder of the protein retains its V-shaped structure. A simulated opening of the cleft of LacI by 500-pN forces revealed the interactions responsible for locking LacI in the V-conformation.

  2. Modeling Materials: Design for Planetary Entry, Electric Aircraft, and Beyond

    NASA Technical Reports Server (NTRS)

    Thompson, Alexander; Lawson, John W.

    2014-01-01

    NASA missions push the limits of what is possible. The development of high-performance materials must keep pace with the agency's demanding, cutting-edge applications. Researchers at NASA's Ames Research Center are performing multiscale computational modeling to accelerate development times and further the design of next-generation aerospace materials. Multiscale modeling combines several computationally intensive techniques ranging from the atomic level to the macroscale, passing output from one level as input to the next level. These methods are applicable to a wide variety of materials systems. For example: (a) Ultra-high-temperature ceramics for hypersonic aircraft-we utilized the full range of multiscale modeling to characterize thermal protection materials for faster, safer air- and spacecraft, (b) Planetary entry heat shields for space vehicles-we computed thermal and mechanical properties of ablative composites by combining several methods, from atomistic simulations to macroscale computations, (c) Advanced batteries for electric aircraft-we performed large-scale molecular dynamics simulations of advanced electrolytes for ultra-high-energy capacity batteries to enable long-distance electric aircraft service; and (d) Shape-memory alloys for high-efficiency aircraft-we used high-fidelity electronic structure calculations to determine phase diagrams in shape-memory transformations. Advances in high-performance computing have been critical to the development of multiscale materials modeling. We used nearly one million processor hours on NASA's Pleiades supercomputer to characterize electrolytes with a fidelity that would be otherwise impossible. For this and other projects, Pleiades enables us to push the physics and accuracy of our calculations to new levels.

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

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

    Zabaras, Nicolas J.

    2016-11-08

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

  4. Parallel Multiscale Algorithms for Astrophysical Fluid Dynamics Simulations

    NASA Technical Reports Server (NTRS)

    Norman, Michael L.

    1997-01-01

    Our goal is to develop software libraries and applications for astrophysical fluid dynamics simulations in multidimensions that will enable us to resolve the large spatial and temporal variations that inevitably arise due to gravity, fronts and microphysical phenomena. The software must run efficiently on parallel computers and be general enough to allow the incorporation of a wide variety of physics. Cosmological structure formation with realistic gas physics is the primary application driver in this work. Accurate simulations of e.g. galaxy formation require a spatial dynamic range (i.e., ratio of system scale to smallest resolved feature) of 104 or more in three dimensions in arbitrary topologies. We take this as our technical requirement. We have achieved, and in fact, surpassed these goals.

  5. At the Nexus of History, Ecology, and Hydrobiogeochemistry: Improved Predictions across Scales through Integration

    DOE PAGES

    Stegen, James C.

    2018-04-10

    To improve predictions of ecosystem function in future environments, we need to integrate the ecological and environmental histories experienced by microbial communities with hydrobiogeochemistry across scales. A key issue is whether we can derive generalizable scaling relationships that describe this multiscale integration. There is a strong foundation for addressing these challenges. We have the ability to infer ecological history with null models and reveal impacts of environmental history through laboratory and field experimentation. Recent developments also provide opportunities to inform ecosystem models with targeted omics data. A major next step is coupling knowledge derived from such studies with multiscale modelingmore » frameworks that are predictive under non-steady-state conditions. This is particularly true for systems spanning dynamic interfaces, which are often hot spots of hydrobiogeochemical function. Here, we can advance predictive capabilities through a holistic perspective focused on the nexus of history, ecology, and hydrobiogeochemistry.« less

  6. Equation-free multiscale computation: algorithms and applications.

    PubMed

    Kevrekidis, Ioannis G; Samaey, Giovanni

    2009-01-01

    In traditional physicochemical modeling, one derives evolution equations at the (macroscopic, coarse) scale of interest; these are used to perform a variety of tasks (simulation, bifurcation analysis, optimization) using an arsenal of analytical and numerical techniques. For many complex systems, however, although one observes evolution at a macroscopic scale of interest, accurate models are only given at a more detailed (fine-scale, microscopic) level of description (e.g., lattice Boltzmann, kinetic Monte Carlo, molecular dynamics). Here, we review a framework for computer-aided multiscale analysis, which enables macroscopic computational tasks (over extended spatiotemporal scales) using only appropriately initialized microscopic simulation on short time and length scales. The methodology bypasses the derivation of macroscopic evolution equations when these equations conceptually exist but are not available in closed form-hence the term equation-free. We selectively discuss basic algorithms and underlying principles and illustrate the approach through representative applications. We also discuss potential difficulties and outline areas for future research.

  7. At the Nexus of History, Ecology, and Hydrobiogeochemistry: Improved Predictions across Scales through Integration

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

    Stegen, James C.

    To improve predictions of ecosystem function in future environments, we need to integrate the ecological and environmental histories experienced by microbial communities with hydrobiogeochemistry across scales. A key issue is whether we can derive generalizable scaling relationships that describe this multiscale integration. There is a strong foundation for addressing these challenges. We have the ability to infer ecological history with null models and reveal impacts of environmental history through laboratory and field experimentation. Recent developments also provide opportunities to inform ecosystem models with targeted omics data. A major next step is coupling knowledge derived from such studies with multiscale modelingmore » frameworks that are predictive under non-steady-state conditions. This is particularly true for systems spanning dynamic interfaces, which are often hot spots of hydrobiogeochemical function. Here, we can advance predictive capabilities through a holistic perspective focused on the nexus of history, ecology, and hydrobiogeochemistry.« less

  8. The Magnetospheric Multiscale Constellation

    NASA Technical Reports Server (NTRS)

    Tooley, C. R.; Black, R. K.; Robertson, B. P.; Stone, J. M.; Pope, S. E.; Davis, G. T.

    2015-01-01

    The Magnetospheric Multiscale (MMS) mission is the fourth mission of the Solar Terrestrial Probe (STP) program of the National Aeronautics and Space Administration (NASA). The MMS mission was launched on March 12, 2015. The MMS mission consists of four identically instrumented spin-stabilized observatories which are flown in formation to perform the first definitive study of magnetic reconnection in space. The MMS mission was presented with numerous technical challenges, including the simultaneous construction and launch of four identical large spacecraft with 100 instruments total, stringent electromagnetic cleanliness requirements, closed-loop precision maneuvering and pointing of spinning flexible spacecraft, on-board GPS based orbit determination far above the GPS constellation, and a flight dynamics design that enables formation flying with separation distances as small as 10 km. This paper describes the overall mission design and presents an overview of the design, testing, and early on-orbit operation of the spacecraft systems and instrument suite.

  9. Simulation Studies of Mechanical Properties of Novel Silica Nano-structures

    NASA Astrophysics Data System (ADS)

    Muralidharan, Krishna; Torras Costa, Joan; Trickey, Samuel B.

    2006-03-01

    Advances in nanotechnology and the importance of silica as a technological material continue to stimulate computational study of the properties of possible novel silica nanostructures. Thus we have done classical molecular dynamics (MD) and multi-scale quantum mechanical (QM/MD) simulation studies of the mechanical properties of single-wall and multi-wall silica nano-rods of varying dimensions. Such nano-rods have been predicted by Mallik et al. to be unusually strong in tensile failure. Here we compare failure mechanisms of such nano-rods under tension, compression, and bending. The concurrent multi-scale QM/MD studies use the general PUPIL system (Torras et al.). In this case, PUPIL provides automated interoperation of the MNDO Transfer Hamiltonian QM code (Taylor et al.) and a locally written MD code. Embedding of the QM-forces domain is via the scheme of Mallik et al. Work supported by NSF ITR award DMR-0325553.

  10. At the Nexus of History, Ecology, and Hydrobiogeochemistry: Improved Predictions across Scales through Integration.

    PubMed

    Stegen, James C

    2018-01-01

    To improve predictions of ecosystem function in future environments, we need to integrate the ecological and environmental histories experienced by microbial communities with hydrobiogeochemistry across scales. A key issue is whether we can derive generalizable scaling relationships that describe this multiscale integration. There is a strong foundation for addressing these challenges. We have the ability to infer ecological history with null models and reveal impacts of environmental history through laboratory and field experimentation. Recent developments also provide opportunities to inform ecosystem models with targeted omics data. A major next step is coupling knowledge derived from such studies with multiscale modeling frameworks that are predictive under non-steady-state conditions. This is particularly true for systems spanning dynamic interfaces, which are often hot spots of hydrobiogeochemical function. We can advance predictive capabilities through a holistic perspective focused on the nexus of history, ecology, and hydrobiogeochemistry.

  11. Modeling Complex Biological Flows in Multi-Scale Systems using the APDEC Framework

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

    Trebotich, D

    We have developed advanced numerical algorithms to model biological fluids in multiscale flow environments using the software framework developed under the SciDAC APDEC ISIC. The foundation of our computational effort is an approach for modeling DNA-laden fluids as ''bead-rod'' polymers whose dynamics are fully coupled to an incompressible viscous solvent. The method is capable of modeling short range forces and interactions between particles using soft potentials and rigid constraints. Our methods are based on higher-order finite difference methods in complex geometry with adaptivity, leveraging algorithms and solvers in the APDEC Framework. Our Cartesian grid embedded boundary approach to incompressible viscousmore » flow in irregular geometries has also been interfaced to a fast and accurate level-sets method within the APDEC Framework for extracting surfaces from volume renderings of medical image data and used to simulate cardio-vascular and pulmonary flows in critical anatomies.« less

  12. Modeling complex biological flows in multi-scale systems using the APDEC framework

    NASA Astrophysics Data System (ADS)

    Trebotich, David

    2006-09-01

    We have developed advanced numerical algorithms to model biological fluids in multiscale flow environments using the software framework developed under the SciDAC APDEC ISIC. The foundation of our computational effort is an approach for modeling DNA laden fluids as ''bead-rod'' polymers whose dynamics are fully coupled to an incompressible viscous solvent. The method is capable of modeling short range forces and interactions between particles using soft potentials and rigid constraints. Our methods are based on higher-order finite difference methods in complex geometry with adaptivity, leveraging algorithms and solvers in the APDEC Framework. Our Cartesian grid embedded boundary approach to incompressible viscous flow in irregular geometries has also been interfaced to a fast and accurate level-sets method within the APDEC Framework for extracting surfaces from volume renderings of medical image data and used to simulate cardio-vascular and pulmonary flows in critical anatomies.

  13. Enhancement of low visibility aerial images using histogram truncation and an explicit Retinex representation for balancing contrast and color consistency

    NASA Astrophysics Data System (ADS)

    Liu, Changjiang; Cheng, Irene; Zhang, Yi; Basu, Anup

    2017-06-01

    This paper presents an improved multi-scale Retinex (MSR) based enhancement for ariel images under low visibility. For traditional multi-scale Retinex, three scales are commonly employed, which limits its application scenarios. We extend our research to a general purpose enhanced method, and design an MSR with more than three scales. Based on the mathematical analysis and deductions, an explicit multi-scale representation is proposed that balances image contrast and color consistency. In addition, a histogram truncation technique is introduced as a post-processing strategy to remap the multi-scale Retinex output to the dynamic range of the display. Analysis of experimental results and comparisons with existing algorithms demonstrate the effectiveness and generality of the proposed method. Results on image quality assessment proves the accuracy of the proposed method with respect to both objective and subjective criteria.

  14. Multiscale Universal Interface: A concurrent framework for coupling heterogeneous solvers

    NASA Astrophysics Data System (ADS)

    Tang, Yu-Hang; Kudo, Shuhei; Bian, Xin; Li, Zhen; Karniadakis, George Em

    2015-09-01

    Concurrently coupled numerical simulations using heterogeneous solvers are powerful tools for modeling multiscale phenomena. However, major modifications to existing codes are often required to enable such simulations, posing significant difficulties in practice. In this paper we present a C++ library, i.e. the Multiscale Universal Interface (MUI), which is capable of facilitating the coupling effort for a wide range of multiscale simulations. The library adopts a header-only form with minimal external dependency and hence can be easily dropped into existing codes. A data sampler concept is introduced, combined with a hybrid dynamic/static typing mechanism, to create an easily customizable framework for solver-independent data interpretation. The library integrates MPI MPMD support and an asynchronous communication protocol to handle inter-solver information exchange irrespective of the solvers' own MPI awareness. Template metaprogramming is heavily employed to simultaneously improve runtime performance and code flexibility. We validated the library by solving three different multiscale problems, which also serve to demonstrate the flexibility of the framework in handling heterogeneous models and solvers. In the first example, a Couette flow was simulated using two concurrently coupled Smoothed Particle Hydrodynamics (SPH) simulations of different spatial resolutions. In the second example, we coupled the deterministic SPH method with the stochastic Dissipative Particle Dynamics (DPD) method to study the effect of surface grafting on the hydrodynamics properties on the surface. In the third example, we consider conjugate heat transfer between a solid domain and a fluid domain by coupling the particle-based energy-conserving DPD (eDPD) method with the Finite Element Method (FEM).

  15. Multiscale Universal Interface: A concurrent framework for coupling heterogeneous solvers

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

    Tang, Yu-Hang, E-mail: yuhang_tang@brown.edu; Kudo, Shuhei, E-mail: shuhei-kudo@outlook.jp; Bian, Xin, E-mail: xin_bian@brown.edu

    2015-09-15

    Graphical abstract: - Abstract: Concurrently coupled numerical simulations using heterogeneous solvers are powerful tools for modeling multiscale phenomena. However, major modifications to existing codes are often required to enable such simulations, posing significant difficulties in practice. In this paper we present a C++ library, i.e. the Multiscale Universal Interface (MUI), which is capable of facilitating the coupling effort for a wide range of multiscale simulations. The library adopts a header-only form with minimal external dependency and hence can be easily dropped into existing codes. A data sampler concept is introduced, combined with a hybrid dynamic/static typing mechanism, to create anmore » easily customizable framework for solver-independent data interpretation. The library integrates MPI MPMD support and an asynchronous communication protocol to handle inter-solver information exchange irrespective of the solvers' own MPI awareness. Template metaprogramming is heavily employed to simultaneously improve runtime performance and code flexibility. We validated the library by solving three different multiscale problems, which also serve to demonstrate the flexibility of the framework in handling heterogeneous models and solvers. In the first example, a Couette flow was simulated using two concurrently coupled Smoothed Particle Hydrodynamics (SPH) simulations of different spatial resolutions. In the second example, we coupled the deterministic SPH method with the stochastic Dissipative Particle Dynamics (DPD) method to study the effect of surface grafting on the hydrodynamics properties on the surface. In the third example, we consider conjugate heat transfer between a solid domain and a fluid domain by coupling the particle-based energy-conserving DPD (eDPD) method with the Finite Element Method (FEM)« less

  16. Refined multiscale fuzzy entropy based on standard deviation for biomedical signal analysis.

    PubMed

    Azami, Hamed; Fernández, Alberto; Escudero, Javier

    2017-11-01

    Multiscale entropy (MSE) has been a prevalent algorithm to quantify the complexity of biomedical time series. Recent developments in the field have tried to alleviate the problem of undefined MSE values for short signals. Moreover, there has been a recent interest in using other statistical moments than the mean, i.e., variance, in the coarse-graining step of the MSE. Building on these trends, here we introduce the so-called refined composite multiscale fuzzy entropy based on the standard deviation (RCMFE σ ) and mean (RCMFE μ ) to quantify the dynamical properties of spread and mean, respectively, over multiple time scales. We demonstrate the dependency of the RCMFE σ and RCMFE μ , in comparison with other multiscale approaches, on several straightforward signal processing concepts using a set of synthetic signals. The results evidenced that the RCMFE σ and RCMFE μ values are more stable and reliable than the classical multiscale entropy ones. We also inspect the ability of using the standard deviation as well as the mean in the coarse-graining process using magnetoencephalograms in Alzheimer's disease and publicly available electroencephalograms recorded from focal and non-focal areas in epilepsy. Our results indicated that when the RCMFE μ cannot distinguish different types of dynamics of a particular time series at some scale factors, the RCMFE σ may do so, and vice versa. The results showed that RCMFE σ -based features lead to higher classification accuracies in comparison with the RCMFE μ -based ones. We also made freely available all the Matlab codes used in this study at http://dx.doi.org/10.7488/ds/1477 .

  17. Heterogeneity and Self-Organization of Complex Systems Through an Application to Financial Market with Multiagent Systems

    NASA Astrophysics Data System (ADS)

    Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

    2017-12-01

    Multiagent systems (MAS) provide a useful tool for exploring the complex dynamics and behavior of financial markets and now MAS approach has been widely implemented and documented in the empirical literature. This paper introduces the implementation of an innovative multi-scale mathematical model for a computational agent-based financial market. The paper develops a method to quantify the degree of self-organization which emerges in the system and shows that the capacity of self-organization is maximized when the agent behaviors are heterogeneous. Numerical results are presented and analyzed, showing how the global market behavior emerges from specific individual behavior interactions.

  18. Tuning Glass Transition in Polymer Nanocomposites with Functionalized Cellulose Nanocrystals through Nanoconfinement.

    PubMed

    Qin, Xin; Xia, Wenjie; Sinko, Robert; Keten, Sinan

    2015-10-14

    Cellulose nanocrystals (CNCs) exhibit impressive interfacial and mechanical properties that make them promising candidates to be used as fillers within nanocomposites. While glass-transition temperature (Tg) is a common metric for describing thermomechanical properties, its prediction is extremely difficult as it depends on filler surface chemistry, volume fraction, and size. Here, taking CNC-reinforced poly(methyl-methacrylate) (PMMA) nanocomposites as a relevant model system, we present a multiscale analysis that combines atomistic molecular dynamics (MD) surface energy calculations with coarse-grained (CG) simulations of relaxation dynamics near filler-polymer interfaces to predict composite properties. We discover that increasing the volume fraction of CNCs results in nanoconfinement effects that lead to an appreciation of the composite Tg provided that strong interfacial interactions are achieved, as in the case of TEMPO-mediated surface modifications that promote hydrogen bonding. The upper and lower bounds of shifts in Tg are predicted by fully accounting for nanoconfinement and interfacial properties, providing new insight into tuning these aspects in nanocomposite design. Our multiscale, materials-by-design framework is validated by recent experiments and breaks new ground in predicting, without any empirical parameters, key structure-property relationships for nanocomposites.

  19. Understanding the influence of solvent field and fluctuations on the stability of photo-induced charge-separated state in molecular triad

    NASA Astrophysics Data System (ADS)

    Balamurugan, D.; Aquino, Adelia; Lischka, Hans; Dios, Francis; Flores, Lionel; Cheung, Margaret

    2013-03-01

    Molecular triad composed of fullerene, porphyrin, and carotene is an artificial analogue of natural photosynthetic system and is considered for applications in solar energy conversion because of its ability to produce long-lived photo-induced charge separated state. The goal of the present multiscale simulation is to understand how the stability of photo-induced charge-separated state in molecular triad is influenced by a polar organic solvent, namely tetrahydrofuran (THF). The multiscale approach is based on combined quantum, classical molecular dynamics, and statistical physics calculations. The quantum chemical calculations were performed on the triad using the second order algebraic diagrammatic perturbation and time-dependent density functional theory. Molecular dynamics simulations were performed on triad in a box of THF solvent with the replica exchange method. The two methods on different length and time scales are bridged through an important sampling technique. We have analyzed the free energy landscape, structural fluctuations, and the long- range electrostatic interactions between triad and solvent molecules. The results suggest that the polarity and re-organization of the solvent is critical in stabilization of charge-separated state in triad. Supported by DOE (DE-FG02-10ER16175)

  20. Image-based multi-scale simulation and experimental validation of thermal conductivity of lanthanum zirconate

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

    Guo, Xingye; Hu, Bin; Wei, Changdong

    Lanthanum zirconate (La2Zr2O7) is a promising candidate material for thermal barrier coating (TBC) applications due to its low thermal conductivity and high-temperature phase stability. In this work, a novel image-based multi-scale simulation framework combining molecular dynamics (MD) and finite element (FE) calculations is proposed to study the thermal conductivity of La2Zr2O7 coatings. Since there is no experimental data of single crystal La2Zr2O7 thermal conductivity, a reverse non-equilibrium molecular dynamics (reverse NEMD) approach is first employed to compute the temperature-dependent thermal conductivity of single crystal La2Zr2O7. The single crystal data is then passed to a FE model which takes into accountmore » of realistic thermal barrier coating microstructures. The predicted thermal conductivities from the FE model are in good agreement with experimental validations using both flash laser technique and pulsed thermal imaging-multilayer analysis. The framework proposed in this work provides a powerful tool for future design of advanced coating systems. (C) 2016 Elsevier Ltd. All rights reserved.« less

  1. Pressure-induced metallization of condensed phase β-HMX under shock loadings via molecular dynamics simulations in conjunction with multi-scale shock technique.

    PubMed

    Ge, Ni-Na; Wei, Yong-Kai; Zhao, Feng; Chen, Xiang-Rong; Ji, Guang-Fu

    2014-07-01

    The electronic structure and initial decomposition in high explosive HMX under conditions of shock loading are examined. The simulation is performed using quantum molecular dynamics in conjunction with multi-scale shock technique (MSST). A self-consistent charge density-functional tight-binding (SCC-DFTB) method is adapted. The results show that the N-N-C angle has a drastic change under shock wave compression along lattice vector b at shock velocity 11 km/s, which is the main reason that leads to an insulator-to-metal transition for the HMX system. The metallization pressure (about 130 GPa) of condensed-phase HMX is predicted firstly. We also detect the formation of several key products of condensed-phase HMX decomposition, such as NO2, NO, N2, N2O, H2O, CO, and CO2, and all of them have been observed in previous experimental studies. Moreover, the initial decomposition products include H2 due to the C-H bond breaking as a primary reaction pathway at extreme condition, which presents a new insight into the initial decomposition mechanism of HMX under shock loading at the atomistic level.

  2. Scale-specific effects: A report on multiscale analysis of acupunctured EEG in entropy and power

    NASA Astrophysics Data System (ADS)

    Song, Zhenxi; Deng, Bin; Wei, Xile; Cai, Lihui; Yu, Haitao; Wang, Jiang; Wang, Ruofan; Chen, Yingyuan

    2018-02-01

    Investigating acupuncture effects contributes to improving clinical application and understanding neuronal dynamics under external stimulation. In this report, we recorded electroencephalography (EEG) signals evoked by acupuncture at ST36 acupoint with three stimulus frequencies of 50, 100 and 200 times per minutes, and selected non-acupuncture EEGs as the control group. Multiscale analyses were introduced to investigate the possible acupuncture effects on complexity and power in multiscale level. Using multiscale weighted-permutation entropy, we found the significant effects on increased complexity degree in EEG signals induced by acupuncture. The comparison of three stimulation manipulations showed that 100 times/min generated most obvious effects, and affected most cortical regions. By estimating average power spectral density, we found decreased power induced by acupuncture. The joint distribution of entropy and power indicated an inverse correlation, and this relationship was weakened by acupuncture effects, especially under the manipulation of 100 times/min frequency. Above findings are more evident and stable in large scales than small scales, which suggests that multiscale analysis allows evaluating significant effects in specific scale and enables to probe the inherent characteristics underlying physiological signals.

  3. Long-Distance Rescue and Slow Extinction Dynamics Govern Multiscale Metapopulations.

    PubMed

    Huth, Géraldine; Haegeman, Bart; Pitard, Estelle; Munoz, François

    2015-10-01

    Rare long-distance dispersal is known to be critical for species dynamics, but how the interplay between short- and long-distance colonization influences regional persistence in a fragmented habitat remains poorly understood. We propose a metapopulation model that combines local colonization within habitat islands and long-distance colonization between islands. We study how regional occupancy dynamics are affected by the multiscale colonization process. We find that the island size distribution (ISD) is a key driver of the long-term occupancy dynamics. When the ISD is heterogeneous-that is, when the size of islands is variable-we show that extinction dynamics become very slow. We demonstrate that this behavior is unrelated to the well-known extinction debt near the critical extinction threshold. Hence, this finding questions the equivalence between extinction debt and critical transitions in the context of metapopulation collapse. Furthermore, we show that long-distance colonization can rescue small islands from extinction and sustain a steady regional occupancy. These results provide novel theoretical and practical insights into extinction dynamics and persistence in fragmented habitats and are thus relevant for the design of conservation strategies.

  4. Simulation of spallation life of metals in relation to operating stresses in the nanosecond loading time range

    NASA Astrophysics Data System (ADS)

    Makarov, P. V.; Bakeev, R. A.

    2015-10-01

    Spall fracture of materials is still the only means for investigation of the material life and mechanisms of its fracture in the micro-, nano-, and picosecond time ranges of tensile loading. The phenomenological model based on the concepts of multiscale fracture of materials as nonlinear dynamic systems is shown to satisfactorily describe their life in the given range. The model is employed for the calculation of spallation life.

  5. Multiscale low-frequency circulation modes in the global atmosphere

    NASA Technical Reports Server (NTRS)

    Lau, K.-M.; Sheu, P.-J.; Kang, I.-S.

    1994-01-01

    In this paper, fundamental multiscale circulation modes in the global atmosphere are identified with the objective of providing better understanding of atmospheric low-frequency variabilities over a wide range of spatial and temporal scales. With the use of a combination of rotated principal component technique, singular spectrum analysis, and phase space portraits, three categories of basic multiscale modes in the atmosphere are found. The first is the interannual-mode (IAM), which is dominated by time scales longer than a year and can be attributed to heating and circulation anomalies associated with the coupled tropical ocean-atmosphere, in particular the El Nino-Southern Oscillation. The second is a set of tropical intraseasonal modes consisting of three separate multiscale patterns (ISO-1, -2, -3) related to tropical heating that can be identified with the different phases of the Madden-Julian Oscillation (MJO), including its teleconnection to the extratropics. The ISO spatial and temporal patterns suggest that the extratropical wave train in the North Pacific and North America is related to heating over the Maritime Continent and that the evolution of the MJO around the equator may require forcing from the extratropics spawning convection over the Indian Ocean. The third category represents extratropical intraseasonal oscillations arising from internal dynamics of the basic-state circulation. In the Northern Hemisphere, there are two distinct circulation modes with multiple frequencies in this category: the Pacific/North America (PNA) and the North Atlantic/Eurasia (NAE). In the Southern Hemisphere, two phase-locked modes (PSA-1 and PSA-2) are found depicting an eastward propagating wave train from eastern Australia, via the Pacific South America to the South Atlantic. The extratropical modes exhibit temporal characteristics such as phase locking and harmonic oscillations possibly associated with quadratically nonlinear dynamical systems. Additionally, the observed monthly and seasonal anomalies arise from a complex interplay of the various multiscale low-frequency modes. The relative dominance of the different modes varies widely from month to month and from year to year. On the monthly time scale, while one or two mechanisms may dominate in one year, no single mechanism seems to dominate for all years. There are indications that when the IAM, that is, ENSO heating patterns are strong, the extratropical modes may be suppressed and vice versa. For the seasonal mean, the interannual mode tends to dominate and the contribution from the PNA remains quite significant.

  6. An approach to multiscale modelling with graph grammars.

    PubMed

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

    2014-09-01

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

  7. 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

  8. Multi-Scale Models for the Scale Interaction of Organized Tropical Convection

    NASA Astrophysics Data System (ADS)

    Yang, Qiu

    Assessing the upscale impact of organized tropical convection from small spatial and temporal scales is a research imperative, not only for having a better understanding of the multi-scale structures of dynamical and convective fields in the tropics, but also for eventually helping in the design of new parameterization strategies to improve the next-generation global climate models. Here self-consistent multi-scale models are derived systematically by following the multi-scale asymptotic methods and used to describe the hierarchical structures of tropical atmospheric flows. The advantages of using these multi-scale models lie in isolating the essential components of multi-scale interaction and providing assessment of the upscale impact of the small-scale fluctuations onto the large-scale mean flow through eddy flux divergences of momentum and temperature in a transparent fashion. Specifically, this thesis includes three research projects about multi-scale interaction of organized tropical convection, involving tropical flows at different scaling regimes and utilizing different multi-scale models correspondingly. Inspired by the observed variability of tropical convection on multiple temporal scales, including daily and intraseasonal time scales, the goal of the first project is to assess the intraseasonal impact of the diurnal cycle on the planetary-scale circulation such as the Hadley cell. As an extension of the first project, the goal of the second project is to assess the intraseasonal impact of the diurnal cycle over the Maritime Continent on the Madden-Julian Oscillation. In the third project, the goals are to simulate the baroclinic aspects of the ITCZ breakdown and assess its upscale impact on the planetary-scale circulation over the eastern Pacific. These simple multi-scale models should be useful to understand the scale interaction of organized tropical convection and help improve the parameterization of unresolved processes in global climate models.

  9. Investigation on thermo-acoustic instability dynamic characteristics of hydrocarbon fuel flowing in scramjet cooling channel based on wavelet entropy method

    NASA Astrophysics Data System (ADS)

    Zan, Hao; Li, Haowei; Jiang, Yuguang; Wu, Meng; Zhou, Weixing; Bao, Wen

    2018-06-01

    As part of our efforts to find ways and means to further improve the regenerative cooling technology in scramjet, the experiments of thermo-acoustic instability dynamic characteristics of hydrocarbon fuel flowing have been conducted in horizontal circular tubes at different conditions. The experimental results indicate that there is a developing process from thermo-acoustic stability to instability. In order to have a deep understanding on the developing process of thermo-acoustic instability, the method of Multi-scale Shannon Wavelet Entropy (MSWE) based on Wavelet Transform Correlation Filter (WTCF) and Multi-Scale Shannon Entropy (MSE) is adopted in this paper. The results demonstrate that the developing process of thermo-acoustic instability from noise and weak signals is well detected by MSWE method and the differences among the stability, the developing process and the instability can be identified. These properties render the method particularly powerful for warning thermo-acoustic instability of hydrocarbon fuel flowing in scramjet cooling channels. The mass flow rate and the inlet pressure will make an influence on the developing process of the thermo-acoustic instability. The investigation on thermo-acoustic instability dynamic characteristics at supercritical pressure based on wavelet entropy method offers guidance on the control of scramjet fuel supply, which can secure stable fuel flowing in regenerative cooling system.

  10. A multiscale model on hospital infections coupling macro and micro dynamics

    NASA Astrophysics Data System (ADS)

    Wang, Xia; Tang, Sanyi

    2017-09-01

    A multiscale model of hospital infections coupling the micro model of the growth of bacteria and the macro model describing the transmission of the bacteria among patients and health care workers (HCWs) was established to investigate the effects of antibiotic treatment on the transmission of the bacteria among patients and HCWs. The model was formulated by viewing the transmission rate from infected patients to HCWs and the shedding rate of bacteria from infected patients to the environment as saturated functions of the within-host bacterial load. The equilibria and the basic reproduction number of the coupled system were studied, and the global dynamics of the disease free equilibrium and the endemic equilibrium were analyzed in detail by constructing two Lyapunov functions. Furthermore, effects of drug treatment in the within-host model on the basic reproduction number and the dynamics of the coupled model were studied by coupling a pharmacokinetics model with the within-host model. Sensitive analysis indicated that the growth rate of the bacteria, the maximum drug effect and the dosing interval are the three most sensitive parameters contributing to the basic reproduction number. Thus, adopting ;wonder; drugs to decrease the growth rate of the bacteria or to increase the drug's effect is the most effective measure but changing the dosage regime is also effective. A quantitative criterion of how to choose the best dosage regimen can also be obtained from numerical results.

  11. Extended Phase-Space Methods for Enhanced Sampling in Molecular Simulations: A Review.

    PubMed

    Fujisaki, Hiroshi; Moritsugu, Kei; Matsunaga, Yasuhiro; Morishita, Tetsuya; Maragliano, Luca

    2015-01-01

    Molecular Dynamics simulations are a powerful approach to study biomolecular conformational changes or protein-ligand, protein-protein, and protein-DNA/RNA interactions. Straightforward applications, however, are often hampered by incomplete sampling, since in a typical simulated trajectory the system will spend most of its time trapped by high energy barriers in restricted regions of the configuration space. Over the years, several techniques have been designed to overcome this problem and enhance space sampling. Here, we review a class of methods that rely on the idea of extending the set of dynamical variables of the system by adding extra ones associated to functions describing the process under study. In particular, we illustrate the Temperature Accelerated Molecular Dynamics (TAMD), Logarithmic Mean Force Dynamics (LogMFD), and Multiscale Enhanced Sampling (MSES) algorithms. We also discuss combinations with techniques for searching reaction paths. We show the advantages presented by this approach and how it allows to quickly sample important regions of the free-energy landscape via automatic exploration.

  12. Newton-Euler Dynamic Equations of Motion for a Multi-body Spacecraft

    NASA Technical Reports Server (NTRS)

    Stoneking, Eric

    2007-01-01

    The Magnetospheric MultiScale (MMS) mission employs a formation of spinning spacecraft with several flexible appendages and thruster-based control. To understand the complex dynamic interaction of thruster actuation, appendage motion, and spin dynamics, each spacecraft is modeled as a tree of rigid bodies connected by spherical or gimballed joints. The method presented facilitates assembling by inspection the exact, nonlinear dynamic equations of motion for a multibody spacecraft suitable for solution by numerical integration. The building block equations are derived by applying Newton's and Euler's equations of motion to an "element" consisting of two bodies and one joint (spherical and gimballed joints are considered separately). Patterns in the "mass" and L'force" matrices guide assembly by inspection of a general N-body tree-topology system. Straightforward linear algebra operations are employed to eliminate extraneous constraint equations, resulting in a minimum-dimension system of equations to solve. This method thus combines a straightforward, easily-extendable, easily-mechanized formulation with an efficient computer implementation.

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

    PubMed Central

    2013-01-01

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

  14. Final Report. Analysis and Reduction of Complex Networks Under Uncertainty

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

    Marzouk, Youssef M.; Coles, T.; Spantini, A.

    2013-09-30

    The project was a collaborative effort among MIT, Sandia National Laboratories (local PI Dr. Habib Najm), the University of Southern California (local PI Prof. Roger Ghanem), and The Johns Hopkins University (local PI Prof. Omar Knio, now at Duke University). Our focus was the analysis and reduction of large-scale dynamical systems emerging from networks of interacting components. Such networks underlie myriad natural and engineered systems. Examples important to DOE include chemical models of energy conversion processes, and elements of national infrastructure—e.g., electric power grids. Time scales in chemical systems span orders of magnitude, while infrastructure networks feature both local andmore » long-distance connectivity, with associated clusters of time scales. These systems also blend continuous and discrete behavior; examples include saturation phenomena in surface chemistry and catalysis, and switching in electrical networks. Reducing size and stiffness is essential to tractable and predictive simulation of these systems. Computational singular perturbation (CSP) has been effectively used to identify and decouple dynamics at disparate time scales in chemical systems, allowing reduction of model complexity and stiffness. In realistic settings, however, model reduction must contend with uncertainties, which are often greatest in large-scale systems most in need of reduction. Uncertainty is not limited to parameters; one must also address structural uncertainties—e.g., whether a link is present in a network—and the impact of random perturbations, e.g., fluctuating loads or sources. Research under this project developed new methods for the analysis and reduction of complex multiscale networks under uncertainty, by combining computational singular perturbation (CSP) with probabilistic uncertainty quantification. CSP yields asymptotic approximations of reduceddimensionality “slow manifolds” on which a multiscale dynamical system evolves. Introducing uncertainty in this context raised fundamentally new issues, e.g., how is the topology of slow manifolds transformed by parametric uncertainty? How to construct dynamical models on these uncertain manifolds? To address these questions, we used stochastic spectral polynomial chaos (PC) methods to reformulate uncertain network models and analyzed them using CSP in probabilistic terms. Finding uncertain manifolds involved the solution of stochastic eigenvalue problems, facilitated by projection onto PC bases. These problems motivated us to explore the spectral properties stochastic Galerkin systems. We also introduced novel methods for rank-reduction in stochastic eigensystems—transformations of a uncertain dynamical system that lead to lower storage and solution complexity. These technical accomplishments are detailed below. This report focuses on the MIT portion of the joint project.« less

  15. Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions

    DOE PAGES

    Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

    2017-06-06

    There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our systemmore » detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.« less

  16. Multiscale Modeling of Carbon Nanotube-Epoxy Nanocomposites

    NASA Astrophysics Data System (ADS)

    Fasanella, Nicholas A.

    Epoxy-composites are widely used in the aerospace industry. In order to improve upon stiffness and thermal conductivity; carbon nanotube additives to epoxies are being explored. This dissertation presents multiscale modeling techniques to study the engineering properties of single walled carbon nanotube (SWNT)-epoxy nanocomposites, consisting of pristine and covalently functionalized systems. Using Molecular Dynamics (MD), thermomechanical properties were calculated for a representative polymer unit cell. Finite Element (FE) and orientation distribution function (ODF) based methods were used in a multiscale framework to obtain macroscale properties. An epoxy network was built using the dendrimer growth approach. The epoxy model was verified by matching the experimental glass transition temperature, density, and dilatation. MD, via the constant valence force field (CVFF), was used to explore the mechanical and dilatometric effects of adding pristine and functionalized SWNTs to epoxy. Full stiffness matrices and linear coefficient of thermal expansion vectors were obtained. The Green-Kubo method was used to investigate the thermal conductivity as a function of temperature for the various nanocomposites. Inefficient phonon transport at the ends of nanotubes is an important factor in the thermal conductivity of the nanocomposites, and for this reason discontinuous nanotubes were modeled in addition to long nanotubes. To obtain continuum-scale elastic properties from the MD data, multiscale modeling was considered to give better control over the volume fraction of nanotubes, and investigate the effects of nanotube alignment. Two methods were considered; an FE based method, and an ODF based method. The FE method probabilistically assigned elastic properties of elements from the MD lattice results based on the desired volume fraction and alignment of the nanotubes. For the ODF method, a distribution function was generated based on the desired amount of nanotube alignment; and the stiffness matrix was calculated. A rule of mixture approach was implemented in the ODF model to vary the SWNT volume fraction. Both the ODF and FE models are compared and contrasted. ODF analysis is significantly faster for nanocomposites and is a novel contribution in this thesis. Multiscale modeling allows for the effects of nanofillers in epoxy systems to be characterized without having to run costly experiments.

  17. Understanding Greenland ice sheet hydrology using an integrated multi-scale approach

    NASA Astrophysics Data System (ADS)

    Rennermalm, A. K.; Moustafa, S. E.; Mioduszewski, J.; Chu, V. W.; Forster, R. R.; Hagedorn, B.; Harper, J. T.; Mote, T. L.; Robinson, D. A.; Shuman, C. A.; Smith, L. C.; Tedesco, M.

    2013-03-01

    Improved understanding of Greenland ice sheet hydrology is critically important for assessing its impact on current and future ice sheet dynamics and global sea level rise. This has motivated the collection and integration of in situ observations, model development, and remote sensing efforts to quantify meltwater production, as well as its phase changes, transport, and export. Particularly urgent is a better understanding of albedo feedbacks leading to enhanced surface melt, potential positive feedbacks between ice sheet hydrology and dynamics, and meltwater retention in firn. These processes are not isolated, but must be understood as part of a continuum of processes within an integrated system. This letter describes a systems approach to the study of Greenland ice sheet hydrology, emphasizing component interconnections and feedbacks, and highlighting research and observational needs.

  18. SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

    PubMed

    Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

    2010-01-01

    Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

  19. Multiscale power analysis for heart rate variability

    NASA Astrophysics Data System (ADS)

    Zeng, Peng; Liu, Hongxing; Ni, Huangjing; Zhou, Jing; Xia, Lan; Ning, Xinbao

    2015-06-01

    We first introduce multiscale power (MSP) method to assess the power distribution of physiological signals on multiple time scales. Simulation on synthetic data and experiments on heart rate variability (HRV) are tested to support the approach. Results show that both physical and psychological changes influence power distribution significantly. A quantitative parameter, termed power difference (PD), is introduced to evaluate the degree of power distribution alteration. We find that dynamical correlation of HRV will be destroyed completely when PD>0.7.

  20. Statistical mechanics of a single particle in a multiscale random potential: Parisi landscapes in finite-dimensional Euclidean spaces

    NASA Astrophysics Data System (ADS)

    Fyodorov, Yan V.; Bouchaud, Jean-Philippe

    2008-08-01

    We construct an N-dimensional Gaussian landscape with multiscale, translation invariant, logarithmic correlations and investigate the statistical mechanics of a single particle in this environment. In the limit of high dimension N → ∞ the free energy of the system and overlap function are calculated exactly using the replica trick and Parisi's hierarchical ansatz. In the thermodynamic limit, we recover the most general version of the Derrida's generalized random energy model (GREM). The low-temperature behaviour depends essentially on the spectrum of length scales involved in the construction of the landscape. If the latter consists of K discrete values, the system is characterized by a K-step replica symmetry breaking solution. We argue that our construction is in fact valid in any finite spatial dimensions N >= 1. We discuss the implications of our results for the singularity spectrum describing multifractality of the associated Boltzmann-Gibbs measure. Finally we discuss several generalizations and open problems, such as the dynamics in such a landscape and the construction of a generalized multifractal random walk.

  1. Toward multiscale modelings of grain-fluid systems

    NASA Astrophysics Data System (ADS)

    Chareyre, Bruno; Yuan, Chao; Montella, Eduard P.; Salager, Simon

    2017-06-01

    Computationally efficient methods have been developed for simulating partially saturated granular materials in the pendular regime. In contrast, one hardly avoid expensive direct resolutions of 2-phase fluid dynamics problem for mixed pendular-funicular situations or even saturated regimes. Following previous developments for single-phase flow, a pore-network approach of the coupling problems is described. The geometry and movements of phases and interfaces are described on the basis of a tetrahedrization of the pore space, introducing elementary objects such as bridge, meniscus, pore body and pore throat, together with local rules of evolution. As firmly established local rules are still missing on some aspects (entry capillary pressure and pore-scale pressure-saturation relations, forces on the grains, or kinetics of transfers in mixed situations) a multi-scale numerical framework is introduced, enhancing the pore-network approach with the help of direct simulations. Small subsets of a granular system are extracted, in which multiphase scenario are solved using the Lattice-Boltzman method (LBM). In turns, a global problem is assembled and solved at the network scale, as illustrated by a simulated primary drainage.

  2. Multi-scale modeling of diffusion-controlled reactions in polymers: renormalisation of reactivity parameters.

    PubMed

    Everaers, Ralf; Rosa, Angelo

    2012-01-07

    The quantitative description of polymeric systems requires hierarchical modeling schemes, which bridge the gap between the atomic scale, relevant to chemical or biomolecular reactions, and the macromolecular scale, where the longest relaxation modes occur. Here, we use the formalism for diffusion-controlled reactions in polymers developed by Wilemski, Fixman, and Doi to discuss the renormalisation of the reactivity parameters in polymer models with varying spatial resolution. In particular, we show that the adjustments are independent of chain length. As a consequence, it is possible to match reactions times between descriptions with different resolution for relatively short reference chains and to use the coarse-grained model to make quantitative predictions for longer chains. We illustrate our results by a detailed discussion of the classical problem of chain cyclization in the Rouse model, which offers the simplest example of a multi-scale descriptions, if we consider differently discretized Rouse models for the same physical system. Moreover, we are able to explore different combinations of compact and non-compact diffusion in the local and large-scale dynamics by varying the embedding dimension.

  3. Nonlinear Synergistic Emergence and Predictability in Complex Systems: Theory and Hydro-Climatic Applications

    NASA Astrophysics Data System (ADS)

    Perdigão, Rui A. P.; Hall, Julia; Pires, Carlos A. L.; Blöschl, Günter

    2017-04-01

    Classical and stochastic dynamical system theories assume structural coherence and dynamic recurrence with invariants of motion that are not necessarily so. These are grounded on the unproven assumption of universality in the dynamic laws derived from statistical kinematic evaluation of non-representative empirical records. As a consequence, the associated formulations revolve around a restrictive set of configurations and intermittencies e.g. in an ergodic setting, beyond which any predictability is essentially elusive. Moreover, dynamical systems are fundamentally framed around dynamic codependence among intervening processes, i.e. entail essentially redundant interactions such as couplings and feedbacks. That precludes synergistic cooperation among processes that, whilst independent from each other, jointly produce emerging dynamic behaviour not present in any of the intervening parties. In order to overcome these fundamental limitations, we introduce a broad class of non-recursive dynamical systems that formulate dynamic emergence of unprecedented states in a fundamental synergistic manner, with fundamental principles in mind. The overall theory enables innovations to be predicted from the internal system dynamics before any a priori information is provided about the associated dynamical properties. The theory is then illustrated to anticipate, from non-emergent records, the spatiotemporal emergence of multiscale hyper chaotic regimes, critical transitions and structural coevolutionary changes in synthetic and real-world complex systems. Example applications are provided within the hydro-climatic context, formulating and dynamically forecasting evolving hydro-climatic distributions, including the emergence of extreme precipitation and flooding in a structurally changing hydro-climate system. Validation is then conducted with a posteriori verification of the simulated dynamics against observational records. Agreement between simulations and observations is confirmed with robust nonlinear information diagnostics.

  4. Realistic Modeling of Multi-Scale MHD Dynamics of the Solar Atmosphere

    NASA Technical Reports Server (NTRS)

    Kitiashvili, Irina; Mansour, Nagi N.; Wray, Alan; Couvidat, Sebastian; Yoon, Seokkwan; Kosovichev, Alexander

    2014-01-01

    Realistic 3D radiative MHD simulations open new perspectives for understanding the turbulent dynamics of the solar surface, its coupling to the atmosphere, and the physical mechanisms of generation and transport of non-thermal energy. Traditionally, plasma eruptions and wave phenomena in the solar atmosphere are modeled by prescribing artificial driving mechanisms using magnetic or gas pressure forces that might arise from magnetic field emergence or reconnection instabilities. In contrast, our 'ab initio' simulations provide a realistic description of solar dynamics naturally driven by solar energy flow. By simulating the upper convection zone and the solar atmosphere, we can investigate in detail the physical processes of turbulent magnetoconvection, generation and amplification of magnetic fields, excitation of MHD waves, and plasma eruptions. We present recent simulation results of the multi-scale dynamics of quiet-Sun regions, and energetic effects in the atmosphere and compare with observations. For the comparisons we calculate synthetic spectro-polarimetric data to model observational data of SDO, Hinode, and New Solar Telescope.

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

    USGS Publications Warehouse

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

    2012-01-01

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

  6. A Multiscale Model for the Quasi-Static Thermo-Plastic Behavior of Highly Cross-Linked Glassy Polymers

    DOE PAGES

    Vu-Bac, N.; Bessa, M. A.; Rabczuk, Timon; ...

    2015-09-10

    In this paper, we present experimentally validated molecular dynamics predictions of the quasi- static yield and post-yield behavior for a highly cross-linked epoxy polymer under gen- eral stress states and for different temperatures. In addition, a hierarchical multiscale model is presented where the nano-scale simulations obtained from molecular dynamics were homogenized to a continuum thermoplastic constitutive model for the epoxy that can be used to describe the macroscopic behavior of the material. Three major conclusions were achieved: (1) the yield surfaces generated from the nano-scale model for different temperatures agree well with the paraboloid yield crite- rion, supporting previous macroscopicmore » experimental observations; (2) rescaling of the entire yield surfaces to the quasi-static case is possible by considering Argon’s theoretical predictions for pure compression of the polymer at absolute zero temperature; (3) nano- scale simulations can be used for an experimentally-free calibration of macroscopic con- tinuum models, opening new avenues for the design of materials and structures through multi-scale simulations that provide structure-property-performance relationships.« less

  7. A multiscale-based approach for composite materials with embedded PZT filaments for energy harvesting

    NASA Astrophysics Data System (ADS)

    El-Etriby, Ahmed E.; Abdel-Meguid, Mohamed E.; Hatem, Tarek M.; Bahei-El-Din, Yehia A.

    2014-03-01

    Ambient vibrations are major source of wasted energy, exploiting properly such vibration can be converted to valuable energy and harvested to power up devices, i.e. electronic devices. Accordingly, energy harvesting using smart structures with active piezoelectric ceramics has gained wide interest over the past few years as a method for converting such wasted energy. This paper provides numerical and experimental analysis of piezoelectric fiber based composites for energy harvesting applications proposing a multi-scale modeling approach coupled with experimental verification. The multi-scale approach suggested to predict the behavior of piezoelectric fiber-based composites use micromechanical model based on Transformation Field Analysis (TFA) to calculate the overall material properties of electrically active composite structure. Capitalizing on the calculated properties, single-phase analysis of a homogeneous structure is conducted using finite element method. The experimental work approach involves running dynamic tests on piezoelectric fiber-based composites to simulate mechanical vibrations experienced by a subway train floor tiles. Experimental results agree well with the numerical results both for static and dynamic tests.

  8. Multiscale Hy3S: hybrid stochastic simulation for supercomputers.

    PubMed

    Salis, Howard; Sotiropoulos, Vassilios; Kaznessis, Yiannis N

    2006-02-24

    Stochastic simulation has become a useful tool to both study natural biological systems and design new synthetic ones. By capturing the intrinsic molecular fluctuations of "small" systems, these simulations produce a more accurate picture of single cell dynamics, including interesting phenomena missed by deterministic methods, such as noise-induced oscillations and transitions between stable states. However, the computational cost of the original stochastic simulation algorithm can be high, motivating the use of hybrid stochastic methods. Hybrid stochastic methods partition the system into multiple subsets and describe each subset as a different representation, such as a jump Markov, Poisson, continuous Markov, or deterministic process. By applying valid approximations and self-consistently merging disparate descriptions, a method can be considerably faster, while retaining accuracy. In this paper, we describe Hy3S, a collection of multiscale simulation programs. Building on our previous work on developing novel hybrid stochastic algorithms, we have created the Hy3S software package to enable scientists and engineers to both study and design extremely large well-mixed biological systems with many thousands of reactions and chemical species. We have added adaptive stochastic numerical integrators to permit the robust simulation of dynamically stiff biological systems. In addition, Hy3S has many useful features, including embarrassingly parallelized simulations with MPI; special discrete events, such as transcriptional and translation elongation and cell division; mid-simulation perturbations in both the number of molecules of species and reaction kinetic parameters; combinatorial variation of both initial conditions and kinetic parameters to enable sensitivity analysis; use of NetCDF optimized binary format to quickly read and write large datasets; and a simple graphical user interface, written in Matlab, to help users create biological systems and analyze data. We demonstrate the accuracy and efficiency of Hy3S with examples, including a large-scale system benchmark and a complex bistable biochemical network with positive feedback. The software itself is open-sourced under the GPL license and is modular, allowing users to modify it for their own purposes. Hy3S is a powerful suite of simulation programs for simulating the stochastic dynamics of networks of biochemical reactions. Its first public version enables computational biologists to more efficiently investigate the dynamics of realistic biological systems.

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

    PubMed

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

    2011-01-01

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

  10. Measuring center of pressure signals to quantify human balance using multivariate multiscale entropy by designing a force platform.

    PubMed

    Huang, Cheng-Wei; Sue, Pei-Der; Abbod, Maysam F; Jiang, Bernard C; Shieh, Jiann-Shing

    2013-08-08

    To assess the improvement of human body balance, a low cost and portable measuring device of center of pressure (COP), known as center of pressure and complexity monitoring system (CPCMS), has been developed for data logging and analysis. In order to prove that the system can estimate the different magnitude of different sways in comparison with the commercial Advanced Mechanical Technology Incorporation (AMTI) system, four sway tests have been developed (i.e., eyes open, eyes closed, eyes open with water pad, and eyes closed with water pad) to produce different sway displacements. Firstly, static and dynamic tests were conducted to investigate the feasibility of the system. Then, correlation tests of the CPCMS and AMTI systems have been compared with four sway tests. The results are within the acceptable range. Furthermore, multivariate empirical mode decomposition (MEMD) and enhanced multivariate multiscale entropy (MMSE) analysis methods have been used to analyze COP data reported by the CPCMS and compare it with the AMTI system. The improvements of the CPCMS are 35% to 70% (open eyes test) and 60% to 70% (eyes closed test) with and without water pad. The AMTI system has shown an improvement of 40% to 80% (open eyes test) and 65% to 75% (closed eyes test). The results indicate that the CPCMS system can achieve similar results to the commercial product so it can determine the balance.

  11. Measuring Center of Pressure Signals to Quantify Human Balance Using Multivariate Multiscale Entropy by Designing a Force Platform

    PubMed Central

    Huang, Cheng-Wei; Sue, Pei-Der; Abbod, Maysam F.; Jiang, Bernard C.; Shieh, Jiann-Shing

    2013-01-01

    To assess the improvement of human body balance, a low cost and portable measuring device of center of pressure (COP), known as center of pressure and complexity monitoring system (CPCMS), has been developed for data logging and analysis. In order to prove that the system can estimate the different magnitude of different sways in comparison with the commercial Advanced Mechanical Technology Incorporation (AMTI) system, four sway tests have been developed (i.e., eyes open, eyes closed, eyes open with water pad, and eyes closed with water pad) to produce different sway displacements. Firstly, static and dynamic tests were conducted to investigate the feasibility of the system. Then, correlation tests of the CPCMS and AMTI systems have been compared with four sway tests. The results are within the acceptable range. Furthermore, multivariate empirical mode decomposition (MEMD) and enhanced multivariate multiscale entropy (MMSE) analysis methods have been used to analyze COP data reported by the CPCMS and compare it with the AMTI system. The improvements of the CPCMS are 35% to 70% (open eyes test) and 60% to 70% (eyes closed test) with and without water pad. The AMTI system has shown an improvement of 40% to 80% (open eyes test) and 65% to 75% (closed eyes test). The results indicate that the CPCMS system can achieve similar results to the commercial product so it can determine the balance. PMID:23966184

  12. Multi-scale dynamical behavior of spatially distributed systems: a deterministic point of view

    NASA Astrophysics Data System (ADS)

    Mangiarotti, S.; Le Jean, F.; Drapeau, L.; Huc, M.

    2015-12-01

    Physical and biophysical systems are spatially distributed systems. Their behavior can be observed or modelled spatially at various resolutions. In this work, a deterministic point of view is adopted to analyze multi-scale behavior taking a set of ordinary differential equation (ODE) as elementary part of the system.To perform analyses, scenes of study are thus generated based on ensembles of identical elementary ODE systems. Without any loss of generality, their dynamics is chosen chaotic in order to ensure sensitivity to initial conditions, that is, one fundamental property of atmosphere under instable conditions [1]. The Rössler system [2] is used for this purpose for both its topological and algebraic simplicity [3,4].Two cases are thus considered: the chaotic oscillators composing the scene of study are taken either independent, or in phase synchronization. Scale behaviors are analyzed considering the scene of study as aggregations (basically obtained by spatially averaging the signal) or as associations (obtained by concatenating the time series). The global modeling technique is used to perform the numerical analyses [5].One important result of this work is that, under phase synchronization, a scene of aggregated dynamics can be approximated by the elementary system composing the scene, but modifying its parameterization [6]. This is shown based on numerical analyses. It is then demonstrated analytically and generalized to a larger class of ODE systems. Preliminary applications to cereal crops observed from satellite are also presented.[1] Lorenz, Deterministic nonperiodic flow. J. Atmos. Sci., 20, 130-141 (1963).[2] Rössler, An equation for continuous chaos, Phys. Lett. A, 57, 397-398 (1976).[3] Gouesbet & Letellier, Global vector-field reconstruction by using a multivariate polynomial L2 approximation on nets, Phys. Rev. E 49, 4955-4972 (1994).[4] Letellier, Roulin & Rössler, Inequivalent topologies of chaos in simple equations, Chaos, Solitons & Fractals, 28, 337-360 (2006).[5] Mangiarotti, Coudret, Drapeau, & Jarlan, Polynomial search and global modeling, Phys. Rev. E 86(4), 046205 (2012).[6] Mangiarotti, Modélisation globale et Caractérisation Topologique de dynamiques environnementales. Habilitation à Diriger des Recherches, Univ. Toulouse 3 (2014).

  13. Model-Based Self-Tuning Multiscale Method for Combustion Control

    NASA Technical Reports Server (NTRS)

    Le, Dzu, K.; DeLaat, John C.; Chang, Clarence T.; Vrnak, Daniel R.

    2006-01-01

    A multi-scale representation of the combustor dynamics was used to create a self-tuning, scalable controller to suppress multiple instability modes in a liquid-fueled aero engine-derived combustor operating at engine-like conditions. Its self-tuning features designed to handle the uncertainties in the combustor dynamics and time-delays are essential for control performance and robustness. The controller was implemented to modulate a high-frequency fuel valve with feedback from dynamic pressure sensors. This scalable algorithm suppressed pressure oscillations of different instability modes by as much as 90 percent without the peak-splitting effect. The self-tuning logic guided the adjustment of controller parameters and converged quickly toward phase-lock for optimal suppression of the instabilities. The forced-response characteristics of the control model compare well with those of the test rig on both the frequency-domain and the time-domain.

  14. Pierre Turq, an inspirational scientist in charge and at interfaces

    NASA Astrophysics Data System (ADS)

    Ancian, Bernard; Bernard, Olivier; Chevalet, Jean; Dahirel, Vincent; Devilliers, Didier; Dubois, Emmanuelle; Dufrêche, Jean-François; Durand-Vidal, Serge; Groult, Henri; Jardat, Marie; Lantelme, Frédéric; Malikova, Natalie; Marry, Virginie; Mériguet, Guillaume; Perzynski, Régine; Rollet, Anne-Laure; Rotenberg, Benjamin; Salanne, Mathieu; Simon, Christian

    2014-05-01

    Pierre Turq has made decisive contributions to the theory and to the multiscale simulation of charged systems, such as molten salts, electrolyte solutions and colloidal suspensions, in the bulk, at interfaces and under confinement. His research line focussed on dynamical properties and was characterised by constant efforts to connect his theoretical work to both experiments and practical applications. In this article, his colleagues and former students pay a tribute to his past and current research interests by illustrating some recent developments accomplished in his laboratory.

  15. Multiscale Asymptotics for the Skeleton of the Madden-Julian Oscillation and Tropical-Extratropical Interactions (Open Access)

    DTIC Science & Technology

    2015-11-30

    equatorial baroclinic dynamics, and (iii) the interactive effects of moisture and convection. More specifically, the model integrates the dry...interactions 5 Par. Derivation Dim. val. Description β 2.3× 10−11 m−1s−1 Variation of Coriolis parameter with latitude θ0 300 K Potential temperature...tropical Coriolis force, and x and y denote the zonal and meridional coordinates. Without the moisture q and convection envelope a, system (1) is the two

  16. The key technique study of a kind of personal navigation oriented LBS system

    NASA Astrophysics Data System (ADS)

    Yan, Lei; Zheng, Jianghua; Zhang, Xin; Peng, Chunhua; He, Lina

    2005-11-01

    With the integration of GIS, IT technology and wireless communication techniques, LBS is fast developing and caused wide concern. Personal navigation is the critical application of LBS. It has higher requirement of data quality, positioning accuracy and multi-model services. The study discusses the key techniques of a personal navigation oriented LBS system. As an example for service platform of China Unicom, NAVISTAR especially emphasizes the importance of spatial data organization. Based-on CDMA1X network, it adopts gpsOne\\MS-Assisted dynamic positioning technique, and puts forward a data organization solution to realize multi-scale representation.

  17. 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-range Coulombic interactions, various non-electrostatic solvent-solute interactions are considered in the present modeling. We demonstrate the consistency between the non-equilibrium charge transport model and the equilibrium solvation model by showing the systematical reduction of the former to the latter at equilibrium. This paper also offers a brief review of the field. PMID:25382892

  18. 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-range Coulombic interactions, various non-electrostatic solvent-solute interactions are considered in the present modeling. We demonstrate the consistency between the non-equilibrium charge transport model and the equilibrium solvation model by showing the systematical reduction of the former to the latter at equilibrium. This paper also offers a brief review of the field.

  19. Quadrantal multi-scale distribution entropy analysis of heartbeat interval series based on a modified Poincaré plot

    NASA Astrophysics Data System (ADS)

    Huo, Chengyu; Huang, Xiaolin; Zhuang, Jianjun; Hou, Fengzhen; Ni, Huangjing; Ning, Xinbao

    2013-09-01

    The Poincaré plot is one of the most important approaches in human cardiac rhythm analysis. However, further investigations are still needed to concentrate on techniques that can characterize the dispersion of the points displayed by a Poincaré plot. Based on a modified Poincaré plot, we provide a novel measurement named distribution entropy (DE) and propose a quadrantal multi-scale distribution entropy analysis (QMDE) for the quantitative descriptions of the scatter distribution patterns in various regions and temporal scales. We apply this method to the heartbeat interval series derived from healthy subjects and congestive heart failure (CHF) sufferers, respectively, and find that the discriminations between them are most significant in the first quadrant, which implies significant impacts on vagal regulation brought about by CHF. We also investigate the day-night differences of young healthy people, and it is shown that the results present a clearly circadian rhythm, especially in the first quadrant. In addition, the multi-scale analysis indicates that the results of healthy subjects and CHF sufferers fluctuate in different trends with variation of the scale factor. The same phenomenon also appears in circadian rhythm investigations of young healthy subjects, which implies that the cardiac dynamic system is affected differently in various temporal scales by physiological or pathological factors.

  20. Optimization of a hydrodynamic separator using a multiscale computational fluid dynamics approach.

    PubMed

    Schmitt, Vivien; Dufresne, Matthieu; Vazquez, Jose; Fischer, Martin; Morin, Antoine

    2013-01-01

    This article deals with the optimization of a hydrodynamic separator working on the tangential separation mechanism along a screen. The aim of this study is to optimize the shape of the device to avoid clogging. A multiscale approach is used. This methodology combines measurements and computational fluid dynamics (CFD). A local model enables us to observe the different phenomena occurring at the orifice scale, which shows the potential of expanded metal screens. A global model is used to simulate the flow within the device using a conceptual model of the screen (porous wall). After validation against the experimental measurements, the global model was used to investigate the influence of deflectors and disk plates in the structure.

  1. A multiscale analysis of stock return co-movements and spillovers: Evidence from Pacific developed markets

    NASA Astrophysics Data System (ADS)

    Das, Debojyoti; Bhowmik, Puja; Jana, R. K.

    2018-07-01

    In this paper we examine the stock market co-movement and volatility spillover dynamics in the Pacific developed markets for a period spanning over January 05, 2001 to January 09, 2018. We employ wavelet-based techniques to study the multiscale co-movement dynamics of stock returns. Additionally, we also study the subtleties of volatility spillover of returns among the sample countries. We find that: (a) diversification benefits in these markets are limited due to higher degrees of integration, (b) Pacific developed markets co-move strongly during the periods of financial crisis (i.e. the contagion hypothesis) and (c) higher degree of volatility spills during financial crisis. We believe our study holds significance in the perspective of international portfolio diversification.

  2. Rough Set Approach to Incomplete Multiscale Information System

    PubMed Central

    Yang, Xibei; Qi, Yong; Yu, Dongjun; Yu, Hualong; Song, Xiaoning; Yang, Jingyu

    2014-01-01

    Multiscale information system is a new knowledge representation system for expressing the knowledge with different levels of granulations. In this paper, by considering the unknown values, which can be seen everywhere in real world applications, the incomplete multiscale information system is firstly investigated. The descriptor technique is employed to construct rough sets at different scales for analyzing the hierarchically structured data. The problem of unravelling decision rules at different scales is also addressed. Finally, the reduct descriptors are formulated to simplify decision rules, which can be derived from different scales. Some numerical examples are employed to substantiate the conceptual arguments. PMID:25276852

  3. Computationally Efficient Multiscale Reactive Molecular Dynamics to Describe Amino Acid Deprotonation in Proteins

    PubMed Central

    2016-01-01

    An important challenge in the simulation of biomolecular systems is a quantitative description of the protonation and deprotonation process of amino acid residues. Despite the seeming simplicity of adding or removing a positively charged hydrogen nucleus, simulating the actual protonation/deprotonation process is inherently difficult. It requires both the explicit treatment of the excess proton, including its charge defect delocalization and Grotthuss shuttling through inhomogeneous moieties (water and amino residues), and extensive sampling of coupled condensed phase motions. In a recent paper (J. Chem. Theory Comput.2014, 10, 2729−273725061442), a multiscale approach was developed to map high-level quantum mechanics/molecular mechanics (QM/MM) data into a multiscale reactive molecular dynamics (MS-RMD) model in order to describe amino acid deprotonation in bulk water. In this article, we extend the fitting approach (called FitRMD) to create MS-RMD models for ionizable amino acids within proteins. The resulting models are shown to faithfully reproduce the free energy profiles of the reference QM/MM Hamiltonian for PT inside an example protein, the ClC-ec1 H+/Cl– antiporter. Moreover, we show that the resulting MS-RMD models are computationally efficient enough to then characterize more complex 2-dimensional free energy surfaces due to slow degrees of freedom such as water hydration of internal protein cavities that can be inherently coupled to the excess proton charge translocation. The FitRMD method is thus shown to be an effective way to map ab initio level accuracy into a much more computationally efficient reactive MD method in order to explicitly simulate and quantitatively describe amino acid protonation/deprotonation in proteins. PMID:26734942

  4. Computationally Efficient Multiscale Reactive Molecular Dynamics to Describe Amino Acid Deprotonation in Proteins.

    PubMed

    Lee, Sangyun; Liang, Ruibin; Voth, Gregory A; Swanson, Jessica M J

    2016-02-09

    An important challenge in the simulation of biomolecular systems is a quantitative description of the protonation and deprotonation process of amino acid residues. Despite the seeming simplicity of adding or removing a positively charged hydrogen nucleus, simulating the actual protonation/deprotonation process is inherently difficult. It requires both the explicit treatment of the excess proton, including its charge defect delocalization and Grotthuss shuttling through inhomogeneous moieties (water and amino residues), and extensive sampling of coupled condensed phase motions. In a recent paper (J. Chem. Theory Comput. 2014, 10, 2729-2737), a multiscale approach was developed to map high-level quantum mechanics/molecular mechanics (QM/MM) data into a multiscale reactive molecular dynamics (MS-RMD) model in order to describe amino acid deprotonation in bulk water. In this article, we extend the fitting approach (called FitRMD) to create MS-RMD models for ionizable amino acids within proteins. The resulting models are shown to faithfully reproduce the free energy profiles of the reference QM/MM Hamiltonian for PT inside an example protein, the ClC-ec1 H(+)/Cl(-) antiporter. Moreover, we show that the resulting MS-RMD models are computationally efficient enough to then characterize more complex 2-dimensional free energy surfaces due to slow degrees of freedom such as water hydration of internal protein cavities that can be inherently coupled to the excess proton charge translocation. The FitRMD method is thus shown to be an effective way to map ab initio level accuracy into a much more computationally efficient reactive MD method in order to explicitly simulate and quantitatively describe amino acid protonation/deprotonation in proteins.

  5. A Multiscale Approach to Modelling Drug Metabolism by Membrane-Bound Cytochrome P450 Enzymes

    PubMed Central

    Sansom, Mark S. P.; Mulholland, Adrian J.

    2014-01-01

    Cytochrome P450 enzymes are found in all life forms. P450s play an important role in drug metabolism, and have potential uses as biocatalysts. Human P450s are membrane-bound proteins. However, the interactions between P450s and their membrane environment are not well-understood. To date, all P450 crystal structures have been obtained from engineered proteins, from which the transmembrane helix was absent. A significant number of computational studies have been performed on P450s, but the majority of these have been performed on the solubilised forms of P450s. Here we present a multiscale approach for modelling P450s, spanning from coarse-grained and atomistic molecular dynamics simulations to reaction modelling using hybrid quantum mechanics/molecular mechanics (QM/MM) methods. To our knowledge, this is the first application of such an integrated multiscale approach to modelling of a membrane-bound enzyme. We have applied this protocol to a key human P450 involved in drug metabolism: CYP3A4. A biologically realistic model of CYP3A4, complete with its transmembrane helix and a membrane, has been constructed and characterised. The dynamics of this complex have been studied, and the oxidation of the anticoagulant R-warfarin has been modelled in the active site. Calculations have also been performed on the soluble form of the enzyme in aqueous solution. Important differences are observed between the membrane and solution systems, most notably for the gating residues and channels that control access to the active site. The protocol that we describe here is applicable to other membrane-bound enzymes. PMID:25033460

  6. A multiscale approach to modelling drug metabolism by membrane-bound cytochrome P450 enzymes.

    PubMed

    Lonsdale, Richard; Rouse, Sarah L; Sansom, Mark S P; Mulholland, Adrian J

    2014-07-01

    Cytochrome P450 enzymes are found in all life forms. P450s play an important role in drug metabolism, and have potential uses as biocatalysts. Human P450s are membrane-bound proteins. However, the interactions between P450s and their membrane environment are not well-understood. To date, all P450 crystal structures have been obtained from engineered proteins, from which the transmembrane helix was absent. A significant number of computational studies have been performed on P450s, but the majority of these have been performed on the solubilised forms of P450s. Here we present a multiscale approach for modelling P450s, spanning from coarse-grained and atomistic molecular dynamics simulations to reaction modelling using hybrid quantum mechanics/molecular mechanics (QM/MM) methods. To our knowledge, this is the first application of such an integrated multiscale approach to modelling of a membrane-bound enzyme. We have applied this protocol to a key human P450 involved in drug metabolism: CYP3A4. A biologically realistic model of CYP3A4, complete with its transmembrane helix and a membrane, has been constructed and characterised. The dynamics of this complex have been studied, and the oxidation of the anticoagulant R-warfarin has been modelled in the active site. Calculations have also been performed on the soluble form of the enzyme in aqueous solution. Important differences are observed between the membrane and solution systems, most notably for the gating residues and channels that control access to the active site. The protocol that we describe here is applicable to other membrane-bound enzymes.

  7. Multiscale modeling of particle in suspension with smoothed dissipative particle dynamics

    NASA Astrophysics Data System (ADS)

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

    2012-01-01

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

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

    ERIC Educational Resources Information Center

    Schwalbe, Michelle Kristin

    2010-01-01

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

  9. Network neuroscience

    PubMed Central

    Bassett, Danielle S; Sporns, Olaf

    2017-01-01

    Despite substantial recent progress, our understanding of the principles and mechanisms underlying complex brain function and cognition remains incomplete. Network neuroscience proposes to tackle these enduring challenges. Approaching brain structure and function from an explicitly integrative perspective, network neuroscience pursues new ways to map, record, analyze and model the elements and interactions of neurobiological systems. Two parallel trends drive the approach: the availability of new empirical tools to create comprehensive maps and record dynamic patterns among molecules, neurons, brain areas and social systems; and the theoretical framework and computational tools of modern network science. The convergence of empirical and computational advances opens new frontiers of scientific inquiry, including network dynamics, manipulation and control of brain networks, and integration of network processes across spatiotemporal domains. We review emerging trends in network neuroscience and attempt to chart a path toward a better understanding of the brain as a multiscale networked system. PMID:28230844

  10. Multiscale volatility duration characteristics on financial multi-continuum percolation dynamics

    NASA Astrophysics Data System (ADS)

    Wang, Min; Wang, Jun

    A random stock price model based on the multi-continuum percolation system is developed to investigate the nonlinear dynamics of stock price volatility duration, in an attempt to explain various statistical facts found in financial data, and have a deeper understanding of mechanisms in the financial market. The continuum percolation system is usually referred to be a random coverage process or a Boolean model, it is a member of a class of statistical physics systems. In this paper, the multi-continuum percolation (with different values of radius) is employed to model and reproduce the dispersal of information among the investors. To testify the rationality of the proposed model, the nonlinear analyses of return volatility duration series are preformed by multifractal detrending moving average analysis and Zipf analysis. The comparison empirical results indicate the similar nonlinear behaviors for the proposed model and the actual Chinese stock market.

  11. Panarchy use in environmental science for risk and resilience planning

    USGS Publications Warehouse

    Angeler, David G.; Allen, Craig R.; Garmestani, Ahjond S.; Gunderson, Lance H.; Linkov, Igor

    2016-01-01

    Environmental sciences have an important role in informing sustainable management of built environments by providing insights about the drivers and potentially negative impacts of global environmental change. Here, we discuss panarchy theory, a multi-scale hierarchical concept that accounts for the dynamism of complex socio-ecological systems, especially for those systems with strong cross-scale feedbacks. The idea of panarchy underlies much of system resilience, focusing on how systems respond to known and unknown threats. Panarchy theory can provide a framework for qualitative and quantitative research and application in the environmental sciences, which can in turn inform the ongoing efforts in socio-technical resilience thinking and adaptive and transformative approaches to management.

  12. Dynamical modeling of microRNA action on the protein translation process

    PubMed Central

    2010-01-01

    Background Protein translation is a multistep process which can be represented as a cascade of biochemical reactions (initiation, ribosome assembly, elongation, etc.), the rate of which can be regulated by small non-coding microRNAs through multiple mechanisms. It remains unclear what mechanisms of microRNA action are the most dominant: moreover, many experimental reports deliver controversial messages on what is the concrete mechanism actually observed in the experiment. Nissan and Parker have recently demonstrated that it might be impossible to distinguish alternative biological hypotheses using the steady state data on the rate of protein synthesis. For their analysis they used two simple kinetic models of protein translation. Results In contrary to the study by Nissan and Parker, we show that dynamical data allow discriminating some of the mechanisms of microRNA action. We demonstrate this using the same models as developed by Nissan and Parker for the sake of comparison but the methods developed (asymptotology of biochemical networks) can be used for other models. We formulate a hypothesis that the effect of microRNA action is measurable and observable only if it affects the dominant system (generalization of the limiting step notion for complex networks) of the protein translation machinery. The dominant system can vary in different experimental conditions that can partially explain the existing controversy of some of the experimental data. Conclusions Our analysis of the transient protein translation dynamics shows that it gives enough information to verify or reject a hypothesis about a particular molecular mechanism of microRNA action on protein translation. For multiscale systems only that action of microRNA is distinguishable which affects the parameters of dominant system (critical parameters), or changes the dominant system itself. Dominant systems generalize and further develop the old and very popular idea of limiting step. Algorithms for identifying dominant systems in multiscale kinetic models are straightforward but not trivial and depend only on the ordering of the model parameters but not on their concrete values. Asymptotic approach to kinetic models allows putting in order diverse experimental observations in complex situations when many alternative hypotheses co-exist. PMID:20181238

  13. Dynamical modeling of microRNA action on the protein translation process.

    PubMed

    Zinovyev, Andrei; Morozova, Nadya; Nonne, Nora; Barillot, Emmanuel; Harel-Bellan, Annick; Gorban, Alexander N

    2010-02-24

    Protein translation is a multistep process which can be represented as a cascade of biochemical reactions (initiation, ribosome assembly, elongation, etc.), the rate of which can be regulated by small non-coding microRNAs through multiple mechanisms. It remains unclear what mechanisms of microRNA action are the most dominant: moreover, many experimental reports deliver controversial messages on what is the concrete mechanism actually observed in the experiment. Nissan and Parker have recently demonstrated that it might be impossible to distinguish alternative biological hypotheses using the steady state data on the rate of protein synthesis. For their analysis they used two simple kinetic models of protein translation. In contrary to the study by Nissan and Parker, we show that dynamical data allow discriminating some of the mechanisms of microRNA action. We demonstrate this using the same models as developed by Nissan and Parker for the sake of comparison but the methods developed (asymptotology of biochemical networks) can be used for other models. We formulate a hypothesis that the effect of microRNA action is measurable and observable only if it affects the dominant system (generalization of the limiting step notion for complex networks) of the protein translation machinery. The dominant system can vary in different experimental conditions that can partially explain the existing controversy of some of the experimental data. Our analysis of the transient protein translation dynamics shows that it gives enough information to verify or reject a hypothesis about a particular molecular mechanism of microRNA action on protein translation. For multiscale systems only that action of microRNA is distinguishable which affects the parameters of dominant system (critical parameters), or changes the dominant system itself. Dominant systems generalize and further develop the old and very popular idea of limiting step. Algorithms for identifying dominant systems in multiscale kinetic models are straightforward but not trivial and depend only on the ordering of the model parameters but not on their concrete values. Asymptotic approach to kinetic models allows putting in order diverse experimental observations in complex situations when many alternative hypotheses co-exist.

  14. 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.

  15. Multiple time-scales and the developmental dynamics of social systems

    PubMed Central

    Flack, Jessica C.

    2012-01-01

    To build a theory of social complexity, we need to understand how aggregate social properties arise from individual interaction rules. Here, I review a body of work on the developmental dynamics of pigtailed macaque social organization and conflict management that provides insight into the mechanistic causes of multi-scale social systems. In this model system coarse-grained, statistical representations of collective dynamics are more predictive of the future state of the system than the constantly in-flux behavioural patterns at the individual level. The data suggest that individuals can perceive and use these representations for strategical decision-making. As an interaction history accumulates the coarse-grained representations consolidate. This constrains individual behaviour and provides the foundations for new levels of organization. The time-scales on which these representations change impact whether the consolidating higher-levels can be modified by individuals and collectively. The time-scales appear to be a function of the ‘coarseness’ of the representations and the character of the collective dynamics over which they are averages. The data suggest that an advantage of multiple timescales is that they allow social systems to balance tradeoffs between predictability and adaptability. I briefly discuss the implications of these findings for cognition, social niche construction and the evolution of new levels of organization in biological systems. PMID:22641819

  16. Multiple time-scales and the developmental dynamics of social systems.

    PubMed

    Flack, Jessica C

    2012-07-05

    To build a theory of social complexity, we need to understand how aggregate social properties arise from individual interaction rules. Here, I review a body of work on the developmental dynamics of pigtailed macaque social organization and conflict management that provides insight into the mechanistic causes of multi-scale social systems. In this model system coarse-grained, statistical representations of collective dynamics are more predictive of the future state of the system than the constantly in-flux behavioural patterns at the individual level. The data suggest that individuals can perceive and use these representations for strategical decision-making. As an interaction history accumulates the coarse-grained representations consolidate. This constrains individual behaviour and provides the foundations for new levels of organization. The time-scales on which these representations change impact whether the consolidating higher-levels can be modified by individuals and collectively. The time-scales appear to be a function of the 'coarseness' of the representations and the character of the collective dynamics over which they are averages. The data suggest that an advantage of multiple timescales is that they allow social systems to balance tradeoffs between predictability and adaptability. I briefly discuss the implications of these findings for cognition, social niche construction and the evolution of new levels of organization in biological systems.

  17. Age-related Multiscale Changes in Brain Signal Variability in Pre-task versus Post-task Resting-state EEG.

    PubMed

    Wang, Hongye; McIntosh, Anthony R; Kovacevic, Natasa; Karachalios, Maria; Protzner, Andrea B

    2016-07-01

    Recent empirical work suggests that, during healthy aging, the variability of network dynamics changes during task performance. Such variability appears to reflect the spontaneous formation and dissolution of different functional networks. We sought to extend these observations into resting-state dynamics. We recorded EEG in young, middle-aged, and older adults during a "rest-task-rest" design and investigated if aging modifies the interaction between resting-state activity and external stimulus-induced activity. Using multiscale entropy as our measure of variability, we found that, with increasing age, resting-state dynamics shifts from distributed to more local neural processing, especially at posterior sources. In the young group, resting-state dynamics also changed from pre- to post-task, where fine-scale entropy increased in task-positive regions and coarse-scale entropy increased in the posterior cingulate, a key region associated with the default mode network. Lastly, pre- and post-task resting-state dynamics were linked to performance on the intervening task for all age groups, but this relationship became weaker with increasing age. Our results suggest that age-related changes in resting-state dynamics occur across different spatial and temporal scales and have consequences for information processing capacity.

  18. Dynamic evaluation of two decades of WRF-CMAQ ozone simulations over the contiguous United States

    EPA Science Inventory

    Dynamic evaluation of the fully coupled Weather Research and Forecasting (WRF)– Community Multi-scale Air Quality (CMAQ) model ozone simulations over the contiguous United States (CONUS) using two decades of simulations covering the period from 1990 to 2010 is conducted to ...

  19. Dynamic evaluation of two decades of WRF-CMAQ ozone simulations over the contiguous United States

    EPA Science Inventory

    Dynamic evaluation of the fully coupled Weather Research and Forecasting (WRF)– Community Multi-scale Air Quality (CMAQ) model ozone simulations over the contiguous United States (CONUS) using two decades of simulations covering the period from 1990 to 2010 is conducted to assess...

  20. 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...

  1. Entropy for the Complexity of Physiological Signal Dynamics.

    PubMed

    Zhang, Xiaohua Douglas

    2017-01-01

    Recently, the rapid development of large data storage technologies, mobile network technology, and portable medical devices makes it possible to measure, record, store, and track analysis of biological dynamics. Portable noninvasive medical devices are crucial to capture individual characteristics of biological dynamics. The wearable noninvasive medical devices and the analysis/management of related digital medical data will revolutionize the management and treatment of diseases, subsequently resulting in the establishment of a new healthcare system. One of the key features that can be extracted from the data obtained by wearable noninvasive medical device is the complexity of physiological signals, which can be represented by entropy of biological dynamics contained in the physiological signals measured by these continuous monitoring medical devices. Thus, in this chapter I present the major concepts of entropy that are commonly used to measure the complexity of biological dynamics. The concepts include Shannon entropy, Kolmogorov entropy, Renyi entropy, approximate entropy, sample entropy, and multiscale entropy. I also demonstrate an example of using entropy for the complexity of glucose dynamics.

  2. Parameters Selection for Bivariate Multiscale Entropy Analysis of Postural Fluctuations in Fallers and Non-Fallers Older Adults.

    PubMed

    Ramdani, Sofiane; Bonnet, Vincent; Tallon, Guillaume; Lagarde, Julien; Bernard, Pierre Louis; Blain, Hubert

    2016-08-01

    Entropy measures are often used to quantify the regularity of postural sway time series. Recent methodological developments provided both multivariate and multiscale approaches allowing the extraction of complexity features from physiological signals; see "Dynamical complexity of human responses: A multivariate data-adaptive framework," in Bulletin of Polish Academy of Science and Technology, vol. 60, p. 433, 2012. The resulting entropy measures are good candidates for the analysis of bivariate postural sway signals exhibiting nonstationarity and multiscale properties. These methods are dependant on several input parameters such as embedding parameters. Using two data sets collected from institutionalized frail older adults, we numerically investigate the behavior of a recent multivariate and multiscale entropy estimator; see "Multivariate multiscale entropy: A tool for complexity analysis of multichannel data," Physics Review E, vol. 84, p. 061918, 2011. We propose criteria for the selection of the input parameters. Using these optimal parameters, we statistically compare the multivariate and multiscale entropy values of postural sway data of non-faller subjects to those of fallers. These two groups are discriminated by the resulting measures over multiple time scales. We also demonstrate that the typical parameter settings proposed in the literature lead to entropy measures that do not distinguish the two groups. This last result confirms the importance of the selection of appropriate input parameters.

  3. 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.

  4. Quantum Information Biology: From Information Interpretation of Quantum Mechanics to Applications in Molecular Biology and Cognitive Psychology

    NASA Astrophysics Data System (ADS)

    Asano, Masanari; Basieva, Irina; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

    2015-10-01

    We discuss foundational issues of quantum information biology (QIB)—one of the most successful applications of the quantum formalism outside of physics. QIB provides a multi-scale model of information processing in bio-systems: from proteins and cells to cognitive and social systems. This theory has to be sharply distinguished from "traditional quantum biophysics". The latter is about quantum bio-physical processes, e.g., in cells or brains. QIB models the dynamics of information states of bio-systems. We argue that the information interpretation of quantum mechanics (its various forms were elaborated by Zeilinger and Brukner, Fuchs and Mermin, and D' Ariano) is the most natural interpretation of QIB. Biologically QIB is based on two principles: (a) adaptivity; (b) openness (bio-systems are fundamentally open). These principles are mathematically represented in the framework of a novel formalism— quantum adaptive dynamics which, in particular, contains the standard theory of open quantum systems.

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

    Majda, Andrew J.; Xing, Yulong; Mohammadian, Majid

    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 heatmore » 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.« less

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    PubMed Central

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

    2017-01-01

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

  8. 3D hierarchical geometric modeling and multiscale FE analysis as a base for individualized medical diagnosis of bone structure.

    PubMed

    Podshivalov, L; Fischer, A; Bar-Yoseph, P Z

    2011-04-01

    This paper describes a new alternative for individualized mechanical analysis of bone trabecular structure. This new method closes the gap between the classic homogenization approach that is applied to macro-scale models and the modern micro-finite element method that is applied directly to micro-scale high-resolution models. The method is based on multiresolution geometrical modeling that generates intermediate structural levels. A new method for estimating multiscale material properties has also been developed to facilitate reliable and efficient mechanical analysis. What makes this method unique is that it enables direct and interactive analysis of the model at every intermediate level. Such flexibility is of principal importance in the analysis of trabecular porous structure. The method enables physicians to zoom-in dynamically and focus on the volume of interest (VOI), thus paving the way for a large class of investigations into the mechanical behavior of bone structure. This is one of the very few methods in the field of computational bio-mechanics that applies mechanical analysis adaptively on large-scale high resolution models. The proposed computational multiscale FE method can serve as an infrastructure for a future comprehensive computerized system for diagnosis of bone structures. The aim of such a system is to assist physicians in diagnosis, prognosis, drug treatment simulation and monitoring. Such a system can provide a better understanding of the disease, and hence benefit patients by providing better and more individualized treatment and high quality healthcare. In this paper, we demonstrate the feasibility of our method on a high-resolution model of vertebra L3. Copyright © 2010 Elsevier Inc. All rights reserved.

  9. Experimental parameter identification of a multi-scale musculoskeletal model controlled by electrical stimulation: application to patients with spinal cord injury.

    PubMed

    Benoussaad, Mourad; Poignet, Philippe; Hayashibe, Mitsuhiro; Azevedo-Coste, Christine; Fattal, Charles; Guiraud, David

    2013-06-01

    We investigated the parameter identification of a multi-scale physiological model of skeletal muscle, based on Huxley's formulation. We focused particularly on the knee joint controlled by quadriceps muscles under electrical stimulation (ES) in subjects with a complete spinal cord injury. A noninvasive and in vivo identification protocol was thus applied through surface stimulation in nine subjects and through neural stimulation in one ES-implanted subject. The identification protocol included initial identification steps, which are adaptations of existing identification techniques to estimate most of the parameters of our model. Then we applied an original and safer identification protocol in dynamic conditions, which required resolution of a nonlinear programming (NLP) problem to identify the serial element stiffness of quadriceps. Each identification step and cross validation of the estimated model in dynamic condition were evaluated through a quadratic error criterion. The results highlighted good accuracy, the efficiency of the identification protocol and the ability of the estimated model to predict the subject-specific behavior of the musculoskeletal system. From the comparison of parameter values between subjects, we discussed and explored the inter-subject variability of parameters in order to select parameters that have to be identified in each patient.

  10. Investigating lithium-ion battery materials during overcharge-induced thermal runaway: an operando and multi-scale X-ray CT study.

    PubMed

    Finegan, Donal P; Scheel, Mario; Robinson, James B; Tjaden, Bernhard; Di Michiel, Marco; Hinds, Gareth; Brett, Dan J L; Shearing, Paul R

    2016-11-16

    Catastrophic failure of lithium-ion batteries occurs across multiple length scales and over very short time periods. A combination of high-speed operando tomography, thermal imaging and electrochemical measurements is used to probe the degradation mechanisms leading up to overcharge-induced thermal runaway of a LiCoO 2 pouch cell, through its interrelated dynamic structural, thermal and electrical responses. Failure mechanisms across multiple length scales are explored using a post-mortem multi-scale tomography approach, revealing significant morphological and phase changes in the LiCoO 2 electrode microstructure and location dependent degradation. This combined operando and multi-scale X-ray computed tomography (CT) technique is demonstrated as a comprehensive approach to understanding battery degradation and failure.

  11. Multiscale multifractal detrended cross-correlation analysis of financial time series

    NASA Astrophysics Data System (ADS)

    Shi, Wenbin; Shang, Pengjian; Wang, Jing; Lin, Aijing

    2014-06-01

    In this paper, we introduce a method called multiscale multifractal detrended cross-correlation analysis (MM-DCCA). The method allows us to extend the description of the cross-correlation properties between two time series. MM-DCCA may provide new ways of measuring the nonlinearity of two signals, and it helps to present much richer information than multifractal detrended cross-correlation analysis (MF-DCCA) by sweeping all the range of scale at which the multifractal structures of complex system are discussed. Moreover, to illustrate the advantages of this approach we make use of the MM-DCCA to analyze the cross-correlation properties between financial time series. We show that this new method can be adapted to investigate stock markets under investigation. It can provide a more faithful and more interpretable description of the dynamic mechanism between financial time series than traditional MF-DCCA. We also propose to reduce the scale ranges to analyze short time series, and some inherent properties which remain hidden when a wide range is used may exhibit perfectly in this way.

  12. Non-equilibrium phase transition in mesoscopic biochemical systems: from stochastic to nonlinear dynamics and beyond

    PubMed Central

    Ge, Hao; Qian, Hong

    2011-01-01

    A theory for an non-equilibrium phase transition in a driven biochemical network is presented. The theory is based on the chemical master equation (CME) formulation of mesoscopic biochemical reactions and the mathematical method of large deviations. The large deviations theory provides an analytical tool connecting the macroscopic multi-stability of an open chemical system with the multi-scale dynamics of its mesoscopic counterpart. It shows a corresponding non-equilibrium phase transition among multiple stochastic attractors. As an example, in the canonical phosphorylation–dephosphorylation system with feedback that exhibits bistability, we show that the non-equilibrium steady-state (NESS) phase transition has all the characteristics of classic equilibrium phase transition: Maxwell construction, a discontinuous first-derivative of the ‘free energy function’, Lee–Yang's zero for a generating function and a critical point that matches the cusp in nonlinear bifurcation theory. To the biochemical system, the mathematical analysis suggests three distinct timescales and needed levels of description. They are (i) molecular signalling, (ii) biochemical network nonlinear dynamics, and (iii) cellular evolution. For finite mesoscopic systems such as a cell, motions associated with (i) and (iii) are stochastic while that with (ii) is deterministic. Both (ii) and (iii) are emergent properties of a dynamic biochemical network. PMID:20466813

  13. Hybrid models for chemical reaction networks: Multiscale theory and application to gene regulatory systems.

    PubMed

    Winkelmann, Stefanie; Schütte, Christof

    2017-09-21

    Well-mixed stochastic chemical kinetics are properly modeled by the chemical master equation (CME) and associated Markov jump processes in molecule number space. If the reactants are present in large amounts, however, corresponding simulations of the stochastic dynamics become computationally expensive and model reductions are demanded. The classical model reduction approach uniformly rescales the overall dynamics to obtain deterministic systems characterized by ordinary differential equations, the well-known mass action reaction rate equations. For systems with multiple scales, there exist hybrid approaches that keep parts of the system discrete while another part is approximated either using Langevin dynamics or deterministically. This paper aims at giving a coherent overview of the different hybrid approaches, focusing on their basic concepts and the relation between them. We derive a novel general description of such hybrid models that allows expressing various forms by one type of equation. We also check in how far the approaches apply to model extensions of the CME for dynamics which do not comply with the central well-mixed condition and require some spatial resolution. A simple but meaningful gene expression system with negative self-regulation is analysed to illustrate the different approximation qualities of some of the hybrid approaches discussed. Especially, we reveal the cause of error in the case of small volume approximations.

  14. Hybrid models for chemical reaction networks: Multiscale theory and application to gene regulatory systems

    NASA Astrophysics Data System (ADS)

    Winkelmann, Stefanie; Schütte, Christof

    2017-09-01

    Well-mixed stochastic chemical kinetics are properly modeled by the chemical master equation (CME) and associated Markov jump processes in molecule number space. If the reactants are present in large amounts, however, corresponding simulations of the stochastic dynamics become computationally expensive and model reductions are demanded. The classical model reduction approach uniformly rescales the overall dynamics to obtain deterministic systems characterized by ordinary differential equations, the well-known mass action reaction rate equations. For systems with multiple scales, there exist hybrid approaches that keep parts of the system discrete while another part is approximated either using Langevin dynamics or deterministically. This paper aims at giving a coherent overview of the different hybrid approaches, focusing on their basic concepts and the relation between them. We derive a novel general description of such hybrid models that allows expressing various forms by one type of equation. We also check in how far the approaches apply to model extensions of the CME for dynamics which do not comply with the central well-mixed condition and require some spatial resolution. A simple but meaningful gene expression system with negative self-regulation is analysed to illustrate the different approximation qualities of some of the hybrid approaches discussed. Especially, we reveal the cause of error in the case of small volume approximations.

  15. Multiscale crystal defect dynamics: A coarse-grained lattice defect model based on crystal microstructure

    NASA Astrophysics Data System (ADS)

    Lyu, Dandan; Li, Shaofan

    2017-10-01

    Crystal defects have microstructure, and this microstructure should be related to the microstructure of the original crystal. Hence each type of crystals may have similar defects due to the same failure mechanism originated from the same microstructure, if they are under the same loading conditions. In this work, we propose a multiscale crystal defect dynamics (MCDD) model that models defects by considering its intrinsic microstructure derived from the microstructure or material genome of the original perfect crystal. The main novelties of present work are: (1) the discrete exterior calculus and algebraic topology theory are used to construct a scale-up (coarse-grained) dual lattice model for crystal defects, which may represent all possible defect modes inside a crystal; (2) a higher order Cauchy-Born rule (up to the fourth order) is adopted to construct atomistic-informed constitutive relations for various defect process zones, and (3) an hierarchical strain gradient theory based finite element formulation is developed to support an hierarchical multiscale cohesive (process) zone model for various defects in a unified formulation. The efficiency of MCDD computational algorithm allows us to simulate dynamic defect evolution at large scale while taking into account atomistic interaction. The MCDD model has been validated by comparing of the results of MCDD simulations with that of molecular dynamics (MD) in the cases of nanoindentation and uniaxial tension. Numerical simulations have shown that MCDD model can predict dislocation nucleation induced instability and inelastic deformation, and thus it may provide an alternative solution to study crystal plasticity.

  16. Experimental investigation of the flow dynamics and rheology of complex fluids in pipe flow by hybrid multi-scale velocimetry

    NASA Astrophysics Data System (ADS)

    Haavisto, Sanna; Cardona, Maria J.; Salmela, Juha; Powell, Robert L.; McCarthy, Michael J.; Kataja, Markku; Koponen, Antti I.

    2017-11-01

    A hybrid multi-scale velocimetry method utilizing Doppler optical coherence tomography in combination with either magnetic resonance imaging or ultrasound velocity profiling is used to investigate pipe flow of four rheologically different working fluids under varying flow regimes. These fluids include water, an aqueous xanthan gum solution, a softwood fiber suspension, and a microfibrillated cellulose suspension. The measurement setup enables not only the analysis of the rheological (bulk) behavior of a studied fluid but gives simultaneously information on their wall layer dynamics, both of which are needed for analyzing and solving practical fluid flow-related problems. Preliminary novel results on rheological and boundary layer flow properties of the working fluids are reported and the potential of the hybrid measurement setup is demonstrated.

  17. Magnetospheric Multiscale Mission Attitude Dynamics: Observations from Flight Data

    NASA Technical Reports Server (NTRS)

    Williams, Trevor; Shulman, Seth; Sedlak, Joseph E.; Ottenstein, Neil; Lounsbury, Brian

    2016-01-01

    The NASA Magnetospheric Multiscale mission, launched on Mar. 12, 2015, is flying four spinning spacecraft in highly elliptical orbits to study the magnetosphere of the Earth. Extensive attitude data is being collected, including spin rate, spin axis orientation, and nutation rate. The paper will discuss the various environmental disturbance torques that act on the spacecraft, and will describe the observed results of these torques. In addition, a slow decay in spin rate has been observed for all four spacecraft in the extended periods between maneuvers. It is shown that this despin is consistent with the effects of an additional disturbance mechanism, namely that produced by the Active Spacecraft Potential Control devices. Finally, attitude dynamics data is used to analyze a micrometeoroid/orbital debris impact event with MMS4 that occurred on Feb. 2, 2016.

  18. Crypt dynamics and colorectal cancer: advances in mathematical modelling.

    PubMed

    van Leeuwen, I M M; Byrne, H M; Jensen, O E; King, J R

    2006-06-01

    Mathematical modelling forms a key component of systems biology, offering insights that complement and stimulate experimental studies. In this review, we illustrate the role of theoretical models in elucidating the mechanisms involved in normal intestinal crypt dynamics and colorectal cancer. We discuss a range of modelling approaches, including models that describe cell proliferation, migration, differentiation, crypt fission, genetic instability, APC inactivation and tumour heterogeneity. We focus on the model assumptions, limitations and applications, rather than on the technical details. We also present a new stochastic model for stem-cell dynamics, which predicts that, on average, APC inactivation occurs more quickly in the stem-cell pool in the absence of symmetric cell division. This suggests that natural niche succession may protect stem cells against malignant transformation in the gut. Finally, we explain how we aim to gain further understanding of the crypt system and of colorectal carcinogenesis with the aid of multiscale models that cover all levels of organization from the molecular to the whole organ.

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

    EPA Science Inventory

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

  20. Taylor-Aris Dispersion: An Explicit Example for Understanding Multiscale Analysis via Volume Averaging

    ERIC Educational Resources Information Center

    Wood, Brian D.

    2009-01-01

    Although the multiscale structure of many important processes in engineering is becoming more widely acknowledged, making this connection in the classroom is a difficult task. This is due in part because the concept of multiscale structure itself is challenging and it requires the students to develop new conceptual pictures of physical systems,…

  1. Thermal nanostructure: An order parameter multiscale ensemble approach

    NASA Astrophysics Data System (ADS)

    Cheluvaraja, S.; Ortoleva, P.

    2010-02-01

    Deductive all-atom multiscale techniques imply that many nanosystems can be understood in terms of the slow dynamics of order parameters that coevolve with the quasiequilibrium probability density for rapidly fluctuating atomic configurations. The result of this multiscale analysis is a set of stochastic equations for the order parameters whose dynamics is driven by thermal-average forces. We present an efficient algorithm for sampling atomistic configurations in viruses and other supramillion atom nanosystems. This algorithm allows for sampling of a wide range of configurations without creating an excess of high-energy, improbable ones. It is implemented and used to calculate thermal-average forces. These forces are then used to search the free-energy landscape of a nanosystem for deep minima. The methodology is applied to thermal structures of Cowpea chlorotic mottle virus capsid. The method has wide applicability to other nanosystems whose properties are described by the CHARMM or other interatomic force field. Our implementation, denoted SIMNANOWORLD™, achieves calibration-free nanosystem modeling. Essential atomic-scale detail is preserved via a quasiequilibrium probability density while overall character is provided via predicted values of order parameters. Applications from virology to the computer-aided design of nanocapsules for delivery of therapeutic agents and of vaccines for nonenveloped viruses are envisioned.

  2. A multi-scale network method for two-phase flow in porous media

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

    Khayrat, Karim, E-mail: khayratk@ifd.mavt.ethz.ch; Jenny, Patrick

    Pore-network models of porous media are useful in the study of pore-scale flow in porous media. In order to extract macroscopic properties from flow simulations in pore-networks, it is crucial the networks are large enough to be considered representative elementary volumes. However, existing two-phase network flow solvers are limited to relatively small domains. For this purpose, a multi-scale pore-network (MSPN) method, which takes into account flow-rate effects and can simulate larger domains compared to existing methods, was developed. In our solution algorithm, a large pore network is partitioned into several smaller sub-networks. The algorithm to advance the fluid interfaces withinmore » each subnetwork consists of three steps. First, a global pressure problem on the network is solved approximately using the multiscale finite volume (MSFV) method. Next, the fluxes across the subnetworks are computed. Lastly, using fluxes as boundary conditions, a dynamic two-phase flow solver is used to advance the solution in time. Simulation results of drainage scenarios at different capillary numbers and unfavourable viscosity ratios are presented and used to validate the MSPN method against solutions obtained by an existing dynamic network flow solver.« less

  3. Nonlinear dynamical systems effects of homeopathic remedies on multiscale entropy and correlation dimension of slow wave sleep EEG in young adults with histories of coffee-induced insomnia.

    PubMed

    Bell, Iris R; Howerter, Amy; Jackson, Nicholas; Aickin, Mikel; Bootzin, Richard R; Brooks, Audrey J

    2012-07-01

    Investigators of homeopathy have proposed that nonlinear dynamical systems (NDS) and complex systems science offer conceptual and analytic tools for evaluating homeopathic remedy effects. Previous animal studies demonstrate that homeopathic medicines alter delta electroencephalographic (EEG) slow wave sleep. The present study extended findings of remedy-related sleep stage alterations in human subjects by testing the feasibility of using two different NDS analytic approaches to assess remedy effects on human slow wave sleep EEG. Subjects (N=54) were young adult male and female college students with a history of coffee-related insomnia who participated in a larger 4-week study of the polysomnographic effects of homeopathic medicines on home-based all-night sleep recordings. Subjects took one bedtime dose of a homeopathic remedy (Coffea cruda or Nux vomica 30c). We computed multiscale entropy (MSE) and the correlation dimension (Mekler-D2) for stages 3 and 4 slow wave sleep EEG sampled in artifact-free 2-min segments during the first two rapid-eye-movement (REM) cycles for remedy and post-remedy nights, controlling for placebo and post-placebo night effects. MSE results indicate significant, remedy-specific directional effects, especially later in the night (REM cycle 2) (CC: remedy night increases and post-remedy night decreases in MSE at multiple sites for both stages 3 and 4 in both REM cycles; NV: remedy night decreases and post-remedy night increases, mainly in stage 3 REM cycle 2 MSE). D2 analyses yielded more sporadic and inconsistent findings. Homeopathic medicines Coffea cruda and Nux vomica in 30c potencies alter short-term nonlinear dynamic parameters of slow wave sleep EEG in healthy young adults. MSE may provide a more sensitive NDS analytic method than D2 for evaluating homeopathic remedy effects on human sleep EEG patterns. Copyright © 2012 The Faculty of Homeopathy. Published by Elsevier Ltd. All rights reserved.

  4. Nonlinear Dynamical Systems Effects of Homeopathic Remedies on Multiscale Entropy and Correlation Dimension of Slow Wave Sleep EEG in Young Adults with Histories of Coffee-Induced Insomnia

    PubMed Central

    Bell, Iris R.; Howerter, Amy; Jackson, Nicholas; Aickin, Mikel; Bootzin, Richard R.; Brooks, Audrey J.

    2012-01-01

    Background Investigators of homeopathy have proposed that nonlinear dynamical systems (NDS) and complex systems science offer conceptual and analytic tools for evaluating homeopathic remedy effects. Previous animal studies demonstrate that homeopathic medicines alter delta electroencephalographic (EEG) slow wave sleep. The present study extended findings of remedy-related sleep stage alterations in human subjects by testing the feasibility of using two different NDS analytic approaches to assess remedy effects on human slow wave sleep EEG. Methods Subjects (N=54) were young adult male and female college students with a history of coffee-related insomnia who participated in a larger 4-week study of the polysomnographic effects of homeopathic medicines on home-based all-night sleep recordings. Subjects took one bedtime dose of a homeopathic remedy (Coffea cruda or Nux vomica 30c). We computed multiscale entropy (MSE) and the correlation dimension (Mekler-D2) for stage 3 and 4 slow wave sleep EEG sampled in artifact-free 2-minute segments during the first two rapid-eye-movement (REM) cycles for remedy and post-remedy nights, controlling for placebo and post-placebo night effects. Results MSE results indicate significant, remedy-specific directional effects, especially later in the night (REM cycle 2) (CC: remedy night increases and post-remedy night decreases in MSE at multiple sites for both stages 3 and 4 in both REM cycles; NV: remedy night decreases and post-remedy night increases, mainly in stage 3 REM cycle 2 MSE). D2 analyses yielded more sporadic and inconsistent findings. Conclusions Homeopathic medicines Coffea cruda and Nux vomica in 30c potencies alter short-term nonlinear dynamic parameters of slow wave sleep EEG in healthy young adults. MSE may provide a more sensitive NDS analytic method than D2 for evaluating homeopathic remedy effects on human sleep EEG patterns. PMID:22818237

  5. Interdisciplinary Modeling and Dynamics of Archipelago Straits

    DTIC Science & Technology

    2009-01-01

    modeling, tidal modeling and multi-dynamics nested domains and non-hydrostatic modeling WORK COMPLETED Realistic Multiscale Simulations, Real-time...six state variables (chlorophyll, nitrate , ammonium, detritus, phytoplankton, and zooplankton) were needed to initialize simulations. Using biological...parameters from literature, climatology from World Ocean Atlas data for nitrate and chlorophyll profiles extracted from satellite data, a first

  6. Dynamic Evaluation of Two Decades of WRF-CMAQ Ozone Simulations over the Contiguous United States (2017 MAC-MAQ Conference Presentation)

    EPA Science Inventory

    Dynamic evaluation of two decades of ozone simulations performed with the fully coupled Weather Research and Forecasting (WRF)–Community Multi-scale Air Quality (CMAQ) model over the contiguous United States is conducted to assess how well the changes in observed ozone air ...

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

    EPA Science Inventory

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

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

    PubMed

    Somvanshi, Pramod Rajaram; Venkatesh, K V

    2014-03-01

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

  9. A multiscale red blood cell model with accurate mechanics, rheology, and dynamics.

    PubMed

    Fedosov, Dmitry A; Caswell, Bruce; Karniadakis, George Em

    2010-05-19

    Red blood cells (RBCs) have highly deformable viscoelastic membranes exhibiting complex rheological response and rich hydrodynamic behavior governed by special elastic and bending properties and by the external/internal fluid and membrane viscosities. We present a multiscale RBC model that is able to predict RBC mechanics, rheology, and dynamics in agreement with experiments. Based on an analytic theory, the modeled membrane properties can be uniquely related to the experimentally established RBC macroscopic properties without any adjustment of parameters. The RBC linear and nonlinear elastic deformations match those obtained in optical-tweezers experiments. The rheological properties of the membrane are compared with those obtained in optical magnetic twisting cytometry, membrane thermal fluctuations, and creep followed by cell recovery. The dynamics of RBCs in shear and Poiseuille flows is tested against experiments and theoretical predictions, and the applicability of the latter is discussed. Our findings clearly indicate that a purely elastic model for the membrane cannot accurately represent the RBC's rheological properties and its dynamics, and therefore accurate modeling of a viscoelastic membrane is necessary. Copyright 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  10. Dynamical glucometry: Use of multiscale entropy analysis in diabetes

    NASA Astrophysics Data System (ADS)

    Costa, Madalena D.; Henriques, Teresa; Munshi, Medha N.; Segal, Alissa R.; Goldberger, Ary L.

    2014-09-01

    Diabetes mellitus (DM) is one of the world's most prevalent medical conditions. Contemporary management focuses on lowering mean blood glucose values toward a normal range, but largely ignores the dynamics of glucose fluctuations. We probed analyte time series obtained from continuous glucose monitor (CGM) sensors. We show that the fluctuations in CGM values sampled every 5 min are not uncorrelated noise. Next, using multiscale entropy analysis, we quantified the complexity of the temporal structure of the CGM time series from a group of elderly subjects with type 2 DM and age-matched controls. We further probed the structure of these CGM time series using detrended fluctuation analysis. Our findings indicate that the dynamics of glucose fluctuations from control subjects are more complex than those of subjects with type 2 DM over time scales ranging from about 5 min to 5 h. These findings support consideration of a new framework, dynamical glucometry, to guide mechanistic research and to help assess and compare therapeutic interventions, which should enhance complexity of glucose fluctuations and not just lower mean and variance of blood glucose levels.

  11. A Multiscale Red Blood Cell Model with Accurate Mechanics, Rheology, and Dynamics

    PubMed Central

    Fedosov, Dmitry A.; Caswell, Bruce; Karniadakis, George Em

    2010-01-01

    Abstract Red blood cells (RBCs) have highly deformable viscoelastic membranes exhibiting complex rheological response and rich hydrodynamic behavior governed by special elastic and bending properties and by the external/internal fluid and membrane viscosities. We present a multiscale RBC model that is able to predict RBC mechanics, rheology, and dynamics in agreement with experiments. Based on an analytic theory, the modeled membrane properties can be uniquely related to the experimentally established RBC macroscopic properties without any adjustment of parameters. The RBC linear and nonlinear elastic deformations match those obtained in optical-tweezers experiments. The rheological properties of the membrane are compared with those obtained in optical magnetic twisting cytometry, membrane thermal fluctuations, and creep followed by cell recovery. The dynamics of RBCs in shear and Poiseuille flows is tested against experiments and theoretical predictions, and the applicability of the latter is discussed. Our findings clearly indicate that a purely elastic model for the membrane cannot accurately represent the RBC's rheological properties and its dynamics, and therefore accurate modeling of a viscoelastic membrane is necessary. PMID:20483330

  12. Blended particle filters for large-dimensional chaotic dynamical systems

    PubMed Central

    Majda, Andrew J.; Qi, Di; Sapsis, Themistoklis P.

    2014-01-01

    A major challenge in contemporary data science is the development of statistically accurate particle filters to capture non-Gaussian features in large-dimensional chaotic dynamical systems. Blended particle filters that capture non-Gaussian features in an adaptively evolving low-dimensional subspace through particles interacting with evolving Gaussian statistics on the remaining portion of phase space are introduced here. These blended particle filters are constructed in this paper through a mathematical formalism involving conditional Gaussian mixtures combined with statistically nonlinear forecast models compatible with this structure developed recently with high skill for uncertainty quantification. Stringent test cases for filtering involving the 40-dimensional Lorenz 96 model with a 5-dimensional adaptive subspace for nonlinear blended filtering in various turbulent regimes with at least nine positive Lyapunov exponents are used here. These cases demonstrate the high skill of the blended particle filter algorithms in capturing both highly non-Gaussian dynamical features as well as crucial nonlinear statistics for accurate filtering in extreme filtering regimes with sparse infrequent high-quality observations. The formalism developed here is also useful for multiscale filtering of turbulent systems and a simple application is sketched below. PMID:24825886

  13. Multi-scale statistical analysis of coronal solar activity

    DOE PAGES

    Gamborino, Diana; del-Castillo-Negrete, Diego; Martinell, Julio J.

    2016-07-08

    Multi-filter images from the solar corona are used to obtain temperature maps that are analyzed using techniques based on proper orthogonal decomposition (POD) in order to extract dynamical and structural information at various scales. Exploring active regions before and after a solar flare and comparing them with quiet regions, we show that the multi-scale behavior presents distinct statistical properties for each case that can be used to characterize the level of activity in a region. Information about the nature of heat transport is also to be extracted from the analysis.

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  15. Homogenization-based interval analysis for structural-acoustic problem involving periodical composites and multi-scale uncertain-but-bounded parameters.

    PubMed

    Chen, Ning; Yu, Dejie; Xia, Baizhan; Liu, Jian; Ma, Zhengdong

    2017-04-01

    This paper presents a homogenization-based interval analysis method for the prediction of coupled structural-acoustic systems involving periodical composites and multi-scale uncertain-but-bounded parameters. In the structural-acoustic system, the macro plate structure is assumed to be composed of a periodically uniform microstructure. The equivalent macro material properties of the microstructure are computed using the homogenization method. By integrating the first-order Taylor expansion interval analysis method with the homogenization-based finite element method, a homogenization-based interval finite element method (HIFEM) is developed to solve a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters. The corresponding formulations of the HIFEM are deduced. A subinterval technique is also introduced into the HIFEM for higher accuracy. Numerical examples of a hexahedral box and an automobile passenger compartment are given to demonstrate the efficiency of the presented method for a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters.

  16. Hybrid Multiscale Simulation of Hydrologic and Biogeochemical Processes in the River-Groundwater Interaction Zone

    NASA Astrophysics Data System (ADS)

    Yang, X.; Scheibe, T. D.; Chen, X.; Hammond, G. E.; Song, X.

    2015-12-01

    The zone in which river water and groundwater mix plays an important role in natural ecosystems as it regulates the mixing of nutrients that control biogeochemical transformations. Subsurface heterogeneity leads to local hotspots of microbial activity that are important to system function yet difficult to resolve computationally. To address this challenge, we are testing a hybrid multiscale approach that couples models at two distinct scales, based on field research at the U. S. Department of Energy's Hanford Site. The region of interest is a 400 x 400 x 20 m macroscale domain that intersects the aquifer and the river and contains a contaminant plume. However, biogeochemical activity is high in a thin zone (mud layer, <1 m thick) immediately adjacent to the river. This microscale domain is highly heterogeneous and requires fine spatial resolution to adequately represent the effects of local mixing on reactions. It is not computationally feasible to resolve the full macroscale domain at the fine resolution needed in the mud layer, and the reaction network needed in the mud layer is much more complex than that needed in the rest of the macroscale domain. Hence, a hybrid multiscale approach is used to efficiently and accurately predict flow and reactive transport at both scales. In our simulations, models at both scales are simulated using the PFLOTRAN code. Multiple microscale simulations in dynamically defined sub-domains (fine resolution, complex reaction network) are executed and coupled with a macroscale simulation over the entire domain (coarse resolution, simpler reaction network). The objectives of the research include: 1) comparing accuracy and computing cost of the hybrid multiscale simulation with a single-scale simulation; 2) identifying hot spots of microbial activity; and 3) defining macroscopic quantities such as fluxes, residence times and effective reaction rates.

  17. Metabolic dynamics in skeletal muscle during acute reduction in blood flow and oxygen supply to mitochondria: in-silico studies using a multi-scale, top-down integrated model.

    PubMed

    Dash, Ranjan K; Li, Yanjun; Kim, Jaeyeon; Beard, Daniel A; Saidel, Gerald M; Cabrera, Marco E

    2008-09-09

    Control mechanisms of cellular metabolism and energetics in skeletal muscle that may become evident in response to physiological stresses such as reduction in blood flow and oxygen supply to mitochondria can be quantitatively understood using a multi-scale computational model. The analysis of dynamic responses from such a model can provide insights into mechanisms of metabolic regulation that may not be evident from experimental studies. For the purpose, a physiologically-based, multi-scale computational model of skeletal muscle cellular metabolism and energetics was developed to describe dynamic responses of key chemical species and reaction fluxes to muscle ischemia. The model, which incorporates key transport and metabolic processes and subcellular compartmentalization, is based on dynamic mass balances of 30 chemical species in both capillary blood and tissue cells (cytosol and mitochondria) domains. The reaction fluxes in cytosol and mitochondria are expressed in terms of a general phenomenological Michaelis-Menten equation involving the compartmentalized energy controller ratios ATP/ADP and NADH/NAD(+). The unknown transport and reaction parameters in the model are estimated simultaneously by minimizing the differences between available in vivo experimental data on muscle ischemia and corresponding model outputs in coupled with the resting linear flux balance constraints using a robust, nonlinear, constrained-based, reduced gradient optimization algorithm. With the optimal parameter values, the model is able to simulate dynamic responses to reduced blood flow and oxygen supply to mitochondria associated with muscle ischemia of several key metabolite concentrations and metabolic fluxes in the subcellular cytosolic and mitochondrial compartments, some that can be measured and others that can not be measured with the current experimental techniques. The model can be applied to test complex hypotheses involving dynamic regulation of cellular metabolism and energetics in skeletal muscle during physiological stresses such as ischemia, hypoxia, and exercise.

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

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

    None

    2011-01-01

    Multi-scale modeling of arterial blood flow can shed light on the interaction between events happening at micro- and meso-scales (i.e., adhesion of red blood cells to the arterial wall, clot formation) and at macro-scales (i.e., change in flow patterns due to the clot). Coupled numerical simulations of such multi-scale flow require state-of-the-art computers and algorithms, along with techniques for multi-scale visualizations. This animation presents early results of two studies used in the development of a multi-scale visualization methodology. The fisrt illustrates a flow of healthy (red) and diseased (blue) blood cells with a Dissipative Particle Dynamics (DPD) method. Each bloodmore » cell is represented by a mesh, small spheres show a sub-set of particles representing the blood plasma, while instantaneous streamlines and slices represent the ensemble average velocity. In the second we investigate the process of thrombus (blood clot) formation, which may be responsible for the rupture of aneurysms, by concentrating on the platelet blood cells, observing as they aggregate on the wall of an aneruysm. Simulation was performed on Kraken at the National Institute for Computational Sciences. Visualization was produced using resources of the Argonne Leadership Computing Facility at Argonne National Laboratory.« less

  19. Multi-scale coupled modelling of waves and currents on the Catalan shelf.

    NASA Astrophysics Data System (ADS)

    Grifoll, M.; Warner, J. C.; Espino, M.; Sánchez-Arcilla, A.

    2012-04-01

    Catalan shelf circulation is characterized by a background along-shelf flow to the southwest (including some meso-scale features) plus episodic storm driven patterns. To investigate these dynamics, a coupled multi-scale modeling system is applied to the Catalan shelf (North-western Mediterranean Sea). The implementation consists of a set of increasing-resolution nested models, based on the circulation model ROMS and the wave model SWAN as part of the COAWST modeling system, covering from the slope and shelf region (~1 km horizontal resolution) down to a local area around Barcelona city (~40 m). The system is initialized with MyOcean products in the coarsest outer domain, and uses atmospheric forcing from other sources for the increasing resolution inner domains. Results of the finer resolution domains exhibit improved agreement with observations relative to the coarser model results. Several hydrodynamic configurations were simulated to determine dominant forcing mechanisms and hydrodynamic processes that control coastal scale processes. The numerical results reveal that the short term (hours to days) inner-shelf variability is strongly influenced by local wind variability, while sea-level slope, baroclinic effects, radiation stresses and regional circulation constitute second-order processes. Additional analysis identifies the significance of shelf/slope exchange fluxes, river discharge and the effect of the spatial resolution of the atmospheric fluxes.

  20. Multiscale integral analysis of a HT leakage in a fusion nuclear power plant

    NASA Astrophysics Data System (ADS)

    Velarde, M.; Fradera, J.; Perlado, J. M.; Zamora, I.; Martínez-Saban, E.; Colomer, C.; Briani, P.

    2016-05-01

    The present work presents an example of the application of an integral methodology based on a multiscale analysis that covers the whole tritium cycle within a nuclear fusion power plant, from a micro scale, analyzing key components where tritium is leaked through permeation, to a macro scale, considering its atmospheric transport. A leakage from the Nuclear Power Plants, (NPP) primary to the secondary side of a heat exchanger (HEX) is considered for the present example. Both primary and secondary loop coolants are assumed to be He. Leakage is placed inside the HEX, leaking tritium in elementary tritium (HT) form to the secondary loop where it permeates through the piping structural material to the exterior. The Heating Ventilation and Air Conditioning (HVAC) system removes the leaked tritium towards the NPP exhaust. The HEX is modelled with system codes and coupled to Computational Fluid Dynamic (CFD) to account for tritium dispersion inside the nuclear power plants buildings and in site environment. Finally, tritium dispersion is calculated with an atmospheric transport code and a dosimetry analysis is carried out. Results show how the implemented methodology is capable of assessing the impact of tritium from the microscale to the atmospheric scale including the dosimetric aspect.

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

    Chacón, L., E-mail: chacon@lanl.gov; Chen, G.; Knoll, D.A.

    We review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLOmore » approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.« less

  2. The social context of carbon sequestration: considerations from a multi-scale environmental history of the Old Peanut Basin of Senegal

    USGS Publications Warehouse

    Tschakert, P.; Tappan, G.

    2004-01-01

    This paper presents the results of a multi-scale investigation of environmental change in the Old Peanut Basin of Senegal throughout the 20th century. Based on historical accounts, ethnographies, aerial photos, satellite images, field and household surveys as well as various participatory research activities with farmers in selected villages, the study attempts to make explicit layered scales of analysis, both temporally and spatially. It shows that, despite some general trends of resource degradation in the Old Peanut Basin, local farming systems have embarked on different pathways of change to adapt to their evolving environment. It also illustrates that high diversity with respect to soil fertility management exists at the farm and household level. Finally, the paper proposes a farmer-oriented approach to carbon sequestration in order to integrate recommended technical options more efficiently into the complex and dynamic livelihoods of smallholders in dryland environments. This approach includes pathway-specific land use and management options at the level of farming systems and, at the level of individual households, a basket of possible practices from which farmers can choose depending on their multiple needs, capacities, and adaptive strategies to cope with risk and uncertainty.

  3. Kalman Filter for Mass Property and Thrust Identification (MMS)

    NASA Technical Reports Server (NTRS)

    Queen, Steven

    2015-01-01

    The Magnetospheric Multiscale (MMS) mission consists of four identically instrumented, spin-stabilized observatories, elliptically orbiting the Earth in a tetrahedron formation. For the operational success of the mission, on-board systems must be able to deliver high-precision orbital adjustment maneuvers. On MMS, this is accomplished using feedback from on-board star sensors in tandem with accelerometers whose measurements are dynamically corrected for errors associated with a spinning platform. In order to determine the required corrections to the measured acceleration, precise estimates of attitude, rate, and mass-properties is necessary. To this end, both an on-board and ground-based Multiplicative Extended Kalman Filter (MEKF) were formulated and implemented in order to estimate the dynamic and quasi-static properties of the spacecraft.

  4. Progression to multi-scale models and the application to food system intervention strategies.

    PubMed

    Gröhn, Yrjö T

    2015-02-01

    The aim of this article is to discuss how the systems science approach can be used to optimize intervention strategies in food animal systems. It advocates the idea that the challenges of maintaining a safe food supply are best addressed by integrating modeling and mathematics with biological studies critical to formulation of public policy to address these challenges. Much information on the biology and epidemiology of food animal systems has been characterized through single-discipline methods, but until now this information has not been thoroughly utilized in a fully integrated manner. The examples are drawn from our current research. The first, explained in depth, uses clinical mastitis to introduce the concept of dynamic programming to optimize management decisions in dairy cows (also introducing the curse of dimensionality problem). In the second example, a compartmental epidemic model for Johne's disease with different intervention strategies is optimized. The goal of the optimization strategy depends on whether there is a relationship between Johne's and Crohn's disease. If so, optimization is based on eradication of infection; if not, it is based on the cow's performance only (i.e., economic optimization, similar to the mastitis example). The third example focuses on food safety to introduce risk assessment using Listeria monocytogenes and Salmonella Typhimurium. The last example, practical interventions to effectively manage antibiotic resistance in beef and dairy cattle systems, introduces meta-population modeling that accounts for bacterial growth not only in the host (cow), but also in the cow's feed, drinking water and the housing environment. Each example stresses the need to progress toward multi-scale modeling. The article ends with examples of multi-scale systems, from food supply systems to Johne's disease. Reducing the consequences of foodborne illnesses (i.e., minimizing disease occurrence and associated costs) can only occur through an understanding of the system as a whole, including all its complexities. Thus the goal of future research should be to merge disciplines such as molecular biology, applied mathematics and social sciences to gain a better understanding of complex systems such as the food supply chain. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen

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

    Plechac, Petr

    2016-03-01

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

  6. Internal Coordinate Molecular Dynamics: A Foundation for Multiscale Dynamics

    PubMed Central

    2015-01-01

    Internal coordinates such as bond lengths, bond angles, and torsion angles (BAT) are natural coordinates for describing a bonded molecular system. However, the molecular dynamics (MD) simulation methods that are widely used for proteins, DNA, and polymers are based on Cartesian coordinates owing to the mathematical simplicity of the equations of motion. However, constraints are often needed with Cartesian MD simulations to enhance the conformational sampling. This makes the equations of motion in the Cartesian coordinates differential-algebraic, which adversely impacts the complexity and the robustness of the simulations. On the other hand, constraints can be easily placed in BAT coordinates by removing the degrees of freedom that need to be constrained. Thus, the internal coordinate MD (ICMD) offers an attractive alternative to Cartesian coordinate MD for developing multiscale MD method. The torsional MD method is a special adaptation of the ICMD method, where all the bond lengths and bond angles are kept rigid. The advantages of ICMD simulation methods are the longer time step size afforded by freezing high frequency degrees of freedom and performing a conformational search in the more important low frequency torsional degrees of freedom. However, the advancements in the ICMD simulations have been slow and stifled by long-standing mathematical bottlenecks. In this review, we summarize the recent mathematical advancements we have made based on spatial operator algebra, in developing a robust long time scale ICMD simulation toolkit useful for various applications. We also present the applications of ICMD simulations to study conformational changes in proteins and protein structure refinement. We review the advantages of the ICMD simulations over the Cartesian simulations when used with enhanced sampling methods and project the future use of ICMD simulations in protein dynamics. PMID:25517406

  7. Efficient Integration of Coupled Electrical-Chemical Systems in Multiscale Neuronal Simulations

    PubMed Central

    Brocke, Ekaterina; Bhalla, Upinder S.; Djurfeldt, Mikael; Hellgren Kotaleski, Jeanette; Hanke, Michael

    2016-01-01

    Multiscale modeling and simulations in neuroscience is gaining scientific attention due to its growing importance and unexplored capabilities. For instance, it can help to acquire better understanding of biological phenomena that have important features at multiple scales of time and space. This includes synaptic plasticity, memory formation and modulation, homeostasis. There are several ways to organize multiscale simulations depending on the scientific problem and the system to be modeled. One of the possibilities is to simulate different components of a multiscale system simultaneously and exchange data when required. The latter may become a challenging task for several reasons. First, the components of a multiscale system usually span different spatial and temporal scales, such that rigorous analysis of possible coupling solutions is required. Then, the components can be defined by different mathematical formalisms. For certain classes of problems a number of coupling mechanisms have been proposed and successfully used. However, a strict mathematical theory is missing in many cases. Recent work in the field has not so far investigated artifacts that may arise during coupled integration of different approximation methods. Moreover, in neuroscience, the coupling of widely used numerical fixed step size solvers may lead to unexpected inefficiency. In this paper we address the question of possible numerical artifacts that can arise during the integration of a coupled system. We develop an efficient strategy to couple the components comprising a multiscale test problem in neuroscience. We introduce an efficient coupling method based on the second-order backward differentiation formula (BDF2) numerical approximation. The method uses an adaptive step size integration with an error estimation proposed by Skelboe (2000). The method shows a significant advantage over conventional fixed step size solvers used in neuroscience for similar problems. We explore different coupling strategies that define the organization of computations between system components. We study the importance of an appropriate approximation of exchanged variables during the simulation. The analysis shows a substantial impact of these aspects on the solution accuracy in the application to our multiscale neuroscientific test problem. We believe that the ideas presented in the paper may essentially contribute to the development of a robust and efficient framework for multiscale brain modeling and simulations in neuroscience. PMID:27672364

  8. Efficient Integration of Coupled Electrical-Chemical Systems in Multiscale Neuronal Simulations.

    PubMed

    Brocke, Ekaterina; Bhalla, Upinder S; Djurfeldt, Mikael; Hellgren Kotaleski, Jeanette; Hanke, Michael

    2016-01-01

    Multiscale modeling and simulations in neuroscience is gaining scientific attention due to its growing importance and unexplored capabilities. For instance, it can help to acquire better understanding of biological phenomena that have important features at multiple scales of time and space. This includes synaptic plasticity, memory formation and modulation, homeostasis. There are several ways to organize multiscale simulations depending on the scientific problem and the system to be modeled. One of the possibilities is to simulate different components of a multiscale system simultaneously and exchange data when required. The latter may become a challenging task for several reasons. First, the components of a multiscale system usually span different spatial and temporal scales, such that rigorous analysis of possible coupling solutions is required. Then, the components can be defined by different mathematical formalisms. For certain classes of problems a number of coupling mechanisms have been proposed and successfully used. However, a strict mathematical theory is missing in many cases. Recent work in the field has not so far investigated artifacts that may arise during coupled integration of different approximation methods. Moreover, in neuroscience, the coupling of widely used numerical fixed step size solvers may lead to unexpected inefficiency. In this paper we address the question of possible numerical artifacts that can arise during the integration of a coupled system. We develop an efficient strategy to couple the components comprising a multiscale test problem in neuroscience. We introduce an efficient coupling method based on the second-order backward differentiation formula (BDF2) numerical approximation. The method uses an adaptive step size integration with an error estimation proposed by Skelboe (2000). The method shows a significant advantage over conventional fixed step size solvers used in neuroscience for similar problems. We explore different coupling strategies that define the organization of computations between system components. We study the importance of an appropriate approximation of exchanged variables during the simulation. The analysis shows a substantial impact of these aspects on the solution accuracy in the application to our multiscale neuroscientific test problem. We believe that the ideas presented in the paper may essentially contribute to the development of a robust and efficient framework for multiscale brain modeling and simulations in neuroscience.

  9. Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen

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

    Plechac, Petr; Vlachos, Dionisios; Katsoulakis, Markos

    2013-09-05

    The overall objective of this project is to develop multiscale models for understanding and eventually designing complex processes for renewables. To the best of our knowledge, our work is the first attempt at modeling complex reacting systems, whose performance relies on underlying multiscale mathematics. Our specific application lies at the heart of biofuels initiatives of DOE and entails modeling of catalytic systems, to enable economic, environmentally benign, and efficient conversion of biomass into either hydrogen or valuable chemicals. Specific goals include: (i) Development of rigorous spatio-temporal coarse-grained kinetic Monte Carlo (KMC) mathematics and simulation for microscopic processes encountered in biomassmore » transformation. (ii) Development of hybrid multiscale simulation that links stochastic simulation to a deterministic partial differential equation (PDE) model for an entire reactor. (iii) Development of hybrid multiscale simulation that links KMC simulation with quantum density functional theory (DFT) calculations. (iv) Development of parallelization of models of (i)-(iii) to take advantage of Petaflop computing and enable real world applications of complex, multiscale models. In this NCE period, we continued addressing these objectives and completed the proposed work. Main initiatives, key results, and activities are outlined.« less

  10. A fast solver for the Helmholtz equation based on the generalized multiscale finite-element method

    NASA Astrophysics Data System (ADS)

    Fu, Shubin; Gao, Kai

    2017-11-01

    Conventional finite-element methods for solving the acoustic-wave Helmholtz equation in highly heterogeneous media usually require finely discretized mesh to represent the medium property variations with sufficient accuracy. Computational costs for solving the Helmholtz equation can therefore be considerably expensive for complicated and large geological models. Based on the generalized multiscale finite-element theory, we develop a novel continuous Galerkin method to solve the Helmholtz equation in acoustic media with spatially variable velocity and mass density. Instead of using conventional polynomial basis functions, we use multiscale basis functions to form the approximation space on the coarse mesh. The multiscale basis functions are obtained from multiplying the eigenfunctions of a carefully designed local spectral problem with an appropriate multiscale partition of unity. These multiscale basis functions can effectively incorporate the characteristics of heterogeneous media's fine-scale variations, thus enable us to obtain accurate solution to the Helmholtz equation without directly solving the large discrete system formed on the fine mesh. Numerical results show that our new solver can significantly reduce the dimension of the discrete Helmholtz equation system, and can also obviously reduce the computational time.

  11. 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.

  12. Multi-scale symbolic transfer entropy analysis of EEG

    NASA Astrophysics Data System (ADS)

    Yao, Wenpo; Wang, Jun

    2017-10-01

    From both global and local perspectives, we symbolize two kinds of EEG and analyze their dynamic and asymmetrical information using multi-scale transfer entropy. Multi-scale process with scale factor from 1 to 199 and step size of 2 is applied to EEG of healthy people and epileptic patients, and then the permutation with embedding dimension of 3 and global approach are used to symbolize the sequences. The forward and reverse symbol sequences are taken as the inputs of transfer entropy. Scale factor intervals of permutation and global way are (37, 57) and (65, 85) where the two kinds of EEG have satisfied entropy distinctions. When scale factor is 67, transfer entropy of the healthy and epileptic subjects of permutation, 0.1137 and 0.1028, have biggest difference. And the corresponding values of the global symbolization is 0.0641 and 0.0601 which lies in the scale factor of 165. Research results show that permutation which takes contribution of local information has better distinction and is more effectively applied to our multi-scale transfer entropy analysis of EEG.

  13. Tracking Virus Particles in Fluorescence Microscopy Images Using Multi-Scale Detection and Multi-Frame Association.

    PubMed

    Jaiswal, Astha; Godinez, William J; Eils, Roland; Lehmann, Maik Jorg; Rohr, Karl

    2015-11-01

    Automatic fluorescent particle tracking is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a probabilistic particle tracking approach based on multi-scale detection and two-step multi-frame association. The multi-scale detection scheme allows coping with particles in close proximity. For finding associations, we have developed a two-step multi-frame algorithm, which is based on a temporally semiglobal formulation as well as spatially local and global optimization. In the first step, reliable associations are determined for each particle individually in local neighborhoods. In the second step, the global spatial information over multiple frames is exploited jointly to determine optimal associations. The multi-scale detection scheme and the multi-frame association finding algorithm have been combined with a probabilistic tracking approach based on the Kalman filter. We have successfully applied our probabilistic tracking approach to synthetic as well as real microscopy image sequences of virus particles and quantified the performance. We found that the proposed approach outperforms previous approaches.

  14. 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.

  15. 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.

  16. Integrated multiscale biomaterials experiment and modelling: a perspective

    PubMed Central

    Buehler, Markus J.; Genin, Guy M.

    2016-01-01

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

  17. Perceptual suppression revealed by adaptive multi-scale entropy analysis of local field potential in monkey visual cortex.

    PubMed

    Hu, Meng; Liang, Hualou

    2013-04-01

    Generalized flash suppression (GFS), in which a salient visual stimulus can be rendered invisible despite continuous retinal input, provides a rare opportunity to directly study the neural mechanism of visual perception. Previous work based on linear methods, such as spectral analysis, on local field potential (LFP) during GFS has shown that the LFP power at distinctive frequency bands are differentially modulated by perceptual suppression. Yet, the linear method alone may be insufficient for the full assessment of neural dynamic due to the fundamentally nonlinear nature of neural signals. In this study, we set forth to analyze the LFP data collected from multiple visual areas in V1, V2 and V4 of macaque monkeys while performing the GFS task using a nonlinear method - adaptive multi-scale entropy (AME) - to reveal the neural dynamic of perceptual suppression. In addition, we propose a new cross-entropy measure at multiple scales, namely adaptive multi-scale cross-entropy (AMCE), to assess the nonlinear functional connectivity between two cortical areas. We show that: (1) multi-scale entropy exhibits percept-related changes in all three areas, with higher entropy observed during perceptual suppression; (2) the magnitude of the perception-related entropy changes increases systematically over successive hierarchical stages (i.e. from lower areas V1 to V2, up to higher area V4); and (3) cross-entropy between any two cortical areas reveals higher degree of asynchrony or dissimilarity during perceptual suppression, indicating a decreased functional connectivity between cortical areas. These results, taken together, suggest that perceptual suppression is related to a reduced functional connectivity and increased uncertainty of neural responses, and the modulation of perceptual suppression is more effective at higher visual cortical areas. AME is demonstrated to be a useful technique in revealing the underlying dynamic of nonlinear/nonstationary neural signal.

  18. Neuromorphic meets neuromechanics, part I: the methodology and implementation

    NASA Astrophysics Data System (ADS)

    Niu, Chuanxin M.; Jalaleddini, Kian; Sohn, Won Joon; Rocamora, John; Sanger, Terence D.; Valero-Cuevas, Francisco J.

    2017-04-01

    Objective: One goal of neuromorphic engineering is to create ‘realistic’ robotic systems that interact with the physical world by adopting neuromechanical principles from biology. Critical to this is the methodology to implement the spinal circuitry responsible for the behavior of afferented muscles. At its core, muscle afferentation is the closed-loop behavior arising from the interactions among populations of muscle spindle afferents, alpha and gamma motoneurons, and muscle fibers to enable useful behaviors. Approach. We used programmable very- large-scale-circuit (VLSI) hardware to implement simple models of spiking neurons, skeletal muscles, muscle spindle proprioceptors, alpha-motoneuron recruitment, gamma motoneuron control of spindle sensitivity, and the monosynaptic circuitry connecting them. This multi-scale system of populations of spiking neurons emulated the physiological properties of a pair of antagonistic afferented mammalian muscles (each simulated by 1024 alpha- and gamma-motoneurones) acting on a joint via long tendons. Main results. This integrated system was able to maintain a joint angle, and reproduced stretch reflex responses even when driving the nonlinear biomechanics of an actual cadaveric finger. Moreover, this system allowed us to explore numerous values and combinations of gamma-static and gamma-dynamic gains when driving a robotic finger, some of which replicated some human pathological conditions. Lastly, we explored the behavioral consequences of adopting three alternative models of isometric muscle force production. We found that the dynamic responses to rate-coded spike trains produce force ramps that can be very sensitive to tendon elasticity, especially at high force output. Significance. Our methodology produced, to our knowledge, the first example of an autonomous, multi-scale, neuromorphic, neuromechanical system capable of creating realistic reflex behavior in cadaveric fingers. This research platform allows us to explore the mechanisms behind healthy and pathological sensorimotor function in the physical world by building them from first principles, and it is a precursor to neuromorphic robotic systems.

  19. Variational multiscale models for charge transport.

    PubMed

    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 for chemo-electro-fluid systems. A number of computational algorithms is developed to implement the proposed new variational multiscale models in an efficient manner. A set of ten protein molecules and a realistic ion channel, Gramicidin A, are employed to confirm the consistency and verify the capability. Extensive numerical experiment is designed to validate the proposed variational multiscale models. A good quantitative agreement between our model prediction and the experimental measurement of current-voltage curves is observed for the Gramicidin A channel transport. This paper also provides a brief review of the field.

  20. 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 for chemo-electro-fluid systems. A number of computational algorithms is developed to implement the proposed new variational multiscale models in an efficient manner. A set of ten protein molecules and a realistic ion channel, Gramicidin A, are employed to confirm the consistency and verify the capability. Extensive numerical experiment is designed to validate the proposed variational multiscale models. A good quantitative agreement between our model prediction and the experimental measurement of current-voltage curves is observed for the Gramicidin A channel transport. This paper also provides a brief review of the field. PMID:23172978

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

    PubMed

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

    2011-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  3. Logical Interactions in AN Expanded Space

    NASA Astrophysics Data System (ADS)

    Tadić, Bosiljka

    Understanding the emergent behavior in many complex systems in the physical world and society requires a detailed study of dynamical phenomena occurring and mutually coupled at different scales. The brain processes underlying the social conduct of each, and the emergent social behavior of interacting individuals on a larger scale, represent striking examples of the multiscale complexity. Studies of the human brain, a paradigm of a complex functional system, are enabled by a wealth of brain imaging data that provide clues of how we comprehend space, time, languages, numbers, and differentiate normal from diseased individuals, for example. The social brain, a neural basis for social cognition, represents a dynamically organized part of the brain which is involved in the inference of thoughts, feelings, and intentions going on in the brains of others. Research in this currently unexplored area opens a new perspective on the genesis of the societal organization at different levels and the associated social values...

  4. deltaGseg: macrostate estimation via molecular dynamics simulations and multiscale time series analysis.

    PubMed

    Low, Diana H P; Motakis, Efthymios

    2013-10-01

    Binding free energy calculations obtained through molecular dynamics simulations reflect intermolecular interaction states through a series of independent snapshots. Typically, the free energies of multiple simulated series (each with slightly different starting conditions) need to be estimated. Previous approaches carry out this task by moving averages at certain decorrelation times, assuming that the system comes from a single conformation description of binding events. Here, we discuss a more general approach that uses statistical modeling, wavelets denoising and hierarchical clustering to estimate the significance of multiple statistically distinct subpopulations, reflecting potential macrostates of the system. We present the deltaGseg R package that performs macrostate estimation from multiple replicated series and allows molecular biologists/chemists to gain physical insight into the molecular details that are not easily accessible by experimental techniques. deltaGseg is a Bioconductor R package available at http://bioconductor.org/packages/release/bioc/html/deltaGseg.html.

  5. Money circulation networks reveal emerging geographical communities

    NASA Astrophysics Data System (ADS)

    Brockmann, D.; Theis, F.; David, V.

    2008-03-01

    Geographical communities and their boundaries are key determinants of various spatially extended dynamical phenomena. Examples are migration dynamics of species, the spread of infectious diseases, bioinvasive processes, and the spatial evolution of language. We address the question to what extend multiscale human transportation networks encode geographical community structures, how they differ from geopolitical classifications, whether they are spatially coherent, and analyse their structure as a function of length scale. Our analysis is based on a proxy network for human transportation obtained from the geographic circulation of more than 10 million dollar bills in the United States recorded at the bill tracking website www.wheresgeorge.com. The data extends that of a previous study (Brockmann et al., Nature 2006) on the discovery of scaling laws of human travel by an order of magnitude and permits an approach to multiscale human transportation from a network perspective.

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

    EPA Science Inventory

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

  7. 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...

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

    EPA Science Inventory

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

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

    PubMed

    Boras, Britton W; Hirakis, Sophia P; Votapka, Lane W; Malmstrom, Robert D; Amaro, Rommie E; McCulloch, Andrew D

    2015-01-01

    The goal of multiscale modeling in biology is to use structurally based physico-chemical models to integrate across temporal and spatial scales of biology and thereby improve mechanistic understanding of, for example, how a single mutation can alter organism-scale phenotypes. This approach may also inform therapeutic strategies or identify candidate drug targets that might otherwise have been overlooked. However, in many cases, it remains unclear how best to synthesize information obtained from various scales and analysis approaches, such as atomistic molecular models, Markov state models (MSM), subcellular network models, and whole cell models. In this paper, we use protein kinase A (PKA) activation as a case study to explore how computational methods that model different physical scales can complement each other and integrate into an improved multiscale representation of the biological mechanisms. Using measured crystal structures, we show how molecular dynamics (MD) simulations coupled with atomic-scale MSMs can provide conformations for Brownian dynamics (BD) simulations to feed transitional states and kinetic parameters into protein-scale MSMs. We discuss how milestoning can give reaction probabilities and forward-rate constants of cAMP association events by seamlessly integrating MD and BD simulation scales. These rate constants coupled with MSMs provide a robust representation of the free energy landscape, enabling access to kinetic, and thermodynamic parameters unavailable from current experimental data. These approaches have helped to illuminate the cooperative nature of PKA activation in response to distinct cAMP binding events. Collectively, this approach exemplifies a general strategy for multiscale model development that is applicable to a wide range of biological problems.

  10. Microtubule-based nanomaterials: Exploiting nature's dynamic biopolymers

    DOE PAGES

    Bachand, George D.; Stevens, Mark J.; Spoerke, Erik David

    2015-04-09

    For more than a decade now, biomolecular systems have served as an inspiration for the development of synthetic nanomaterials and systems that are capable of reproducing many of unique and emergent behaviors of living systems. In addition, one intriguing element of such systems may be found in a specialized class of proteins known as biomolecular motors that are capable of performing useful work across multiple length scales through the efficient conversion of chemical energy. Microtubule (MT) filaments may be considered within this context as their dynamic assembly and disassembly dissipate energy, and perform work within the cell. MTs are onemore » of three cytoskeletal filaments in eukaryotic cells, and play critical roles in a range of cellular processes including mitosis and vesicular trafficking. Based on their function, physical attributes, and unique dynamics, MTs also serve as a powerful archetype of a supramolecular filament that underlies and drives multiscale emergent behaviors. In this review, we briefly summarize recent efforts to generate hybrid and composite nanomaterials using MTs as biomolecular scaffolds, as well as computational and synthetic approaches to develop synthetic one-dimensional nanostructures that display the enviable attributes of the natural filaments.« less

  11. Development of fine-resolution analyses and expanded large-scale forcing properties. Part II: Scale-awareness and application to single-column model experiments

    DOE PAGES

    Feng, Sha; Vogelmann, Andrew M.; Li, Zhijin; ...

    2015-01-20

    Fine-resolution three-dimensional fields have been produced using the Community Gridpoint Statistical Interpolation (GSI) data assimilation system for the U.S. Department of Energy’s Atmospheric Radiation Measurement Program (ARM) Southern Great Plains region. The GSI system is implemented in a multi-scale data assimilation framework using the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. From the fine-resolution three-dimensional fields, large-scale forcing is derived explicitly at grid-scale resolution; a subgrid-scale dynamic component is derived separately, representing subgrid-scale horizontal dynamic processes. Analyses show that the subgrid-scale dynamic component is often a major component over the large-scale forcing for grid scalesmore » larger than 200 km. The single-column model (SCM) of the Community Atmospheric Model version 5 (CAM5) is used to examine the impact of the grid-scale and subgrid-scale dynamic components on simulated precipitation and cloud fields associated with a mesoscale convective system. It is found that grid-scale size impacts simulated precipitation, resulting in an overestimation for grid scales of about 200 km but an underestimation for smaller grids. The subgrid-scale dynamic component has an appreciable impact on the simulations, suggesting that grid-scale and subgrid-scale dynamic components should be considered in the interpretation of SCM simulations.« less

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

    DTIC Science & Technology

    2011-04-09

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

  13. 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

  14. Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.

    PubMed

    Biggs, Matthew B; Papin, Jason A

    2013-01-01

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

  15. From microjoules to megajoules and kilobars to gigabars: probing matter at extreme states of deformation

    NASA Astrophysics Data System (ADS)

    Remington, Bruce A.

    2014-10-01

    Over the past 3 decades there has been an exponential increase in the newly emerging field of matter at extreme states of deformation and compression. This has been due to the confluence of new experimental facilities, new experimental techniques, new theory, and new multiscale simulation techniques. Regimes of science and research hitherto thought out of reach in terrestrial settings are now being accessed routinely. High energy lasers and pulsed power facilities are accessing high pressure macroscopic states of matter, and next generation light sources combined with smaller drive lasers are probing the quantum response of matter at the atomistic level. Combined, this gives multiscale experimental access of the properties and dynamics of matter from femtoseconds to microseconds and from kilobars to gigabars of pressure. There are a multitude of new regimes of science and research that these new developments make possible. Examples include planetary formation dynamics, asteroid and meteor impact dynamics, space hardware response to hypervelocity interplanetary dust impacts, reactor component response to prolonged exposure to radiation damage, advanced research into light weight armor, and capsule dynamics in inertial confinement fusion (ICF). I will review highlights and advances in this rapidly developing field of science and research, touching on experiments at a wide range of facilities (NIF, Z, Omega, Jupiter, Trident, Vulcan, Orion, LULI, LIL, Gekko, Shenguang, LCLS, DCS). I will also review a wide variety of sophisticated new experimental techniques being developed and new developments in theory and multiscale modeling. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

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

    NASA Astrophysics Data System (ADS)

    Tao, W. K.

    2017-12-01

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

  17. Computational and experimental single cell biology techniques for the definition of cell type heterogeneity, interplay and intracellular dynamics.

    PubMed

    de Vargas Roditi, Laura; Claassen, Manfred

    2015-08-01

    Novel technological developments enable single cell population profiling with respect to their spatial and molecular setup. These include single cell sequencing, flow cytometry and multiparametric imaging approaches and open unprecedented possibilities to learn about the heterogeneity, dynamics and interplay of the different cell types which constitute tissues and multicellular organisms. Statistical and dynamic systems theory approaches have been applied to quantitatively describe a variety of cellular processes, such as transcription and cell signaling. Machine learning approaches have been developed to define cell types, their mutual relationships, and differentiation hierarchies shaping heterogeneous cell populations, yielding insights into topics such as, for example, immune cell differentiation and tumor cell type composition. This combination of experimental and computational advances has opened perspectives towards learning predictive multi-scale models of heterogeneous cell populations. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. A Parallel, Multi-Scale Watershed-Hydrologic-Inundation Model with Adaptively Switching Mesh for Capturing Flooding and Lake Dynamics

    NASA Astrophysics Data System (ADS)

    Ji, X.; Shen, C.

    2017-12-01

    Flood inundation presents substantial societal hazards and also changes biogeochemistry for systems like the Amazon. It is often expensive to simulate high-resolution flood inundation and propagation in a long-term watershed-scale model. Due to the Courant-Friedrichs-Lewy (CFL) restriction, high resolution and large local flow velocity both demand prohibitively small time steps even for parallel codes. Here we develop a parallel surface-subsurface process-based model enhanced by multi-resolution meshes that are adaptively switched on or off. The high-resolution overland flow meshes are enabled only when the flood wave invades to floodplains. This model applies semi-implicit, semi-Lagrangian (SISL) scheme in solving dynamic wave equations, and with the assistant of the multi-mesh method, it also adaptively chooses the dynamic wave equation only in the area of deep inundation. Therefore, the model achieves a balance between accuracy and computational cost.

  19. The Center for Multiscale Plasma Dynamics, Final Report

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

    Gombosi, Tamas I.

    The University of Michigan participated in the joint UCLA/Maryland fusion science center focused on plasma physics problems for which the traditional separation of the dynamics into microscale and macroscale processes breaks down. These processes involve large scale flows and magnetic fields tightly coupled to the small scale, kinetic dynamics of turbulence, particle acceleration and energy cascade. The interaction between these vastly disparate scales controls the evolution of the system. The enormous range of temporal and spatial scales associated with these problems renders direct simulation intractable even in computations that use the largest existing parallel computers. Our efforts focused on twomore » main problems: the development of Hall MHD solvers on solution adaptive grids and the development of solution adaptive grids using generalized coordinates so that the proper geometry of inertial confinement can be taken into account and efficient refinement strategies can be obtained.« less

  20. Elastic Multi-scale Mechanisms: Computation and Biological Evolution.

    PubMed

    Diaz Ochoa, Juan G

    2018-01-01

    Explanations based on low-level interacting elements are valuable and powerful since they contribute to identify the key mechanisms of biological functions. However, many dynamic systems based on low-level interacting elements with unambiguous, finite, and complete information of initial states generate future states that cannot be predicted, implying an increase of complexity and open-ended evolution. Such systems are like Turing machines, that overlap with dynamical systems that cannot halt. We argue that organisms find halting conditions by distorting these mechanisms, creating conditions for a constant creativity that drives evolution. We introduce a modulus of elasticity to measure the changes in these mechanisms in response to changes in the computed environment. We test this concept in a population of predators and predated cells with chemotactic mechanisms and demonstrate how the selection of a given mechanism depends on the entire population. We finally explore this concept in different frameworks and postulate that the identification of predictive mechanisms is only successful with small elasticity modulus.

  1. ESCOMPTE 2001: multi-scale modelling and experimental validation

    NASA Astrophysics Data System (ADS)

    Cousin, F.; Tulet, P.; Rosset, R.

    2003-04-01

    ESCOMPTE is a European pollution field experiment located in the Marseille / Fos-Berre area in the summer 2001.This Mediterranean area, with frequent pollution peaks, is characterized by a complex topography subject to sea breeze regimes, together with intense localized urban, industrial and biogenic sources. Four POI have been selected, the most significant being POI2a / b, a 6-day pollution episode extensively documented for dynamics, radiation, gas phase and aerosols, with surface measurements (including measurements at sea in the gulf of Genoa, on board instrumented ferries between Marseille and Corsica), 7 aircrafts, lidar, radar and constant-level flight balloon soundings. The two-way mesoscale model MESO-NH-C (MNH-C), with horizontal resolutions of 9 and 3 km and high vertical resolution (up to 40 levels in the first 2 km), embedded in the global CTM Mocage, has been run for all POIs, with a focus here on POI2b (June 24-27,2001), a typical high pollution episode. The multi-scale modelling system MNH-C+MOCAGE allows to simulate local and regional pollution issued from emission sources in the Marseille / Fos-Berre area as well as from remote sources (e.g. the Po Valley and / or western Mediterranean sources) and their associated transboundary pollution fluxes. Detailed dynamical, chemical and aerosol (both modal and sectional spectra with organics and inorganics) simulations generally favorably compare to surface(continental and on ships), lidar and along-flight aircraft measurements.

  2. 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...

  3. Collaborative Simulation Grid: Multiscale Quantum-Mechanical/Classical Atomistic Simulations on Distributed PC Clusters in the US and Japan

    NASA Technical Reports Server (NTRS)

    Kikuchi, Hideaki; Kalia, Rajiv; Nakano, Aiichiro; Vashishta, Priya; Iyetomi, Hiroshi; Ogata, Shuji; Kouno, Takahisa; Shimojo, Fuyuki; Tsuruta, Kanji; Saini, Subhash; hide

    2002-01-01

    A multidisciplinary, collaborative simulation has been performed on a Grid of geographically distributed PC clusters. The multiscale simulation approach seamlessly combines i) atomistic simulation backed on the molecular dynamics (MD) method and ii) quantum mechanical (QM) calculation based on the density functional theory (DFT), so that accurate but less scalable computations are performed only where they are needed. The multiscale MD/QM simulation code has been Grid-enabled using i) a modular, additive hybridization scheme, ii) multiple QM clustering, and iii) computation/communication overlapping. The Gridified MD/QM simulation code has been used to study environmental effects of water molecules on fracture in silicon. A preliminary run of the code has achieved a parallel efficiency of 94% on 25 PCs distributed over 3 PC clusters in the US and Japan, and a larger test involving 154 processors on 5 distributed PC clusters is in progress.

  4. Multiscale solvers and systematic upscaling in computational physics

    NASA Astrophysics Data System (ADS)

    Brandt, A.

    2005-07-01

    Multiscale algorithms can overcome the scale-born bottlenecks that plague most computations in physics. These algorithms employ separate processing at each scale of the physical space, combined with interscale iterative interactions, in ways which use finer scales very sparingly. Having been developed first and well known as multigrid solvers for partial differential equations, highly efficient multiscale techniques have more recently been developed for many other types of computational tasks, including: inverse PDE problems; highly indefinite (e.g., standing wave) equations; Dirac equations in disordered gauge fields; fast computation and updating of large determinants (as needed in QCD); fast integral transforms; integral equations; astrophysics; molecular dynamics of macromolecules and fluids; many-atom electronic structures; global and discrete-state optimization; practical graph problems; image segmentation and recognition; tomography (medical imaging); fast Monte-Carlo sampling in statistical physics; and general, systematic methods of upscaling (accurate numerical derivation of large-scale equations from microscopic laws).

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

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

  6. Scalable free energy calculation of proteins via multiscale essential sampling

    NASA Astrophysics Data System (ADS)

    Moritsugu, Kei; Terada, Tohru; Kidera, Akinori

    2010-12-01

    A multiscale simulation method, "multiscale essential sampling (MSES)," is proposed for calculating free energy surface of proteins in a sizable dimensional space with good scalability. In MSES, the configurational sampling of a full-dimensional model is enhanced by coupling with the accelerated dynamics of the essential degrees of freedom. Applying the Hamiltonian exchange method to MSES can remove the biasing potential from the coupling term, deriving the free energy surface of the essential degrees of freedom. The form of the coupling term ensures good scalability in the Hamiltonian exchange. As a test application, the free energy surface of the folding process of a miniprotein, chignolin, was calculated in the continuum solvent model. Results agreed with the free energy surface derived from the multicanonical simulation. Significantly improved scalability with the MSES method was clearly shown in the free energy calculation of chignolin in explicit solvent, which was achieved without increasing the number of replicas in the Hamiltonian exchange.

  7. Initial Satellite Formation Flight Results from the Magnetospheric Multiscale Mission

    NASA Technical Reports Server (NTRS)

    Williams, Trevor; Ottenstein, Neil; Palmer, Eric; Farahmand, Mitra

    2016-01-01

    This paper describes the underlying dynamics of formation flying in a high-eccentricity orbit such as that of the Magnetospheric Multiscale mission. The GPS-based results used for MMS navigation is summarized, as well as the procedures that are used to design the maneuvers used to place the spacecraft into a tetrahedron formation and then maintain it. The details of how to carry out these maneuvers are then discussed. Finally, the numerical results that have been obtained concerning formation flying for the MMS mission to date (e.g. tetrahedron sizes flown, maneuver execution error, fuel usage, etc.) are presented in detail.

  8. Multiscale investigation of chemical interference in proteins

    NASA Astrophysics Data System (ADS)

    Samiotakis, Antonios; Homouz, Dirar; Cheung, Margaret S.

    2010-05-01

    We developed a multiscale approach (MultiSCAAL) that integrates the potential of mean force obtained from all-atomistic molecular dynamics simulations with a knowledge-based energy function for coarse-grained molecular simulations in better exploring the energy landscape of a small protein under chemical interference such as chemical denaturation. An excessive amount of water molecules in all-atomistic molecular dynamics simulations often negatively impacts the sampling efficiency of some advanced sampling techniques such as the replica exchange method and it makes the investigation of chemical interferences on protein dynamics difficult. Thus, there is a need to develop an effective strategy that focuses on sampling structural changes in protein conformations rather than solvent molecule fluctuations. In this work, we address this issue by devising a multiscale simulation scheme (MultiSCAAL) that bridges the gap between all-atomistic molecular dynamics simulation and coarse-grained molecular simulation. The two key features of this scheme are the Boltzmann inversion and a protein atomistic reconstruction method we previously developed (SCAAL). Using MultiSCAAL, we were able to enhance the sampling efficiency of proteins solvated by explicit water molecules. Our method has been tested on the folding energy landscape of a small protein Trp-cage with explicit solvent under 8M urea using both the all-atomistic replica exchange molecular dynamics and MultiSCAAL. We compared computational analyses on ensemble conformations of Trp-cage with its available experimental NOE distances. The analysis demonstrated that conformations explored by MultiSCAAL better agree with the ones probed in the experiments because it can effectively capture the changes in side-chain orientations that can flip out of the hydrophobic pocket in the presence of urea and water molecules. In this regard, MultiSCAAL is a promising and effective sampling scheme for investigating chemical interference which presents a great challenge when modeling protein interactions in vivo.

  9. Hierarchical coarse-graining strategy for protein-membrane systems to access mesoscopic scales

    PubMed Central

    Ayton, Gary S.; Lyman, Edward

    2014-01-01

    An overall multiscale simulation strategy for large scale coarse-grain simulations of membrane protein systems is presented. The protein is modeled as a heterogeneous elastic network, while the lipids are modeled using the hybrid analytic-systematic (HAS) methodology, where in both cases atomistic level information obtained from molecular dynamics simulation is used to parameterize the model. A feature of this approach is that from the outset liposome length scales are employed in the simulation (i.e., on the order of ½ a million lipids plus protein). A route to develop highly coarse-grained models from molecular-scale information is proposed and results for N-BAR domain protein remodeling of a liposome are presented. PMID:20158037

  10. 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.

  11. Epidemic outbreaks and its control using a fractional order model with seasonality and stochastic infection

    NASA Astrophysics Data System (ADS)

    He, Shaobo; Banerjee, Santo

    2018-07-01

    A fractional-order SIR epidemic model is proposed under the influence of both parametric seasonality and the external noise. The integer order SIR epidemic model originally is stable. By introducing seasonality and noise force to the model, behaviors of the system is changed. It is shown that the system has rich dynamical behaviors with different system parameters, fractional derivative order and the degree of seasonality and noise. Complexity of the stochastic model is investigated by using multi-scale fuzzy entropy. Finally, hard limiter controlled system is designed and simulation results show the ratio of infected individuals can converge to a small enough target ρ, which means the epidemic outbreak can be under control by the implementation of some effective medical and health measures.

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

    Antonelli, Perry Edward

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

  13. Direct observation of a single nanoparticle-ubiquitin corona formation

    NASA Astrophysics Data System (ADS)

    Ding, Feng; Radic, Slaven; Chen, Ran; Chen, Pengyu; Geitner, Nicholas K.; Brown, Jared M.; Ke, Pu Chun

    2013-09-01

    The advancement of nanomedicine and the increasing applications of nanoparticles in consumer products have led to administered biological exposure and unintentional environmental accumulation of nanoparticles, causing concerns over the biocompatibility and sustainability of nanotechnology. Upon entering physiological environments, nanoparticles readily assume the form of a nanoparticle-protein corona that dictates their biological identity. Consequently, understanding the structure and dynamics of a nanoparticle-protein corona is essential for predicting the fate, transport, and toxicity of nanomaterials in living systems and for enabling the vast applications of nanomedicine. Here we combined multiscale molecular dynamics simulations and complementary experiments to characterize the silver nanoparticle-ubiquitin corona formation. Notably, ubiquitins competed with citrates for the nanoparticle surface, governed by specific electrostatic interactions. Under a high protein/nanoparticle stoichiometry, ubiquitins formed a multi-layer corona on the particle surface. The binding exhibited an unusual stretched-exponential behavior, suggesting a rich binding kinetics. Furthermore, the binding destabilized the α-helices while increasing the β-sheet content of the proteins. This study revealed the atomic and molecular details of the structural and dynamic characteristics of nanoparticle-protein corona formation.The advancement of nanomedicine and the increasing applications of nanoparticles in consumer products have led to administered biological exposure and unintentional environmental accumulation of nanoparticles, causing concerns over the biocompatibility and sustainability of nanotechnology. Upon entering physiological environments, nanoparticles readily assume the form of a nanoparticle-protein corona that dictates their biological identity. Consequently, understanding the structure and dynamics of a nanoparticle-protein corona is essential for predicting the fate, transport, and toxicity of nanomaterials in living systems and for enabling the vast applications of nanomedicine. Here we combined multiscale molecular dynamics simulations and complementary experiments to characterize the silver nanoparticle-ubiquitin corona formation. Notably, ubiquitins competed with citrates for the nanoparticle surface, governed by specific electrostatic interactions. Under a high protein/nanoparticle stoichiometry, ubiquitins formed a multi-layer corona on the particle surface. The binding exhibited an unusual stretched-exponential behavior, suggesting a rich binding kinetics. Furthermore, the binding destabilized the α-helices while increasing the β-sheet content of the proteins. This study revealed the atomic and molecular details of the structural and dynamic characteristics of nanoparticle-protein corona formation. Electronic supplementary information (ESI) available: Experimental and computational methods as well as supporting figures. See DOI: 10.1039/c3nr02147e

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

    PubMed Central

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

    2012-01-01

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

  15. Complexity analysis of brain activity in attention-deficit/hyperactivity disorder: A multiscale entropy analysis.

    PubMed

    Chenxi, Li; Chen, Yanni; Li, Youjun; Wang, Jue; Liu, Tian

    2016-06-01

    The multiscale entropy (MSE) is a novel method for quantifying the intrinsic dynamical complexity of physiological systems over several scales. To evaluate this method as a promising way to explore the neural mechanisms in ADHD, we calculated the MSE in EEG activity during the designed task. EEG data were collected from 13 outpatient boys with a confirmed diagnosis of ADHD and 13 age- and gender-matched normal control children during their doing multi-source interference task (MSIT). We estimated the MSE by calculating the sample entropy values of delta, theta, alpha and beta frequency bands over twenty time scales using coarse-grained procedure. The results showed increased complexity of EEG data in delta and theta frequency bands and decreased complexity in alpha frequency bands in ADHD children. The findings of this study revealed aberrant neural connectivity of kids with ADHD during interference task. The results showed that MSE method may be a new index to identify and understand the neural mechanism of ADHD. Copyright © 2016 Elsevier Inc. All rights reserved.

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

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

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

  17. Intermediate-scale plasma irregularities in the polar ionosphere inferred from GPS radio occultation

    NASA Astrophysics Data System (ADS)

    Shume, E. B.; Komjathy, A.; Langley, R. B.; Verkhoglyadova, O.; Butala, M. D.; Mannucci, A. J.

    2015-02-01

    We report intermediate-scale plasma irregularities in the polar ionosphere inferred from high-resolution radio occultation (RO) measurements using GPS (Global Positioning System) to CASSIOPE (CAScade Smallsat and IOnospheric Polar Explorer) satellite radio links. The high inclination of CASSIOPE and the high rate of signal reception by the GPS Attitude, Positioning, and Profiling RO receiver on CASSIOPE enable a high-resolution investigation of the dynamics of the polar ionosphere with unprecedented detail. Intermediate-scale, scintillation-producing irregularities, which correspond to 1 to 40 km scales, were inferred by applying multiscale spectral analysis on the RO phase measurements. Using our multiscale spectral analysis approach and satellite data (Polar Operational Environmental Satellites and Defense Meteorological Satellite Program), we discovered that the irregularity scales and phase scintillations have distinct features in the auroral oval and polar cap. We found that large length scales and more intense phase scintillations are prevalent in the auroral oval compared to the polar cap implying that the irregularity scales and phase scintillation characteristics are a function of the solar wind and magnetospheric forcings.

  18. Modeling evolution of spatially distributed bacterial communities: a simulation with the haploid evolutionary constructor

    PubMed Central

    2015-01-01

    Background Multiscale approaches for integrating submodels of various levels of biological organization into a single model became the major tool of systems biology. In this paper, we have constructed and simulated a set of multiscale models of spatially distributed microbial communities and study an influence of unevenly distributed environmental factors on the genetic diversity and evolution of the community members. Results Haploid Evolutionary Constructor software http://evol-constructor.bionet.nsc.ru/ was expanded by adding the tool for the spatial modeling of a microbial community (1D, 2D and 3D versions). A set of the models of spatially distributed communities was built to demonstrate that the spatial distribution of cells affects both intensity of selection and evolution rate. Conclusion In spatially heterogeneous communities, the change in the direction of the environmental flow might be reflected in local irregular population dynamics, while the genetic structure of populations (frequencies of the alleles) remains stable. Furthermore, in spatially heterogeneous communities, the chemotaxis might dramatically affect the evolution of community members. PMID:25708911

  19. System and methods for predicting transmembrane domains in membrane proteins and mining the genome for recognizing G-protein coupled receptors

    DOEpatents

    Trabanino, Rene J; Vaidehi, Nagarajan; Hall, Spencer E; Goddard, William A; Floriano, Wely

    2013-02-05

    The invention provides computer-implemented methods and apparatus implementing a hierarchical protocol using multiscale molecular dynamics and molecular modeling methods to predict the presence of transmembrane regions in proteins, such as G-Protein Coupled Receptors (GPCR), and protein structural models generated according to the protocol. The protocol features a coarse grain sampling method, such as hydrophobicity analysis, to provide a fast and accurate procedure for predicting transmembrane regions. Methods and apparatus of the invention are useful to screen protein or polynucleotide databases for encoded proteins with transmembrane regions, such as GPCRs.

  20. Multiscale Approach to Small River Plumes off California

    NASA Astrophysics Data System (ADS)

    Basdurak, N. B.; Largier, J. L.; Nidzieko, N.

    2012-12-01

    While larger scale plumes have received significant attention, the dynamics of plumes associated with small rivers typical of California are little studied. Since small streams are not dominated by a momentum flux, their plumes are more susceptible to conditions in the coastal ocean such as wind and waves. In order to correctly model water transport at smaller scales, there is a need to capture larger scale processes. To do this, one-way nested grids with varying grid resolution (1 km and 10 m for the parent and the child grid respectively) were constructed. CENCOOS (Central and Northern California Ocean Observing System) model results were used as boundary conditions to the parent grid. Semi-idealized model results for Santa Rosa Creek, California are presented from an implementation of the Regional Ocean Modeling System (ROMS v3.0), a three-dimensional, free-surface, terrain-following numerical model. In these preliminary results, the interaction between tides, winds, and buoyancy forcing in plume dynamics is explored for scenarios including different strengths of freshwater flow with different modes (steady and pulsed). Seasonal changes in transport dynamics and dispersion patterns are analyzed.

  1. A comparative analysis of alternative approaches for quantifying nonlinear dynamics in cardiovascular system.

    PubMed

    Chen, Yun; Yang, Hui

    2013-01-01

    Heart rate variability (HRV) analysis has emerged as an important research topic to evaluate autonomic cardiac function. However, traditional time and frequency-domain analysis characterizes and quantify only linear and stationary phenomena. In the present investigation, we made a comparative analysis of three alternative approaches (i.e., wavelet multifractal analysis, Lyapunov exponents and multiscale entropy analysis) for quantifying nonlinear dynamics in heart rate time series. Note that these extracted nonlinear features provide information about nonlinear scaling behaviors and the complexity of cardiac systems. To evaluate the performance, we used 24-hour HRV recordings from 54 healthy subjects and 29 heart failure patients, available in PhysioNet. Three nonlinear methods are evaluated not only individually but also in combination using three classification algorithms, i.e., linear discriminate analysis, quadratic discriminate analysis and k-nearest neighbors. Experimental results show that three nonlinear methods capture nonlinear dynamics from different perspectives and the combined feature set achieves the best performance, i.e., sensitivity 97.7% and specificity 91.5%. Collectively, nonlinear HRV features are shown to have the promise to identify the disorders in autonomic cardiovascular function.

  2. Information-Theoretical Quantifier of Brain Rhythm Based on Data-Driven Multiscale Representation

    PubMed Central

    2015-01-01

    This paper presents a data-driven multiscale entropy measure to reveal the scale dependent information quantity of electroencephalogram (EEG) recordings. This work is motivated by the previous observations on the nonlinear and nonstationary nature of EEG over multiple time scales. Here, a new framework of entropy measures considering changing dynamics over multiple oscillatory scales is presented. First, to deal with nonstationarity over multiple scales, EEG recording is decomposed by applying the empirical mode decomposition (EMD) which is known to be effective for extracting the constituent narrowband components without a predetermined basis. Following calculation of Renyi entropy of the probability distributions of the intrinsic mode functions extracted by EMD leads to a data-driven multiscale Renyi entropy. To validate the performance of the proposed entropy measure, actual EEG recordings from rats (n = 9) experiencing 7 min cardiac arrest followed by resuscitation were analyzed. Simulation and experimental results demonstrate that the use of the multiscale Renyi entropy leads to better discriminative capability of the injury levels and improved correlations with the neurological deficit evaluation after 72 hours after cardiac arrest, thus suggesting an effective diagnostic and prognostic tool. PMID:26380297

  3. Acoustics of multiscale sorptive porous materials

    NASA Astrophysics Data System (ADS)

    Venegas, R.; Boutin, C.; Umnova, O.

    2017-08-01

    This paper investigates sound propagation in multiscale rigid-frame porous materials that support mass transfer processes, such as sorption and different types of diffusion, in addition to the usual visco-thermo-inertial interactions. The two-scale asymptotic method of homogenization for periodic media is successively used to derive the macroscopic equations describing sound propagation through the material. This allowed us to conclude that the macroscopic mass balance is significantly modified by sorption, inter-scale (micro- to/from nanopore scales) mass diffusion, and inter-scale (pore to/from micro- and nanopore scales) pressure diffusion. This modification is accounted for by the dynamic compressibility of the effective saturating fluid that presents atypical properties that lead to slower speed of sound and higher sound attenuation, particularly at low frequencies. In contrast, it is shown that the physical processes occurring at the micro-nano-scale do not affect the macroscopic fluid flow through the material. The developed theory is exemplified by introducing an analytical model for multiscale sorptive granular materials, which is experimentally validated by comparing its predictions with acoustic measurements on granular activated carbons. Furthermore, we provide empirical evidence supporting an alternative method for measuring sorption and mass diffusion properties of multiscale sorptive materials using sound waves.

  4. Automatic event detection in low SNR microseismic signals based on multi-scale permutation entropy and a support vector machine

    NASA Astrophysics Data System (ADS)

    Jia, Rui-Sheng; Sun, Hong-Mei; Peng, Yan-Jun; Liang, Yong-Quan; Lu, Xin-Ming

    2017-07-01

    Microseismic monitoring is an effective means for providing early warning of rock or coal dynamical disasters, and its first step is microseismic event detection, although low SNR microseismic signals often cannot effectively be detected by routine methods. To solve this problem, this paper presents permutation entropy and a support vector machine to detect low SNR microseismic events. First, an extraction method of signal features based on multi-scale permutation entropy is proposed by studying the influence of the scale factor on the signal permutation entropy. Second, the detection model of low SNR microseismic events based on the least squares support vector machine is built by performing a multi-scale permutation entropy calculation for the collected vibration signals, constructing a feature vector set of signals. Finally, a comparative analysis of the microseismic events and noise signals in the experiment proves that the different characteristics of the two can be fully expressed by using multi-scale permutation entropy. The detection model of microseismic events combined with the support vector machine, which has the features of high classification accuracy and fast real-time algorithms, can meet the requirements of online, real-time extractions of microseismic events.

  5. Multi-scale heterogeneity of the 2011 Great Tohoku-oki Earthquake from dynamic simulations

    NASA Astrophysics Data System (ADS)

    Aochi, H.; Ide, S.

    2011-12-01

    In order to explain the scaling issues of earthquakes of different sizes, multi-scale heterogeneity conception is necessary to characterize earthquake faulting property (Ide and Aochi, JGR, 2005; Aochi and Ide, JGR, 2009).The 2011 Great Tohoku-oki earthquake (M9) is characterized by a slow initial phase of about M7, a M8 class deep rupture, and a M9 main rupture with quite large slip near the trench (e.g. Ide et al., Science, 2011) as well as the presence of foreshocks. We dynamically model these features based on the multi-scale conception. We suppose a significantly large fracture energy (corresponding to slip-weakening distance of 3.2 m) in most of the fault dimension to represent the M9 rupture. However we give local heterogeneity with relatively small circular patches of smaller fracture energy, by assuming the linear scaling relation between the radius and fracture energy. The calculation is carried out using 3D Boundary Integral Equation Method. We first begin only with the mainshock (Aochi and Ide, EPS, 2011), but later we find it important to take into account of a series of foreshocks since the 9th March (M7.4). The smaller patches including the foreshock area are necessary to launch the M9 rupture area of large fracture energy. We then simulate the ground motion in low frequencies using Finite Difference Method. Qualitatively, the observed tendency is consistent with our simulations, in the meaning of the transition from the central part to the southern part in low frequencies (10 - 20 sec). At higher frequencies (1-10 sec), further small asperities are inferred in the observed signals, and this feature matches well with our multi-scale conception.

  6. Filters for Improvement of Multiscale Data from Atomistic Simulations

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

    Gardner, David J.; Reynolds, Daniel R.

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

  7. Filters for Improvement of Multiscale Data from Atomistic Simulations

    DOE PAGES

    Gardner, David J.; Reynolds, Daniel R.

    2017-01-05

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

  8. Mapping Transient Hyperventilation Induced Alterations with Estimates of the Multi-Scale Dynamics of BOLD Signal.

    PubMed

    Kiviniemi, Vesa; Remes, Jukka; Starck, Tuomo; Nikkinen, Juha; Haapea, Marianne; Silven, Olli; Tervonen, Osmo

    2009-01-01

    Temporal blood oxygen level dependent (BOLD) contrast signals in functional MRI during rest may be characterized by power spectral distribution (PSD) trends of the form 1/f(alpha). Trends with 1/f characteristics comprise fractal properties with repeating oscillation patterns in multiple time scales. Estimates of the fractal properties enable the quantification of phenomena that may otherwise be difficult to measure, such as transient, non-linear changes. In this study it was hypothesized that the fractal metrics of 1/f BOLD signal trends can map changes related to dynamic, multi-scale alterations in cerebral blood flow (CBF) after a transient hyperventilation challenge. Twenty-three normal adults were imaged in a resting-state before and after hyperventilation. Different variables (1/f trend constant alpha, fractal dimension D(f), and, Hurst exponent H) characterizing the trends were measured from BOLD signals. The results show that fractal metrics of the BOLD signal follow the fractional Gaussian noise model, even during the dynamic CBF change that follows hyperventilation. The most dominant effect on the fractal metrics was detected in grey matter, in line with previous hyperventilation vaso-reactivity studies. The alpha was able to differentiate also blood vessels from grey matter changes. D(f) was most sensitive to grey matter. H correlated with default mode network areas before hyperventilation but this pattern vanished after hyperventilation due to a global increase in H. In the future, resting-state fMRI combined with fractal metrics of the BOLD signal may be used for analyzing multi-scale alterations of cerebral blood flow.

  9. Multiscale Dynamics of Solar Magnetic Structures

    NASA Technical Reports Server (NTRS)

    Uritsky, Vadim M.; Davila, Joseph M.

    2012-01-01

    Multiscale topological complexity of the solar magnetic field is among the primary factors controlling energy release in the corona, including associated processes in the photospheric and chromospheric boundaries.We present a new approach for analyzing multiscale behavior of the photospheric magnetic flux underlying these dynamics as depicted by a sequence of high-resolution solar magnetograms. The approach involves two basic processing steps: (1) identification of timing and location of magnetic flux origin and demise events (as defined by DeForest et al.) by tracking spatiotemporal evolution of unipolar and bipolar photospheric regions, and (2) analysis of collective behavior of the detected magnetic events using a generalized version of the Grassberger-Procaccia correlation integral algorithm. The scale-free nature of the developed algorithms makes it possible to characterize the dynamics of the photospheric network across a wide range of distances and relaxation times. Three types of photospheric conditions are considered to test the method: a quiet photosphere, a solar active region (NOAA 10365) in a quiescent non-flaring state, and the same active region during a period of M-class flares. The results obtained show (1) the presence of a topologically complex asymmetrically fragmented magnetic network in the quiet photosphere driven by meso- and supergranulation, (2) the formation of non-potential magnetic structures with complex polarity separation lines inside the active region, and (3) statistical signatures of canceling bipolar magnetic structures coinciding with flaring activity in the active region. Each of these effects can represent an unstable magnetic configuration acting as an energy source for coronal dissipation and heating.

  10. Multiscale methods for computational RNA enzymology

    PubMed Central

    Panteva, Maria T.; Dissanayake, Thakshila; Chen, Haoyuan; Radak, Brian K.; Kuechler, Erich R.; Giambaşu, George M.; Lee, Tai-Sung; York, Darrin M.

    2016-01-01

    RNA catalysis is of fundamental importance to biology and yet remains ill-understood due to its complex nature. The multi-dimensional “problem space” of RNA catalysis includes both local and global conformational rearrangements, changes in the ion atmosphere around nucleic acids and metal ion binding, dependence on potentially correlated protonation states of key residues and bond breaking/forming in the chemical steps of the reaction. The goal of this article is to summarize and apply multiscale modeling methods in an effort to target the different parts of the RNA catalysis problem space while also addressing the limitations and pitfalls of these methods. Classical molecular dynamics (MD) simulations, reference interaction site model (RISM) calculations, constant pH molecular dynamics (CpHMD) simulations, Hamiltonian replica exchange molecular dynamics (HREMD) and quantum mechanical/molecular mechanical (QM/MM) simulations will be discussed in the context of the study of RNA backbone cleavage transesterification. This reaction is catalyzed by both RNA and protein enzymes, and here we examine the different mechanistic strategies taken by the hepatitis delta virus ribozyme (HDVr) and RNase A. PMID:25726472

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

    Zhang, Na; Zhang, Peng; Kang, Wei

    Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters aremore » systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately.« less

  12. The fusion code XGC: Enabling kinetic study of multi-scale edge turbulent transport in ITER [Book Chapter

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

    D'Azevedo, Eduardo; Abbott, Stephen; Koskela, Tuomas

    The XGC fusion gyrokinetic code combines state-of-the-art, portable computational and algorithmic technologies to enable complicated multiscale simulations of turbulence and transport dynamics in ITER edge plasma on the largest US open-science computer, the CRAY XK7 Titan, at its maximal heterogeneous capability, which have not been possible before due to a factor of over 10 shortage in the time-to-solution for less than 5 days of wall-clock time for one physics case. Frontier techniques such as nested OpenMP parallelism, adaptive parallel I/O, staging I/O and data reduction using dynamic and asynchronous applications interactions, dynamic repartitioning for balancing computational work in pushing particlesmore » and in grid related work, scalable and accurate discretization algorithms for non-linear Coulomb collisions, and communication-avoiding subcycling technology for pushing particles on both CPUs and GPUs are also utilized to dramatically improve the scalability and time-to-solution, hence enabling the difficult kinetic ITER edge simulation on a present-day leadership class computer.« less

  13. A multiscale computational approach to dissect early events in the Erb family receptor mediated activation, differential signaling, and relevance to oncogenic transformations.

    PubMed

    Liu, Yingting; Purvis, Jeremy; Shih, Andrew; Weinstein, Joshua; Agrawal, Neeraj; Radhakrishnan, Ravi

    2007-06-01

    We describe a hierarchical multiscale computational approach based on molecular dynamics simulations, free energy-based molecular docking simulations, deterministic network-based kinetic modeling, and hybrid discrete/continuum stochastic dynamics protocols to study the dimer-mediated receptor activation characteristics of the Erb family receptors, specifically the epidermal growth factor receptor (EGFR). Through these modeling approaches, we are able to extend the prior modeling of EGF-mediated signal transduction by considering specific EGFR tyrosine kinase (EGFRTK) docking interactions mediated by differential binding and phosphorylation of different C-terminal peptide tyrosines on the RTK tail. By modeling signal flows through branching pathways of the EGFRTK resolved on a molecular basis, we are able to transcribe the effects of molecular alterations in the receptor (e.g., mutant forms of the receptor) to differing kinetic behavior and downstream signaling response. Our molecular dynamics simulations show that the drug sensitizing mutation (L834R) of EGFR stabilizes the active conformation to make the system constitutively active. Docking simulations show preferential characteristics (for wildtype vs. mutant receptors) in inhibitor binding as well as preferential enhancement of phosphorylation of particular substrate tyrosines over others. We find that in comparison to the wildtype system, the L834R mutant RTK preferentially binds the inhibitor erlotinib, as well as preferentially phosphorylates the substrate tyrosine Y1068 but not Y1173. We predict that these molecular level changes result in preferential activation of the Akt signaling pathway in comparison to the Erk signaling pathway for cells with normal EGFR expression. For cells with EGFR over expression, the mutant over activates both Erk and Akt pathways, in comparison to wildtype. These results are consistent with qualitative experimental measurements reported in the literature. We discuss these consequences in light of how the network topology and signaling characteristics of altered (mutant) cell lines are shaped differently in relationship to native cell lines.

  14. Multicomponent, Multiphase Thermodynamics of Swelling Porous Media With Electroquasistatics. 1. Macroscale Field Equations

    DTIC Science & Technology

    2001-08-08

    entropy inequality with independent variables consistent with several natural systems and apply the resulting constitutive theory near equi- librium...1973. [3] L. S. Bennethum and J. H. Cushman. Multiscale , hybrid mixture theory for swelling systems - I: Balance laws. International Journal of...Engineering Science, 34(2):125–145, 1996. [4] L. S. Bennethum and J. H. Cushman. Multiscale , hybrid mixture theory for swelling systems - II: Constitutive

  15. Status and future of MUSE

    NASA Astrophysics Data System (ADS)

    Harfst, S.; Portegies Zwart, S.; McMillan, S.

    2008-12-01

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

  16. BGK-MD, Version 1.0

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

    Haack, Jeffrey; Shohet, Gil

    2016-12-02

    The software implements a heterogeneous multiscale method (HMM), which involves solving a classical molecular dynamics (MD) problem and then computes the entropy production in order to compute the relaxation times towards equilibrium for use in a Bhatnagar-Gross-Krook (BGK) solver.

  17. Atomistic potentials based energy flux integral criterion for dynamic adiabatic shear banding

    NASA Astrophysics Data System (ADS)

    Xu, Yun; Chen, Jun

    2015-02-01

    The energy flux integral criterion based on atomistic potentials within the framework of hyperelasticity-plasticity is proposed for dynamic adiabatic shear banding (ASB). System Helmholtz energy decomposition reveals that the dynamic influence on the integral path dependence is originated from the volumetric strain energy and partial deviatoric strain energy, and the plastic influence only from the rest part of deviatoric strain energy. The concept of critical shear banding energy is suggested for describing the initiation of ASB, which consists of the dynamic recrystallization (DRX) threshold energy and the thermal softening energy. The criterion directly relates energy flux to the basic physical processes that induce shear instability such as dislocation nucleations and multiplications, without introducing ad-hoc parameters in empirical constitutive models. It reduces to the classical path independent J-integral for quasi-static loading and elastic solids. The atomistic-to-continuum multiscale coupling method is used to simulate the initiation of ASB. Atomic configurations indicate that DRX induced microstructural softening may be essential to the dynamic shear localization and hence the initiation of ASB.

  18. Using nonlinear methods to quantify changes in infant limb movements and vocalizations.

    PubMed

    Abney, Drew H; Warlaumont, Anne S; Haussman, Anna; Ross, Jessica M; Wallot, Sebastian

    2014-01-01

    The pairing of dynamical systems theory and complexity science brings novel concepts and methods to the study of infant motor development. Accordingly, this longitudinal case study presents a new approach to characterizing the dynamics of infant limb and vocalization behaviors. A single infant's vocalizations and limb movements were recorded from 51-days to 305-days of age. On each recording day, accelerometers were placed on all four of the infant's limbs and an audio recorder was worn on the child's chest. Using nonlinear time series analysis methods, such as recurrence quantification analysis and Allan factor, we quantified changes in the stability and multiscale properties of the infant's behaviors across age as well as how these dynamics relate across modalities and effectors. We observed that particular changes in these dynamics preceded or coincided with the onset of various developmental milestones. For example, the largest changes in vocalization dynamics preceded the onset of canonical babbling. The results show that nonlinear analyses can help to understand the functional co-development of different aspects of infant behavior.

  19. Using nonlinear methods to quantify changes in infant limb movements and vocalizations

    PubMed Central

    Abney, Drew H.; Warlaumont, Anne S.; Haussman, Anna; Ross, Jessica M.; Wallot, Sebastian

    2014-01-01

    The pairing of dynamical systems theory and complexity science brings novel concepts and methods to the study of infant motor development. Accordingly, this longitudinal case study presents a new approach to characterizing the dynamics of infant limb and vocalization behaviors. A single infant's vocalizations and limb movements were recorded from 51-days to 305-days of age. On each recording day, accelerometers were placed on all four of the infant's limbs and an audio recorder was worn on the child's chest. Using nonlinear time series analysis methods, such as recurrence quantification analysis and Allan factor, we quantified changes in the stability and multiscale properties of the infant's behaviors across age as well as how these dynamics relate across modalities and effectors. We observed that particular changes in these dynamics preceded or coincided with the onset of various developmental milestones. For example, the largest changes in vocalization dynamics preceded the onset of canonical babbling. The results show that nonlinear analyses can help to understand the functional co-development of different aspects of infant behavior. PMID:25161629

  20. Sparsity enabled cluster reduced-order models for control

    NASA Astrophysics Data System (ADS)

    Kaiser, Eurika; Morzyński, Marek; Daviller, Guillaume; Kutz, J. Nathan; Brunton, Bingni W.; Brunton, Steven L.

    2018-01-01

    Characterizing and controlling nonlinear, multi-scale phenomena are central goals in science and engineering. Cluster-based reduced-order modeling (CROM) was introduced to exploit the underlying low-dimensional dynamics of complex systems. CROM builds a data-driven discretization of the Perron-Frobenius operator, resulting in a probabilistic model for ensembles of trajectories. A key advantage of CROM is that it embeds nonlinear dynamics in a linear framework, which enables the application of standard linear techniques to the nonlinear system. CROM is typically computed on high-dimensional data; however, access to and computations on this full-state data limit the online implementation of CROM for prediction and control. Here, we address this key challenge by identifying a small subset of critical measurements to learn an efficient CROM, referred to as sparsity-enabled CROM. In particular, we leverage compressive measurements to faithfully embed the cluster geometry and preserve the probabilistic dynamics. Further, we show how to identify fewer optimized sensor locations tailored to a specific problem that outperform random measurements. Both of these sparsity-enabled sensing strategies significantly reduce the burden of data acquisition and processing for low-latency in-time estimation and control. We illustrate this unsupervised learning approach on three different high-dimensional nonlinear dynamical systems from fluids with increasing complexity, with one application in flow control. Sparsity-enabled CROM is a critical facilitator for real-time implementation on high-dimensional systems where full-state information may be inaccessible.

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